COMMISSION FOR AGRICULTURAL METEOROLOGY OPAG 2

Support Systems for Agrometeorological Services (ICSAS)

Implementation/Coordination Team Report to CAgM-XV SESSION

2

Index 1- Introduction

2- Ensuring effective implementation and adoption within the Member Countries of OPAG 2 activities: revision and coordination actions.

3- Generalities about the revision of the operational applications of current tools and information delivery systems, and the formulation of recommendations on procedures, methodologies and resources

4- Revision of the operational applications of current agrometeorological data, analytical tools, and information delivery systems.

4.1 Region IV: 4.2 Region III. 4.3 Region I. 4.4 Region II. 4.5 Region V. 4.6 Region VI

5- Recommendations on procedures, methodologies and resources to improve the regional-based capability for operational applications 6- General recommendations from ICSAS 7. Promotion actions of OPAG work 8- References 9- Annex- The questionnarie

3

1- Introduction

The Commission for Agricultural Meteorology (CAgM) of WMO at its fourteenth session confirmed the Open Programme Area Group (OPAG) on Support Systems for Agrometeorological Services, and constituted an Implementation/Coordination Team (ICT) for this OPAG. This ICT is mainly based on regional representation and focuses on coordinating operational and implementation aspects. CAgM requested this ICT team to maintain an active and responsive overview of all activities related to the Support Systems for Agrometeorological Services, including the collection and Evaluation of Operational Agrometeorological Tools and Methodologies, and the Communication of Agrometeorological Products and Services. Attention is focused on operational applications of current agrometeorological data, analytical tools, and information delivery systems at the national and regional levels and makes recommendations on procedures, methodologies and resources to improve the regional-based capability for operational applications. Another important task of the ICT is to appraise and report on current regional capabilities and make recommendations on procedures, methodologies and resources to improve the regional-based capability for operational applications. Finally, the ICT is to make recommendations for improving the use of support systems in agrometeorology for the benefit of agriculture at the national and regional levels. In these last years, agriculture has been at the centre of the world attention due to the sudden and dramatic rise of prices between the end of 2007 and the first half of 2008, followed by the world financial crisis that affected all countries form the second half of 2008. An urgent need for decisive actions to free humanity from hunger an poverty has been stressed by l’Aquila Food Security Initiative adopted at G8 summit in June 2009, where a declaration stated the necessity to focus the attention on agriculture and rural development promoting sustainable agricultural production and a greater productivity and economic growth in the rural world through appropriate policies. It is indubitable that sustainable agriculture urges to incorporate weather and climate information in order to make the system” efficient and effective. Agrometeorological tools, technologies and methodologies must be implemented and adapted to provide the most noticeable information to support farmers and decision makers. A more efficient coping with climate variability is also needed by the farming communities, and agrometeorological information is increasing its significance in risk hazards and natural disasters monitoring and assessment. Different agricultural systems (crops, livestocks, rangelands, grasslands, forestries, fisheries ) and regions (with their diverse geographical, climatic, tradition and social aspects) ask for different applications and utilities: a common requisite is to use scientifically validated tools ( do not compromise the science) and broaden communication extent and quality. (the value of information diminishes if it is not provided in a form that users can understand and apply). This ICT report summarise the various terms of reference for the WMO regions. From the material received from the ICT members for Europe, Asia, Southwest Pacific, Africa, Americas, and from material obtained from other sources, conclusions have been drawn, and recommendations made which are contained in the OPAG 2 report for CAgM-XV session to consider.

4

Terms of reference:

(a) To review and coordinate the activities of the OPAG, as well as additional related activities of priority to the Commission, in order to ensure their effective implementation and adoption within Member countries; (b) To review the operational applications of current agrometeorological data, analytical tools, and information delivery systems at the national and regional levels; (c) To make recommendations on procedures, methodologies and resources to improve the regional-based capability for operational applications; (d) To raise awareness of the work of the OPAG and to capture opportunities for promoting its work; (e) To liaise with the coordinator for policy support in capacity building and the coordinator for bridging of the gaps between products/methods and producers of the CAgM MG, as appropriate, in the implementation of the activities of the team (f) To prepare reports in accordance with timetables established by the OPAG and/or MG.

Membership for ICSAS

Chair Federica ROSSI RA VI (Italy)

Co-Chair E. PALACIOS RA III (Ecuador)

Mohamed DAWOD RA I (Egypt)

Huailiang CHEN RA II (China)

Miguel EGAÑA RA III (Chile)

Adriana CORTEZ RA IV (Venezuela)

Flaviana HILARIO RA V (Philippines)

Svetlana KORSAKOVA RA VI (Ukraine)

5

2- Ensuring effective implementation and adoption within the Member Countries of

OPAG 2 activities: revision and coordination actions.

Coordination is not easy and it normally requires initial resources and investment. Coordination of knowledge and information-sharing is crucial to ensure OPAG team activities become part of purposeful whole. In this sense efforts have been made to manage communication and interdependencies between members to achieve the OPAG 2 main goals and seek for ways to ensure effective implementation of activities and recommendations within the Member Countries. A shared background is also based on a shared understanding of the current situation, considering that RAs have different common grounds: agriculture and agrometeorological applications differ on facts (geography, climate, history …), conventions, norms and procedures. To facilitate such joint cooperation, a questionnaire directly involving Member Countries and distributed through WMO was used to have a basis for understanding the current status of availability of support systems and their applications in operational Agrometeorology in various countries. Simple and understandable questions were specifically formulated to solve basic questions about: “What do we have so far”, “how we use it”, “what is demand”, “how the products can be improved”. 72 Countries have answered, so a feedback about concerns and limitations has been gained from 15 Countries belonging to RA I (Africa), 16 to RA II (Asia), 3 to RA II (South America), 7 to RA IV (North America, Central America and the Carribean), 4 to RA V (South-West Pacific), and 27 from RA VI (Europe). The results are explicative of the current status and the local expectances, opening horizons on the needs on requirements about the type and aims of support systems to be implemented and adopted. Some statistics are reported on Annex 1. Members of this OPAG team have shared common responsibilities to maintain an active and reactive overview of activities related to support systems in the different geographic areas, both in reviewing the operational applications and making appropriate recommendations. Continuity with the activities of the previous OPAG 2 team was maintained, and attention was also driven to the opportunity to implement and develop two project previously proposed ("Applications of MODIS to agriculture", "Transferring research results and tools to operational applications in agriculture developing a transparent protocol"). Knowledge about existing tools and methodologies and about ways to communicate them to users is at the basis of a effective possibilities of implementation and adoption of reliable support systems: mutual exchanges of intermediate and final results hence was promoted between this ICT and the two OPAG2 ETs: 2.2 - Expert Team on Collection and Evaluation of Operational Agrometeorological Tools and Methodologies (ETATM), 2.3 - Expert Team on Communication of Agrometeorological Products and Services (ETCAPS). Between existing supporting systems in agrometeorology, WAMIS is one of the most operational and promising. WAMIS makes agrometeorological products issued by WMO members available to the global agricultural community on a near real-time basis.. Provision of a central location for agrometeorological information can help the users quickly and easily evaluate the various bulletins and gain insight into improving their own bulletins,. WAMIS also hosts a tools and resources section with the themes of data, information, dissemination, and feedback, and includes links to useful available software, guides, web portals, training resources, and tutorials. Being a web

6

systems, WAMIS is easily accessed from remote locations, and may offer timely information with one-click of the mouse button. But the access to on-line information may be restricted for many reasons: a WAMIS mirroring site has been established and is hosted at CNR- IBIMET Bologna under the responsibility of the current chair of OPAG2 (F. Rossi). This mirror site allows faster downloads of WAMIS agrometeorological tools and resources for users at some specific location, offers a alternative point to speed up the total number of downloads, counterbalances sudden temporary enhance of traffic or possible breakdown of the main server. An other very important support system in agrometeorology is INSAM Society. The INSAM web site is fully maintained in the web server at IBIMET Bologna, and its scientific, technical, operational, didactic supports are made available to more of 1400 members via the continuously updated page www.agrometeorology.org with Rossi being the Editor. The site is kept updated daily, and contains information on news (highlights on agrometeorology, vacancies, highlights), operational topics (market place, on line weather and climate information, selected bibliography, accounts of operational agrometeorology, applications to solve farming problems, educational aspects, environmental sustainability and other ). In specific, useful tools for support systems implementation include "Software Tools useful in Agrometeorology”, that introduces to helpful software available to agrometeorologists. Online Weather and Climate Information for Agrometeorologists, that contains information about Analysis of Current Conditions (Global and regional monitoring maps provide rainfall information - accumulated rainfall, rainfall anomaly, and rainfall percent of normal) for the past 3hours, 24 hours, 10 days, 30 days, 60 days, and 90 days - and on Analytical Tools. Needs for agrometeorological solutions to farming problems provides as well a discussion forum on problems for which operational solutions with agrometeorological components are highly required, but not yet or incompletely available, or available but not applied. Pre-publication information may be exchanged and experiences swapped on possible services, research, training/extension and policies related to food security, on-farm and market related. In the Abridged final report of the XIV session of the Commission, recommendation was given (CAgM/MMG/Doc. 9.2, p. 2) that CNR–IBIMET in Bologna, Italy, consider compiling a bibliography of available products, quarterly, and make it available to the WAMIS and INSAM users, in order to improve information on availability and accessibility of open-source software (e.g. GIS databases) for decision support. This activity is currently carried out, and provides further scientific support to operational applications of current data, analytical tools, and information delivery systems. The service reaches 116 Countries, to which almost 1400 members belongs. 3- Generalities about the revision of the operational applications of current tools and information delivery systems, and the formulation of recommendations on procedures, methodologies and resources Revision of the operational applications of current agrometeorological data, analytical tools, and information delivery systems at the national and regional levels, and formulating recommendations on procedures, methodologies and resources to improve the regional-based capability for operational applications are the main terms of this current report. The work developed in the course of the four-years commitments, and largely discussed at the ICT Meeting, held in New Delhi on 26-28 February 2009. At the meeting, ICT members Drs. Huailiang CHEN, Mohamed Abd El-Rhman Ali DAWOD, Flaviana HILARIO, Svetlana KORSAKOVA, Federica ROSSI were joined by Drs L.S. RATHORE, Raymond MOTHA, Shiv ATTRI, and from Drs M.V.K. SIVAKUMAR and R. STEFANSKI from WMO. ICT member who were not present provided their material and comments to the chair and colleagues, so that all the RAs were virtually present at the meeting. The ICT meeting took large profit by the fact it was held in conjunction with the International Conference on Challenges and

7

Opportunities in Agrometeorology (23-25 Feb 2009), organized by the Indian Agrometeorological Society, addressing very important issues useful to ICSAS. The basis concepts of the conference have been incorporated into the analysis reported here, since the increasing concerns on the need to develop a new vision of Agrometeorology, that should focalize on the operational implementation of new tools and methods to support farmers in their daily work and, at the same time, to face emergency situations resulting from natural disasters and to conserve the resource base of food production to ensure sustainability. There is now a growing recognition of the importance of operational agrometeorological services (including pests and diseases; early warning and monitoring systems; short- and medium-range weather forecasts; climate prediction/ forecasting for the agricultural, livestock, forestry and fisheries sectors). Agrometeorological information plays a valuable part not only in making daily and seasonal farm management decisions but also in risk management and early warning systems. The ability to integrate information from interdisciplinary sources utilizing new computer-based technologies and telecommunications creates a great opportunity to enhance the role of agrometeorologists in many decision-making processes. The global food security and sustainable agriculture are the key challenges before the scientific community in the present era of enhanced climate variability, rapidly rising population and dwindling resources. No part of the world is immune from meteorological extremes of one sort or another posing threat to the food security. Agrometeorology has to make most efficient use of the opportunities available in achieving the objectives of enhancing productivity and maintenance of sustainability. Increased awareness and technological advancement have provided opportunities to develop efficient agrometeorological services which may cope up with risks. The problem has been recognized to be addressed collectively by scientists, planners and the society as a whole. The conference had upon the above issues to devise improved methods and techniques for better prediction, preparedness and mitigation of the adverse weather impacts on agriculture production. It also has provided inputs about make farming community, risk managers and media aware of the possible impact, consequences and mitigation measures to sustain food security. Perspectives on operational agrometeorological services currently being provided at the national, regional and international level have been critically reviewed and recommendations on addressing the priority issues presented. The urgencies to development products that can bridge the gaps between user needs and its relevance to climate sensitive decision making in agriculture were pointed out, as well as the needs to provide access to information and skills to help farmers make the best possible use resources and services available to them. As stated in the WMO/CAgM Guide to Agricultural Meteorological Practices -GAMP- development and establishment of agrometeorological supports and dissemination of information must increase in all Regions. Agrometeorological services in developing countries have to shoulder greater responsibilities due to greater population pressure and changing modes of agricultural practices. More and more demands pertaining to agrometeorological information and services are expected from the farming communities in the future on technologies, farming systems patterns, water management, weather based pest and disease control etc., preferably with local innovations as starting points. Thus the future challenges include the necessity to emphasize a bottom up approach so that forecasts, specific advisories and contingency planning reach even the small farmers for applications in their planning and day-to-day field operations. Agrometeorological services in developed countries focus on the provision of environmental data and information to national policy and decision makers; mainly in support of sustainable food production, sustainable use of resources, carbon sequestration in agro-ecosytems and land management practices that affect exchange processes of greenhouse gasses. Because developed countries may have or develop technology to initially adapt more readily to climate change and climate variability, technology transfer may play a certain role but local innovations remain most important for application under the very different conditions in developing countries.

