为提高全球降水卫星计划(Integrated Multi-satellite Retrievals for Global Precipitation Measurement，GPM IMERG)等卫星降水数据的空间分辨率，以北部湾经济区为研究区，探讨最优的降尺度方案。以2001-2020年GPM卫星降水数据为数据源，构建地理加权回归模型(geographically weighted regression，GWR)，结合归一化植被指数(normalized difference vegetation in-dex，ND VI)、增强型植被指数(enhanced vegetation index，EVI)、数字高程模型(digital elevation model，DEM)和坡度数据;分别以NDVI和EVI为解释变量对北部湾经济区GPM数据进行降尺度，并进一步探讨滞后期为0～3月的植被指数对降尺度结果的影响;然后基于研究区内24个气象站点观测值进行精度验证。结果表明:GPM数据与气象站点实测数据在时间和空间上表现出较好的一致性和适用性，各站点决定系数介于0。65～0。93。降尺度数据在保证数据精度的前提下，空间分辨率有较大提升(由0。1°提升至1 km)，且EVI降尺度GPM数据精度优于NDVI降尺度结果。考虑时滞效应时，滞后期为1～2个月的EVI为解释变量时，降尺度GPM数据精度最优，且干旱年份降尺度结果优于湿润年份。在北部湾经济区，EVI比ND VI更适合GPM数据做降尺度因子，使用滞后期为1～2个月的EVI降尺度结果更精确。
Downscaling of GPM Data in Beibu Gulf Economic Zone Considering Time Delay Effect
In order to improve the spatial resolution of satellite precipitation data such as Integrated Multi-satellite Retrievals for Global Precipitation Measurement(GPM IMERG),the Beibu Gulf Economic Zone was taken as the study area to explore the optimal downscaling schemes.Using the global precipitation measurement(GPM)satellite precipitation data from 2001 to 2020 as the data source,a geographically weighted regression model(GWR)was constructed combining normalized difference vegetation index(NDVI),enhanced vegetation index(EVI),digital elevation model(DEM)and slope data.NDVI and EVI were used as explanatory variables to downscale the GPM data in the Beibu Gulf Economic Zone,and the impact of the vegetation index with a lag period of 0～3 months on the downscaling results was further discussed.Then,the accuracy was verified based on the 43 meteorological stations in the study area.The results show that GPM data and measured data from meteorological stations show good consistency and applicability in time and space,and the determination coefficient of each station is between 0.65 and 0.93.On the premise of ensuring the data accuracy,the spatial resolution of the downscale data has been greatly improved(from 0.1° to 1 km),and the EVI downscale GPM data accuracy is better than the NDVI downscale results.When considering time lag effects in translation,using the EVI with a lag of 1～2 months as the explanatory variable,the downscaled GPM data accuracy is optimal,and the downscaled results are better for dry years than for wet years.In the Beibu Gulf Economic Zone,the EVI is more suitable than the NDVI as a downscaled factor for GPM data,using a lag of 1～2 months.
Integrated Multi-satellite Retrievals for Global Precipitation Measurement(GPM IMERG)geographically weighted regression modeldownscalingvegetation indexBeibu Gulf Economic Zone
万方数据
维普
