What is he best known for?
The fields of study he is best known for:
- Statistics
- Meteorology
- Tropical cyclone
The scientist’s investigation covers issues in Meteorology, Ensemble forecasting, Ensemble prediction, Applied mathematics and North American Mesoscale Model.
His Meteorology study integrates concerns from other disciplines, such as Algorithm and Energy.
His Ensemble forecasting study combines topics from a wide range of disciplines, such as Scatter plot, Contingency table and Weather forecasting.
His Ensemble prediction research incorporates elements of Probabilistic logic, Forecast skill, Statistics and Geopotential height.
He combines subjects such as Parametrization, Covariance, Metric and Numerical weather prediction with his study of Applied mathematics.
He has included themes like Centroid and Mesoscale meteorology in his North American Mesoscale Model study.
His most cited work include:
- The ECMWF Ensemble Prediction System: Methodology and validation (1235 citations)
- Stochastic representation of model uncertainties in the ECMWF ensemble prediction system (806 citations)
- The Singular-Vector Structure of the Atmospheric Global Circulation (556 citations)
What are the main themes of his work throughout his whole career to date?
Roberto Buizza mostly deals with Meteorology, Climatology, Ensemble prediction, Ensemble forecasting and Probabilistic logic.
In his research, Range is intimately related to Predictability, which falls under the overarching field of Meteorology.
His Climatology research incorporates themes from Drainage basin and Storm, Severe weather.
His work carried out in the field of Ensemble prediction brings together such families of science as Initial value problem, Machine learning, Ensemble average and Artificial intelligence.
His research in Ensemble forecasting focuses on subjects like Global Forecast System, which are connected to Consensus forecast.
His Numerical weather prediction study incorporates themes from Weather forecasting and Applied mathematics.
He most often published in these fields:
- Meteorology (56.46%)
- Climatology (28.57%)
- Ensemble prediction (29.25%)
What were the highlights of his more recent work (between 2017-2021)?
- Meteorology (56.46%)
- Predictability (16.33%)
- Numerical weather prediction (15.65%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Meteorology, Predictability, Numerical weather prediction, Remote sensing and Weather forecasting.
His work on Storm is typically connected to Snow cover as part of general Meteorology study, connecting several disciplines of science.
His Numerical weather prediction study combines topics in areas such as Econometrics and Operations research.
The concepts of his Weather forecasting study are interwoven with issues in Ensemble averaging, Tornado and Forecast skill.
Ensemble forecasting is closely connected to Climatology in his research, which is encompassed under the umbrella topic of Winter storm.
His Ensemble forecasting research includes elements of Range and Ensemble prediction.
Between 2017 and 2021, his most popular works were:
- CERA‐20C: A Coupled Reanalysis of the Twentieth Century (104 citations)
- What Is the Predictability Limit of Midlatitude Weather (56 citations)
- Satellite and in situ observations for advancing global earth surface modelling: A review (47 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Meteorology
- Machine learning
His main research concerns Climatology, Remote sensing, Meteorology, Numerical weather prediction and Predictability.
The Climatology study combines topics in areas such as Earth system model, Winter storm and Limit.
Roberto Buizza works mostly in the field of Remote sensing, limiting it down to topics relating to Weather and climate and, in certain cases, Earth system science.
His Weather forecasting study, which is part of a larger body of work in Meteorology, is frequently linked to Snow cover, bridging the gap between disciplines.
His Numerical weather prediction research is multidisciplinary, relying on both Monsoon, Ensemble prediction and Econometrics.
His Ensemble forecasting study often links to related topics such as Data assimilation.
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