8

4- Revision of the operational applications of current agrometeorological data, analytical tools, and information delivery systems. Most of the National Meteorological and Hydrological Services provides agrometeorological services in their country. However, the services provided and the tools available vary from country to country and region to region. 4.1 Region IV: In Region IV, an impressive array of agrometeorological data, analytical tools, and information delivery systems are used. North America- An impressive array of agrometeorological data, analytical tools, and information delivery systems are used within North America to help monitor, analyze, and disseminate agricultural weather information. Canada, the United States of America, and Mexico all have organizations that are responsible for providing agricultural weather information to the local farming communities. Much of this information is disseminated via agrometeorological bulletins or crop reports which contain agricultural weather information. Each of these countries makes extensive use of advanced technologies, such as GIS, remote sensing, and crop modeling, in their agricultural weather monitoring and assessment activities. Some of the resulting data and products are disseminated via the bulletins, while even more of the resulting data and products can be found on the Internet. Following are specific examples describing how these advanced technologies are being used in North America to support operational agrometeorological services on national and regional spatial scales. The Agriculture and Agri-Food Canada (AAFC) Drought Watch Program operationally monitors the impacts of climate variability on water supply and agriculture and promotes practices that improve drought mitigation and response. In support of these efforts, the Drought Watch Program provides a wealth of information to the farming community, including maps of temperature, precipitation, drought indices, soil moisture, and growing degree days at national and regional levels. These products are produced using a variety of data types and advanced technologies, including surface observations, remotely-sensed data, model-derived estimates, and GIS. The Canadian government does not publish a national agricultural weather bulletin, however, several Canadian provinces regularly publish crop reports which contain information describing how weather is impacting agriculture. Provinces known to prepare reports include Alberta, Saskatchewan, Manitoba, Ontario, and Quebec. Much of the agricultural and weather information is provided in text and tabular format, but the inclusion of growing degree data and various maps demonstrates that at the very least simple crop models and basic GIS technologies are being used to aid report preparation. In 1988, Statistics Canada established the Crop Condition Assessment Program (CCAP), an operational decision support system that helps users monitor crop, pasture, and rangeland conditions across portions of Canada and the United States and can be used to forecast spring wheat yields as the growing season progresses. The CCAP is a robust system that uses National Oceanic and Atmospheric Administration (NOAA) AVHRR satellite data to monitor agricultural conditions, linear regression modeling to relate crop yields to these remote sensing data, and a geographic information system (GIS) to visualize and further analyze this information. Thus, the CCAP serves as an excellent example of how remote sensing, GIS, and crop modeling technologies can be combined to facilitate agrometeorological monitoring on national and regional spatial scales. Similar to the Canadian CCAP, the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) uses NOAA AVHRR data to operationally monitor crop conditions across the United States. NASS also uses satellite imagery to help estimate crop acreages and yields and for creating GIS-compatible data layers that identify and delineate select field crops For example, NASS has used Indian Resourcesat-1 Advanced Wide Field Sensor (AWiFS) and National

9

Aeronautical and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) data to help estimate wheat, corn, and soybean acreages at the state and county levels for portions of the United States. The USDA World Agricultural Outlook Board (WAOB), in conjunction with the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC), publishes the Weekly Weather and Crop Bulletin (WWCB), a comprehensive collection of value-added text, tables, charts, and maps summarizing weather impacts on domestic and international crop production. Many of the products contained within the WWCB are prepared using advanced technologies, such as GIS, remote sensing, and crop models. For example, WWCB maps of daily weather records, snow depth, and tropical cyclone impacts on agriculture are created using GIS. NOAA Geostationary Operational Environmental Satellite (GOES) imagery is sometimes included in the WWCB to illustrate significant weather events. Although satellite imagery is not always published in the bulletin, USDA meteorologists regularly examine remote sensing data when preparing their weekly crop weather assessments. NOAA National Weather Service (NWS) radar-derived multi sensor precipitation estimates, NOAA CPC satellite-derived precipitation estimates, NASA MODIS data, and NOAA vegetation health data are among some of the remote sensing products that USDA meteorologists examine each week. USDA meteorologists also use crop models to help monitor crop progress and to help estimate yields. These models are generally simple in nature, relying primarily on growing degree day data and regression analysis to accomplish these tasks. The USDA Natural Resources Conservation Service (NRCS) National Water and Climate Center (NWCC) uses a variety of agrometeorological data, analytical tools, and information delivery systems to support their operational activities. Among the responsibilities of the NWCC is to provide water supply forecasts, water and climate analyses, and water quality and quantity expertise in support of farmstead, field level, watershed, and river basin evaluations. NWCC hydrologists primarily use statistical models while preparing their water supply forecasts. The NWCC has also experimented with the use of simulation models, but the use of such models is currently limited. NWCC staff use GIS extensively to map their water supply forecasts and to display observations of temperature, precipitation, and snow depth on regional spatial scales. Since 1999, NOAA, USDA, and the National Drought Mitigation Center have partnered to produce the U.S. Drought Monitor (USDM), a collaborative product which provides a single snapshot of the spatial extent and intensity of drought across the United States each week. On a rotating basis, a drought expert from one of the partnering organizations serves as the weekly USDM author. During the update process, the author consults data from numerous sources while updating the USDM, including products derived from various surface observing networks, numerical models, and remote sensing data. Examples of these products include maps of the Palmer Drought Index, Crop Moisture Index, Standardized Precipitation Index , radar-derived precipitation estimates, and the Vegetation Drought Response Index (VegDRI). Because the USDM is updated using GIS, many of these products are often imported into the GIS to facilitate data analysis. In addition to examining numerous drought-related products, the USDM author solicits feedback from drought experts across the country as drafts of the USDM are prepared. As a result, the USDM is a robust product that provides a consensus opinion of the drought situation across the United States each week and uses an array of advanced technologies to support these efforts. Building upon the success of the USDM, drought experts in Canada, Mexico, and the United States began working together in 2002 to produce the North American Drought Monitor (NADM) product each month. Similar to the USDM, the NADM is updated using a GIS and incorporates drought-related products and expertise from each country to provide a comprehensive and integrated assessment of drought in the Northern Hemisphere. Mexican NADM authors use a variety of products to help guide their assessments, including maps of the percent of normal precipitation, Palmer Drought Index, Standardized Precipitation Index, satellite-derived vegetation health, and modeled soil moisture. Such products are clearly not just drought specific; these products help agricultural meteorologists monitor the overall impact of weather on Mexican agriculture as well.

10

The National Meteorological Service (SMN) of Mexico publishes a daily agricultural weather bulletin that describes the stages of crop development and how favorable the weather is for agriculture and summarizes recent weather observations and expected changes in the weather across the country. The Secretariat of Agriculture, Livestock, Rural Development, Food and Fisheries (SAGARPA) also provides access to agrometeorological information via an impressive web portal that links to each of the State Offices of Information for Sustainable Rural Development (OEIDRUS. Product availability varies among states, but some of the more common products include maps of crop production potential, recent weather observations, and access to dynamic GIS maps which illustrate the location of agrometeorological stations. The National Research Institute for Forestry, Agriculture, and Livestock Production (INIFAP) offers a variety of agrometeorological products and services to the farming community in Mexico. Data from a network of more than 800 agricultural weather stations are downloaded every 15 minutes by the INIFAP National Laboratory for Modeling and Remote Sensing. These data are used to produce static maps of temperature, precipitation, and relative humidity for varying time scales on the state level. The National Laboratory for Modeling and Remote Sensing also offers a dynamic GIS mapping capability, enabling customers to generate national or state maps of cumulative precipitation, average temperature, average relative humidity, and average radiation for user-defined time periods. Finally, INIFAP offers a number of interactive applications on-line, including the ability to calculate the growing degree days for numerous crops, station evapotranspiration, and water requirements for vines. Central America. In Central America, the quantity and diversity of the agrometeorological data, analytical tools, and information delivery systems used in providing operational agricultural weather services is somewhat less than that in North America. Likewise, the use of GIS, remote sensing, and crop modeling in support of these services is generally more limited. Although few Central American countries have been successful in incorporating these advanced technologies into operational agricultural weather programs, the capacity to adopt these technologies for such purposes appears to be growing. Following is an examination of the agrometeorological products and services provided in Central American countries and examples of the advanced technologies that are currently being used in each country. In Guatemala, the National Meteorological Service (NMS) and Ministry of Agriculture collaborate to periodically publish an agrometeorological bulletin. The most recent publication included a summary of the current weather patterns, a forecast of the onset of the rainy season, and recommendations regarding the best time to sow crops. The bulletin also contained an NDVI map, demonstrating their use of remote sensing data. The Internet sites for the Guatemalan NMS and Ministry of Agriculture [26] provide evidence that GIS is regularly used to prepare maps, some of which likely aid agrometeorological monitoring. In El Salvador, the NMS regularly prepares three agrometeorological bulletins each month. These bulletins contain an abundance of agricultural weather information, including national maps of available soil moisture, time series of air temperature, soil temperature, and hours of sunlight for stations located in different agricultural zones, and value-added text describing the recent weather and observed crop development. The El Salvador NMS uses GIS to generate several operational weather products, including maps of temperature, precipitation, and climate zones. The Costa Rica NMS web site provides links to several papers documenting the relationship between ENSO and agricultural production. GIS and crop models were used while conducting these studies. Although the Costa Rica NMS does not prepare agrometeorological-specific forecasts, they do provide ENSO forecasts in their monthly bulletin. Given the link between ENSO and agricultural production, the value of their ENSO forecasts could be improved by including likely agricultural impacts with their ENSO forecasts. It is unclear if the National Meteorological Services of Nicaragua and Panama regularly prepare agricultural-specific weather products, but both agencies clearly recognize the impact weather has

11

on agriculture. Furthermore, both countries use advanced technologies in support of their meteorological services. For example, the Nicaragua NMS has participated in studies aimed at reducing the vulnerability of the agricultural sector to climate variability. The Nicaragua NMS has also used a range of GIS software to map natural hazards and to conduct scenario analyses. In Panama, one function of the NMS is to provide meteorological information to help the agricultural sector determine the optimal time to plant and harvest crops, monitor drought, and manage irrigation supplies. The Panama NMS has used GIS to create numerous products, including maps of rainfall, temperature, and potential evapotranspiration. Thus, if NMS personnel in Nicaragua and Panama have agrometeorological training and access to agricultural data, the potential exists for both agencies to provide relatively robust agricultural weather products to the farming community. Elsewhere in Central America, the Belize NMS has an agrometeorological section that provides four day forecasts of temperatures and precipitation, but it does not appear that GIS, remote sensing, or crop modeling are used in the preparation of these forecasts. In Honduras, the NMS provides monthly regional rainfall forecasts in both tabular and map format, but there is no reference to agriculture in the provision of these products. Caribbean In the Caribbean, the National Meteorological Services of several countries indicate that they provide products and services to support local agricultural interests. Within this group, only a few countries use advanced technologies, such as GIS, remote sensing, and crop modeling, to facilitate agrometeorological data display and analysis. Of the remaining countries that provide agricultural weather services, product availability appears to be limited. Following is a more detailed examination of the agrometeorological data, analytical tools, and information delivery systems that are being used in the Caribbean. The Meteorology Institute of the Republic of Cuba publishes a decadal agrometeorological bulletin which contains a variety of products that benefit the local agricultural sector. Example products include maps of rainfall, vegetation conditions, and agricultural drought; tables of weather data for select agrometeorological stations; and value-added text summarizing weather impacts on crop progress and conditions. The Cuban NMS uses advanced technologies extensively in the operational production of these agricultural weather products. For example, the NMS uses quantitative models to determine crop water availability, estimate crop yields, and forecast the potential arrival of mold spores. In addition, GIS plays a key role in the provision of agrometeorological services. GIS is used to process, analyze, and display a large quantity of agricultural weather data and serves as an important component in operational agrometeorological modeling activities. The Caribbean Institute for Meteorology and Hydrology (CIMH) is a training and research organization that seeks to improve meteorological and hydrological services throughout the region. A component of the CIMH is the Caribbean Agrometeorology Network (CarAgMet). Member countries of CarAgMet include Barbados, Grenada, Guyana, Saint Lucia, Saint Vincent/Grenadines, and Trinidad & Tobago. One of the primary goals of the network is to provide information and advice to the farming community to enhance agricultural productivity in the Caribbean. Through various studies, CarAgMet has demonstrated the benefits of using GIS and crop modelling to process, analyze, and display agrometeorological data, however, the use of advanced technologies to support operational agrometeorological services appears to be limited. The Dominican Republic National Bureau of Meteorology has an Agrometeorology Division that generates several agricultural weather products each month. Example products include tables summarizing various rainfall (e.g., total rainfall, percent of normal rainfall, maximum rainfall in 24 hours, days of month rainfall observed) and temperature (e.g., record maxima and minima) statistics. The Agrometeorology Division also publishes a monthly agroclimatic bulletin that describes the recent weather in each cropping area, provides data describing crop water requirements during different stages of development for various crops, and offers producers advice in response to recent weather observations. Although the Dominican Republic NMS generates a variety of operational agrometeorological products, they do not appear to use GIS and remote sensing technologies to support these efforts.

12

Elsewhere in the Caribbean, the Jamaican NMS provides weather information to the farming community, but NMS personnel indicate a desire to work more closely with the Ministry of Agriculture and to use GIS to map crop zones. Similarly, the Dominica NMS and the NMS of the Netherlands Antilles and Aruba indicate that they support the agricultural community, but the products and services provided and the use of advanced technologies is not evident on their web sites. Finally, some countries do not appear to provide operational agrometeorological products or services to their local farming communities. Such countries include the Bahamas, Haiti, and Antigua and Barbuda. This review of the operational applications of current agrometeorological data, analytical tools, and information delivery systems at the national and regional levels has revealed that only a handful of countries within the Region were found to use these tools extensively to support the operational provision of agrometeorological products and services. Such countries include Canada, the United States, Mexico, Guatemala, El Salvador, and Cuba. A common theme shared among these countries is the presence of well-established organizations and partnerships within each country that provide operational agrometeorological products and services as part of their mission. Furthermore, these organizations and partnerships are often staffed by well-educated, highly-skilled individuals that have not just embraced, but often promote, the notion that accurate and timely weather and climate information can significantly benefit sustainable agriculture. This combination of resources provides a favorable environment for incorporating new technologies into operational agrometeorological services and can serve as a model for expanding the use of advanced technologies elsewhere throughout the Region. Of the remaining countries within RA-IV, the majority have used advanced technologies to facilitate various meteorological and agricultural activities, but not necessarily operational agrometeorological activities. For example, the National Meteorological Service of Nicaragua has used GIS to map natural hazards and to conduct scenario analyses, while the Ministry of Agriculture in Jamaica has used GIS to evaluate soil and land use patterns. In these and other cases, organizations have demonstrated their proficiency in using advanced technologies to address agricultural-specific and meteorological-specific issues, but these organizations do not appear to be using these capabilities to support operational agrometeorological products and services. Significantly, various studies have demonstrated how GIS, remote sensing, and crop modeling can be used to better understand weather and climate impacts on agriculture within the Region. For example, GIS and crop models were used in studies linking the phase of the ENSO to agricultural production in Costa Rica. In this and similar studies, advanced technologies have been helpful in identifying agrometeorological relationships, but transitioning these new findings and technologies into operational agrometeorological products and services has been slow to occur. Thus, the majority of the countries within RA-IV have demonstrated the potential to use advanced technologies to support agrometeorological products and services. More work is needed, however, to incorporate these technologies into operational applications. Some of the information contained within this report was obtained through personal communications (e.g., email, in-person conversations), but much of the information was gleaned from the Internet (e.g., agency web sites, conference proceedings, peer-reviewed publications). The availability of information varies significantly among countries; some countries offer a thorough description of their operational agrometeorological products and services, while other countries provide little, if any, details. Although some countries provide little information because they offer few products and services, other countries appear to offer relatively robust products and services but provide little supporting documentation. As a result, it is possible, if not likely, that the use of advanced technologies is more widespread than reported here. Finally, the examples presented in this report are intended to provide some insight into the operational use of GIS, remote sensing, and crop models in RA-IV countries. These examples do not necessarily represent the full capabilities of each country.

