1980–2020年AVHRR中国积雪物候数据集

A dataset of snow cover phenology in China based on AVHRR from 1980 to 2020

积雪物候是指季节性积雪随季节周期的变化趋势和变化规律,对融雪径流、土壤冻融、植被物候和动物迁徙等过程有着重要影响,是积雪区能量平衡、水文、生态及气象模型的重要输入因子,也是积雪变化研究主要内容之一。中国是中低纬度主要的季节性积雪区,积雪物候研究具有重要的意义。本文基于1980–2020年5 km AVHRR逐日无云积雪面积产品,制备了中国长时间序列积雪物候数据集,该数据集包含积雪日数、积雪初日、积雪终日三个数据子集。利用地面气象台站实测雪深数据对产品进行验证,验证结果表明:积雪日数、积雪初日和积雪终日验证相关系数R2分别为0.80,0.76和0.94,均方根误差RMSE分别为22.78天,17.87天和16.39天,平均绝对误差MAE分别为13.26天,7.51天和7.76天,精度可靠。本数据集可服务于中国积雪时空变化分析,为气候变化,水文水资源,生态环境,人文经济等科学研究、工程建设以及社会服务提供基础数据资料。

Snow cover phenology characterizes the changing trend and law of seasonal snow cover with seasonal cycles,which has an important effect on the processes of snowmelt runoff,soil freezing and thawing,vegetation phenology and animal migration.The phenological parameters of snow cover are important input factors for energy balance,hydrology,ecology and meteorological models of snow cover areas,and they are also one of the main contents of snow cover change research.China is a major area of seasonal snow cover in the middle and low latitudes,and the study on snow phenology in China is of great significance.In this paper,based on the NIEER-CGF-AVHRR-SCE product,we have prepared a long-term series snow phenology dataset of China,including three data subsets(i.e.snow cover days,the start day of snow cover,and the melt day of snow cover).The product was validated with the measured snow depth data from the ground meteorological station,and the results of high accuracy show that the verification correlation coefficient“R2”for the number of days of snow cover,the first day of snow cover,and the melt day of snow cover are 0.8,0.76 and 0.94 respectively;their root mean square error“RMSE”are 22.78,17.87 and 16.39 respectively;their mean absolute error“MAE”are 13.26,7.51 and 7.76 respectively.This dataset can be used to analyze the temporal and spatial changes of snow cover in China,and provide basic data for scientific research,engineering construction,and social services such as climate research,hydrological management,ecological environment,humanities and economics.