CLDAS土壤湿度模拟结果及评估

中国气象局陆面数据同化系统（CLDAS V1.0）由陆面驱动数据融合和陆面模式模拟两部分组成。基于驱动数据，选取Canmunity Land Model 3.5（CLM3.5）作为CLDAS V1.0系统的陆面模式进行模拟试验，并对土壤模拟结果进行评估。利用2013年经过质量控制的中国气象局业务化自动土壤水分观测站实况数据、青藏高原试验观测数据及国际同类产品对模拟结果进行评估，结果表明:从各省以及全国平均结果看，相关系数普遍在0.8以上，偏差基本为-0.04~0.04 mm3·mm-3，平均均方根误差为0.04~0.05 mm3·mm-3，在青藏高原地区与国际同类产品相比，精度也有一定提高。总体而言，模拟结果已达到较高精度，数据集产品对中国区域干旱监测等具有重要意义。

The Simulation and Evaluation of Soil Moisture Based on CLDAS

The national weather service modernization is the core and key to the modernization of the national weather, which is an important symbol to enhance China meteorological technology level and professional ability. China Meteorological Administration publishes the national meteorological modernization objectives and evaluation plan (2014-2020), which clearly proposes the development of multi-source data fusion data set, and the land surface data fusion is one of the most important parts. Using the technique of multi-source data fusion, China Meteorological Administration Land Data Assimilation System (CLDAS) integrates observation of ground, satellite and numerical model to obtain the high-quality temperature, pressure, humidity, wind speed, the grid point data of precipitation and radiation and other factors, and then to drive land surface model to simulate different depths of soil temperature and moisture.CLM3.5 land surface model is used to simulate land surface soil moisture of different depths, and then results are assessed using 3 ground datasets. The first is the automatic soil moisture observation of CMA in 2013, which is checked strictly by quality control process, the second is CTP-SMTMN data, and the last is GLDAS soil moisture and ERA-Interim Reanalysis. A comprehensive assessment for soil moisture is conducted and it shows that the correlation coefficient reaches a high level in most provinces, which can better reflect the objective change of soil moisture and has a strong guiding role. In statistical analysis of time series by selecting the representative station, surface soil moisture changing rates are higher than deeper layers, because the interaction between surface soil and the atmospheric boundary layer feedback is more sensitive, and the water heat exchange are more frequent. On the Tibetan Plateau, using Taylor diagrams comparison, it''s found simulation results in the appraisal process of different indices are better than the other two kinds of foreign soil moisture data. In summary, the correlation coefficient is up to 0.8, and deviation is about -0.04 mm³·mm^-3 to 0.04 mm³·mm^-3 and root mean square error is lower than 0.04-0.05 mm³·mm^-3 from stations of provinces average and all over the country.