Rodrigo GarcíaManzanas

Curriculum Vitae

Personal DataDate and

Place of Birth30/August/1983, Oviedo (Spain).

Email rodrigo.manzanas@universite-paris-saclay.fr.

ORCIDwebpage

http://orcid.org/0000-0002-0001-3448.

EducationSeptember

2016PhD Programme in Science, Technology and Computation, University ofCantabria, Santander (Spain).PhD thesis: Statistical downscaling of precipitation in seasonal forecasting: Advan-tages and limitations of different approaches, http: // meteo. unican. es/ en/ theses/rmanzanas . Extraordinary Award from the University of Cantabria to the best PhD Thesisin Sciences in 2016. Extraordinary Award from the Social Council of the University ofCantabria.

October 2012 Master in Mathematics and Computer Science, University of Cantabria, San-tander (Spain).Master thesis: Ajuste de modelos lineales generalizados para su aplicación a la regional-ización de precipitación (Adjustment of generalized linear models for statistical downscalingof precipitation), http: // meteo. unican. es/ en/ theses/ rmanzanas_ master .

February2008

Five-year degree in Physics, University of Salamanca, Salamanca (Spain).Specialization: Atmospheric Physics and Meteorology.

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Professional ExperienceParticipation in competitive R&D projects

March2019–present

Position: Science officer, Intergovernmental Panel on Climate Change (IPCC),Working Group I, Université Paris-Saclay (France).

January 2018–February

2019

Position: Researcher, National Spanish Council for Research (CSIC), Institute ofPhysics of Cantabria (IFCA), Santander (Spain).Project: Enhancing Food Security in AFRIcan AgriCULTUral Systems with the Support ofREmote Sensing (AfriCultuReS). Funding institution: European Commission.Main achievements:� Calibration and quality assessment of seasonal predictions for Africa.� Research on seasonal predictability sources for Africa.

January 2017–December

2017

Position: Researcher, National Spanish Council for Research (CSIC), Institute ofPhysics of Cantabria (IFCA), Santander (Spain).Project: Quality Assessment Strategies for Multi-model Seasonal Forecasts (QA4Seas).Funding institution: European Commission.Main achievements:� Calibration and quality assessment of seasonal predictions.� Development of software tools with a special focus on the reproducibility of results and the

provision of adequate provenance information for different climate products (climate4Rand METACLIP).

October2014–

December2016

Position: R&D manager and researcher, Predictia Intelligent Data Solutions,Avda. los Castros s/n, Edificio I+D+i, S345, Santander (Spain).Main achievements:� Development of statistical downscaling techniques for practical applications in seasonal

forecasting, with a focus on market possibilities.� Research towards the development of climate services.

May 2013–September

2014

Position: Researcher, University of Cantabria, Santander (Spain).Project: EUropean Provision Of Regional Impact Assessment on a Seasonal-to-decadaltimescale (EUPORIAS). Funding institution: European Commission (through grant agree-ment 308291).Main achievements:� Study of the drift in seasonal forecasts.� Provision of bias-corrected data.� Statistical downscaling of climate surface variables in East Africa.� Assessment of the skill of the downscaled seasonal predictions.

August2010–April

2013

Position: Researcher, National Spanish Council for Research (CSIC), Institute ofPhysics of Cantabria (IFCA), Santander (Spain).Project: Quantifying Weather and Climate Impacts on Health in Developing Countries(QWeCI). Funding institution: European Commission (through grant agreement 243964).Main achievements:� Assessment of the skill of seasonal precipitation forecasts worldwide.� Analysis of the role of ENSO on the skill of global seasonal forecasts.� Development of the QWeCI statistical downscaling portal, open to partners with an initial

set of statistical-based seasonal predictions (in user-friendly formats) with documentationand support on good practices of use.

� Provision of downscaled and calibrated seamless seasonal forecasts in Africa (Senegal,Ghana and Malawi), with uncertainty estimations.

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Participation in other contracts, agreements or R&D projectsNovember

2017–March2018

Position: International consultant for FAO (UN), Philippine Atmospheric Geo-physical and Astronomical Services Administration (PAGASA), Manila (Philippines).Project: Enhanced Production and Risk Management in Agriculture Decision SupportSystem (EPRiMA). Funding institutions: Food and Agriculture Organization of the UnitedNations (FAO).Main achievements:� Training of PAGASA’s staff on the interpretation, access, manipulation and validation of

seasonal climate forecasts.� Delivery of statistically downscaled seasonal climate forecasts for the Philippines.

