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READ ME 文档链接 https://download.csdn.net/download/weixin_46629224/15750582 The goal of the NASA Global Land Data Assimilation System (GLDAS) is to generate optimal fields of land surface states and fluxes, by ingesting satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques (Rodell et al., 2004). GLDAS drives multiple, offline (not coupled to the atmosphere) land surface models, integrates a huge quantity of observation-based data, and executes globally at high resolutions (2.5° to 1 km), enabled by the Land Information System (LIS) (Kumar et al., 2006). Currently, GLDAS drives four land surface models (LSMs): Noah, Catchment (CLSM), the Community Land Model (CLM), and the Variable Infiltration Capacity (VIC). More information is available at the Land Data Assimilation Systems (LDAS) and Land Information System (LIS) websites. This document specifically describes the reprocessed data products of Version 2 of the Global Land Data Assimilation System (hereafter, GLDAS-2).

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用统计降尺度方法做东江流域极端降水的未来情景预测，荣艳淑，王文，本文利用1961年～2000年共40年的实测气象站点逐日气象资料和NCEP再分析资料，以及英国气候中心的HadCM3模式2011～2099年的输出数据，用SDSM