GUEMAS Virginie

Virginie GUEMAS

Head of the Climate Prediction Group
within the Earth Sciences Department
at the Barcelona Supercomputing Center (BSC), Barcelona, Spain.
Ramon y Cajal fellow (Highly competitive grant : 2% success)


Visiting Scientist in the EAC team (Equipe ARPEGE Climat)
from the GMGEC group (Goupe de Météorologie de Grande Echelle et Climat)

Email :

Phone : +33 (0) 5 61 07 96 07 / +34 934 137 679


 Research interests

- Understanding sources of climate predictability at sub-seasonal to decadal timescales and attribution of climate events exploiting successful climate predictions
- Climate forecasting system development : initialization, ensemble generation and bias correction techniques as well as improvement of process representation through inclusion of new model parameterizations / components, parameter calibration and resolution increase
- Understanding sources of model errors, both systematic errors and case studies


- Co-coordinator of the ERA4CS MEDSCOPE project (2017-2019) on enhancing climate prediction capability with a focus on Western Europe.

- PI of the H2020-funded APPLICATE (2016-2020) project focusing on the linkages between the Arctic and mid-latitude regions.

- PI of the H2020-funded INTAROS (2016-2020) project focusing on documenting the Arctic climate.

- PI of the Copernicus C3S-MAGIC (2016-2019) project aiming at developing a web interface for an easy evaluation of CMIP-class models and their climate change projections

- PI of the FP7 EU-funded PREFACE (2013-2017) project focusing on improving the representation of climate processes in the Tropical Atlantic region.

- PI of the FP7 EU-funded EUCLEIA (2014-2017) project focusing on attribution of climate extreme events.

- PI of the ESA CMUG2 (2014-2017) project focusing on exploiting high-resolution high-quality satellite observations for initialization and verification of climate predictions.

- PI of the H2020 EU-funded IMPREX (2015-2019) project focusing on forecasting and attributing hydro-meteorological extremes.

- PI of the national HIATUS (2016-2018) project aiming at understanding the mechanisms behind periods of reduced warming or cooling under climate change.

- PRIMAVERA : I am co-WP2 leader of the
H2020 PRIMAVERA (PRocess-based climate sIMulations : AdVances in high resolution modelling and European climate Risk Assessment) project.

- I am also involved in the FP7-funded SPECS and EUPORIAS and the Copernicus QA4Seas projects

- I was PI of the national PICA-ICE (2013-2015) project focusing on improving seasonal predictions of the Arctic sea ice conditions and their impact on the Northern mid-latitudes.

  Student Supervision

Ruben Cruz, PhD student, October 2015 - present : Regional Arctic sea ice predictability and prediction on seasonal to interannual timescales.

Aude Carreric, PhD student, October 2015 - present : La diversité d’ENSO dans le changement climatique. Co-supervision

Danila Volpi, PhD Student, January 2011 - March 2015 : Benefits and drawbacks of different initialization techniques in global dynamical climate predictions. Co-supervision

  Peer-reviewed Publications

[46] Bellprat O, Massonnet F, Siegert S, Prodhomme C, Guemas V. Doblas-Reyes F, Uncertainty propagation in observational references to climate model scales, Remonte Sensing of Environment, in press.

[45] Ardilouze C, Batte L, Bunzel F, Decremer D, Deque M, Doblas-Reyes F, Douville H, Fereday D, Guemas V, MacLachlan C, Muller W, Prodhomme C, 2017, Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability. Climate Dynamics, 10.1007/s00382-017-3555-7.

[44] Volpi D, Guemas V, Doblas-Reyes F, 2017, Comparison of full field and anomaly initialisation for decadal climate prediction : towards an optimal consistency between the ocean and sea-ice anomaly initialisation state. Climate Dynamics, doi:10.1007/s00382-016-3373-3.

[43] Massonnet F, Bellprat O, Guemas V, Doblas-Reyes F, 2017, Using climate models to estimate the quality of global observational data sets. Sciences, doi : 10.1126/science.aaf6369.

[42] Prodhomme C, Batte L, Massonnet F, Guemas V, Davini P, Doblas-Reyes F, 2017, Benefits of increasing the model resolution for the seasonal forecast quality in EC-Earth. Journal of Climate, doi/10.1175/JCLI-D-16-0117.1.

[41] Volpi D, Guemas V, Doblas-Reyes F, Hawkins E, Nichols N, 2017, Decadal climate prediction with a refined anomaly initialisation approach. Climate Dynamics, 48 (5), 1841–1853, doi:10.1007/s00382-016-3176-6.

