Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 17
Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6891-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6891-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 17
Model evaluation paper
 | 
12 Sep 2022
Model evaluation paper |  | 12 Sep 2022

Assessment of the data assimilation framework for the Rapid Refresh Forecast System v0.1 and impacts on forecasts of a convective storm case study

Ivette H. Banos, Will D. Mayfield, Guoqing Ge, Luiz F. Sapucci, Jacob R. Carley, and Louisa Nance

Data sets

Assessment of the data assimilation framework for the prototype Rapid Refresh Forecast System and impacts on forecasts of convective storms Ivette H. Banos, Will D. Mayfield, Guoqing Ge, Luiz F. Sapucci, Jacob R. Carley, and Louisa Nance https://doi.org/10.5281/zenodo.5226389

Model code and software

Rapid Refresh Forecast System (RRFS) v0.1 Ivette H. Banos, Will D. Mayfield, Guoqing Ge, Luiz F. Sapucci, Jacob R. Carley, and Louisa Nance https://doi.org/10.5281/zenodo.5546592

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Short summary
A prototype data assimilation system for NOAA’s next-generation rapidly updated, convection-allowing forecast system, or Rapid Refresh Forecast System (RRFS) v0.1, is tested and evaluated. The impact of using data assimilation with a convective storm case study is examined. Although the convection in RRFS tends to be overestimated in intensity and underestimated in extent, the use of data assimilation proves to be crucial to improve short-term forecasts of storms and precipitation.
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