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Improved Land Use and Leaf Area Index Enhances WRF-3DVAR Satellite Radiance Assimilation: A Case Study Focusing on Rainfall Simulation in the Shule River Basin during July 2013

Journal article
Authors J. Yang
Z. Ji
Deliang Chen
S. Kang
C. Fu
K. Duan
M. Shen
Published in Advances in Atmospheric Sciences
Volume 35
Issue 6
Pages 628-644
ISSN 0256-1530
Publication year 2018
Published at Department of Earth Sciences
Pages 628-644
Language en
Keywords land use, leaf area index, radiance assimilation, rainfall simulation, WRF-3DVAR
Subject categories Physical Geography

Abstract

The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level (surface-sensitive) channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets. Here, we used an improved land use and leaf area index (LAI) dataset in the WRF-3DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels (e.g., channel 3), the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.

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