[40] Krikken F, Hazeleger W, Vlot W, Schmeits M, Guemas V, 2017, Skill improvement of dynamical seasonal Arctic sea ice forecasts. Geophysical Research Letters, doi:10.1002/2016GL068462.

[39] García-Serrano J, Frankignoul C, King MP, Arribas A, Gao Y, Guemas V, Matei D, Msadek R, Park W, Sanchez-Gomez E, 2017, Multi-model assessment of linkages between eastern Arctic sea-ice variability and the Euro-Atlantic atmospheric circulation in current climate, Climate Dynamics, doi:10.1007/s00382-016-3454-3.

[38] Bellprat O, Massonnet F, García-Serrano J, Fuckar N, Guemas V, Doblas-Reyes F, 2016, The role of Arctic sea ice and sea surface temperatures on the cold 2015 February over North America. Bulletin of the American Meteorological Society, 97, S36-S41, doi:10.1175/BAMS-D-16-0159.1.

[37] Fuckar N, Massonnet C, Guemas V, Garcia-Serrano J, Bellprat O, Doblas-Reyes F, Acosta M, 2016, Record low northern hemisphere sea ice extent in March 2015. Bulletin of American Meteorological Society, 97, S136-S140, doi:10.1175/BAMS-D-16-0153.1.

[36] Haarsma RJ, Roberts M, Vidale PL, Senior CA, Bellucci A, Corti S, Fučkar NS, Guemas V, von Hardenberg J, Hazeleger W, Kodama C, Koenigk T, Leung LR, Lu J, Luo JJ, Mao J, Mizielinski MS, Mizuta R, Nobre P, Satoh M, Scoccimarro E, Semmler T, Small J, von Storch JS, 2016, High Resolution Model Intercomparison Project (HighResMIP). Geosci. Model Dev. Discuss., 9, 4185-4208, doi:10.5194/gmd-9-4185-2016.

[35] Guemas V, Chevallier M, Deque M, Bellprat O, Doblas-Reyes F J, 2016, Impact of sea ice initialisation on sea ice and atmosphere prediction skill on seasonal timescales. Geophysical Research Letters, 43 (8), 3889-3896, doi:10.1002/2015GL066626.

[34] Carrassi A, Guemas V, Doblas-Reyes F J, Volpi D, Asif M, 2016, Sources of skill in near-term climate prediction : generating initial conditions. Climate Dynamics, 47 (12), 3693–3712.

[33] Fuckar N S, Guemas V, Johnson N C, Massonnet F, Doblas-Reyes F J, 2015, Clusters of interannual sea ice variability in the Northern Hemisphere. Climate Dynamics, 45, 1-17, doi:10.​1007/​s00382-015-2917-2.

[32] Massonnet F, Guemas V, Fuckar N S, Doblas-Reyes, F J, 2015, The 2015 high record of Antarctic sea ice extent [in "Explaining Extreme Events of 2014 from a Climate Perspective"]. Bull. Amer. Meteor. Soc., 96 (9), S163-S167, doi:10.1175/BAMS-D-15-00093.1.

[31] Day J, Tietsche S, Collins M, Goessling H, Guemas V , Guillory A, Hurlin W, Ishii M, Keeley S, Matei D, Msadek R, Sigmond M, Tatebe H, Hawkins E, 2016, The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1. Geosci. Model Dev. Discuss., 9, 2255-2270, doi:10.5194/gmdd-9-2255-2016.

[30] Stroeve J, Blanchard-Wrigglesworth E, Guemas V, Howell S, Massonnet F, Tietsche S, 2015, Improving Predictions of Arctic Sea Ice Extent. EOS, 96, doi:10.1029/2015EO031431.

[29] Jung T, Doblas-Reyes FJ, Goessling H, Guemas V, Bitz C, Buontempo C, Caballero R, Jokobsen E, Karcher M, Koenigk T, Matei D, Overland J, Spengler T, Yang S, 2015, Polar-lower latitude linkages and their role in weather and climate prediction. Bull. Amer. Meteor. Soc., 96, ES197-ES200, doi:10.1175/BAMS-D-15-00121.1.

[28] García-Serrano J, Guemas V,, Doblas-Reyes F, 2015, Added-value from initialization in predictions of Atlantic multi-decadal variability. Climate Dynamics, 44 (9-10), 2539-2555, doi:10.1007/s00382-014-2370-7.