July 2004–September

2014

Position: International consultant for FAO (UN), Peruvian National Servicefor Meteorology and Hydrology (SENMAHI), Lima (Perú).Project: Analysis and Mapping of Impacts under Climate Change for Adaptation and FoodSecurity (AMICAF). Funding institutions: Japanese Ministry of Agriculture and the Foodand Agriculture Organization of the United Nations (FAO).Main achievements:� Training of SENAMHI’s staff on the application of statistical techniques for climate

analysis and downscaling.� Generation of statistically downscaled climate change scenarios of precipitation and

temperature for Peru.Scholar fellowships

March2010–July

2010

Position: Researcher, University of Cantabria, Santander (Spain).Project: Forest fires under climate, social and economic changes in Europe, the Mediter-ranean and other fire-affected areas of the world (FUME). Funding institution: EuropeanCommission.

January 2009–December

2009

Position: Researcher, University of Cantabria, Santander (Spain).Project: Escenarios regionales de cambio climático en Cantabria. Funding institution:Gobierno de Cantabria.

LanguagesSpanish Native.English Fluent. Official certificate EOI: C1 level.Italian Fluent. Official certificate PLIDA: C1 level.French Basic.

Computer skillsProgramming

languagesMatlab (advanced), R (ad-vanced), Python (basic).

Collaborativetools for

open-sourcesoftware

development

Git, GitHub, Jupyter.

Miscellaneous SVN, Latex, Office, Illustrator,etc.

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Attended courses and workshopsSeptember

2011Summer school ‘Climate impacts modeling for developing countries: Water,agriculture and health’, The Abdus Salam International Centre for TheoreticalPhysics, Trieste (Italy).

January 2009 UK-India workshop ‘Downscaling and linking to applications’, University ofEast Anglia, Norwich (UK).

Given courses and workshopsSeptember

2017Summer school ‘Big data and climate services’, University of Cantabria, Suances(Spain).Invited lecture ‘Climate services: A challenge por big data”

April 2017 Training on statistical downscaling of climate change projections in Paraguay,Asunción (Paraguay).International consultancy for FAO (UN)-Paraguay

March 2017 Training on statistical downscaling of climate change projections in Uruguay,Montevideo (Uruguay).International consultancy for FAO (UN)-Uruguay

March 2017 Training on statistical downscaling of climate change projections in Indone-sia, Bogor (Indonesia).International consultancy for FAO (UN)-Indonesia

August 2016 Training on statistical downscaling of climate change projections in Zambia,Lusaka (Zambia).International consultancy for FAO (UN)-Zambia

December2015

Training on statistical downscaling of climate change projections in Malawi,Blantyre (Malawi).International consultancy for FAO (UN)-Zambia

August 2011 Training on the use of the Data Access and Statistical Downscaling portalsdeveloped at the University of Cantabria, Joint AAP/WMO/ACMAD Workshopfor Western, Central and North African Countries on the Generation of ClimateProducts to Support Long-term Adaptation Planning, Accra (Ghana).

Lectures2018-2019 Associate professor, Calculus II, University of Cantabria (Department of Applied

Mathematics and Computer Science), Santander (Spain).2018-2019 Master in Data Science, Introduction to big data and open science, Data mining,

Machine Learning I, UIMP-University of Cantabria, Santander (Spain).2017-2018 Master in Data Science, Data mining, UIMP-University of Cantabria, Santander

(Spain).

PhD thesis judged

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July 2018 PhD Programme in Civil Engineering, University of Cantabria, Santander(Spain).José Antonio Álvarez Antolínez PhD thesis: Morphodynamic coastal evolution in a changingclimate.

Papers reviewed forInternational journals, Atmospheric Science Letters, Net Journal of AgriculturalScience, Quarterly Journal of the Royal Meteorological Society, PLoS ONE, ClimateDynamics, International Journal of Climatology, Climate Services, Oxford ResearchEncyclopedia of Climate Science, Asia-Pacific Journal of Atmospheric Sciences.

