Improving Short-Term QPF Using Geostationary Satellite All-Sky Infrared Radiances: Real-Time Ensemble Data Assimilation and Forecast during the PRECIP 2020 and 2021 Experiments

The Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) aims to improve our understanding of extreme rainfall processes in the East Asian summer monsoon. A convection-permitting ensemble-based data assimilation and forecast system (the PSU WRF-EnKF system) was run in real time in the summers of 2020–21 in advance of the 2022 field campaign, assimilating all-sky infrared (IR) radiances from the geostationary Himawari-8 and GOES-16 satellites, and provid-ing 48-h ensemble forecasts every day for weather briefings and discussions. This is the first time that all-sky IR data assimilation has been performed in a real-time forecast system at a convection-permitting resolution for several seasons. Compared with retrospective forecasts that exclude all-sky IR radiances, rainfall predictions are statistically significantly improved out to at least 4–6 h for the real-time forecasts, which is comparable to the time scale of improvements gained from assimilating observations from the dense ground-based Doppler weather radars. The assimilation of all-sky IR radiances also reduced the forecast errors of large-scale environments and helped to maintain a more reasonable ensemble spread compared with the counterpart experiments that did not assimilate all-sky IR radiances. The results indicate strong potential for improving routine short-term quantitative precipitation forecasts using these high-spatiotemporal-resolution satellite observations in the future.

This is the accepted version of the following article: [Improving Short-Term QPF Using Geostationary Satellite All-Sky Infrared Radiances: Real-Time Ensemble Data Assimilation and Forecast during the PRECIP 2020 and 2021 Experiments. Weather and Forecasting 38, 4 p591-609 (2023)], which has been published in final form at https://doi.org/10.1175/WAF-D-22-0156.1.

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Work Title Improving Short-Term QPF Using Geostationary Satellite All-Sky Infrared Radiances: Real-Time Ensemble Data Assimilation and Forecast during the PRECIP 2020 and 2021 Experiments
Access
Open Access
Creators
  1. Yunji Zhang
  2. Xingchao Chen
  3. Michael M. Bell
Keyword
  1. Forecast verification/skill
  2. Numerical weather prediction/forecasting
  3. Short-range prediction
  4. Data assimilation
  5. Ensembles
License CC BY 4.0 (Attribution)
Work Type Article
Publisher
  1. Weather and Forecasting
Publication Date April 17, 2023
Publisher Identifier (DOI)
  1. https://doi.org/10.1175/WAF-D-22-0156.1
Deposited March 18, 2024

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Version 1
published

  • Created
  • Added ZhangChenBell_2022_PSU_WRF-EnKF_PRECIP_r2_final.docx
  • Added Creator Yunji Zhang
  • Added Creator Xingchao Chen
  • Added Creator Michael M. Bell
  • Published
  • Updated Keyword, Publication Date Show Changes
    Keyword
    • Forecast verification/skill, Numerical weather prediction/forecasting, Short-range prediction, Data assimilation, Ensembles
    Publication Date
    • 2023-04-01
    • 2023-04-17
  • Updated