13

4.2 Region III. The aspect of the agro-meteorogical services operational applications, established in the member countries of the AR III have been surveyed through a questionnaire developed with the purpose to monitor the current situation and obtain information that can contribute to formulate recommendations in the procedures, methodologies and resources to improve the capacity of regional base for operational applications in agrometeorology. Countries objects of the survey were Peru, Argentina, Colombia, Chile, Equator, Bolivia, Venezuela, Brazil, Uruguay and Paraguay. A high percentage of the Agrometeorogical Services in South America are tied to the National Weather Service and they are depending on the economic resources of the State. Nevertheless, in some countries like Paraguay and Venezuela, there are agrometeorogical units that do not directly depend on the National Meteorological Service. In the case of Paraguay the developer the of Agrometeorogical services are the Direction of Agricultural Investigation and the Program of Agrometeorology of the Department of Agriculture and Stockbreeding; in the case of Venezuela this role is assigned to the Institute of Agricultural Investigations (INIA) and the Department of for the Environment MPPA. The 70% of the National Weather Services, have agrometeorological units independent in the operational aspects, and 100% of them economically depend on the state contributions: this makes them highly vulnerable in the budgetary allocations when the domestic economy is suffering or in the cases when the governmental priorities are changed. The main users of the agrometeorological services generated in each country are the individual agricultural producers, or associated, who directly benefit from the decisions for the daily agricultural management and/or medium term planning. Updated agrometeorogical information are diffused directly to the farmers through official companies that likewise utilize such information in its Management (Departments of Agriculture, mass media, Regional Governments, Forest Corporations, Agricultural Services and cattle Raiser and other). Is important to indicate that some companies, as the National weather service of Argentina, diffuses the totality of its products through a website, in which is possible to obtain information of: water balance (decadal), agroclimatic bulletin (decadal, including descriptions and maps of temperature, haste, humidity, degrees day and relative humidity, covering the area from the latitude 22º South and 42º South), evolution of main cultivations, soil humidity, daily forecasts (validity 24, 48, and 72 hrs), processed satellite imagery, (that indicates the density of the vegetation through the Green index factor) and maps of average decadal of effective solar heliophany. The operating agrometeorological products provided by the National Weather or Hydrologic Service in South America are meanly based on bulletins and agrometeorological announcements, such as daily forecasts of special events communication, or warnings. In the special case of Chile warnings of frost, forest fires, or vegetable plagues are provided, unfortunately this last warning has been suspended after having been prepared for a decade due to the lack of information about insects capture. In general, the Agrometeorological Services National of the various countries incorporate in their functions the elaboration of studies and investigations that serve and support the agricultural sector. For example, the Service of Brazil diffuses information of support to the Agrarian Reform and the Family Agriculture; Chile continues devising agricultural zoning advices of some regions, provided for their operational application to the National Institute of Investigation Agribusiness (INIA), Offices of the secretary Ministerial of Agriculture, etc. As reported in Tab 1., the countries of Region III use, on the average, 77% of the total of the existing technological capacities (GIS, satellite products and software) in their procedures for agrometeorogical applications operations, but the satellite information is fundamentally used for the forecast and it is not specifically supporting operational agrometeorogical application. About he use

14

of these technologies, strong gaps exist among the different countries. Argentina and Uruguay reach the lowest values, between a 20% and a 30% of the available capacities.

Table.1 Availability of data, analytic tools and methods in the Agro-meteorological services. 86% of the countries (Table 2) consider that the availability of data is deficient. The efficiency of available computational database of fast consultation is greatly suffering when interruption of information occur. In the case of Chile, it is expected to incorporate during the year 2009 the information generated by the agrometeorological network to the Climatological database of the National Weather Service. The development of computational methods has permitted to the 29% of the countries to include especially statistical and analytic tools which have applied in studies and investigations operated to support the productive agricultural sector. This facility of analytic tools (software) incorporated the computation should, however, be associated to the capacity of the professionals to understand them and to apply them. This aspect itself does not comply in a large extent of the region, due to the self-taught learning of such software. The experience of the National weather service has served in the majority of the countries (57%) as a pivot to establish methodologies, in particular forecasts as other aspects related to the diffusion of weather service applied to the agriculture., as shown in Table 2.

Table Nº2 Expression of limits and problems to carry out agrometeorological services. CHILE ARGENTINA COLOMBIA PERU VENEZUELA BRASIL ECUADORa) actual availability of data

NO YES YES  YES NO YES YES

b) analytical instruments .

NO  YES YES YES NO YES YES

c) methods for the supply of operational agrometeorological services

YES NO YES YES NO YES YES

Table 2 Resources to be developed to improve the capacity of operational applications In general the satellite products for agrometeorological practices in the region are scarce. Images utilized are form GOES 12, NOAA 15 and 17, GOING, SENSE and WV for supporting the generation of forecasts. They are few the countries utilizing the NDVI in the shape of data and of image or images of Hidroestimadores GOES and CMORPH. In some countries as Paraguay, images are bought inside the Risks Management Unit (UGR) of the MAG and works through conventions with Institutes of investigation, Universities and private institutions to share the costs of the images. Also the information freely available in the WEB are utilized, as in the case of Modis products According to the survey, although the countries consider necessary the satellite information in agrometeorogical applications, NMHS utilizing satellite products specifically for these applications are scarce, and the generalized use of satellite technology is exclusively for supporting the generation of forecasts. This is due to the difficulties in accessing information, lack of training of qualified personal y and high cost of the technology.

15

Some agrometeorogical indexes obtained, emitted and utilized by the NMHS for agrometeorological practices originate from satellite products. These applications are mainly based on estimations and comparison of vegetation normalized indices (NDVI), estimation of the index of vegetation leaf area indexes (IAF), maximum and minimum relative humidity, thermal oscillation, number of rainy and sunny days, and composite indices generated from several variables, i.e. water balances, start and finishing dates of the rain season, number of humid months.

The 80% of the NHMS the Region have knowledge about Geographical Information Systems, that are hence quite largely utilized in agrometeorological applications. Main uses are about the generation of agroclimatic risk maps in cultivations, agricultural zoning and agrometeorology advices, elaboration of thematic maps, simulation modeling, pest and diseases warnings.

Data availability is a key point in support systems: some country, as Chile, is improving the availability of basic information, with the execution of a project among institutions linking the agricultural (INIA: National institute of Investigation Agribusiness, FDF: Foundation of Agricultural Development) and the weather (DMC: Weather direction of Chile) communities. Through this project, in the first semester of the year 2009 a network of 110 automatic stations with remote interrogation was established for the benefit of the operational agrometeorology operational. Insufficient training in the management of analytic tools, exploitation of the satellite technology and its application in the agrometeorological operational, besides limitations in the methodology for the provisioning of operating agrometeorogical services and scarce technological resources are constant problems to be remarked for nearly all countries.

To the common opinion, the operational capacities of the national agrometeorological services could be fortified by establishing internal strategic alliances with other services of the region, with the purpose to better qualify agrometeorology people in elaboration of products based on satellite parameters., to ensure adequate use of GIS, remote sensing and technological transfer. Important tools to be fortified are quality control of the basic data, availability of GIS and RS products, satellite receivers of highly resolution and ability to manage satellite-based parameters to be applied to operational agrometeorology, availability of guides and publications in Spanish, agrometeorogical models and numerical models for seasonal predictions. Integrated courses, as the previous HIMAT in Colombia, are concrete possibilities to reinforce the capabilities to adopt support systems, and the necessary competences are available within the Region, as for example in CPTEC-SDA and the University of Costa Rica

In recent years the 50% of the NMHSs have involved the farmer to assess the ways and the structures of the weather products applied to the agriculture, utilizing surveys that have outlined the needs of agrometeorological information, considering farmers needs and requirements for short, medium and long time planning and contributions to the sustainability of the operational applications. An increase of efficiency in communication should assure as a minimum that the information is obtained in continuous form; with networks that tend to the modernization, to favor a progressive development in the operating aspect and of agricultural planning. In this way, it would be possible to contribute directly to some innovation as, for example, precision agriculture.

4.3 Region I. About 200 millions Africans are chronically hungry, and nearly 30 millions require emergency food and agricultural assistance in any one year. The number of Africans living in absolute poverty (with incomes of 1 dollar a day or even less) has risen to 340 millions, and most of this people relies on subsistence agriculture.

Climate is a key variable for Africa: most of Africa’s disasters are meteorologically related, posing serious threats to the continent’s ability to attain the Millenima development goals and sustainable development. The livelihoods of many millions of people, especially in the less developed countries, are critically dependent on seasonal climate.

The continent encompasses a rich mosaic of ecological settings, which together contain a wealth of biologically and economically important resources. The continent of Africa has varied climatic regions, from the West through the Centre to the Horn, North to South. One quarter of the continental land area is hyper-arid, one third is humid and the remainder is dryland, comprised

16

mainly of semi-arid and dry sub-humid. The rainfall systems are different in different regions or within the same countries; Unit-modal system with one peak within the calendar year .Bimodal system within the calendar year and even overlapping to two calendar years, roughly 90% of agricultural activities are rain fed with only 10% irrigated.

With a rain season length of the order of 90 days, the northern part of the Sahel is most sensitive to climatic fluctuations even if the drought resistance of traditional food crops is naturally high even though at seedling and flowering time sensitivity to water stress remains high. A dry spell during these periods can cause the complete loss of the harvest. Meanwhile, in the southern areas where the climate is not a limiting factor and the agriculture production systems are more differentiated: food crops, with long cycle varieties, are more sensible during rain season onset, forcing the farmers to repeated seedlings.

Varied cropping and animal production systems are practiced with varying degrees of involvement. The climate and geophysical characteristics of each region determine its level of involvement in either the cropping or animal production systems. Other determining factors worth mentioning are the financial, technical and skilled man power as well. Sub-Saharan African economies are predominantly agrarian in structure, despite persistent food crises, agriculture remains the highest employer with 70% of the work force in the rural sector and 25% of GDP derives from it.

Agrometeorological tools used to salvage this economic sector and enhance the living standards of those involved are described below. The level of usage of each depends on their technical know-how, as well as the economic potentials of each country.

The survey of operational support systems given here is mainly regarding Egypt, since Egyptian Meteorology Authority (EMA) was supporting this work inside this OPAG:

Several operational applications of current agrometeorological data are active to support farming activities. The chilling requirements of many fruit species are forecasted, with the objective to predict time for spraying hormone for breaking dormancy status, yield quality and quantity, expected harvesting date for each crop at different locations. Outputs are weekly reports (form October to April) which describe the accumulation of chilling requirements (in %) for major deciduous fruit trees, by using hourly temperature data from observation networks of meteorological stations.

Specific services regard economically important crops. Cotton is a very significant crop in Africa: applications to planting data determination are a primary objective in several countries, with the aim to identify the planting time within the proper temperature that suits seed germination and seedling growth without occurring in early spring climate hazards. The application is used regularly as a reference in the Egyptian cotton cultivation national wide. Outputs are daily recommendations which are sent by fax to each governorate from mid-February to the end of March, and are based on the temperature forecast up to 10 days in order to estimate daily soil temperature at the depth 20 cm. A combined observational-modelling approach is carried out, where hourly soil temperature (°C) from observation network of agro meteorological stations are integrated by tools developed within specific researches that predict the value of maximum daily soil grass temperature at depth 20 cm. Simple relations and linear equations are used so far, with the prevision of utilizing MESSIR-VISION Server Operational Data Base (ODB) to forecast 10 day from Numerical Weather Prediction (ECMWF)

Weekly reports are prepared which contain heat units for main strategic crops (wheat, maize, rice, potato, soybean, sugarcane, cotton and faba bean), frost injury early warning, water and fertilizing requirement. Forecasts of the flight path of desert locusts are utilized in Egypt the charts of wind direction at 500-meter height from (NWP).

An important application of meteorological forecast is dedicated to the long range forecast of Nile flood. Egypt’s main and almost exclusive source of surface water is the river Nile, one of the longest rivers in the world with a total length of 6710 km. Long range forecasting has both theoretical and practical implications. A number of studies on specific regions during different seasons revealed the existence of certain predictive potential associated with short-term climate

17

variability. Deterministic climate models and statistical techniques have been built to use this predictive potential.

Investigations have correlated Sea Surface Temperature (SST) fields over Indian, Pacific and Atlantic oceans with the total Natural flow of the river Nile at Aswan. Sea surface Temperature (SST) over six different regions have been found to be correlated with the total natural flow of Nile at Aswan throughout the years . Also, a multiple regression model has been developed to forecast the total natural flow of the river at Aswan. A month forecast (July) of Nile flood is released, and many research activities are in course, developing the forecast method using CLIMLAP software tools.

In Egypt, evaporation form Nasser Lake is one of the important elements for water budget and water management. Lake Evaporation is estimated by aerodynamic formulas using meteorological measurements from floating station on the lake. Cooperation between EMA and The Permanent Joint Technical Commission for Nile waters (PJTC) .Monthly reports of evaporation of Lake Nasser are issued.

Africa has a large number of agro meteorological observation tools: the location of the 495 stations including Agro meteorological and Meteorological stations is reported below. The data derived from observation tools are utilized in most Meteorological and Agrometeorological Services in many Countries in Africa

Figure 1. Location of 495 African stations Some interesting project is under preparation to be operationally applied in Africa: PUMA (Preparation for the Use of Meteosat Second Generation MSG in Africa is a European sponsored project is for better application of MSG in exchange of satellite derived data on weather

18

parameters, images and models. MESSIR VISION software is being developed by Corobor for exploitation. EMA wants to develop its capacity to produce added value forecasting products in the field of agro-meteorology, marine and general forecasting. This goal will be reached through the implementation of an Operational Data Base (ODB) for agro-meteorology and general meteorological data and also EMA operate an atmospheric model over Egypt, it should be integrated with the system. Between the analytical tools available, some computer-based models that simulate weather data for crop modelling and risk management are: Crop Yield Models, as Crop simulation software – DSSAT, Decision Support System for Agrometeorological Transfer to improve farm management, especially in decision making strategies; Statistical packages INSTAT, already useful for agriculture, now with added tools for environmental analyses like the statistics of extremes, with a free version for Africa now available; FAO and DAILYET software tools to calculate evapotranspiration, freely available for Africa, CLIMLAB. The Egyptian Meteorological Authority on agricultural climatology since 1980 has developed method for the analysis of climatic data, particularly temperature, wind speed and relative humidity records for agricultural planning and issues regularly the" Ten-Days Agro meteorological Weather Report "(TDAWR). The report gives climatologically data and weather information's from 12 selected meteorological stations which represent different districts of the country, supporting farm activities, crop production, plant protection, water balance for crops. This report, that is low cost and may be exported to all countries, can be a useful support system for agrometeorological purposes. 4.4 Region II. For Region II, some countries like China and India provide a variety of agrometeorological information and forecasting services on operational basis. They also use advanced technologies such as GIS and remote sensing as well as numerical models to determine crop growth/condition/yield. These two countries also have soil moisture monitoring stations unlike the other countries in the Region. Pakistan and Mongolia also provide agrometeorological services in their country but the range of products and services are limited compared to China and India. Most countries in the Region disseminate their information thru internet and also radio broadcasting. This report is mainly related to the development status of Chinese Agrometeorological Service Support System, given the involvement of the Henan Institute of Meteorological Sciences in this OPAG. China is transforming its traditional agriculture into modern agriculture, which is characterized by advanced science and technology, commercialization, intensiveness and industrialization. As a result, agrometeorology is challenged by a series of new situations, demands and tasks. It has been a general trend to promote the development of modern agrometeorology as a strong scientific support for modern agricultural production, aiming at realizing agricultural disaster prevention, socialist new countryside construction, national grain security and so on. Modern agrometeorology is a new system featured by automatic monitoring, accurate forecasting, quantitative evaluation, systematic services, electric transmission and export personnel. Therefore, the data, materials, technologies, measures, index, modules, equipment and operation procedures of traditional agrometeorology shall be improved and promoted, so that traditional agrometeorology can be transformed into modern agrometeorology. As a result, a series of new demands on agrometeorological observation, material processing and information transmission are raised. The routine meteorological data include air temperature, precipitation, precipitation day, evaporation flux, sunshine duration, solar radiation, wind velocity and direction, ground temperature, different depth soil temperature, atmospheric circulation index, SST, etc. Crop data regard: Crop growth stages, growth quantity (like density, LAI, etc.), yield formation elements, plant diseases and insect pests, agrometeorological disasters, etc. from each agrometeorological observation station, and data on natural pasture growth period and yield, livestock and herding in