Contributions to software developmentclimate4R R-based framework (http://www.meteo.unican.es/climate4R) for transpar-

ent climate data access, post-processing (including bias correction and down-scaling) and visualization.climate4R is based on the following main packages:� loadeR: Climate data access (either locally or remotely from OPenDAP servers) in a

user-transparent way building on NetCDF Java.� transformeR: Climate data manipulation and transformation including subsetting, regrid-

ding, and data conversion.� downscaleR: Empirical-statistical downscaling with the most popular approaches (bias

correction, Model Output Statistics, Perfect Prognosis) and techniques.� visualizeR: Climate data visualization, with special focus on ensemble forecasting and

uncertainty communication.calibratoR R-package for calibration of seasonal forecasts (http://github.com/

SantanderMetGroup/calibratoR).METACLIP(METAdatafor CLImateProducts)

Language-independent framework envisaged to tackle the problem of cli-mate product provenance description (http://www.metaclip.org).METACLIP is based on semantics exploiting the web standard Resource Description Frame-work (RDF), building on domain-specific extensions of standard vocabularies (e.g. PROV-O)describing the different aspects involved in climate product generation. The METACLIPInterpreter, a web-based interactive front-end for metadata visualization helps a diversity ofusers with different levels of expertise to trace and understand the provenance of a widevariety of climate data products, and to fully reproduce them.

StatisticalDownscalingPortal (SDP)

Web-based application for easy-friendly statistical downscaling of regionalclimate change scenarios (http://www.meteo.unican.es/downscaling).The SDP from the University of Cantabria allows end-users to downscale the coarse outputsfrom global climate models in the region of interest (using historical observed records) bymeans of a wide range of statistical techniques.

MeteoLab Open-source Matlab toolbox for statistical (data mining) analysis in meteo-rology (http://www.meteo.unican.es/es/software/meteolab).

Awards

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Extraordinary Award from the University of Cantabria, to the best PhD Thesisin sciences in 2016.

Extraordinary Award from the Social Council of the University of Cantabria.

Contributions to congresses and workshops19 Mar 2019 Case studies in the Copernicus Atmosphere Monitoring Service (CAMS),

Workshop on Copernicus climate change and atmosphere monitoring services, San-tander (Spain), Invited talk.R. Manzanas

17 Jan 2019 Seasonal climate forecast multi-model combination and skill assessment, 2ndSECLI-Firm Stakeholder Workshop on Energy Wind Production, Milan (Italy), In-vited talk.F. J. Doblas-Reyes, R. Manzanas, J. M. Gutiérrez, S. Hemri, J. Bhend, N. González-Reviriego, I. Jiménez, L. Lledó, R. Marcos, A. Soret, M. Terrado and V. Torralba

20 Sep 2018 Process-conditioned bias correction for seasonal forecasting: A case-studywith ENSO in Peru, 8th International Workshop in Climate Informatics, Boulder(USA), Poster.J. M. Gutiérrez, J. Bedia, M. Iturbide, S. Herrera, R. Manzanas, J. Baño-Medina, M. D.Frías, D. San-Martín, J. Fernández and A. S. Cofiño

14 May 2018 Process-conditioned bias correction for seasonal forecasting: A case-studywith ENSO in Peru, 2nd Workshop on Bias Correction in Climate Studies, San-tander (Spain), Oral.R. Manzanas and J. M. Gutiérrez

14 May 2018 DownscaleR: An R-based package for statistical downscaling and bias cor-rection within the climate4R framework, 2nd Workshop on Bias Correction inClimate Studies, Santander (Spain), Poster.M. Iturbide, J. Bedia, S. Herrera, J. Baño-Medina, R. Manzanas and J. M. Gutiérrez

6 Oct 2016 Downscaling tools for adapting climate predictions to the user’s needs: Chal-lenges for their integration into climate services, International Conference onClimate Science and Climate Services, Exeter (UK), Invited talk.J. Bedia, A. S. Cofiño, J. M. Gutiérrez, J. Fernández, S. Herrera, R. Manzanas, M. Vega,M. Iturbide and M. E. Magariño

6 Oct 2016 Advantages and limitations of different statistical downscaling approachesfor seasonal forecasting, International Conference on Climate Science and ClimateServices, Exeter (UK), Invited talk.R. Manzanas, J. M. Gutiérrez and A. Weisheimer

4 Oct 2016 Can bias correction methods improve the accuracy and reliability of seasonalforecasts?, Berlin-Workshop on Bias Correction in Climate Studies, Berlin (Ger-many), Oral.J. M. Gutiérrez and R. Manzanas.

