黑河流域多年月平均湿度（1961-2010）

采用黑河计划数据管理中心提供的黑河流域及周边地区21个气象常规观测站及黑河周边13个全国基准站的站点数据信息，对逐日湿度进行统计整理，计算逐个站点的1961-2010年多年逐月湿度数据。对其进行空间平稳性分析，计算变异系数，若变异系数大于100%，则采用地理加权回归计算站点与地理地形因素关系，得逐月湿度分布趋势；若变异系数小于等于100%，则采用普通最小二乘回归计算站点湿度值与地理地形因素（经纬度、高程、坡度、坡向等）的关系，得逐月湿度分布趋势；对去掉趋势后的残差采用HASM（High Accuracy Surface Modeling Method）进行拟合修正。最后将趋势面结果与残差修正结果相加即得1961-2010年黑河流域多年月平均湿度分布。时间分辨率：1961-2010年多年月平均湿度。空间分辨率：500m。

Using station data from 21 conventional meteorological observation stations in the Heihe River Basin and its surrounding areas, as well as 13 national reference stations around the Heihe River, provided by the Heihe Plan Data Management Center, we first conducted statistical collation and processing of daily humidity data, and calculated the long-term monthly humidity data for each station over the period 1961–2010. Subsequently, spatial stationarity analysis was performed and the coefficient of variation was calculated. If the coefficient of variation exceeded 100%, geographically weighted regression (GWR) was employed to quantify the relationship between station humidity and geographic terrain factors, thus deriving the monthly humidity distribution trend. If the coefficient of variation was less than or equal to 100%, ordinary least squares (OLS) regression was used to analyze the relationship between station humidity values and geographic terrain factors including latitude, longitude, elevation, slope, aspect, etc., to obtain the monthly humidity distribution trend. The residuals after removing the trend were then fitted and corrected using HASM (High Accuracy Surface Modeling Method). Finally, the trend surface results and the residual correction results were summed to generate the long-term monthly average humidity distribution over the Heihe River Basin for the period 1961–2010. Temporal resolution: Long-term monthly average humidity for 1961–2010. Spatial resolution: 500 m.