Publications

Yue, SY; Yang, K; Lu, H; Zhou, X; Chen, DL; Guo, WD (2021). Representation of Stony Surface-Atmosphere Interactions in WRF Reduces Cold and Wet Biases for the Southern Tibetan Plateau. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 126(21), e2021JD035291.

Abstract
Current regional and global climate models often have significant cold and wet biases in the simulation of climate for the Southern Tibetan Plateau (STP). This region has complex terrain and steep slopes, and the underlying surface in many areas is stony with little soil and vegetation, which causes negligible infiltration and rapid runoff. The default soil type (loam) in the Weather Research and Forecasting (WRF) is thus replaced with bedrock to improve the representation of the mountainous hydrological processes in this region. The domain of bedrock is identified by using satellite-based Normalized Difference Vegetation Index (NDVI) and terrain elevation standard deviation. The model results demonstrate that the WRF-simulated precipitation and temperature are sensitive to soil type setting in this region. After the soil type is corrected, the mean precipitation bias at weather stations in the STP is reduced from 35 mm to -6 mm and the cold bias of 2 m air temperature is reduced from 1.5 degrees C to 0.8 degrees C when evaluated against weather station data. The relevant land and atmospheric processes are explored. The revision of the soil type from loam to bedrock results in increased sensible heat flux and decreased evaporation. A higher sensible heat flux results in higher air temperature, and the suppressed evaporation attenuates precipitation-evaporation feedback. The altered energy budget enhances the valley wind, resulting in a sinking motion anomaly and reduced precipitation over lower elevations. The study highlights the critical role of soil type in the realistic representation of land-atmosphere interactions by numerical models for the unique region.

DOI:
10.1029/2021JD035291

ISSN:
2169-897X