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20 Apr 2016 ECOMS-UDG. A user-friendly data access gateway to seasonal forecastdatasets allowing R-based remote data access, visualization-validation, biascorrection and downscaling, European Geosciences Union (EGU) General Assem-bly 2016, Vienna (Austria), Poster.A. S. Cofiño, J. M. Gutiérrez, J. Fernández, J. Bedia, M. Vega, S. Herrera, M. D. Frías, M.Iturbide, M. E. Magariño and R. Manzanas.

8 Apr 2016 Statistically downscaled projected climate in the Philippines (2020-2079),International Symposium on Tropical Meteorology and Marine Science and Tech-nology, Guangzhou (China), Oral.J. Basconcillo, A. Lucero, A. Solís, H. Kanamaru, R. Manzanas, F. Hilario, E. Juanillo, J.Ruiz, G. A. Durán, T. Koizumi, E. Bautista and R. Jr. Sandoval.

19 Dec 2014 Sensitivity of statistical downscaling techniques to reanalysis choice andimplications for regional climate change scenarios, 2014 American GeophysicalUnion (AGU) Fall Meeting, San Francisco (USA), Oral.R. Manzanas, S. Brands, D. San-Martín, A. Lucero, C. Limbo and J. M. Gutiérrez.

2 Oct 2014 SPECS-PREFACE workshop on initial shock, drift and systematic error, Cli-mate Prediction Task Force virtual workshop bias corrections in subseasonal tointerannual predictions, Invited talk.F. J. Doblas-Reyes, E. Sánchez-Gómez, N. Fuckar, C. Prodhomme, D. Volpi, R. Weber,H. Pohlmann, T. Losada, E. Mohino, B. Rodríguez-Fonseca, T. Demissie, T. Toniazzo, R.Manzanas and J. Shonk.

2 May 2014 Assessing the drift of seasonal forecasts, European Geosciences Union (EGU)General Assembly 2014, Vienna (Austria), Poster.R. Manzanas, J. Fernández, M. E. Magariño, J. M. Gutiérrez, F. J. Doblas-Reyes, G.Nikulin and C. Buontempo.

26 October2012

Seasonal predictability of wintertime insolation and wind speed on theIberian Peninsula using the Snow Advance Index, 8◦ Congreso Internacionalde la Asociación Española de Climatología (AEC), Salamanca (Spain), Poster.S. Brands, R. Manzanas, S. Herrera and J. M. Gutiérrez.

25 October2012

A critical reassessment of statistical downscaling techniques under climatechange conditions in Spain: Accuracy, distributional similarity and robust-ness, 8◦ Congreso Internacional de la Asociación Española de Climatología (AEC),Salamanca (Spain), Poster.R. Manzanas, J. M. Gutiérrez, D. San Martín, S. Brands and S. Herrera.

10 October2012

Assessing the robustness of statistical downscaling techniques for their appli-cation under climate change conditions, 12th Annual Meeting of the EuropeanMeteorological Society (EMS) and the 9th European Conference on Applied Clima-tology (ECAC), Lodz (Poland), Oral.R. Manzanas, J. M. Gutiérrez, D. San Martín, S. Brands and S. Herrera.

10 October2012

Seasonal predictability of wintertime precipitation in Europe using the SnowAdvance Index, 12th Annual Meeting of the European Meteorological Society(EMS) and the 9th European Conference on Applied Climatology (ECAC), Lodz(Poland), Oral.S. Brands, R. Manzanas, J. M. Gutiérrez and J. Cohen.

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22 August2011

Beyond ENSEMBLES: Data Access and Statistical Downscaling Portals,Joint AAP/WMO/ACMAD Workshop for Western, Central and North AfricanCountries on the Generation of Climate Products to Support Long-term Adap-tation Planning, Accra (Ghana), Invited talk.R. Manzanas, A. S. Cofiño, D. San Martín, J. M. Gutiérrez, J. Fernández and S. Herrera.

11 May 2011 The ENSEMBLES Downscaling Portal. Beyond the ENSEMBLES project,9th Global Organization for Earth System Science Portals (GO-ESSP) Workshop,Asheville (USA), Oral.A. S. Cofiño, D. San Martín, S. Brands, J. M. Gutiérrez, J. Fernández, S. Herrera and R.Manzanas.

