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Accurate predictions of weather extremes such as heat waves or heavy precipitation are indispensable so that preventive actions can be taken by the authorities and the public at an early stage. The "Large-scale dynamics and predictability" group at the Institute of Meteorology and Climate Research investigates the physical and dynamical processes that control predictability and forecast skill of the atmospheric circulation. Our research is based on experiments with numerical weather prediction models, statistical analyses of large data sets as well as machine learning.
|C. Grams, J. Dorrington (in collaboration with EnBW)|
|How does the model representation of (micro-)physical heating rates influence warm conveyor belt ascent: A model-intercomparison using ICON and the IFS?||A. Oertel|
|Machine learning-based predictions of the intensity of warm conveyor belts associated with extratropical cyclones||J. Quinting|
|Predictability of surface weather on subseasonal timescales due to the influence of weather regimes||M. Osman|
|Representation of the relationship between the MJO and WRs by S2S models||M. Osman|