19

some areas (like Qinghai and Inner Mongolia). Data on soil features soil humidity, wilting moisture, field capacity, dry soil layer and precipitation penetrating depth for some units, aiming at guiding the fertilizing on the basis of diagnosis of soil fertility. Ecological data: are about water area of lakes, water temperature, water table, flow flux, water quality, soil erosion, forest fire disaster, heavy fog, marsh area, etc., and ecological element monitoring data including dustfall, atmospheric particulates, natural pasture yield and nutrition, soil moisture and nutrition, wind erosion, due traveling, etc. from ecological observation stations in Qinghai Province. Satellite data are including EOS/MODIS, NOAA/AVHRR, FY1, FY3A, TM, ETM+, CBERS, SPOT, QuickBird and IKNOIS. Remote sensing data from polar meteorological satellite are mainly transmitted through DVBS and received freely. There are systems in some provinces (municipalities or autonomous regions) to directly receive and process EOS/MODIS and polar meteorological satellite data. GIS data are fundamental geographic data with the scale of 1:4,000,000, 1:1,000,000, 1:250,000 and 1:50,000. The main data processing tools in provincial agrometeorological services at present consist of data processing software like Excel, Access, SPSS, SAS, Matlab, Sufer, Grapher and SQL server 2000, remote sensing image processing software like ENVI, ERDAS and PCI and geographic information system software like ARCGIS, Arcview, Mapinfo, MAPGIS and SUPERMAP. The polar meteorological satellite data and EOS/MODIS data are mainly processed through the satellite data receiving, processing and analyzing software and systems developed by Beijing ShineTek satellite Application System Engineering Co., Ltd. In addition, there are also AB agrometeorological data coding program, precipitation and soil moisture statistics software and data inquiry software which are developed independently. In order to promote the provincial agrometeorological operation level, China Meteorological Administration organized 10 provincial (municipal or autonomous region) meteorological bureaus including Anhui, Henan, Hebei, Hubei, Guangxi, Beijing and Jiangxi and developed the new generation of Provincial Agrometeorological Operation and Service System (PAMOS), which was a comprehensive agrometeorological operation and service system and included the functional modules of database, agrometeorological information, agrometeorological forecasting, agrometeorological resource development and application, satellite remote sensing and agrometeorological information service and has been widely applied in the meteorological departments of 34 provinces, municipalities and autonomous regions of China. In addition, according to the local agricultural production features as well as the contents of agrometeorological services, the agrometeorological operation and service system is also developed with the functions covering agrometeorological information forecasting, agrometeorological disaster monitoring, alarming and evaluation, soil moisture monitoring and forecasting, crop yield and growth period forecasting, plant diseases and insect pests forecasting and remote sensing monitoring, etc.:Agrometeorological information forecasting include agrometeorological ten-day/monthly report coding system, ten-day/monthly report analyzing and processing system, agrometeorological information forecasting system and observation information and operation system of autonomous meteorological station. Agrometeorological disaster monitoring and early warning evaluation are well developed. They are mainly including drought monitoring evaluation and early warning system, drought or excessive rain monitoring system (soil moisture), drought disaster damage evaluation mode, dry-hot wind disaster damage evaluation mode, low temperature and cold damage forecasting mode for rice, late frost damage forecasting mode and agrometeorological disaster monitoring and early warning system. Soil moisture monitoring and forecasting are about soil moisture analyzing and processing system, soil moisture drawing system, soil moisture forecasting system, soil moisture monitoring and predication operation system, meteorological service and operation system for optimal water-saving irrigation.

20

Yield forecasting system, growth stages forecasting system, crop yield prediction system are based on dynamic—Stat. model (such as WOFST or DSSAT for wheat, DYCYFOS for Maize), simulation system on meteorological influence on rice growth and yield, Rcsodsvb of Jiangxi, medlar picking stage forecasting mode, etc. National meteorological grades prediction system on plant diseases and insect pests occurrence, meteorological prediction system on locust disaster in the grassland of Inner Mongolia, meteorological prediction system on pine caterpillars disaster in Aershan, Inner Mongolia, predication system on Phytophthora infestans of potato in central Inner Mongolia, locust disaster forecasting service system of Qinghai, meteorological prediction system on rice insect prevention in Chongqing, meteorological prediction system on rice blast in Chongqing, meteorological prediction system on main rice insect disaster in Fujian and medlar black fruit disease forecasting mode; Satellite remote sensing is operationally applied in several cases: monitoring mode on rubber growth of Hainan province, monitoring system on fire disaster, plant growth, soil moisture and heavy fog, ecological environment monitoring and evaluation system, monitoring model on natural pasture yield and evaluation model on grazing capacity in cold season in Inner Mongolia, meteorological prediction system on forest fire disaster, monitoring system on forest fire –point, information system on climate resources and ecological environment in northeastern China, polar meteorological satellite receiving and processing system of Liaoning, meteorological satellite environment monitoring system of Liaoning, DVBS satellite controlling and processing system of Liaoning and remote sensing satellite material processing platform of Liaoning. The national meteorological administration has entrusted SuperMap Company to develop the System of Elaborate Agricultural Climate Zonal Product Making and some provincial and municipal meteorological bureaus have developed some agricultural climate zone systems and other systems by themselves, including agricultural climate zone division system of Fujian, meteorological evaluation system on ecological quality of Fujian, simulation mode on banana planting benefit of Hainan, calculation software for reference evapotranspiration and crop water demand in farmland, decision-making accessory system for agricultural communication system in Xingtai city, greenhouse vegetable service system in Cangzhou city, characteristic agricultural service system in Cangzhou city, spun gold date service system, drought index inquiry and forecasting system of Cangzhou city, vine meteorological service system in Qinghuangdao city and sunlight greenhouse vegetable service system in Shijiazhuang City. Surface meteorological station shall upload the real-time elements including temperature, moisture and wind to the provincial meteorology bureau in the form of code with ftp, and the provincial meteorology bureau shall upload them to China Meteorology Administration. The elements are uploaded efficiently and accurately, for the provincial, regional and national meteorology departments are all provided with the code recognition and translation system which is developed independently. The agrometeorological station shall upload the real-time elements including disaster and soil moisture to the provincial meteorology bureau in the form of code with ftp, E-mail and web office system, and the provincial meteorology bureau shall upload them to China Meteorology Administration. The elements are uploaded efficiently and accurately, for either the national meteorological operation and service information system or the meteorological information and disaster information input system developed by provincial units is able to decode and analysis the data. The remote sensing data of MODIS, NOAA and FY etc. are mainly received freely through DVB-S system. Some provinces have established the operation systems which are able to receive satellite data directly. Such as crop planting area, insect pest area, etc. which shall be gained from agricultural departments and so on in the form of E-mail, fax and letter without fixed periods. Many media are used for the releasing of service products information. The Chinese Meteorological Administration has a special TV meteorological channel which consistently

21

broadcasts meteorological information like weather forecast, weather report and weather news and related news on agriculture, environment, traffic and tourism for 24h a day. What’s more, in case there are serious meteorological matters like typhoon landing and sand storm, the channel will have live reports and broadcasting. NMC will release the latest weather forecast every 1 hour and agricultural meteorological forecast regularly. Some areas like Shandong Province also set special meteorological channels which can be received by CATV users within the areas. The important agrometeorological information of the areas shall be co-released by the meteorology bureau and the local TV stations. China Meteorological News, as the only special meteorological newspaper in China, is dedicated to publicizing best meteorological services, especially meteorological decision-making services as well as their huge benefits, rapidly developing construction of meteorological modernization, thriving ideological civilization construction and the magnificent achievements under the guidance of the reform and opening-up policy, and popularizing meteorological science and technology. The key provincial or regional meteorological news or agrometeorological service column shall be publicized in the local newspaper. Network has been the most popular mode for agrometeorological information releasing at present. The city (or provincial, national) meteorological departments are all provided with special websites to release meteorological information and related services regularly or irregularly. Some data are shared in the form of computer texts (like word) or computer forms (like excel) within a LAN, or transmitted through Lotus NOTES system or E-mail. The other meteorological information releasing media include radio, public screen, loudspeaker in countryside, cell phone text, news conference, fax and governmental information exchange. Some provinces even establish the information releasing systems of their own, such as Qinghai meteorological information operation system and Chongqing meteorological information sharing platform. The application of the analysis tools and operation systems above provides better meteorological services for the promotion of agricultural productivity, enhances the efficiency of agricultural productivity and promotes the ability of operation application. However, there are still problems limiting the potentialities of current support systems. Poor agrometeorological observation measures and low degree of automatics in data acquisition is still a limit: soil drilling, aluminum alloy, drier, scale and calculator have been used in soil moisture observation for year, and crop and phonological observation are undertaken completely through manual sampling, granular counting, manual collection of agrometeorological observation data, agrometeorological report excerption and manual auditing, which both take more time and make more mistakes. In addition, there are less agrometeorological automatic observation programs, which are unable to meet the demand of operation services. With the development of modern agriculture, consistent adjustment of agricultural planting structure and production formation as well as the development of urbanization and industrialization, some crops for observation have been useless. The changing of observation targets has made the observation lands and agricultural production technology and observation data unrepresentative. Poor effectiveness of agrometeorological observation data regard some important parameter, as soil moisture. Since the observation of soil moisture takes more time, it used to be undertaken 1-2 times per ten days, which makes the data obtained invalidly and thus unable to meet the demand of real-time monitoring. In addition, since the agrometeorological observation data are transmitted in code, some information cannot be uploaded and applied in time, for they cannot be included into the coding scope due to the limitation of code. Meanwhile, the agrometeorological (AB) report and soil moisture report are not uploaded timely.

22

The mathematical statistics analysis programs and remote sensing data processing software applied into the operations at present are too expensive to be developed and promoted. Moreover, there are more general software and programs than special data analysis tools for agrometeorological field, and the development programs in different provinces are limited in functions and automatization. Due to the lacking of promotion trainings on the data analysis tools (including INSTAT, AgroShell, etc.) recommended by WMO, the tools are seldom used in the daily agrometeorological operation services. Chinese agrometeorological operations are short of the data analysis tools and pre-evaluation systems for the evaluation of the effect of climate changes on agriculture. There are many types of agrometeorological services, each of which has different demands for data, materials, methods and systems. At present, the operation system and software are universal in the country, so they are with low error rate and unable to the meet the demands of different climate areas and different provinces, though they are functional. The agrometeorological operations are in short of mechanical mode and perfect agrometeorological disaster monitoring, warning and evaluation systems. The technologies and methods for agrometeorological services are often obsolete and shall be renewed. Remote sensing data and GIS data are just applied initially, so the quantitative remote sensing application is in low level without further development. The agrometeorological forecasting technologies are developing slowly, and the agriculture weather forecasting including seeding period forecasting, key growth period forecasting, agrometeorological disaster forecasting and insect pest forecasting which are closely connected to agricultural production shall be further strengthened. In addition, the forecasting and prediction on characteristic agriculture, construction agriculture and fishery shall be developed more deeply. What’s more, the quantitative, dynamic and mechanical numerical simulation method for crop growth is mainly applied to field experiment, which still has a long way to go before being used in operation. The agrometeorological information service products are not that normative and quantitative. There are no necessary agrometeorological index and quantitative evaluation models. Meanwhile, the evaluation of the effect of climate conditions on agricultural production is still mainly described in common words with low quantification which is unable to better meet the demands of users. Information delivery system suffer from various limitations. The agrometeorological observation contents are generally complicated and include a large amount of descriptions, and code is unable to fully and correctly reflect the situation of large fields, so the provincial or national units are not able to be informed of enough information. The releasing of meteorological service products used to be undertaken from superior to inferior and from decision-making departments to local functional agricultural departments, so the peasants are unable to receive the service products or receive them with great postponement. Highly-effective and automatic information releasing systems are still lacking.. The service product makers have to spend a lot of time in transforming the pattern of the same material, inputting them to the Internet, adding receivers, changing file names and uploading with ftp or sending with E-mail, which are so lowly-efficient and easy to make mistakes. Single agrometeorological service productions are not well integrated with the new technologies like RS and GIS, etc. The information coverage is limited. For instance, the meteorological alarming news publicized through cell phone text or countryside loudspeaker can only be received in rich and plain areas, and the news released through TV can only be received by CATV users. For the remote or poverty-stricken areas, there are limited facilities to receive agrometeorological information. Effective feedback mechanism is missing. The servers and decision-makers are hard to be informed of the effects of the service after releasing the products, which is unfavorable to find out

