Publications

Ren, J; Huang, CL; Hou, JL; Zhang, Y; Yang, L (2025). Optimizing snow property forecasts over the tibetan plateau through hybrid assimilation of satellite precipitation and water vapor radiances using WRF model configured with Noah-MP. JOURNAL OF HYDROLOGY-REGIONAL STUDIES, 59, 102334.

Abstract
Study region: The Eastern region of the Qinghai-Tibet Plateau (EQTP) Study focus: A regional numerical weather prediction and data assimilation system is constructed to investigate the impact of assimilating Global Precipitation Measurement (GPM) precipitation and Himawari-8/Advanced Himawari Imager (AHI) water vapor radiance using Weather Research and forecast (WRF) model and Four-dimensional variational assimilation (4Dvar) method on snow properties predictions. The predictions were compared with some reference datasets, including MODIS,VIIRS,GLDAS and ERA5-land. New hydrological insights for the region: DA_G&A showed a significant increase in deep snow area (SD >15 cm), and a decrease in shallow snow area (SD<5 cm). Comparing with some reference datasets, the predictions exhibit good physical consistency between snow parameters and fine temporal-spatial resolution. The forecasts are found to be reliable and reasonable. However, Noah-MP coupled in WRF tends to overestimate SCF and SAL, which is largely attributed to the limitations of the associated parameterization schemes. These findings highlight the assimilation of atmospheric data can improve the forecasting of snow properties. However, in Noah-MP, there remains significant uncertainty in the snow-related parameterization schemes and initial conditions.

DOI:
10.1016/j.ejrh.2025.102334

ISSN:
2214-5818