What is he best known for?
The fields of study he is best known for:
- Statistics
- Climate change
- Climatology
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 most cited work include:
- DEVELOPMENT OF A EUROPEAN MULTIMODEL ENSEMBLE SYSTEM FOR SEASONAL-TO-INTERANNUAL PREDICTION (DEMETER) (785 citations)
- Fundamental challenge in simulation and prediction of summer monsoon rainfall (501 citations)
- Near-term climate change: Projections and predictability (487 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Climatology (80.75%)
- Meteorology (24.84%)
- Forecast skill (26.71%)
What were the highlights of his more recent work (between 2017-2021)?
- Climatology (80.75%)
- Climate model (27.33%)
- Predictability (27.64%)
In recent papers he was focusing on the following fields of study:
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.
Between 2017 and 2021, his most popular works were:
- What global reanalysis best represents near surface winds (52 citations)
- Robust skill of decadal climate predictions (38 citations)
- Towards operational predictions of the near-term climate (37 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Climate change
- Climatology
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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