Atmospheric Forcing Data Assimilation For CLM And Its Applications In China

Climate studies need long serial of historic data sets of high quality. There aremany station and remote sensing observation data in China, but there are no perfectland data assimilation systems and no assimilated land ananlysis data of high qualityat present. Meanwhile, as an important tool to evaluate land surface change and theatmosphere-land interactions, the development and performances of land surfacemodel rely upon the quality of data, so it is urgent to develop land data assimilationsystem and use it to provide more accurate atmospheric forcing data for land surfacemodels.This study is carried out focusing on providing more accurate atmospheric forcingfor land surface models and developing a land data assimilation system. The mainconclusions can be summarized as follows: 1) A 3DVar assimilation system is developed for assimilating the atmosphericforcing variables respectively by setting background error covariance inassimilation system. This assimilation system can also be used to assimilatepredication variables in land surface models, such as soil temperature and soilmoisture etc.2) Common Land Model (CLM) is validated for land surface variables (includingsoil temperature and soil moisture) over China by using desert observation dataand AMSR-E remote sensed soil moisture data, the results show that CLM cangrasp the distribution and change trends about hydrothermal characteristics overthe complex underlying surface of China region, thus good simulationperformances are achieved.3) A method to compute mean solar radiation at surface in any time interval based onNCEP reanalysis is presented to meet the requirements of land surface model,then a set of diurnal variation of solar radiation data is established, which can beused as data basis for model validation and analysis. The usability of this data setis verified. This data set can compensate the shortage of solar radiationobservations. With this data set applicated as one of the CLM atmosphericforcings, the performance of CLM is markedly enhanced with respect to soiltemperature.4) A precipitation rate data set of diurnal variation with multi-source precipitationdata assimilated is developed. The station observed daily precipitation data areused to generate precipitation rate of diurnal variation based on the diurnal variation of NCEP precipitation rate data, then, the 3DVar data assimilationsystem is used to assimilate precipitation data from different sources (includingInternational exchange station, Micaps and TRMM satellite-observed precipitation)and the newly-build assimilated precipitation rate data can effectively enhance theperformance of CLM with respect to soil moisture as one of the CLM atmosphericforcings.5) The atmospheric forcing data are established for CLM based on newly built solarradiation and assimilated precipitation rate data respectively. The influences withdifferent atmospheric forcing to the simulated land variables of land surfacemodel are disscused and analysized. Meanwhile, a set of soil temperature and soilmoisture data is established and the distribution and evolvement of land surfacevariables (including soil temperature and soil moisture) is analysized.In brief, this thesis develops a 3DVar assimilation system for atmospheric forcingvariables of land surface model and establishes a set of relative accurate atmosphericforcing data with diurnal variation that meets the requirements of land surface model.By applying these data into CLM, a set of soil temperature and soil moisture data isgenerated, providing the basis for model validation, simulation analysis and climatechange studies.