23

problems and make improvement. Agrometeorological information is slowly renewed (usually once a month or per ten days). Though some areas have begun to release agrometeorological forecasting information per week, the information is not publicized consistently and timely. 4.5 Region V. For RA V, many countries provide agrometeorological information and services through the agrometeorological service unit in the national meteorological and hydrometeorological agencies except Fiji. The services are mostly in the form of issuing regular bulletins or advisories, providing early warning system as appropriate and strategic studies. Rainfall forecast from short to medium to long term are being issued in some countries using statistical techniques. For example, the Bureau of Meteorology of the Austrialian Government provides 3-months rainfall outlooks for the coming season, derived from the Bureau's official seasonal climate outlook model. 5-days rainfall forecast are provided for the different territories: forecasts are updated twice a day. Comparison of Rainfall forecast maps with related Recent rainfall maps can be useful for reviewing the accuracy of the forecasts. The comparison however, needs to allow for the different time period each map date represents. The Recent rainfall maps show rainfall measured over the 24 hour period concluding at 9 am local time of that day, while the rainfall forecast period covers the 24 hours concluding at 12 UTC (10 pm EST, 9:30 pm CST or 8 pm WST) on the previous day. Maps are available in Internet together with many direct and indirect information as, for example, monthly evapotraspiration measured by the use of a "class A evaporation pan". Information on this parameter is important due to the country geographic and climatic features: areas in central Australia are very dry, and therefore have a high rate of evaporation. In contrast, coastal areas tend to have a lower evaporation rate as a result of their proximity to a large water source. Australian Government is The Australian Government is supporting drought affected farmers, rural communities and agriculture-dependent small businesses through income support, interest rate subsidies and free counselling. These measures recognise the impact of severe drought on rural and regional communities, the environment and the broader Australian economy. A Drought Assistance telephone Hotline is also available to support to local farm-workers under the Drought Force program and free financial, social and emotional counselling services. Forecasts are provided also in all major rural areas in New Zealand, that are covered with a 10 day weather forecast, temperature data and a seasonal outlook for any region.A specific regular commentary is available on-line on the El Nino Southern Oscillation The outlooks are generated by the Predictive Ocean Atmosphere Model for Australia (POAMA), a dynamic computer model of the climate system run at the Bureau of Meteorology. The outlooks are included in the monthly model summary of predictions from POAMA and other models operated by international organisations. Indian Ocean Dipole forecasts results come from the operational version of POAMA (1.5b). POAMA is run each day and gives forecasts out to nine months ahead. Probabilities are based on the range of predictions from the most 30 recent daily forecasts of POAMA. The probability distributions shown provide a range of possible developments in sea surface temperature (SST) in the equatorial Pacific Ocean (NINO regions) and for the Indian Ocean. Inadequate human resources (low skill), technology, computing facilities and limited coverage of national climatological stations network (in particular rainfall), data discontinuity were common reasons given by the countries that limit the capacity of the NMHSs to provide the agrometeorological services. Some countries are using remote sensing and GIS in research and development activities but not in operational mode. About RS, some operational application is carried out about assessment of crop monitoring (LANDSAT, SPOT, and AVHRR), and microwave (e.g., ERS, RADARSAT, JERS), soil moisture, vegetation status. Some example of operational application of support systems in dealing with important threats follow. Southeast Asian tropical forests are of considerable ecological and economic importance and make up about 20% of the world’s tropical forest resource. Information on biomass burning within the Indo-Malayan region is needed to assist in the modelling of large-scale atmospheric

24

pollution and climate change phenomena and for regional use by land use managers, habitat conservationists, and national and regional policy makers. Mainland Southeast Asia is the focus of the Southeast Asian fire, since it is more strongly seasonal and less humid than many parts of insular South-east Asia (Nix, 1983) and thus both favour the use of fire as a land management tool and support more fire-prone ecosystems (54% of forest formations are tropical seasonal forest compared to 4% within insular regions, FAO, 1993). The mainland Southeast Asian product offers an analysis of the spatial and temporal distribution of vegetation fire in mainland Southeast Asia using AVHRR 1 km resolution data for the period of single dry season. A regional cooperation in forest fire management has been established in 1992 as a consequence of the regional smog problems caused by land-use fires. In that occasion, member states of the Association of South East Asian Nations ASEAN created joint activities to encounter problems arising from 370 Forest Fire and Degradation Assessment trans boundary haze pollution. Most important in future regional ASEAN-wide cooperation in fire management will be the sharing of resources to better predicting fire hazard and fire effects on ecosystems and atmosphere; detecting, monitoring and evaluating fires; and sharing fire suppression technologies. The ASEAN region will potentially serve as a pilot region in which resource sharing will be based on the fact that two distinct fire problem seasons exist within the region. While within Indonesia the fire season is mainly during the months of September to November (southern hemisphere dry season), the fire season in monsoon-influenced SE Asia is between January and May. Sharing resources means that hard and software technologies and required personnel can concentrate on the hemispheric fire problems, and even costly fire suppression equipment, e.g. airplanes, can be used more economically throughout the whole year. Satellite observations providing a global survey of the composition of biomass burning plumes and their dispersal in the global atmosphere have become available by the middle to late 1990s. Global mapping of CO and O3 columns are achieved by the Global Ozone Monitoring Experiment GOME and Scanning Imaging Absorption Spectrometer for Atmospheric Cartography/Chemistry SCIAMACHY) sensors. The technological advancement in space remote sensing has been widely experimented in last three decades to obtain the desired information. The inability to detect wild land fires during initial stages and take rapid aggressive action on new fires is perhaps the most limiting factor in controlling such wild land fires. This is especially true for fires in areas with limited access. Providing an effective response to wild land fires requires four stages of analysis and assessment: determining fire potential risk, detecting fire starts, monitoring active fires, and conducting post-fire degradation assessment are all basic questions only partially answered. Identification of Fishing Zone is an important problem in Region V, where coastal zone management and optimization of ocean resources have grown in importance. Remote sensing methods have helped greatly in the optimization of ocean resources. SST derived from NOAA-AVHRR satellite serves as a very useful indicator of prevailing and changing environmental conditions and is one of the important parameters which decides suitable environmental conditions for fish aggregation. SST images obtained from satellite imagery over three or four days are composited and the minimum and maximum temperatures are noted down. These values are processed to obtain maximum contrast of the thermal information. This information is used to prepare relative thermal gradient images. From these images, features such as thermal boundaries, relative temperature gradients to a level of 1 degree centigrade, level contour zones, eddies and upwelling zones are identified. These features are transferred using optical instruments to corresponding sectors of the coastal maps prepared with the help of Naval Hydrograph charts. Later, the location of the Potential Fishing Zone (PFZ) with reference to a particular fishing centre is drawn by identifying the nearest point of the thermal feature to that fishing centre. The information extracted consists of distance in kilometres, depth (for position fixing) and bearing in degrees with reference to the North for a particular fishing centre.

25

In Region V, there is still considerable work to be done before the full benefits of remotely sensed data in agrometeorological applications can be realized. Training is needed on the use of remotely-sensed data, and capability building in terms of infrastructure is also required. There is also a need for easy access to satellite data. The period over which remotely sensed data are available has little impact on agricultural applications. Most agricultural research and management is interested in current or future concerns. However, for the few agricultural projects dealing with historical context, the recording period could be restricting. Remote sensing, unlike meteorological data, has not been recorded for a century. The longest time series currently available of free to ground remotely sensed data covering Australia at monthly time steps is AVHRR at 15 years. LANDSAT data has been recorded since 1972, but can be quite expensive when acquiring a long time series 4.6 Region VI. Region VI is a mosaic of countries different for agricultural traditions and features, climate, economic and social conditions, where the common EU regulation unifies protocols of joint development. Agrometeorological services and their products are operated at local (national or often smaller scale) level, and this makes also composite the scenarios of tools used and their operational applications. There are a number of operational products targeted to agrometeorological applications available from the NMHSs. Examples are the agrometeorological bulletins released by the Austrian Weather Services (ZAMG), the German Weather Services DWD1, the Servizio Idro Meteo of the Agenzia Regionale Prevenzione e Ambiente region Emilia Romagna ARPA-SIM in Italy, the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss), the French Weather services (Météo France) or the U.K. Met Office. Centres on Agrometeorological Forecasting Belarus and Moldova are collects and generalizes agrometeorological data, which are used to evaluate the weather conditions influence on the agricultural crops growth in decadal bulletin. In the Russian Federation and Ukraine, many regions (Oblast) issue their own agrometeorological bulletins. The bulletins are either available on the internet or supplied on a subscription basis. The content is usually in a format suitable for the end-users, but the amount of information varies considerably from product to product. In most cases, 5- to 7-days forecasts are given for mean, minimum and maximum temperature, rainfall probability and rainfall amounts, solar radiation, potential and actual evapotranspiration (reference evapotranspiration), the climatological water budget, soil water status, soil temperature, growing degree days and phenological stages, harvesting dates. In addition, weekly and monthly retrospectives with focus the most important agro-meteorological elements are also available from various NMHSs. They can be used by the stakeholders to better interpret the forecasts. To the same category of short-term forecasts also belong operational products developed for the management of pests and diseases, for example PLASMO (Plasmopora Simulation Model), PHYTOPRE (a comprehensive information and decision support system for late blight in potatoes, or SOPRA (an operational model to forecast the appearance of apple aphid, apple sawfly apple moth). In addition to the products summarized so far, there is huge amount of meteorological data available through the internet and of potential usefulness in agrometeorological applications. Deterministic forecasts to the medium range and probabilistic predictions out to the season are operationally carried out throughout Europe. To large extent, the systems employed are developed and maintained in the framework of international centres or coordinated activities. This holds true for the following systems: the prediction systems by ECMWF; the Unified Model, i.e. the suite of atmospheric and oceanic numerical modelling software developed and used at the U.K. Met Office; ALADIN, the system developed in collaboration among the NMHSs of Algeria, Austria, Belgium,

26

Bulgaria, Croatia, Czech Rep., France, Hungary, Morocco, Poland, Portugal, Romania, Slovakia, Slovenia, Tunisia and Turkey; the prediction system of the Consortium for Small-Scale Modeling (COSMO), with partners from Germany, Switzerland, Italy, Greece, Poland and Romania; the HIRLAM prediction system, with partners from Denmark, Estonia, Finland, Iceland, Ireland, The Netherlands, Norway, Spain, and Sweden. Prediction systems cover spatial domains that extend from the global to the regional scale. Correspondingly, a full palette of models is employed for operational forecasting, including global as well as regional models and high-resolution, limited-area models (LAMs). The massive enhancement in spatial resolution of atmospheric models that has taken place over the last few years has allowed to enlarge the agrometeorological applications of deterministic forecasts, either for ECMWF and with respect to regional models and LAMs. Both COSMO as well as the U.K. Met Office, for instance, are now operating LAMs at a horizontal resolution of 1 to 3 km, making it possible to realistically depict topographic features that are crucial for obtaining a realistic depiction of the local weather in complex terrain. As a result of this evolution, reliable short-term forecasts are now available for a much wider spectrum of meteorological elements than a decade ago. During the last decades, the use of simulation (statistical or mechanistic) models to support agrometeorological decision making has increased considerably for addressing a range of questions. Besides models for the management of pests and diseases, models are operationally used for forecasting frost occurrence (for example ANGELA in Trentino Alto Adige, DISGELO in Emilia Romagna, both Italian regions), models for the management of water resources. Drought monitoring is a very sensible issue, and the overall goal is to provide information that enables and persuades people and organisations to take action to maximise the probability of successful crop production and/or minimise the potential damage to established crops and other assets. A Drought Monitoring Center of the Interstate Council for Hydrometeorology has been developed by All-Russian Institute for Agricultural Meteorology, based on a combination of the unique experience of Russia in the development of physically-based indicators to describe the drought with the modern capabilities of scientific and technical knowledge, information and computing technologies. One of the primary objectives of this center is to develop the procedures for monitoring agricultural droughts (intensity, area, duration), their early diagnosis, drought impact on the condition of crops, pastures, meadows, and crop yields. The system provides a regular (each decade) a comprehensive assessment of the emergence and development of varying drought intensity in the light of their main components - the high air temperatures, atmospheric and soil drought, dry winds and the issuance of synthetic (generic) the result of observation points. ARRIAM forecast the expected drought development using the estimated drought category for ith dekad and informs possible users. The system carries out the assessment of drought and their classification into 5 categories of intensity: very strong, strong, medium, weak and lack of drought. Crop growth models are used to provide timely information for a number of farm operations. Moreover, they can be used to produce yield forecasts at the regional and national scale. Worth mentioning in this context are the crop yield predictions prepared by the Agriculture Unit of the Joint Research Centre (JRC) of the European Commission2 to provide the Directorate General for Agriculture with real-time yield estimates during the growing season for the European Union member states. The forecasting system is built on the Crop Growth Monitoring System (CGMS) developed by Alterra and which makes use of the agrometeorological model WOFOST (WOrld FOod Studies) (Supit et al., 1994). At JRC, crop yield forecasting is carried out in the framework of the so-called AGRI4CAST action (ex MARS-STAT). An important feature of AGRI4CAST is that yield forecasts are actually issued without accessing weather forecasts and climate outlooks, but using observed weather data up to the current date and climatological fields for the remaining of the growing season.

27

In the last few years a big number or Internet applications for agrometeorological purposes has been realised. Among the countries, but also within the same country, different applications have been realised, characterised by a different structure and organisation. Several meteorological and climatological databases can be easily accessed from the Internet. An extensive list can be found at the Internet site of the Usenet newsgroup sci.geo.meteorology (http://www.scd.ucar.edu/dss/faq/). The Register of Ecological Models REM at the University of Kassel in Germany is a meta-database for existing mathematical models in ecology (http://dino.wiz.uni-kassel.de/ecobas.html). Also, the "AgroExpert" Disease Forecasting System (http://www.adcon.at/Products/AgroExpert.html) is a complex system intended to reduce the amount of chemicals used in the treatment of plant diseases. Basically, the system uses climatic data which is processed according to rules developed by plant protection researchers, to establish the optimum time for chemical treatments. The system has been used in Northern Europe for the past five years. It employs a network of solar-powered weather stations to monitor rainfall, humidity, temperature, leaf wetness and other factors. Farmers can be contacted by phone or pager, or can access the system directly via a PC and modem to determine the optimum time for chemical treatment. An Information and Advisory System for Farmers, that is a combination of an Advisory System and a Decision Support System is available in CIS Countries to provide information services concerning current and forthcoming weather at a particular location, and is on the base of subscription to farms of the different size as well as to some insurance companies working in an area of agriculture. Items regard plant cultivation, fruit growing, greenhouse gardening, animal husbandry, yield forecasting, harvesting and storage. A more detailed survey on the support systems in the European part of CIS Countries is reported here, given the active collaboration of several local NMHSs with this OPAG. Agrometeorological products are various, and include Bulletins and review (week, decade, month, and vegetation period) of weather impact on agricultural crops (enclosed with tables and schematic maps); field works carrying out during vegetation period; data on wintering conditions of the major crops, horticulture crops and vineyards; data on the productive water reserves in soil at the beginning of the spring field works; real data on available soil moisture in crops fields during cultivation period; forecasts of the yield and the gross harvest of principal crops up to 1-3 months (grain crops, maize, buckwheat, leguminous crops, sunflower seeds, sugar-beet roots, potato tubers); data on real and expected conditions of crops growth phases; real and expected data on active and effective air temperature; multiannual average data on soil moisture, active and effective air temperature, terms of cultivation/growth periods; information about winter cereal crop conditions in autumn after the termination of vegetation for economic regions and Russian Federation as a whole, issue of agrometeorological annual book (enclosed with tables, graphics and diagrams); series of reviews on environmental contamination conditions from different sources (Russia Federation); prediction processing fruit trees from apple seed worm and cherry fruit fly (Ukraine); forecast of flowering fruit trees and vineyards (Ukraine). The above forms of information are available for the government authorities and Ministry of Agriculture free of charge because NHMSs is the state organizations. Agrometeorological information is delivered to users through modern communication means, including Internet, telephone, and fax in printed, audio and visual forms as well as by means of interviews, and, where appropriate for the type of data, by mail. In Ukraine all operational materials are used by organizations of agricultural complex for: - study and use of spatial variation of soil moisture on the territory of Ukraine; - economic analysis and evaluation of losses in agriculture from unfavorable weather conditions; - create a good climate control in greenhouses; - the development of nature-protective measures; - calculation of economic efficiency and the use of fertilizers, crop programming;

