Abstract: A technique to apply the forecast model as a general weak constraint in a complex variational algorithm, such as NCEP?s regional 4DVAR data assimilation system, is presented. The proposed definition of the model error has ...

Abstract: A methodology for model error estimation is proposed and examined in this study. It provides estimates of the dynamical model state, the bias, and the empirical parameters by combining three approaches: 1) ensemble data ...

Abstract: A new four-dimensional variational data assimilation (4DVAR) system is developed at the Cooperative Institute for Research in the Atmosphere (CIRA)/Colorado State University (CSU). The system is also called the Regional ...

Abstract: Four-dimensional variational (4DVAR) data assimilation experiments for the East Coast winter storm of 25 January 2000 (i.e., ?blizzard of 2000?) were performed. This storm has received wide attention in the United States, ...

Abstract: In the near future, the Global Precipitation Measurement (GPM) mission will provide precipitation observations with unprecedented accuracy and spatial/temporal coverage of the globe. For hydrological applications, the ...

Abstract: The National Centers for Environmental Prediction fine-resolution four-dimensional variational (4DVAR) data assimilation system is used to study the Great Plains tornado outbreak of 3 May 1999. It was found that the 4DVAR ...

Abstract: he main purpose of the present study is to assess the value of synthetic satellite imagery as a tool for model evaluation performance in addition to more traditional approaches. For this purpose, synthetic GOES-10 imagery ...