[27] Guemas V, Blanchard-Wrigglesworth E, Chevallier M, Day J J, Déqué M, Doblas-Reyes F J, Fučkar N, Germe A, Hawkins E, Keeley S, Koenigk T, Salas y Mélia D, Tietsche S, 2015, A review on Arctic sea ice predictability and prediction on seasonal-to-decadal timescales, Quarterly Journal of the Royal Meteorology Society, doi:10.1002/qj.2401.

[26] Guemas V, García-Serrano J, Mariotti A, Doblas-Reyes F, Caron L-P, 2015, Prospects for decadal climate prediction in the Mediterranean region. Quarterly Journal of the Royal Meteorological Society, 141, 580-597, doi:10.1002/qj.2379.

[25] Guemas V, Auger L, Doblas-Reyes FJ, Rust H, Ribes A, 2014, Dependencies in Statistical Hypothesis Tests for Climate Time Series. Bulletin of the American Meteorological Society, 95 (11), 1666-1667.

[24] Fučkar N, Volpi D, Guemas V, Doblas-Reyes F, 2014, A posteriori adjustment of near-term climate predictions : Accounting for the drift dependence on the initial conditions. Geophysical Research Letters, 41 (14), 5200–5207, doi:10.1002/2014GL060815.

[23] Carrassi A, Weber R, Guemas V, Doblas-Reyes F, Asif M, Volpi D, 2014, Full-Field and Anomaly Initialization using a low-order climate model : a comparison and proposals for advanced formulations. Non linear processes in geophysics, 21, 521-537, doi:10.5194/npg-21-521-2014.

[22] Guemas V, Doblas-Reyes F J, Mogensen K, Keeley S. , Tang Y., 2014, Ensemble of sea ice initial conditions for interannual climate predictions. Climate Dynamics, 43(9-10), 2813-2829, doi:10.1007/s00382-014-2095-7.

[21] Tietsche S., Day J. J., Guemas V., Hurlin W.J., Keeley S.P.E., Matei D., Msadek R., Collins M., Hawkins E., 2014, Seasonal to interannual Arctic sea-ice predictability in current GCMs. Geophysical Research Letters, 41(3), 1035-1043, doi:10.1002/2013GL058755.

[20] Guemas V., Auger L, Doblas-Reyes F., 2014, Hypothesis testing for auto-correlated short climate time series. Journal of Applied Meteorology and Climatology, 53(3), 637-651, doi:10.1175/JAMC-D-13-064.1.

[19] Guemas V., Doblas-Reyes F., Germe A., Chevallier M., Salas y Mélia D., 2013, September 2012 Arctic sea ice minimum : Discriminating between sea ice memory, the August 2012 extreme storm and prevailing warm conditions [in "Explaining Extreme Events of 2012 from a Climate Perspective"], Bull. Amer. Meteor. Soc., 94 (9), S20-S22.

[18] Wouters B., Hazeleger W., Drijfhout S., van Oldenborgh G., Guemas V., 2013, Multiyear predictability of the North Atlantic subpolare gyre. Geophysical Research Letters, 40(12), 3080-3084, doi:10.1002/grl.50585.

[17] Volpi, D., Doblas-Reyes F. J., García-Serrano J., Guemas V., 2013, Dependence of the climate prediction skill on spatio-temporal scales : internal versus radiatively-forced contribution. Geophysical Research Letters, 40(12), 3213-3219, doi:10.1002/grl.50557.

[16] Guemas V. , Doblas-Reyes F. J., Andreu-Burillo I., Asif M., 2013, Retrospective prediction of the global warming slowdown in the past decade. Nature Climate Change, 3, 649-653, doi : 10.1038/nclimate1863.

[15] Doblas-Reyes F. J., Andreu-Burillo I., Chikamoto Y., García-Serrano J., Guemas V., Kimoto M., Mochizuki T., Rodrigues L. R. L. and van Oldenborgh G. J., 2013, Initialized near-term regional climate change prediction. Nature Communications, 4, 1715, doi:10.1038/ncomms2704.

[14] Hazeleger, W., Guemas V., Wouters B., Corti S., Andreu-Burillo I., Doblas-Reyes F. J., Wyser K., Caian M., 2013, Multiyear climate predictions using two initialisation strategies. Geophysical Research Letters, 40(9), 1794-1798, doi:10.1002/grl.50355.

[13] Guemas, V., Corti S., Garcìa-Serrano J., Doblas-Reyes F., Balmaseda M., Magnusson L., 2013, The Indian Ocean : the region of highest skill worldwide in decadal climate prediction, Journal of Climate, 26(3), 726-739 doi:10.1175/JCLI-D-12-00049.1.