28

- development systems for management of rivers system , reservoirs and irrigation systems; - the definition of norm irrigation for crops with different types of irrigation; - developing ways to combat soil erosion; - decisions diverse issues related to the sowing of spring crops and reseeding of winter crops. In Ukraine, the system of forecasting crop yields and an estimate of losses based on a rational combination of traditional data collection and monitoring include of materials at various scales of remote sensing systems creates a center of GIS Analyst in cooperation with the Department on forecasting methods of remote sensing of the Institute State Statistics of Ukraine. The function of such a monitoring system should monitor the dynamics of crops and vegetation conditions. In Russian Federation in late 2003, MCC of Ministry of Agriculture handed over for trial operation system “Agrokosmos”. Data on cloud cover, indices NDVI and some other data can be obtained via the Internet virtually all Russia, a system developed jointly with the Space Research Institute. Used images obtained from NOAA and TERRA. For calibration and refinement of estimates and forecasts of crop yield on the basis of remote sensing data need to use additional sources of information. In particular, data on the environmental condition in Russia and other territories (Ukraine, Belarus, Moldova etc.) accumulating at the present time in the World Data Center (RIHMI-WDC) in Roshydromet, in NHMSs, stations and posts. Most interesting in terms of assessing and predicting crop yields, are the base of agro-meteorological data produced by AWS Agrometeorologist, equipped with such software, as AGRO, AMFD, PERSONA system, etc. Most AEZ/GIS LRIS systems are designed to address issues mainly at national and subnational levels. The use of GIS is not yet common in provincial and rural settings because only few administrators and managers have recognized its strategic importance in planning. The technology needs to be brought down to more detailed scales to meet the needs of local government units, farmers, extensionists, and local researchers. Lack of digital data (terrain, land use, etc.), unavailability of data-sharing procedures and data standards, compartmentalization of departments and lack of coordination are also limiting the progress of AEZ /GIS use in countries in the region. The introduction in operative practical AWS agrometeorologist with elements of GIS technology as on territory of the Ukraine (developed by Kiev firm "Spetsavtomatika") as a whole, so and on separate region, has united operative processing and checking quality to information, existing methods of the forecasts and accounts, output types to product in united technology, which has allowed Ukrainian Hydrometeorological Center and regional Hydrometeorological Centers to leave on new level of the servicing the users, connected with use the modern computing machinery and channels of communication. Specialized agrometeorological support system is based on developed by Kiev firm "Spetsavtomatika" computer technologies of processing and analysis of the information, estimation of natural-resource potential of Ukraine for cultivation practically of all crops. Methodical part is presented by agrometeorological calculation, recommendation and estimation, allowing to take stock of weather conditions at motivation of the structure of the crop rotations, methods of the calculation of the terms and rates of fertilizer application depending on conditions warm- and moisture supply. Observed data over the communications network enter into PC regional Hydrometeorological Centers and Ukrainian Hydrometeorological Center, where pass the checking, decoding and fill up base of the operative. Afterward this information is used as directly for servicing the users, so and as an information database for realization of calculation all over the spectrum agrometeorological forecasts, for drawing up of agrotechnical recommendations for updating technology of crops cultivation depending on established weather conditions, for automatic forming of ten-day and monthly bulletins and annual review. Agro meteorological review of the year include agrometeorological supervision on all stations made by means of program complexes AMFD and AGRO.

29

Agrometeorologist’s AWS provides, between the others : long-term database observations on all type of information for different type of crops, charting on the cartographical basis of any information of the agrometeorological contents for any term or period, formation by the specialist- agrometeorologist's the new types of maps for the chosen crops, areas, terms and other types of the information, .making up of maps with drawing of the information of each station or post of the observations, or averaging on region, zone; carrying out of calculations of the phenological phases, droughts forecast, yield forecast. In the menu "Forecasts" the group of maps is accumulated, where user can set to the nested algorithms different parameters, receiving agrometeorological forecasts, estimation of conditions vegetation for various crops, for various terms etc. Models about the influence of the environment conditions to productivity of crops include the description of the main processes of the plants (photosynthesis, respiration, growing and assimilate partitioning ) and the influence of meteorological factor on crop productivity. The forecasts agrometeorological is based on 1-1,5 months and more predictions for . winter wheat, rye and barley, spring barley, oats, buckwheat, millet, rice, sunflower. Severe agricultural drought are experienced in some regions of Russia, Ukraine and other CIS countries. In severe drought years, crop yield are reduced to 40-60 % as compared to non- drought years. Drought Monitoring Center of the Interstate Council for Hydrometeorology operates on the basis of the SU "All-Russia Research Institute for Agricultural Meteorology (PG" ARRIAM) of Roshydromet In PG ARRIAM has developed the concept and automated system for evaluation of drought on Earth observation data. They are based on a combination of the unique experience of Russia in the development of physically-based indicators to describe the drought with the modern capabilities of scientific and technical knowledge, information and computing technologies. One of the primary objectives of this center is to develop the procedures for monitoring agricultural droughts (intensity, area, duration), their early diagnosis, drought impact on the condition of crops, pastures, meadows, and crop yields. The system provides a regular (decadal) comprehensive assessment of the emergence and development of varying drought intensity in the light of their main components - the high air temperatures, atmospheric and soil drought, dry winds. ARRIAM forecast the expected drought development using the estimated drought category for decades and informs possible users. Drought monitoring is carried out each decade from the first decade of May to late September. Utilization of satellite information, primarily, for assessing crop conditions, crop productivity and anomalous conditions (drought, frost) belongs to the same line of activities has high prospects for sustainable management of farming processes. New information products are produced on a regular basis, in particular, global maps of cloudiness and SST generated from data of five geostationary satellites METEOSAT-5 METEOSAT-7, GMS, GOES-W, GOES-E, thematic maps of NDVI distribution over the European part of Russia, snow and cloud cover on the data from RESURS-O1 N4 (MR-900) and NOAA (AVHRR) and other products (SRC Planeta) (SAT-29, 1999-2000). The Information and Advisory System for Farmers has been developed within National Institute on Agricultural Meteorology (Federal Service on Hydro-Meteorology and Environment Monitoring). The system is a combination of an Advisory System and a Decision Support System and it provides information services concerning current and forthcoming weather at a particular location. The service is available on the base of subscription to farms of the different size as well as to some insurance companies working in an area of agriculture. The system is the first national information interactive tool of Ukraine, and provides end-users with the information about the potential of natural resources within a territory, about climate and current weather and some forecasts, about weather impacts on farmer’s activities. System is an Internet application available as a web resource and offers personalized information, advices and recommendations on Plant and fruit growing and greenhouse gardening, animal husbandry, yield forecast, harvesting and storage. Input data include routine observations from the agro-meteorological network, data from devices and information about the farm received from the end-user. Data base updating is conducted every ten days, but some parameters are renewed every day or when the corresponding data become available.

30

5- Recommendations on procedures, methodologies and resources to improve the regional-based capability for operational applications New technologies and tools able to drastically improve the agrometeorological services and facilitate the decision making processes are currently present in nearly all countries, but the ability of different regions to adopt them as operational tools is greatly variable. Improving the status of agrometeorological services/products which are old, obsolete and poor in operation, highlighting the local characteristics of meteorological information and increasing the practicability of serving farmers is recommended to progress the capability for operational applications. For example:

improvement of station networks, timeliness of data transfer from local to data analysis centre, forecast delivery from data analysis centre to users, ability to localize climate forecast information and assess the impact, and availability of effective dissemination system are the key factors for the success of operational agrometeorological services. Therefore, strategy to reinforce the operational agrometeorological services should cover all these aspects.

Poor agrometeorological observation measures and low automatization of material

acquisition are still a constraint in many countries. Strengthening of automatic agrometeorological observation and increasing the temporal and spatial intensity of agrometeorological data should be effective ways to improve the effectiveness of the agrometeorological support systems, also in monitoring agrometeorological disasters and forecast hazards.

GIS have been shown as powerful tools to support several agrometeorological applications, however this facility has not been yet completely exploited. In recent years the use of GIS has continued to expand as software has become more affordable and user friendly, computers have become cheaper and more efficient, and GIS-compatible data have become more readily available. For many years, in fact, commercial off-the-shelf GIS were prohibitively expensive and too complicated for many potential users to operate. GIS interfaces were often difficult to navigate, the software required costly computers, and few data sets were provided in an easily accessible GIS-compatible format. Evidence of this present expansion is apparent mainly throughout RA-IV; RA-VI; RA-V, where many countries have at least one government agency that is using GIS to accomplish various mission objectives. Often these agencies contain the national meteorological and agricultural services for these countries, but these services do not necessarily use or have access to GIS to support operational agrometeorological activities. Given these technological advances and working relationships, one suggestion for expanding the use of GIS within the regions is to encourage those agencies responsible for providing operational agrometeorological products and services to seek support from other agencies within their country that are using GIS. These GIS-savvy agencies could provide support in a variety of forms, ranging from offering basic GIS training and advice to regularly providing GIS services to facilitate operational agrometeorological activities. The most obvious benefit associated with using GIS freeware is cost savings. A few negatives associated with using GIS freeware include limited software support, application instability, and potential computer security risks. When GIS is used to facilitate operational agrometeorological products and services, it is critical that the GIS software is reliable and that help is available to address any potential problems. As a result, it is strongly recommended that commercially-available GIS software are used to support operational agrometeorological products and services because the benefits of application stability and continued software support far outweigh the cost savings and potential negatives associated with using freeware. Furthermore, commercial

31

providers of GIS software often provide links to user communities where users regularly share code and advice. These user communities are very valuable sources of information, helping GIS users accomplish a variety of tasks including maximizing system performance, extending functionality, customizing applications, and automating data processing. Commercial providers of GIS software have been known to include base data with their software, and an increasing number of groups and organizations, including government agencies, are providing GIS-compatible data free of charge. These developments have made it possible for GIS users to create detailed agrometeorological analyses at relatively minimal cost. RS products are the exemplary tools driving territorial planning process and agricultural production monitoring and management: - agro-ecological zoning. - analysis of the spatial distribution of crop yield, - assessment of the extension of cultivated areas, - implementation of modern production techniques, as precision agriculture, - Determination of crop health . - Other promising areas of applications include: - disaster assessment (all the regions) - drought monitoring (all the regions) - Forest fire monitoring (mainly RA II and RA V) - Environmental monitoring (important - forestry information (mainly RA III) - Identification of fishing zone (important, for example, RA V). In general, several decision-making processes, as land use assessment, adaptation of climate change and variability, planning and optimization of fragile resources, and in general sustainability constrains can be facilitated by adoption of RS information. Remote sensing is a valuable source of data especially when regional-scale issues are the concern. however, there are some limitations of remote sensing regarding agricultural applications including data availability, length of recording period; limited mapping capability; requirement of expertise and computer facilities; and cost. Agricultural research with remote sensing requires a moderate level of expertise and computing support. The processing of remotely sensed data requires an investment in training of personnel as well as adequate computers and data storage. Computer hardware and software are important, but perhaps more important is “mindware” to ensure the correct use of remote sensing to assist in the decision making process. Cost of remote sensing projects can be prohibitive, especially when fine detail is needed over large areas. However, this depends on the application and the appropriate remote sensing platform. With the launch of the TERRA satellite in 1999, came a new era in remote sensing: no cost moderate to fine resolution data. The spatial resolution of the ASTER and MODIS sensors is appropriate for many different agricultural applications. However, some remote sensing data is currently expensive for large areas of land (e.g., 1,000 km2), including very high spatial resolution data (e.g., IKONOS or airborne systems), and hyper spectral data. The new generation of satellite sensors (e.g. MODIS on TERRA platform, VEGETATION on SPOT, SEVIRI on MSG, AVHRR-3 on EPS/NOAA) has brought an upgraded level of remote-sensed information to the user community thanks to a much better spatial, temporal, spectral and angular sampling of the radiative fields. The time resolution and global coverage provided by the new instruments, together with the extensive sampling in both the spectral and angular domains, paved the way for a broad spectrum of novel applications, namely within the scope of land surface processes and land-atmosphere interactions. For example MSG provides an image repeat cycle of 15 minutes offering new opportunities to detect short-term evolution of vegetation resources. Such feature must be considered particularly relevant over areas characterized by a high cloud occurrence as well as for semi-arid ecosystems having short vegetation cycles.

32

The synoptic view and the repetitive cover afforded by satellite data allow multi-temporal observation of seasonal changes. To make best use of such information it is necessary to combine it with other data. The need for a marriage between remote sensing, earthbound survey, cartography and spatial and statistical analysis techniques is readily apparent and can be reached through the adoption of GIS and databases within all crop assessment methodologies. Numerous crop models are used by the agrometeorological and farming communities to monitor and manage agricultural activities. These models vary significantly in complexity, from simple growing degree day models that estimate crop phenology based on cumulative heat units to sophisticated simulation models that forecast crop yields by incorporating soil, weather, farm management and other data. It is recommended that WAMIS devote a section to help users locate, download, and apply crop models that are suitable for their region. If the CAgM sponsored a roving seminar on geospatial technologies, it would be very beneficial to include a section demonstrating how GIS and remote sensing could be used in crop modelling. Combination of meteorological data analysis, models outputs, GIS and RS requires considerable resources to process and display. These resources may include highly-trained staff, high-end computers, and a significant time commitment to ensure that the resulting products are accurate and reliable. Even in the richer and more advanced countries, these cost and resource requirements limit the extent to which commercially available satellite data can be used for operational agrometeorological monitoring. Given these hurdles, a much more cost-effective means for incorporating remote sensing derived products into operational agrometeorological activities is clearly desirable. Although modern technology has improved agrometeorological information and increased the number of end-users, continued improvements are necessary to ensure that the content of the information is adequate to fulfill the requirements of the farming communities. At any level, these objectives can only be achieved through active co-operation between NMHSs, agricultural extension services, farmers and their associations, research institutes, universities, and industry. Communication strategies between stakeholders, including effective use of the media must be enhanced. In fact, any improvement in the use of support systems may easily become ineffective unless the user understands and applies the information provided. Furthermore, campaigns to raise public awareness and disseminate information in order to involve a broad array of stakeholders are crucial in all regions. These campaigns can also be an opportunity for adaptation decision makers to better understand the perception and views of the public on the issues Several government agencies and non-profit organizations worldwide regularly prepare products that could potentially benefit the operational agrometeorological services of many regions. These products are often made available free of charge via the Internet and are provided in formats that enable simple visual inspection or more detailed spatial analysis. Therefore, it is strongly recommended that NMHSs examine these satellite-derived data and products and consider incorporating them into their operational agrometeorological activities. Members of the CAgM should also encourage providers of remote sensing data and products to increase the number of regions for which they make this information available and urge these organizations to create more agrometeorological-specific products. Financial, computing, and personnel resources may limit the extent to which these organizations can expand efforts, but it is possible that some of these agencies can make additional data and products available with minimal additional effort because data processing and display is often automated. The CAgM may also consider offering training in the use of remote sensing data for agrometeorological analyses. This training could be combined with GIS training to create a roving seminar on the use of geospatial technologies for agrometeorological data display and analysis. Finally, the CAgM should continue to use WAMIS to publicize sources of geospatial information, including remote sensing and other GIS-ready data, and to disseminate training materials.

