Impacts of Land Use/Land Cover Distributions and Vegetation Amount on Land Surface Temperature Simulation in East China

Earth and Space Science

Yanhong Gao¹  Suosuo Li²  Yongjie Pan² 

[1] Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences Fudan University Shanghai China;Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions Northwest Institute of Eco‐Environment and Resources Chinese Academy of Sciences Lanzhou China;

关键词: Land surface model;    land surface temperature;    LULC products;    MODIS LST;   

DOI  :  10.1029/2020EA001544

来源: DOAJ

【 摘 要 】

Abstract Land surface temperature (LST) plays a crucial role in the earth system because its heterogeneous spatial distributions can trigger local circulations through land surface‐atmosphere interactions. An accurate simulation of the LST spatial distribution heavily rely on the accuracy of the land surface characteristics, such as LULC (land use/land cover). To investigate the impact of uncertainty in LULC maps on LST simulation, the Community Land Model, version 4.5 (CLM4.5), was used in this study with four LULC products as overlying vegetation characteristics. East China, with its complex land surface characteristics, was employed as the study area. The simulation results were compared to the observations at nine China Meteorological Administration (CMA) stations and to Moderate Resolution Imaging Spectroradiometer data (MOIDIS_LST) over the whole study region. Based on the comparison at CMA stations, CLM4.5 can properly simulate ground temperature. However, large differences are found between MODIS_LST and the simulated LST, particularly over crop areas. Comparison of simulated results using different LULC products showed a large dissimilarity over forest areas, mainly due to the different identification methods for forest types. Large biases in the prescribed leaf area index (LAI) of the model are also found compared with MODIS_LAI. Then, the LAI in the model default data was replaced by the MODIS_LAI product, which greatly reduces the LST simulation biases. These findings provide insights into improving the simulation of LST and land‐atmosphere interactions in regional weather models or global climate models.

【 授权许可】

Unknown