13 October2010

ENSO-driven predictability of tropical dry autumns using the seasonal EN-SEMBLES multimodel, 10th Annual Meeting of the European MeteorologicalSociety (EMS) and the 8th European Conference on Applied Climatology (ECAC),Zurich (Switzerland), Oral.R. Manzanas, J. M. Gutiérrez, A. S. Cofiño and M. D. Frías.

26 May 2010 Predictability of monthly European precipitation and temperature based onENSO-NAO interactions, ESF-MedCLIVAR Workshop on ‘Hydrological, socioe-conomic and ecological impacts of the North Atlantic Oscillation in the Mediter-ranean region’, Zaragoza (Spain), Oral.R. Manzanas, J. M. Gutiérrez, M. D. Frías and A. S. Cofiño.

3 May 2010 ENSO-driven skill of ENSEMBLES STREAM 2 multimodel seasonal precip-itation hindcasts over the globe, European Geosciences Union (EGU) GeneralAssembly 2010, Vienna (Austria), Oral.R. Manzanas, J. M. Gutiérrez, A. S. Cofiño and M. D. Frías.

Publications• R. Manzanas, J. M. Gutiérrez, J. Bhend, S. Hemri, F. J. Doblas-Reyes, V.Torralba, E. Penabad, A. Brookshaw Bias adjustment and ensemble recalibrationmethods for seasonal forecasting: A comprehensive intercomparison usingthe C3S dataset Climate Dynamics, 2019, doi: 10.1007/s00382-019-04640-4• M. Iturbide, J. Bedia, S. Herrera, J. Baño-Medina, J. Fernández, M. D. Frías, R.Manzanas, D. San-Martín, E. Cimadevilla, A. S. Cofiño and J. M. Gutiérrez TheR-based ‘climate4R’ open framework for reproducible climate data accessand post-processing Environmental Modelling & Software, 111:42–54. 2019, doi:10.1016/j.envsoft.2018.09.009• J. M. Gutiérrez, J. Bedia, M. Iturbide, S. Herrera, R. Manzanas, J. Baño-Medina,M. D. Frías, D. San-Martín, J. Fernández and A. S. Cofiño Climate research repro-ducibility with the ‘climate4R’ R-based framework in Proceedings of the 8thInternational Workshop on Climate Informatics 2018 (CI2018). NCAR TechnicalNote NCAR/TN-550+PROC, 2018, doi: 10.5065/D6BZ64XQ• R. Manzanas and J. M. Gutiérrez. Process-conditioned bias correction forseasonal forecasting: A case-study with ENSO in Peru Climate Dynamics,52(3-4):1673–1683, 2018, doi: 10.1007/s00382-018-4226-z.

