Yunnan Province is a region with frequent droughts; thus, drought monitoring research is important for implementing active and effective measures to mitigate drought and scientifically guide agricultural production. In this study, the Tropical Rainfall Measuring Mission (TRMM 3B43) remote sensing-based product is used as the data source, and a geographically weighted regression (GWR) model, normalized difference vegetation index (NDVI) data and gross primary productivity (GPP) are used as independent variables. The TRMM 3B43 data are downscaled to 1 km spatial resolution to obtain two downscaled precipitation models (GWR_NDVI and GWR_GPP). The precipitation anomaly percentage (Pa) index and the tropical rainfall condition index (TRCI) are used to evaluate the drought situation in Yunnan Province from 2009 to 2018, and the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) are used to verify the Pa and TRCI. The results show the following: (1) With an R² as high as 0.8821 and BIAS close to zero, the TRMM 3B43 monthly precipitation is significantly correlated with the measured precipitation. The GWR_NDVI data increase the R² at the monthly scale by 0.0114; the GWR_NDVI data show greater improvements from spring and winter than from summer and autumn; and the R² of the GWR_NDVI data for some sites are slightly reduced. The R² of GWR_GPP data is smaller than that of the TRMM data and GWR_NDVI data at all timescales. (2) Drought occurs every month from 2009 to 2018; it decreases from November to February of the following year and is generally alleviated from March to April; and the incidence of drought from 2009 to 2014 is generally higher than that from 2015 to 2018. The Pa and TRCI show strong correlations with the SPI and SPEI and thus can be used to effectively monitor drought events in Yunnan, although the degree of drought assessed by the Pa and TRCI differs. (3) The spatial distribution of precipitation in Yunnan Province shows little precipitation in the north and east but abundant precipitation in the south and west. Precipitation is mainly concentrated from May to October, with the most abundant precipitation occurring in July.

云南省是干旱频发的地区。因此，干旱监测研究对于采取积极有效的措施减轻干旱和科学指导农业生产具有重要意义。在这项研究中，使用基于热带雨量测量任务（TRMM 3B43）的遥感产品作为数据源，并使用了地理加权回归（GWR）模型，归一化差异植被指数（NDVI）数据和总初级生产力（GPP）用作自变量。将TRMM 3B43数据缩减到1 km空间分辨率，以获得两个缩减的降水模型（GWR_NDVI和GWR_GPP）。利用降水异常百分率指数（Pa）和热带降水状况指数（TRCI）评估了云南省2009年至2018年的干旱状况，用标准降水指数（SPI）和标准降水蒸散指数（SPEI）来验证Pa和TRCI。结果表明：（1）具有R ²高达0.8821，BIAS接近于零，TRMM 3B43月降水量与实测降水量显着相关。GWR_NDVI数据使R ²每月增加0.0114；GWR_NDVI数据显示，春季和冬季比夏季和秋季有更大的改善；某些站点的GWR_NDVI数据的R ²略有降低。的- [R ²在所有时间尺度上，GWR_GPP数据的总和小于TRMM数据和GWR_NDVI数据的总和。（2）从2009年到2018年每个月发生干旱; 它从次年的11月至次年的2月减少，而从3月至4月通常有所减轻；Pa和TRCI与SPI和SPEI密切相关，因此可用于有效监测云南的干旱事件，尽管干旱程度已评估为2009年至2014年。 Pa和TRCI有所不同。（3）云南省降水的空间分布表明，北部和东部降水很少，而南部和西部降水丰富。降雨主要集中在5月至10月，而最丰富的降水发生在7月。