• Adv. Atmos. Sci.  2018, Vol. 35 Issue (6): 628-644    DOI: 10.1007/s00376-017-7120-4
    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
    Junhua YANG1, Zhenming JI2(), Deliang CHEN3, Shichang KANG1, 7, Congshen FU4, Keqin DUAN5, Miaogen SHEN6, 7
    1State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
    2School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China
    3Department of Earth Sciences, University of Gothenburg, Gothenburg 40530, Sweden
    4Yale School of Forestry and Environmental Studies, Yale University, New Haven, Connecticut 06511, USA
    5College of Tourism and Environment, Shaanxi Normal University, Xi'an 710000, China
    6Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
    7CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
    Abstract
    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.

    Keywords WRF-3DVAR      land use      leaf area index      radiance assimilation      rainfall simulation     
    Just Accepted Date: 14 March 2018   Issue Date: 12 April 2018
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    Junhua YANG
    Zhenming JI
    Deliang CHEN
    Shichang KANG
    Congshen FU
    Keqin DUAN
    Miaogen SHEN
    Cite this article:   
    Junhua YANG,Zhenming JI,Deliang CHEN, et al. 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[J]. Adv. Atmos. Sci., 2018, 35(6): 628 -644 .
    URL:  
    http://159.226.119.58/aas/EN/10.1007/s00376-017-7120-4     OR     
    http://159.226.119.58/aas/EN/Y2018/V35/I6/628
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