2023 - Research.com Environmental Sciences in Spain Leader Award
Climatology, Forecast skill, Predictability, Meteorology and Climate change are his primary areas of study. His study on Sea surface temperature is often connected to Initialization as part of broader study in Climatology. The study incorporates disciplines such as Quantitative precipitation forecast, Range, Anomaly and Econometrics in addition to Forecast skill.
Francisco J. Doblas-Reyes interconnects Atmosphere, Monsoon, Teleconnection and Sea ice in the investigation of issues within Predictability. His Meteorology research incorporates elements of Probabilistic logic and Consensus forecast. His Climate model research integrates issues from Global warming and Ensemble forecasting.
His main research concerns Climatology, Meteorology, Forecast skill, Predictability and Climate model. The Sea surface temperature research Francisco J. Doblas-Reyes does as part of his general Climatology study is frequently linked to other disciplines of science, such as Initialization, therefore creating a link between diverse domains of science. Francisco J. Doblas-Reyes focuses mostly in the field of Meteorology, narrowing it down to topics relating to Probabilistic logic and, in certain cases, Ensemble forecasting.
His research integrates issues of Anomaly and Econometrics in his study of Forecast skill. His work carried out in the field of Predictability brings together such families of science as Sea ice and Hindcast. His Climate model research focuses on Northern Hemisphere and how it relates to Geopotential height.
Francisco J. Doblas-Reyes focuses on Climatology, Climate model, Predictability, Forecast skill and Wind speed. His Climatology research is multidisciplinary, incorporating elements of Climate change and Precipitation. Francisco J. Doblas-Reyes has included themes like Mode, Environmental planning, Northern Hemisphere, Teleconnection and Earth system science in his Climate model study.
His Predictability study integrates concerns from other disciplines, such as Hindcast and Climate services. The Forecast skill study combines topics in areas such as Biomass and Agricultural productivity. Francisco J. Doblas-Reyes combines subjects such as Natural resource economics and Energy market with his study of Wind speed.
The scientist’s investigation covers issues in Climatology, Climate model, Forecast skill, Precipitation and Climate change. His Climatology research includes themes of Biomass and Predictability. The various areas that Francisco J. Doblas-Reyes examines in his Climate model study include Blocking, Earth system science and Environmental planning.
His study in Forecast skill is interdisciplinary in nature, drawing from both Agricultural productivity and Severe weather. Solar variation, Lead and Sea level is closely connected to Atmospheric circulation in his research, which is encompassed under the umbrella topic of Precipitation. His work deals with themes such as Errors-in-variables models, Weather and climate, Weather forecasting and Environmental resource management, which intersect with Climate change.
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Near-term climate change: Projections and predictability
Ben Kirtman;Scott B. Power;Akintayo John Adedoyin;George J. Boer.
DEVELOPMENT OF A EUROPEAN MULTIMODEL ENSEMBLE SYSTEM FOR SEASONAL-TO-INTERANNUAL PREDICTION (DEMETER)
T. N. Palmer;A. Alessandri;U. Andersen;P. Cantelaube.
Bulletin of the American Meteorological Society (2004)
The rationale behind the success of multi-model ensembles in seasonal forecasting – I. Basic concept
Renate Hagedorn;Francisco J. Doblas-Reyes;T. N. Palmer.
Tellus A (2005)
Fundamental challenge in simulation and prediction of summer monsoon rainfall
Bin Wang;Qinghua Ding;Xiouhua Fu;In-Sik Kang.
Geophysical Research Letters (2005)
Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales
Peter Bechtold;Martin Köhler;Thomas Jung;Francisco Doblas-Reyes.
Quarterly Journal of the Royal Meteorological Society (2008)
Malaria early warnings based on seasonal climate forecasts from multi-model ensembles
M. C. Thomson;F. J. Doblas-Reyes;S. J. Mason;R. Hagedorn.
Decadal Climate Prediction: An Update from the Trenches
Gerald A. Meehl;Lisa Goddard;George Boer;Robert Burgman.
Bulletin of the American Meteorological Society (2014)
Contribution of land surface initialization to subseasonal forecast skill: first results from a multi-model experiment.
R. D. Koster;S. P.P. Mahanama;S. P.P. Mahanama;T.J. Yamada;T.J. Yamada;T.J. Yamada;Gianpaolo Balsamo.
Geophysical Research Letters (2010)
The rationale behind the success of multi-model ensembles in seasonal forecasting – II. Calibration and combination
Francisco J. Doblas-Reyes;Renate Hagedorn;T. N. Palmer.
Tellus A (2005)
Stochastic parametrization and model uncertainty
T. N. Palmer;R. Buizza;F. Doblas-Reyes;Thomas Jung.
EPIC3ECMWF Technical Memorandum, 598, 42 p. (2009)
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