CLDAS和GLDAS土壤温度数据在陕西省的适用性评估

利用陕西省2016年97站逐日5cm土壤温度观测数据,结合相关系数、平均偏差和均方根误差等统计参数,评估了中国气象局陆面数据同化系统CLDAS2.0和美国全球陆面数据同化系统不同陆面模式(Noah-GLDAS2.1,Noah-GLDAS1,CLM-GLDAS1)土壤温度数据在陕西省的适用性。结果表明:(1)CLDAS2.0在陕西省的相关系数最高,均方根误差最小,Noah-GLDAS2.1次之,Noah-GLDAS1最差。(2)从陕西省3个区域的时间演变序列的分析可以看到,CLDAS2.0和Noah-GLDAS2.1能很好模拟出土壤温度的季节变化以及日变化,Noah-GLDAS1、CLMGLDAS1对于日变化的模拟较差,且前两者偏差也明显小于后两者。(3)Noah-GLDAS2.1在陕北与关中地区土壤温度模拟能力与CLDAS2.0相差无几,但在陕南地区CLDAS2.0要好于Noah-GLDAS2.1。总体来看,CLDAS2.0对陕西省土壤温度模拟能力最好,在陕西省有着更好的适用性。

Applicability Evaluation of CLDAS and GLDAS Soil Temperature Data in Shaanxi Province

Based on the daily 5 cm soil temperature data observed by 97 meteorological stations in Shaanxi Province in 2016, combined with statistical parameters such as correlation coefficient, average deviation and root mean square error, the applicability of CMA (China Meteorological Administration) Land Data Assimilation System (CLDAS 2.0) and American Global Land surface Data Assimilation System (Noah GLDAS 2.1, Noah GLDAS1, CLM GLDAS 1) soil temperature data in Shaanxi Province was evaluated. The results show that: (1) CLDAS 2.0 had the highest correlation coefficient and the smallest root mean square error in Shaanxi Province, followed by Noah GLDAS 2.1 and Noah GLDAS 1. (2) From the analysis of the time evolution series of three regions in Shaanxi Province, it can be seen that CLDAS 2.0 and Noah GLDAS 2.1 can well simulate the seasonal and daily changes of soil temperature, and the simulations of daily changes of Noah GLDAS 1 and CLM GLDAS 1 are poor, and the deviations of the former two are significantly less than those of the latter two. (3) The soil temperature simulation ability of Noah GLDAS 2.1 in the northern Shaanxi and Guanzhong area is similar to that of CLDAS 2.0, but that of CLDAS 2.0 in the southern Shaanxi area is better than that of Noah GLDAS 2.1. Generally speaking, CLDAS 2.0 has the best ability to simulate soil temperature, and has better applicability in Shaanxi Province.