precipitation observational capabilities at the brazilian institute for space research carlos...

Precipitation Observational

Capabilities at the Brazilian

Institute for Space Research

Carlos Frederico Angelis*

Luiz Augusto Toledo Machado*

Carlos Augusto Morales**

* Brazilian Institute for Space Research – INPE/CPTEC

** University of Sao Paulo – USP/IAG

Instituto Nacional de Pesquisas Espaciais

Centro de Previsão de Tempo e Estudos Climáticos

Instituto Nacional de Pesquisas EspaciaisInstituto Nacional de Pesquisas EspaciaisBrazilian Institute for Space ResearchBrazilian Institute for Space Research

INPEINPE


Weather Forecast and Climate Studies Centre

CPTEC



Centro de Previsão de Tempo e Estudos ClimáticosCentro de Previsão de Tempo e Estudos ClimáticosWeather Forecast and Climate Studies CentreWeather Forecast and Climate Studies Centre

CPTECCPTEC

Main facilities and data:

NEC supercomputers SX-4 e SX-6;

GOES, METEOSAT, NOAA, ACQUA,TERRA,TRMM database;

350 Data Collecting Plataforms (DCP);

16 Weather Radars



Satellite PrecipitationSatellite Precipitation

Operational Monitoring of Rainfall

Hydroestimator. An improved version of NESDIS Auto-estimator (Vicente et al. 1998/2001)




Issues being addressed by CPTEC´s Satellite Meteorology team :

1. The Hydroestimator does not consider different rainfall regimes over

South America;

2. The Hydroestimator uses only GOES images for precipitation estimation;

3. Although the Hydroestimator makes use of orography, wind and

precipitable water data produced by ETA model, it still uses Brightness

Temperature to access rain rates.




1. The Hydroestimator does not consider the different rainfall regimes over South America

Location of all DCP´s whose data are transmitted to the Brazilian Data Collecting Sattelite (SCD) and downlinked to CPTEC



Rainfall regimes based on 1-yr hourly precipitation data

VariableVariable

1 – Amount of rain 1 – Amount of rain

2 – Mean precipitation2 – Mean precipitation

3 – Mean precipitation for rainy hours3 – Mean precipitation for rainy hours

4 – Rainy hours and total of hours recorded ratio4 – Rainy hours and total of hours recorded ratio

5 – Mean precipitation - January5 – Mean precipitation - January

6 – Mean precipitation - February6 – Mean precipitation - February

7 – Mean precipitation - March7 – Mean precipitation - March

8 – Mean precipitation - April8 – Mean precipitation - April

9 – Mean precipitation - May9 – Mean precipitation - May

10 – Mean precipitation - June10 – Mean precipitation - June

11 – Mean precipitation - July11 – Mean precipitation - July

12 – Mean precipitation - August12 – Mean precipitation - August

13 – Mean precipitation - September13 – Mean precipitation - September

14 – Mean precipitation - October14 – Mean precipitation - October

15 – Mean precipitation - November15 – Mean precipitation - November

16 – Mean precipitation - December16 – Mean precipitation - December

17 – 117 – 1stst harmonic amplitude harmonic amplitude

18 – 118 – 1stst harmonic phase harmonic phase

19 – 219 – 2ndnd harmonic amplitude harmonic amplitude

20 – 220 – 2ndnd harmonic phase harmonic phase


1. The Hydroestimator does not consider the different rainfall regimes over South America




2. The Hydroestimator uses only GOES images for precipitation estimation

Due to the hurricane season over the Northern Hemisphere, CPTEC does not receive GOES images regularly. The Hydroestimator has produced only 8 daily accumullated rainfall estimations during September 2004.

It causes impact on many users like agricultural companies which depend on daily precipitation to plan soybean, corn, bean and other crops.



Mean precipitation - October/2004

METEOSAT images have just been introduced to Hydroestimator when GOES images are not available

Satellite PrecipitationSatellite Precipitation2. The Hydroestimator uses only GOES images for precipitation estimation

GOES METEOSAT GOES - METEOSAT




3. The Hydroestimator uses Brightness Temperature to access rain rates

Other parameters different from Brightness Temperature have been tested

in order to develop a new algorithm which considers regional rainfall

regimes and physical properties of convective systems.





According to Machado et al. (2004) the life span of a convective system is significantly related to its area expansion.

Area expansion and associated Std Deviation as a function of the convective system lifetime





Forecasting and tracking of active convective cells cloud clusters



Weather RadarsWeather Radars

16 weather radars are being integrated in two different networks

Operational weather radars in South America




The radars networks are producing data which, in a near future, will be valuable to shed

light on important topics like:

1. Which meteorological and climate processes are linked to the Amazonian and global climates?

2. How does the surface heterogeneity interfere in the vertical movements and also in the cloudiness? What are

the effects of regional and long distance transportation of heat, humidity and aerosols?

3. What is the limit of current models in conceiving scenarios about land use and climate change impacts on

global climate?

4. How does the South American Low Level Jets (SALLJ) vary as a function of synoptical conditions? What is the

role of synoptical systems associated with the westerly flows in high altitudes? Does the Chaco Low play an

important role on the SALLJ modulation?

5. What is SALLJ spatial structure and its temporal variability? What are the impacts of SALLJ on Mesoscale

Convective Systems over the Prata Basin?

6. Do atmospheric simulation models reproduce satisfactorily SALLJ spatial and temporal structures in different

spatial and temporal scales?




The Amazonian radar network will be fundamental to confirm the direction of

rainfall propagation in Western Amazon showed by previous research.

Difference between 1800 and 0600 LST (left) and 2100 and 0900 LST (right) SSM/I images averaged over the period 1992-1997. Blue shades indicate morning maxima and red shades indicate afternoon maxima (Negri et al., 2000)




TRMM-PR overlaid with gauge first harmonic phase (Angelis et al., 2004)



The Amazonian radar network will be fundamental to confirm the direction of

rainfall propagation in Western Amazon showed by previous research.

CPTEC´s Satellite Meteorology team is the only group that works

on research and development of meteorological and climatological

operational products in Brazil .



precipitation observational capabilities at the brazilian institute for space research carlos...

Documents

daily precipitation

satellite precipitation

pesquisas espaciais

meteosat instituto nacional

clusters instituto nacional

different rainfall regimes

space research inpe

rainy hours