Articles | Volume 15, issue 17
Geosci. Model Dev., 15, 6891–6917, 2022
https://doi.org/10.5194/gmd-15-6891-2022
Geosci. Model Dev., 15, 6891–6917, 2022
https://doi.org/10.5194/gmd-15-6891-2022
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 et al.

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Cited articles

Alexander, C. and Carley, J.: Short-Range Weather in operations, Bulletin of the UFS Community, p. 9, https://doi.org/10.25923/k3zn-xe66, 2020. a, b
Alpert, J. C., Yudin, V. A., and Strobach, E.: Atmospheric Gravity Wave Sources Correlated with Resolved-scale GW Activity and Sub-grid Scale Parameterization in the FV3gfs Model, in: AGU Fall Meeting Abstracts, vol. 2019, SA21A–02, 2019. a
Azevedo, H. B. D., Gonçalves, L. G. G. D., Kalnay, E., and Wespetal, M.: Dynamically weighted hybrid gain data assimilation: perfect model testing, Tellus A, 72, 1–11, https://doi.org/10.1080/16000870.2020.1835310, 2020. a
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Bannister, R. N., Chipilski, H. G., and Martinez-Alvarado, O.: Techniques and challenges in the assimilation of atmospheric water observations for numerical weather prediction towards convective scales, Q. J. Roy. Meteor. Soc., 146, 1–48, https://doi.org/10.1002/qj.3652, 2020. a, b
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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.