利用多源遥感数据改进地面太阳直射辐射估算

MULTI-REMOTE SENSING DATA FOR IMPROVING ESTIMATION OF GROUND SOLAR DIRECT NORMAL RADIATION

通过夏冬两季不同时间分辨率的气溶胶和大气可降水数据对太阳直射辐射估算进行敏感性分析,结果表明,气溶胶产品对太阳辐射估算结果的敏感性更高。融合MODIS与FY-3A的两种气溶胶产品来优化新疆地区气溶胶数据,尤其是高反射的沙漠与戈壁地区的气溶胶信息得到较大改善;同时通过引入FY-2D云类型数据更好地刻画了不同类型云层对太阳辐射估算精度的影响,以便更准确地估算新疆地区的地面太阳直射辐射。以喀什和乌鲁木齐站的观测值为参照,验证结果表明优化后的估算比优化前精度有明显提高。

The sensitivities of the aerosol and precipitable water vapor （PWV） data for the estimation model of solar direct normal radiation in summer and winter were examined and analyzed using daily, ten-days or monthly aerosol products and PWV data derived from the FY-3A satellite data acquired in the summer and winter of 2010 and 2011. The results showed that the aerosol data has much more sensitive influence on the estimation of the solar direct normal radiation than the PWV data. Afterwards, the MODIS aerosol data derived using deep blue algorithm were fused with the FY-3A aerosol products to optimize the aerosol distribution of Xinjiang area, especially to improve aerosol data in the high reflective surfaces in the desert and Gobi areas. Furthermore, the cloud type data derived from the FY-2D satellite data was used to better characterize the impact of the clouds on the estimation of solar direct normal radiation. The solar horizontal direct radiation of the entire Xinjiang was then derived using the fine-tuned model and the atmospheric parameters derived from the FY-2D, FY-3A and MODIS data. The meteorological observations of solar direct radiation at Kasi and Urumqi stations were used as reference and compared with the modeled results. Comparison showed that the estimation of the solar direct radiation in Xinjiang was obviously improved after optimizing aerosol data and incorporating the cloud type information into the modeling.