Essential Site Maintenance: Authorea-powered sites will be updated circa 15:00-17:00 Eastern on Tuesday 5 November.
There should be no interruption to normal services, but please contact us at [email protected] in case you face any issues.

loading page

Assimilating Precipitation Data via full-hydrometeor scheme in WRF 4D-Var for Convective Precipitation Forecast Associated with the Northeast Cold Vortex
  • +3
  • Sen Yang,
  • Deqin Li,
  • Yunxia Duan,
  • Yongsheng Chen,
  • Zhiquan Liu,
  • Xiang-Yu Huang
Sen Yang
Institute of Atmospheric Environment
Author Profile
Deqin Li
Shenyang Atmospheric Environment Research Institute, China Meteorological Administration

Corresponding Author:[email protected]

Author Profile
Yunxia Duan
Shenyang Atmospheric Environment Research Institute, China Meteorological Administration
Author Profile
Yongsheng Chen
York University
Author Profile
Zhiquan Liu
National Center for Atmospheric Research (UCAR)
Author Profile
Xiang-Yu Huang
Institute of Urban Meteorology, CMA
Author Profile

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 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. Ten 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 schemes. The assimilation of precipitation data 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 hour 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.