Assimilating precipitation data via full‐hydrometeor scheme in WRF 4D‐Var for convective precipitation forecast associated with the Northeast China cold vortex (NCCV)
Yang, S., Li, D., Duan, Y., Chen, Y., Liu, Z., et al. (2025). Assimilating precipitation data via full‐hydrometeor scheme in WRF 4D‐Var for convective precipitation forecast associated with the Northeast China cold vortex (NCCV). Journal of Geophysical Research: Atmospheres, doi:https://doi.org/10.1029/2024JD042427
| Title | Assimilating precipitation data via full‐hydrometeor scheme in WRF 4D‐Var for convective precipitation forecast associated with the Northeast China cold vortex (NCCV) |
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| Genre | Article |
| Author(s) | S. Yang, D. Li, Y. Duan, Y. Chen, Zhiquan Liu, X. Huang |
| Abstract | The full‐hydrometeor four‐dimensional variational (4D‐Var) assimilation scheme in the Weather Research and Forecasting (WRF) model, based on the WRF single‐moment 6‐class microphysics scheme (WSM6), is utilized to assimilate precipitation data. The focus is on short‐term convective precipitation forecasts influenced by the Northeast China cold vortex (NCCV). Four assimilation experiments were designed to compare the warm rain scheme with the full‐hydrometeor scheme, as well as to examine the differences between assimilating hourly surface rain gauge data and multi‐source integrated precipitation products. Nine cases of intense convective precipitation related to NCCV were analyzed. The results demonstrate that the initial analysis of ice‐phase hydrometeors was satisfactory across the three experiments utilizing the full‐hydrometeor 4D‐Var assimilation scheme. The assimilation of precipitation data using the full‐hydrometeor scheme in WRF 4D‐Var effectively adjusted atmospheric thermodynamic properties and decreased model spin‐up time, leading to improved precipitation forecasts, especially for the 0–3 hr period. Furthermore, the assimilation of rain gauge data or multi‐source integrated precipitation data has been demonstrated to be an effective approach for enhancing the accuracy of weather forecasts. |
| Publication Title | Journal of Geophysical Research: Atmospheres |
| Publication Date | Apr 28, 2025 |
| Publisher's Version of Record | https://doi.org/10.1029/2024JD042427 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d7xs60tg |
| OpenSky Listing | View on OpenSky |
| MMM Affiliations | PARC |