33

Although specific separate training in new tools and technologies may be useful to develop knowledge and operational skill within NHMS, those providing the training and services may not be the most proficient in agrometeorological and agroclimatic concepts. One way to overcome this shortcoming is to build on the success of previous CAgM roving seminars and offer additional seminars describing how to use GIS and RS to prepare operational agrometeorological products. Ideally, seminar content and instruction would be provided by GIS and RS experts who have experience developing and running operational agrometeorological applications regularly. Although this approach may be more costly than the former because the training would require international travel and accommodations, this latter approach would ensure that the training is catered toward those groups and individuals specifically interested in developing operational agrometeorological products. A proper implementation of agrometeorological support in farming activities implies the creation of a better perception and awareness of the effective value of weather and climate related information. All the types of divulgation may be useful to implement farmers confidence and perception. Practical handbooks support (inexpensive, understandable, accessible) may be used to train farmers on the use of agrometeorological advices. Internet or CDs, at least, could be used to disseminate specific recently developed techniques and applications, to improve the understanding of the variability in climate and its effect on agricultural production and natural resource management. A constant update of the contents is essential to meet the changing demands of new technology to cope with climate change and climate variability.Promoting the establishment of countryside information service is considered strategic to strengthen direct services to farmers. E-learning methods are very suitable to provide a fast response to new technologies and can reach a wide audience, potentially spanning the entire globe. Focusing of operational applications of agrometeorology towards the actual needs of the farmers translates into the elaboration of agrometeorological products based on the specific needs demands of each region. Efficient ways to delivery information to end users in a efficient and fast way must be established using, where possible, new ICT and, in other cases, locally-suited traditional information channels. Support systems for agrometeorological services must consider all these suggestions and recommendations useful to address farmers towards short term adaptation practices in relation to climate change, and to provide foundation in planning long-term adaptation. 6. General recommendations from ICSAS Support systems for agrometeorological services must be considered for taking decisions at

different levels of scale: farm-scale (irrigation, fertilization, land preparation, planting, pest management); catchment scale (land-water resources, environmental management, land use, agroclimatic zoning); marketing scale (crop yield forecast, harvesting time, quality), policy scale (water allocation planning, extreme event protection, adaptation or mitigation issues).

Agrometeorology operational applications and information delivery systems can very

profitable to optimize knowledge about weather- climate-crop relations and appreciate risks and hence assist to spell out the sort of information that farmers need to adopt strategic and tactical planning.

Meteorological support systems must be promoted to maintain local tradition in agriculture.

Local knowledge is holistic, trusted and validated by culture and experience, and may be profitably conjugated to new technologies on weather and climate.

34

A recharge of knowledge and trust bases must be looked for agrometeorological applications: links within plant-canopy interactions information with agrometeorological models and development of integrated methods would allow to improve further understanding of the physical mechanisms inside crop canopies and to adopt correct operational tools.

Support systems in agrometeorology (GIS and RS in specific) should be considered as tools

effective to generate a more eco-efficient agriculture which conciliates production to a reduction in resource degradation. Strategic use of such technological tools in addressing toward agro-ecological zoning and precision farming issues should be exploited.

National agencies responsible for providing agrometeorological products and services should

seek support, if needed, to adopt GIS and RS technology from other agencies. The use of remote sensing to monitor agricultural and natural resources of a region must be

extended, since it may support more efficient agricultural practices and positively affect the decision making processes. To obtain this objective. much more cost-effective means for incorporating satellite data into operational agrometeorological activities should be found.

Training workshop on Agrometeorology based on MODIS tools and products, and better

validation of MODIS products, including the last products released, as Land Cover Dynamics and Land Cover Type.

Efforts should be undertaken to foster the development of monthly to seasonal forecast

systems suitable for agricultural decision-making problems. There is a need for targeted research programmes supported by research centres, weather services and agrometeorological agencies. Such promotion might as well match the activities of WCASP and CLIPS.

There is a urgent need to have more interactions between users and NMHS, that should

allocate some resources (5% of their budget) to improve interactions paths with users. Information provided to users must be timely, accurate, cost effective and feedback mechanisms facilitate the effective management. In fact, implementation mighty be largely assisted by results evaluation, user needs assessment, active dialogue and exchange. These objectives can only be achieved through active co-operation between NMHSs, agricultural extension services, farmers and their associations, research institutes, universities, industry and enterprises.

Agrometeorological support systems should be considered in the view of their potential to

support science-based tools for determining strategies designed to help policymakers and managers to evaluate the best options for reducing vulnerability of food systems to global environmental change, while minimizing further environmental degradation.

NMHS must be proactive in getting involved with existing agricultural fora in order to further

improve users interactions. Communication strategies of agrometeorological information to inform about their effective value are necessary to involve a broad array of stakeholders, included adaptation decision makers.

WAMIS should be addressed as a pro-active, common instrument to share bulletins,

geospatial information, crop models and to disseminate training material. INSAM must be supported and utilized as a common exchange basis of agrometeorological

information and products, information on innovation and potential utilities, free-source of shared resources. The number of members and the world-wide spread membership reached so far ensures a large audit and a comprehensive regional diffusion.

35

7. Promotion actions of OPAG work

Chair, co-chair and members of this OPAG have been maintaining strict and interactive contacts with their national, regional and international interlocutors, spreading information about contents and aims of its work. In specifics, the presence of this OPAG 2.1. was represented at the following meetings: - WMO/COST Symposium on Climate Change and Variability- Agro Meteorological Monitoring

and Coping Strategies for Agriculture in conjunction with CAgM Expert Team 3.2 on Climate Risks in Vulnerable Areas: Agrometeorological Monitoring and Coping Strategies, 4-6 Jun. Oscarborg, Norway,

- International Conference on Challenges and Opportunities in Agrometeorology, 23-25 Feb

2009, New Delhi, India - International Symposium "Climate Change and Adaptation Options in Agriculture" June 22-23

2009, held in Vienna, Several national meetings of national Agrometeorological Societies (as, for example, 12° Italian National Congress Nazionale Agrometeorology-Sassari 15-17 Giugno 2009, 2008; Training on Trends in Plant Ecophysiology and Ecosystem Ecology Research Universita’ di Palermo.22-27 June 2008, Scientific and technical Days on “Methodologies to assess water needs at farma and catchment scale, Università di Catania. “Taormina, 12-14 November 2008, GRUSI. Study Group on Irrigation problems. CNR Roma, 13-14 January 2009). An active and official collaboration has been kept with COST 734 Action Impacts of Climate Change and Variability on European Agriculture – CLIVAGRI. COST Actio, carried out at European level, assure a fast and streamlined flow of information with regard to results of research activities from regions not directly involved in the project. Therefore, efforts and cooperation in this field are valorised, providing a relevant and efficient way of information dissemination. This OPAG and the COST Action have been connected with other projects, also exploiting the simultaneous participation of experts in these activities, organised in the frame of EUMETSAT (the European Organisation for the Exploitation of Meteorological Satellites) with its SAF (Satellite Application Facilities) activities on climate monitoring, numerical weather prediction, and land surface analysis, as well as with GRAS (Global Navigation Satellite System Receiver for Atmospheric Sounding), CLIPS (Climate Information and Prediction Services), THORPEX, an international research programme to accelerate improvements in the accuracy of 1-day to 2-week high-impact weather forecasts, as well as with the pr0-active maintenance of the web-site INSAM (the International Society of Agricultural Meteorology. Several common actions have been common interest of this OPAG and COST 734 Action, which main objective is the evaluation of possible impacts from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. The definition of the current and future levels of critical thresholds and hazards for agricultural activity and environmental resources have been part of the research of COST and have been used as starting information for OPAG: agroclimatic indices and simulation models review and assessment of tools used to relate climate with agricultural processes; evaluation of the current trends of agroclimatic indices and simulation model outputs describing agricultural impacts and hazard levels; developing and assessing future regional and local scenarios of agroclimatic conditions; risk assessment and foreseen impacts on agriculture. Based on these results, possible actions (specific recommendations, suggestions, warning systems) are still under elaboration and proposition to the end-users, depending on their needs.

36

The book on "Survey of agrometeorological practices and applications in Europe regarding climate changes impacts" is a important inventory on support systems useful in Agrometeorology: Agroclimatic Indices and Models; Trends in Agroclimatic Indices and Model Outputs; Satellite Data Records Survey; Climate Change Scenarios; Risk Assessment and Foreseen Impacts on Agriculture, and includes a general description of the activity performed in Europe in the field of climate change and variability impacts on agriculture. Although limited by the quantity of answering COST countries and by the quality of the answers, the wide range of presented information, including data, models, indices, methods, tools, can represent an useful support for the workers of agricultural sectors (farmers, technicians, decision makers, etc.) to better plan the analysis and the adaptation of future European agriculture to climate change and variability impacts. 8- References Abhineet J., Shirish A. Ravan, R.K. Singh, K.K. Das, P.S. Roy, 1996. Forest fire risk modelling using Remote Sensing and Geographic Information System . Current Science, 70(10): 928-933. Abreu, J.P, 2008. A Agrometeorologia no Presente e no Futuro. Jornadas Técnicas “A Importância da Meteorologia na Agricultura”. Beja, Portugal. Badhwar, G. D., MacDonald, R.B., and Mehta, N.C. 1986. Satellite-derived LAI and vegetation maps as input to global cycle models-a hierarchical approach. Int. J. Remote Sensing, 7: 265-281. Baronti, S., F. del Frate, P. Ferrazzoli, S. Paloscia, P. Pampaloni and G. Schiavon 1995, SAR polarimetric features of agricultural areas. International Journal of Remote Sensing, 16, 2639-2656. Bedritsky, A.I. 2009. Substantive provisions and priorities of development of hydrometeorological activity for the period till 2030. Report of the Roshydromet head Borgeaud, M. and J. Noll 1994, Analysis of theoretical surface scattering models for polarimetric microwave remote sensing of bare soils. International Journal of Remote Sensing, 15, 2931-2942. Brown, J.F., B.D. Wardlow, T. Tadesse, M.J. Hayes, and B.C. Reed. 2008. The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation. GIScience & Remote Sensing, 45, 16-46. Chen, J.M. and Cihlar, J. 1996. Retrieving leaf area index of boreal conifer forests using Landsat TM images. Remote Sens.Environ., 55: 153-162. Clevers, J.G.P.W. and van Leeuwen, H.J.C. 1996. Combined use of optical and microwave remote sensing data for crop growth monitoring. Remote Sens. Environ., 56: 42 - 51. Dadhwal, V.K. 1999. Remote Sensing and GIS for agricultural crop acreage and yield estimation. Internat. Arch. Photogramm. & Remote Sensing, XXXII, 7-W9, 58-67. Dawod ,M.A.A & M.A.El-Rafy, 2008 . Study of Heat transference in boundary layer over Bahteem Agro meteorology Station, Meteorological Research Bulletin – the Egyptian Meteorological Authority , ISSN 1987-1014, Vol 23,Cairo ,Egypt Dawod ,M.A.A & M.A.El-Rafy, 2006. Effect of the Climatic Change on Nasser Lake Evaporation in Egypt , Meteorological Research Bulletin – the Egyptian Meteorological Authority ,ISSN 1987-1014, Volume 21,Cairo, Egypt.14-26 Dawod ,M.A.A & M.A.El-Rafy, 2007 Climatological view of extreme weather phenomena over Egypt, Meteorological Research Bulletin – the Egyptian Meteorological Authority ,ISSN 1987-1014, Volume 22 Cairo ,Egypt 54-81

37

Dawod ,M.A.A,2003: Climatic variabilities over Egypt North Coastal area and East Africa area in relation to Sea Surface Temperature pattern, Ph.D.,Thesis, Faculty of science, Cairo University, 2003. Dawod ,M.A.A ,2004 :Verification the long rang forecast of Nile flood of season 2001/2002 and 2002/2003, Nine workshop on meteorology and sustainable development, the Egyptian Meteorological Authority, Cairo, Egypt, 28-29 April 2004, Arabic languages Meteorological Research Bulletin –ISSN 1987-1014, Volume 19, January 2005,Cairo ,Egypt, 156-170 pp DeFries, R. S., M. C. Hansen, and J. R. G. Townshend, 2000. Global continuous fields of vegetation characteristics: a linear mixture model applied to multi-year 8km AVHRR data. International Journal of Remote Sensing, 21(6/7): 1389-1414. Doraiswamy, P.C., T.R. Sinclair, S. Hollinger, B. Akhmedov, A. Stern and J. P Dawod ,M.A.A,2002:Long rang forecast of seasonal rainfall of the north coast of Egypt, The 27 th International Conference for Statistics, Computer Science and its applications, the Egyptian statistics society ,April 13-18 ,2002,123-139 pp Fan, Y. and H. van den Dool. 2004. The CPC global monthly soil moisture data set at ½ degree resolution for 1948–present. Journal of Geophysical Research, 109, D10102. Fang, H. L., Wu, B. F., Liu, H. Y. and Huang, X. 1998. Using NOAA AVHRR and Landsat TM to estimate rice area year-by-year. International Journal of Remote Sensing 19, 521525. Garen, D.C. 1992. Improved techniques in regression-based streamflow volume forecasting. Journal of Water Resources Planning and Management, 118, 654-670. Hilario, Flaviana D. And Juliet Mangera(2000) Soil Moisture and Vegetation Monitoring Using AirSAR Data. PAGASA Internal Report. Jackson, R. D. (1982). Soil moisture inferences from thermal infra-red measurements of vegetation temperatures. IEEE Transactions on Geoscience and Remote Sensing 20, 282-286. Joyce, R. J., J.E. Janowiak, P.A. Arkin and P. Xie. 2004. CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of Hydrometeorology, 5, 487-503. Kleschenko, A. 2004. AGROMETEOROLOGICAL APPLICATIONS FOR SUSTAINABLE MANAGEMENT OF FARMING SYSTEMS. WMO/TD No. 1175, CAgM Report No. 92, pp. 5-28. Kleschenko, A. 2009. System for Providing Farmers with Agro-Meteorological Information on the Base of Web-Technology. International Workshop, May 2009, Australia Kogan, F.N. 2001. Operational space technology for global vegetation assessment. Bulletin of the American Meteorological Society, 82, 1949-1964. Lawrimore, J., R.R. Heim Jr., M. Svoboda, V. Swail and P.J. Englehart. 2002. Beginning a new era of drought monitoring across North America. Bulletin of the American Meteorological Society, 83, 1191-1192. Laili, N., H. Mariamni and K.M. Noh 1998, “An Evaluation of Multi-band/Multipolarised SAR Data for Vegetation Discrimination in Malaysia”, in Proceedings for the 19th Asian Conference on Remote Sensing, Manila, Philippines.