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• J. M. Gutiérrez, D. Maraun, M. Widmann, R. Huth, E. Hertig, R. Benestad, O.Roessler, J. Wibig, R. Wilcke, S. Kotlarski, D. San Martín, S. Herrera, J. Bedia, A.Casanueva, R. Manzanas, M. Iturbide, M. Vrac, M. Dubrovsky, J. Ribalaygua, J.Pórtoles, O. Räty, J. Räisänen, B. Hingray, D. Raynaud, M. J. Casado, P. Ramos,T. Zerenner, M. Turco, T. Bosshard, P. Štěpánek, J. Bartholy, R. Pongracz, D. E.Keller, A. M. Fischer, R. M. Cardoso, P. M. M. Soares, B. Czernecki and C. PagéAn intercomparison of a large ensemble of statistical downscaling methodsover Europe: Results from the VALUE perfect predictor cross-validation ex-periment International Journal of Climatology, 1–36, 2018, doi: 10.1002/joc.5462• G. Nikulin, S. Asharaf, M. E. Magariño, S. Calmanti, R. M. Cardoso, J. Bhend,J. Fernández, M. D. Frías, K. Fröhlich, B. Früh, S. Herrera, R. Manzanas, J. M.Gutiérrez, U. Hansson, M. Kolax, M. A. Liniger, P. M. M. Soares, C. Spirig and K.Wyser. Dynamical and statistical downscaling of a global seasonal hindcast ineastern Africa Climate Services, 9:72–85, 2018, doi: 10.1016/j.cliser.2017.11.003• M. D. Frías, M. Iturbide, R. Manzanas, J. Bedia, J. Fernández, S. Herrea, A. S.Cofiño and J. M. Gutiérrez. An R-package to visualize and communicate un-certainty in seasonal climate prediction. Environmental Modelling & Software,99:101–110, 2018, doi: 10.1016/j.envsoft.2017.09.008• P. Falloon, M. B. Soares, R. Manzanas, D. San-Martín, F. Liggins, I. Taylor,R. Kahana, J. Wilding, C. Jones, R. Comer, E. De Vreede, W. S. de Cerff, C.Buontempo, A. Brookshaw, S. Stanley, R. Middleham, D. Pittams, E. Lawrence,E. Bate, H. Peter, K. Uzell and M. Richards. The Land Management Tool:developing a climate service in Southwest UK. Climate Services, 9:86-100,2018, doi: 10.1016/j.cliser.2017.08.002• A. S. Cofiño, J. Bedia, M. Iturbide, M. Vega, S. Herrera, J. Fernández, M. D. Frías,R. Manzanas and J. M. Gutiérrez. The ECOMS User Data Gateway: Towardsseasonal forecast data provision and research reproducibility in the era of cli-mate services. Climate Services, 9:33-43, 2018, doi: 10.1016/j.cliser.2017.07.001.• R. Manzanas, J. M. Gutiérrez, J. Fernández, E. van Meijgaard, S. Calmanti, M. E.Magariño, A. S. Cofiño and S. Herrera. Dynamical and statistical downscaling ofseasonal temperature forecasts in Europe: Added value for user applications.Climate Services, 9:44-56, 2018, doi: 10.1016/j.cliser.2017.06.004.• R. Manzanas, A. Lucero, A. Weisheimer and J. M. Gutiérrez. Can biascorrection and statistical downscaling methods improve the skill of sea-sonal precipitation forecasts? Climate Dynamics, 50(3-4):1161-1176, 2018, doi:10.1007/s00382-017-3668-z.• J. Fernández, A. Casanueva, J. P. Montávez, M. A. Gaertner, M. J. Casado,R. Manzanas and J. M. Gutiérrez. Regional climate projections over Spain:Atmosphere. Future climate projections. CLIVAR exchanges 73: Special issueon climate over the Iberian Peninsula: An overview of CLIVAR-Spain coordinatedscience, 2017, URL: http://www.clivar.org/documents/exchanges-73

• R. Manzanas. Assessing the suitability of statistical downscaling ap-proaches for seasonal forecasting in Senegal. Atmospheric Science Letters,18(9):381–386, 2017, doi: 10.1002/asl.767

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• D. San Martín, R. Manzanas, S. Brands, S. Herrera and J. M. Gutiérrez.Reassessing model uncertainty for regional projections of precipitation withan ensemble of statistical downscaling methods. Journal of Climate, 30(1):203–223, 2017, doi: 10.1175/JCLI-D-16-0366.1.• R. Manzanas, S. Brands, D. San Martín, A. Lucero, C. Limbo and J. M. Gutiérrez.Statistical downscaling in the Tropics can be sensitive to reanalysis choice: Acase study for precipitation in the Philippines. Journal of Climate, 28(10):4171–4184, 2015, doi: 10.1175/JCLI-D-14-00331.1.• R. Manzanas, L. K. Amekudzi, K. Preko, S. Herrera and J. M. Gutiérrez.Precipitation variability and trends in Ghana: An intercomparison of obser-vational and reanalysis products. Climatic Change, 124(4):805–819, 2014, doi:10.1007/s10584-014-1100-9.• R. Manzanas, M. D. Frías, A. S. Cofiño and J. M. Gutiérrez. Validation of 40year multimodel seasonal precipitation forecasts: The role of ENSO on theglobal skill. Journal of Geophysical Research: Atmospheres, 119(4):1708–1719,2014, doi: 10.1002/2013JD020680.• J. M. Gutiérrez, D. San Martín, S. Brands, R. Manzanas and S. Herrera.Reassessing statistical downscaling techniques for their robust applicationunder climate change conditions. Journal of Climate, 26(1):171–188, 2013, doi:10.1175/JCLI-D-11-00687.1.• S. Brands, R. Manzanas, J. M. Gutiérrez and J. Cohen. Seasonal predictabilityof wintertime precipitation in Europe using the Snow Advance Index. Journalof Climate, 25(12):4023–4028, 2012, doi: 10.1175/JCLI-D-12-00083.1.

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