青海省长序列高分辨率气象要素栅格数据集构建与评估
Construction and Evaluation of Qinghai Meteorological Forcing Dataset
中文摘要：
采用中国区域近地面气象要素驱动数据集（CMFD）研制方法，融合青海省气象局高时空分辨率气象观测数据，构建了1979—2018年青海省逐3h的0.01°×0.01°栅格数据集，为气候变化、生态评估、水资源评估提供基础数据。评估结果显示，在月尺度上，气温与观测数据的相关系数接近1.0，相对湿度为0.92，降水为0.85，气压为0.82，风速最低，为0.74；与NCEP、ERA5、CLDAS多类数据集评估结果对比显示，青海省长序列高分辨率气象要素栅格数据集气温与区域站实测数据的相关系数超过0.74，高于ERA5和NCEP，降水与区域站实测数据相关系数超过0.51，明显高于CMAP、ERA5及GPCP数据集，且时空分辨率方面亦有优势。
中文关键词：
青海省，高分辨率，栅格数据集，数据评估
KeyWords：
Qinghai Province, high-resolution, raster dataset, data evaluation
Abstract：
By using the method of China Meteorological Forcing Dataset (CMFD) and integrating the high spatio-temporal resolution meteorological observation data, a 3-hourly, 0.01° gridded dataset of Qinghai Province from 1979 to 2018 is constructed so as to provide basic data for climate change study, ecological assessment and water resources assessment. The results of dataset evaluation show that the correlation coefficient of temperature is 1.0 in monthly-scale, and that of the relative humidity, precipitation, air pressure, and wind speed are 0.92, 0.85, 0.82, and 0.74, respectively. The comparison of dataset evaluation between Qinghai Meteorological Forcing Dataset (QMFD) and NCEP, ERA5 and CLDAS datasets show that the correlation coefficient of temperature data between QMFD and the observation data from regional stations exceeds 0.74, higher than that of ERA5 and NCEP. Meanwhile, the correlation coefficient of precipitation data between QMFD and the observation data from regional stations is above 0.51, which is obviously higher than that of CMAP, ERA5 and GPCP. Moreover, QMFD exhibits its own advantages in spatial and temporal resolutions.