38

McKee, T.B., N.J. Doesken and J. Kleist. 1993. The relationship of drought frequency and duration to time scales. Preprints, Eighth Conference on Applied Climatology, Anaheim, California, 179-184. Myneni, R.B., Nemani, R.R. and Running, S.W. 1997. Estimation of global leaf area index and absorbed PAR using radiative transfer models. IEEE Trans. on Geosc. and Rem. Sensing, 35(6): 1380-1393. Motha R. , 2009: Developing an adaptation strategy for sustainable agriculture : Journal –Idojaras, Quarterly Journal of the Hungarian Meteorological Service: Vol. 113 * N. 1 – 2 , 117-128 pp. Mueller, R. 2000. Categorized mosaicked imagery from the National Agricultural Statistics Service crop acreage estimation program. Proceedings of the ASPRS 2000 Conference, Washington, D.C. Mueller, R. and M. Ozga. 2002. Creating a cropland data layer for an entire state. Proceedings of the ACSM-ASPRS 2002 Conference, Washington, D.C. Pagano, T.C., D.C. Garen, T.R. Perkins and P.A. Pasteris. 2009. Daily updating of operational statistical seasonal water supply forecasts for the western U.S. Journal of the American Water Resources Association, 45, 767-778. Palmer, W.C. 1965. Meteorological drought. U.S. Weather Bureau Research Paper No. 45, Washington, D.C., 58. Price, J.C. 1993. Estimating leaf area index from satellite data. IEEE Trans. Geoscience Remote Sensing, 31: 727-734. Puterbaugh, T.L. and B.R. Rippey. 2002. The Weekly Weather and Crop Bulletin – Serving U.S. agriculture. In Improving Agrometeorological Bulletins, Proceedings of the Inter-Regional Workshop (M.V.K. Sivakumar ed.) held in Bridgetown, Barbados, 15-19 October 2001. Geneva, Switzerland, World Meteorological Organization. Qiu, J., Gao, W. and Lesht, B.M. 1998. Inverting optical reflectance to estimate surface properties of vegetation canopies. Int. J. Remote Sens., 19: 641-656. Rasmussen, M. S. (1992). Assessment of millet yields and production in northern Burkina Faso using integrated NDVI from AVHRR. International Journal of Remote Sensing 13, 3431-3442. Reichert, G.C., P.R. Nixon and R.N. Dobbins. 1998. Statistics Canada’s near real time crop condition assessment program utilizing NOAA AVHRR data – Remote sensing, GIS and the Internet. Proceedings of the International Conference on Agricultural Statistics, Washington, D.C., 142-148. Ross, S., B. Brisco, R.J. Brown, S. Yun and G. Staples 1998, “Paddy Rice Monitoring with RADARSAT-1” Proceedings for the 19th Asian Conference on Remote Sensing, Manila, Philippines. Seo, D.J. 1998. Real-time estimation of rainfall fields using radar rainfall and rain gauge data. Journal of Hydrology, 208, 37-52. Shannon, H.D. 2006. The Weekly Weather and Crop Bulletin: Integrating agricultural and meteorological data for decision makers. In Modeling and Remote Sensing Applied to Agriculture (U.S. and Mexico) (C.W. Richardson, A.D. Baez-Gonzalez, and M. Tiscareño-Lopez, eds.)

39

Svoboda, M., D. LeComte, M. Hayes, R. Heim, K. Gleason, J. Angel, B. Rippey, R. Tinker, M. Palecki, D. Stooksbury, D. Miskus and S. Stephens. 2002. The Drought Monitor: An integrated approach to water supply assessment. Bulletin of the American Meteorological Society, 83, 1181-1190. Tennakoon, S. B., Murty, V. N. and Eiumnoh, A. (1992). Estimation of cropped area and grain yield of rice using remote sensing. International Journal of Remote Sensing 13, 427-439. Ustinova, O. 2004. Agrometeorological products and their economic benefits in the Russian Federation. WMO/TD No. 1175, CAgM Report No. 93, pp. 74-78. Wade, G., R.W. Mueller, P.W. Cook and P.C. Doraiswamy. 1994. AVHRR map products for crop condition assessment: A geographic information systems approach. Photogrammetric Engineering & Remote Sensing, 60, 1145-1150.

40

Annex 1- Questionnarie

Answers from 73 Countries WMO Region I (Africa) #15 WMO Region II (Asia) #16 WMO Region III (South America) #3 WMO Region IV (North America, Central America and the Caribbean) #7 WMO Region V (South-West Pacific) #4 WMO Region VI (Europe) #28

QUESTIONS: To what extent new techniques such as remote sensing, GIS, modelling are used for data collection, analysis and operational recommendations ?

41

Frequency Percent Frequency Percent

Always 18 27.27 18 27.27Never 15 22.73 33 50.00Occasionally 20 30.30 53 80.30Often 13 19.70 66 100.00

Frequency Missing = 6

Remote sensing:

Agroclimatic indexes and simulation models Plant growth models

Geographic information systems:

Frequency Percent Frequency Percent Always 17 26.56 17 26.56 Never 20 31.25 37 57.81 Occasionally 13 20.31 50 78.13 Often 14 21.88 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Always 13 19.70 13 19.70 Never 13 19.70 26 39.39 Occasionally 20 30.30 46 69.70 Often 20 30.30 66 100.00 Frequency Missing = 6

Are equipment and devices for data collection and analyses made by national or foreign companies?

Frequency Percent Frequency Percent Always 9 14.06 9 14.06 Never 31 48.44 40 62.50 Occasionally 13 20.31 53 82.81 Often 11 17.19 64 100.00 Frequency Missing = 8

42

Measurement stations:

Workstations:

4- Is the budgetary allocations for meteorological-agrometeorological services sufficient? Allocation for meteorology:

Allocation for Agrometeorology:

Frequency Percent Frequency Percent Both 13 19.40 13 19.40 Foreign 31 46.27 44 65.67 National 23 34.33 67 100.00 Frequency Missing = 5

Frequency Percent Frequency Percent Both 10 16.13 10 16.13 Foreign 32 51.61 42 67.74 National 20 32.26 62 100.00 Frequency Missing = 10

Frequency Percent Frequency Percent Fair 21 32.81 21 32.81 Insufficient 23 35.94 44 68.75 Largely insufficient 7 10.94 51 79.69 Sufficient 13 20.31 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Fair 16 24.62 16 24.62 Insufficient 30 46.15 46 70.77 Largely insufficient 14 21.54 60 92.31 Sufficient 5 7.69 65 100.00 Frequency Missing = 7

43

There are state programs (if yes, specify details when possible ) on re-equipment of NMHSs by modern communications facilities, equipment and devices for data gathering?

New communication facilities:

New data-acquisition equipments:

New data-management equipments:

Frequency Percent Frequency Percent In preparation 9 13.43 9 13.43 No 28 41.79 37 55.22 Yes 30 44.78 67 100.00 Frequency Missing = 5

Frequency Percent Frequency Percent In preparation 14 20.90 14 20.90 No 19 28.36 33 49.25 Yes 34 50.75 67 100.00 Frequency Missing = 5

Frequency Percent Frequency Percent In preparation 11 16.67 11 16.67 No 25 37.88 36 54.55 Yes 30 45.45 66 100.00 Frequency Missing = 6

44

What is your consideration about the degree of the public investments in National Meteorological and Agrometeorological Services?

What is, in general, the degree of utilization of NMHSs products and services?

Kind of use and frequency of use of different NMHSs products and services used in agrometeorology in your Country (RA)

Improving the farming techniques:

Frequency Percent Frequency Percent Excellent 3 4.62 3 4.62 Fair 24 36.92 27 41.54 Good 7 10.77 34 52.31 Low 31 47.69 65 100.00 Frequency Missing = 7

Frequency Percent Frequency Percent Excellent 5 7.46 5 7.46 Fair 22 32.84 27 40.30 Good 38 56.72 65 97.01 Low 2 2.99 67 100.00 Frequency Missing = 5

Frequency Percent Frequency Percent Always 12 18.18 12 18.18 Never 2 3.03 14 21.21 Occasionally 29 43.94 43 65.15 Often 23 34.85 66 100.00 Frequency Missing = 6

45

Improve sustainability:

Better use of resources (land, soil, water etc)

Reduce or mitigate hazards, disasters:

Health improvement and safeguard:

Protect ecosystems and biodiversity:

Frequency Percent Frequency Percent Always 7 11.11 7 11.11 Never 3 4.76 10 15.87 Occasionally 31 49.21 41 65.08 Often 22 34.92 63 100.00 Frequency Missing = 9

Frequency Percent Frequency Percent Always 13 20.31 13 20.31 Never 4 6.25 17 26.56 Occasionally 15 23.44 32 50.00 Often 32 50.00 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Always 22 32.84 22 32.84 Occasionally 18 26.87 40 59.70 Often 27 40.30 67 100.00 Frequency Missing = 5

Frequency Percent Frequency Percent Always 10 15.63 10 15.63 Never 5 7.81 15 23.44 Occasionally 29 45.31 44 68.75 Often 20 31.25 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Always 4 6.25 4 6.25 Never 2 3.13 6 9.38 Occasionally 33 51.56 39 60.94 Often 25 39.06 64 100.00

46

Other:

How important is the demand of agrometeorological services in your Country/RA at the national and regional levels?

Demand of agrometeorological services at national level:

Demand of agrometeorological services at national level:

Which kinds of improvements are needed to increase the value of agrometeorological products and services for agricultural production?

Frequency Percent Frequency Percent Always 2 2.94 2 2.94 No other 64 94.12 66 97.06 Often 2 2.94 68 100.00 Frequency Missing = 4

Frequency Percent Frequency Percent Important at national level 37 55.22 37 55.22 No demand 3 4.48 40 59.70 fair at national level 27 40.30 67 100.00 Frequency Missing = 5

Frequency Percent Frequency Percent Fair at regional level 18 26.87 18 26.87 Important at regional level 22 32.84 40 59.70 No demand 27 40.30 67 100.00 Frequency Missing = 5

47

More knowledge about the potentialities offered by agrometeorology

More knowledge about agrometeorology products:

More facilities to use agrometeorological products:

More training of the personnel:

More technological information:

Frequency Percent Frequency Percent Important 31 47.69 31 47.69 Not so important 1 1.54 32 49.23 Very important 33 50.77 65 100.00 Frequency Missing = 7

Frequency Percent Frequency Percent Important 32 50.00 32 50.00 Not so important 3 4.69 35 54.69 Very important 29 45.31 64 100 00

Frequency Percent Frequency Percent Important 32 50.00 32 50.00 Not so important 3 4.69 35 54.69 Very important 29 45.31 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Important 28 43.75 28 43.75 Not so important 6 9.38 34 53.13 Very important 30 46.88 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Important 30 46.88 30 46.88 Not so important 10 15.63 40 62.50 Very important 24 37.50 64 100.00 Frequency Missing = 8

48

More public diffusion of the meaning of “agrometeorology”:

Other:

Which kinds of improvements are needed to increase the value of agrometeorological products and services for civil and economy uses? Imim------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ Improved dissemination of their potential utility:

Frequency Percent Frequency Percent Important 26 40.00 26 40.00 Not so important 5 7.69 31 47.69 Very important 34 52.31 65 100.00 Frequency Missing = 7

Frequency Percent Frequency Percent Important 3 4.55 3 4.55 No other 55 83.33 58 87.88 Very important 8 12.12 66 100.00 Frequency Missing = 6

Frequency Percent Frequency Percent Important 31 47.69 31 47.69 Not so Important 3 4.62 34 52.31 Very important 31 47.69 65 100.00 Frequency Missing = 7

49

More knowledge about type and usefulness of agrometeorological products:

More facilities to use agrometeorological products:

More training of the personnel belonging to different administrations:

More technological information:

More public diffusion of the meaning of “agrometeorology” and of its applications

Frequency Percent Frequency Percent Important 32 50.00 32 50.00 Not so Important 2 3.13 34 53.13 Very important 30 46.88 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Important 31 48.44 31 48.44 Not so Important 7 10.94 38 59.38 Very important 26 40.63 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Important 27 42.19 27 42.19 Not Important 1 1.56 28 43.75 Not so Important 8 12.50 36 56.25 Very important 28 43.75 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Important 35 54.69 35 54.69 Not so Important 9 14.06 44 68.75 Very important 20 31.25 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Important 29 44.62 29 44.62 Not so Important 4 6.15 33 50.77 Very important 32 49.23 65 100.00 Frequency Missing = 7

50

More exchange of information between stakeholders

How the demand of the users is studied to understand the needs of other public services and users for weather, climate and agrometeorological information and in the perspective to create a demand for them?

Attempt to understand the needs of other services to use weather, climate, agrometeorological information:

Attempt to create a demand:

Are advertising media used to demonstrate the value of agrometeorological services for decision-makers in agriculture, technician, farmers?

Frequency Percent Frequency Percent Important 24 37.50 24 37.50 Not so Important 3 4.69 27 42.19 Very important 37 57.81 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Excellen 4 6.67 4 6.67 Fair 24 40.00 28 46.67 Good 24 40.00 52 86.67 Low 7 11.67 59 98.33 Null 1 1.67 60 100.00 Frequency Missing = 12

Frequency Percent Frequency Percent Excellen 3 5.17 3 5.17 Fair 26 44.83 29 50.00 Good 19 32.76 48 82.76 Low 10 17.24 58 100.00 Frequency Missing = 14

51

Newspapers:

TV/radio:

E-mail:

Web:

Are advertising media used for demonstration the value of agrometeorological services to decision-makers, politicians, the private sector and public at large?

Frequency Percent Frequency Percent Always 10 15.38 10 15.38 Never 7 10.77 17 26.15 Occasionally 36 55.38 53 81.54 Often 12 18.46 65 100.00 Frequency Missing = 7

Frequency Percent Frequency Percent Always 12 18.46 12 18.46 Never 7 10.77 19 29.23 Occasionally 37 56.92 56 86.15 Often 9 13.85 65 100.00 Frequency Missing = 7

Frequency Percent Frequency Percent Always 5 7.81 5 7.81 Never 14 21.88 19 29.69 Occasionally 25 39.06 44 68.75 Often 20 31.25 64 100.00 Frequency Missing = 8

Frequency Percent Frequency Percent Always 18 28.13 18 28.13 Never 14 21.88 32 50.00 Occasionally 14 21.88 46 71.88 Often 18 28.13 64 100.00 Frequency Missing = 8

52

Newspapers:

TV/radio

E-mail

Web:

Frequency Percent Frequency Percent Always 8 12.70 8 12.70 Never 7 11.11 15 23.81 Occasionally 39 61.90 54 85.71 Often 9 14.29 63 100.00 Frequency Missing = 9

Frequency Percent Frequency Percent Always 8 12.70 8 12.70 Never 9 14.29 17 26.98 Occasionally 35 55.56 52 82.54 Often 11 17.46 63 100.00 Frequency Missing = 9

Frequency Percent Frequency Percent Always 4 6.45 4 6.45 Never 20 32.26 24 38.71 Occasionally 23 37.10 47 75.81 Often 15 24.19 62 100.00 Frequency Missing = 10

Frequency Percent Frequency Percent Always 15 24.19 15 24.19 Never 18 29.03 33 53.23 Occasionally 15 24.19 48 77.42 Often 14 22.58 62 100.00 Frequency Missing = 10