GSMaP RIKEN Nowcast: Global Precipitation Nowcasting with Data Assimilation

Global Satellite Mapping of Precipitation (gsmap) Project

Precipitation is one of the most important parameters on the earth system, and the global distribution of precipitation and its change are essential data for modeling the water cycle, maintaining the ecosystem environment, agricultural production, improvements of the weather forecast precision, flood warning and so on. In the GPM (Global Precipitation Measurement) project, the microwave radiome...

THE GLOBAL SATELLITE MAPPING OF PRECIPITATION (GSMaP) PROJECT PART II ALGORITHM AND PRECIPITATION MODEL DEVELOPMENT

*National Institute of Information and Communications Technology, Tokyo, Japan +Meteorological Research Institute, Ibaraki, Japan #Hokkaido Tokai University, Hokkaido, Japan @Tokyo Metropolitan Institute of Technology, Tokyo, Japan &Osaka Prefecture University, Osaka, JAPAN **Japan Aerospace Exploration Agency, Tokyo, Japan ++Shimane University, Shimane, Japan ##Center for Climate System Resear...

Nowcasting of Precipitation

A Bayesian Quantitative Precipitation Nowcast Scheme

Very short-period quantitative precipitation forecast (QPF) or nowcast schemes provide deterministic output that fails to convey explicit measures of the uncertainty in the forecast. Presented here is a forecast methodology based upon a Bayesian hierarchical model that produces a QPF product for a 1-h period along with an associated estimated forecast error field. The precipitation forecast qua...

Effective Assimilation of Global Precipitation: Simulation Experiments

Past attempts to assimilate precipitation by nudging or variational methods have succeeded 1 in forcing the model precipitation to be close to the observed values. However, the model 2 forecasts tend to lose their additional skill after few forecast hours. In this study, a local 3 ensemble transform Kalman filter (LETKF) is used to effectively assimilate precipitation by 4 allowing ensemble mem...