[12] Guemas, V., Salas-Melia D., Kageyama M., Giordani H., Voldoire A., 2013, Impact of the ocean diurnal cycle on the North Atlantic European mean climate in a regionally coupled model, Dynamics of Atmospheres and Oceans, 60, 28-45, doi:10.1016/j.dynatmoce.2013.01.001.

[11] Smith D. M., Scaife A. A., Boer G. J., Caian M., Doblas-Reyes F. J., Guemas V., Hawkins E., Hazeleger W., Hermanson L., Ho C. K., Ishii M., Kharin V., Kimoto M., Kirtman B., Lean J., Matei D., Merryfield W. J., Müller W. A., Pohlmann H., Rosati A., Wouters B., Wyser K., 2013, Real-time multi-model decadal climate predictions, Climate Dynamics, 41(11-12), 2875-2888, doi:10.1007/s00382-012-1600-0.

[10] Hourdin F., Foujols M.A., Codron F., Guemas, V., Dufresne J.L., Bony S., Denvil S., Guez L., Lott F., Gatas J., Braconnot P., Marti O., Meurdesoif Y. Bopp, L., 2013, Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model, Climate Dynamics, 40(9-10), 2167-2192, doi : 10.1007/s00382-012-1411-3.

[9] Guemas, V., Doblas-Reyes F., Lienert F., Du H., Soufflet Y., 2012, Identifying the causes for the poor decadal climate prediction skill over the North Pacific, Journal of Geophysical Research, 117(D20), 2156-2202, D20111, doi:10.1029/2012JD018004.

[8] Du H., Doblas-Reyes F., Garcìa-Serrano J., Guemas V., Soufflet Y., Wouters B., 2012, Sensitivity of decadal predictions to the initial atmospheric and oceanic perturbations, Climate Dynamics, 39 (7-8), 2013-2023. doi : 10.1007/s00382-011-1285-9.

[7] Guemas, V., Codron F., 2011, Differing impacts of resolution changes in latitude and longitude on the mid-latitudes in the LMDZ GCM. Journal of Climate, 24 (22), 5831-5849. doi : 10.1175/2011JCLI4093.1.

[6] Guemas, V., Salas-Melia D., Kageyama M., Giordani H., Voldoire A., 2011, Impact of the ocean mixed layer diurnal variations on the intraseasonal variability of Sea Surface Temperatures in the Atlantic Ocean. Journal of Climate, 24 (12), 2889-2914. doi : 10.1175/2010JCLI3660.1.

[5] Ménégoz, M., Guemas, V., Salas-Melia D., Voldoire A., 2010, Winter interactions between aerosols and weather regimes in the North-Atlantic European region. Journal of Geophysical Research, 115, D09201. doi : 10.1029/2009JD012480.

[4] Guemas, V., Salas-Melia D., Kageyama M., Giordani H., Voldoire A., Sanchez-Gomez E., 2010, Summer interactions between weather regimes and surface ocean in the North-Atlantic region. Climate Dynamics, 34 (4), 527-546. doi : 10.1007/s00382-008-0491-6. Also see the Erratum.

[3] Guemas, V., Salas-Melia D., Kageyama M., Giordani H., Voldoire A., Sanchez-Gomez E., 2009, Winter interactions between weather regimes and marine surface in the North-Atlantic European region. Geophysical Research Letters, 36(9), L09816. doi : 10.1029/2009GL037551. Also see the Erratum.

[2] Guemas, V., Salas-Melia, D., 2008, Simulation of the Atlantic Meridional Overturning Circulation in an Atmosphere-Ocean Global Coupled Model. Part II : A weakening in a climate change experiment : a feedback mechanism. Climate Dynamics, 30 (7-8), 831-844. doi : 10.1007/s00382-007-0328-8.

[1] Guemas, V., Salas-Melia, D., 2008, Simulation of the Atlantic Meridional Overturning Circulation in an Atmosphere-Ocean Global Coupled Model. Part I : A mechanism governing the variability of ocean convection in a preindustrial experiment. Climate Dynamics, 31 (1), 29-48. doi : 10.1007/s00382-007-0336-8.

  Teaching experience

- 2006-2009 : Mechanics and Thermodynamics lessons to BSc 1st year, ENM (Ecole Nationale de la Météorologie, Météo-France)

- 2006-2009 : Statistics lessons to BSc 1st year, ENM (Ecole Nationale de la Météorologie, Météo-France)

Le contenu de cette page n’engage que son auteur et en aucune manière la responsabilité du CNRM-GAME.