###### Abstract  
The impact of drought on terrestrial ecosystem Gross Primary Productivity (GPP) is strong and widespread; therefore, it is important to study the response of terrestrial ecosystem GPP to drought. In this paper, we compared the correlations of Sun-induced Chlorophyll fluorescence (SIF), Enhanced Vegetation Index (EVI), and Normalized Differential Vegetation Index (NDVI) with the drought index sc_PDSI, estimated GPP in Yunnan Province, China, based on SIF_TOTAL data (SIF data with canopy effects eliminated), and analyzed the response characteristics of GPP to drought for one mega-drought event (2009-2011) in combination with the sc_PDSI drought index. The results show that SIF is more sensitive to drought than the NDVI and EVI; the correlation between the GPP estimated based on SIF data (GPPSF) and the actual observed flux values (R\({}^{2}\) = 0.83) is better than GPPGLASS and GPPLUE, and the RMSE is also lower than those two products. This drought has a serious impact on GPP, and the monthly average values of the effect of drought on GPP (GPPd) in Yunnan Province in 2009, 2010, and 2011 are \(-\)11.37 gC\(\cdot\)m\({}^{-2}\cdot\)month\({}^{-1}\), \(-\)23.48 gC\(\cdot\)m\({}^{-2}\cdot\)month\({}^{-1}\) and \(-\)17.92 gC\(\cdot\)m\({}^{-2}\cdot\)month\({}^{-1}\), which are 8.6%, 17.48% and 13.85% of the monthly average in a normal year, respectively. The spatial variability of GPP response to drought is significant, which is mainly determined by the degree, and duration of the drought, the vegetation type, the topography, and anthropogenic factors. In conclusion, GPPSIF quickly and accurately reflects the process of this drought, and this study helps to elucidate the response of GPP to drought conditions and provides more scientific information for drought prediction and ecosystem management. Sun-induced Chlorophyll fluorescence (SIF); drought; Gross Primary Productivity (GPP); Yunnan; vegetation 2  
Index (EVI), and the Normalized Difference Water Index (NDWI) [4]. It is well known that an arid environment can lead to changes in the vegetation physiological and metabolic functions of vegetation, which can reduce photosynthesis and fluorescence production [5; 6]. However, these vegetation indices are only sensitive to changes in the canopy structure and pigment concentration and are not directly related to photosynthesis [7]. Therefore, when drought occurs, the spectral characteristics of the vegetation canopy do not change immediately, resulting in GPP based on these vegetation indices not reflecting drought quickly and accurately, and the response to drought has a significant lag effect [7]. Sun-induced Chlorophyll fluorescence (SIF) data is a light signal produced by vegetation during photosynthesis, a concomitant product of photosynthesis, and has the advantage of providing more intuitive information on plant biochemical, physiological, and metabolic functions than reflectance-based vegetation indices [8]. Therefore, SIF has been used to study water stress at different spatial scales. During drought, fluorescence decreases due to water stress even if vegetation canopy greenness remains constant [5] Therefore, SIF is more sensitive to vegetation stress by drought than vegetation index, which measures only vegetation greenness [9]. Special research, however, is not available at present to demonstrate that SIF-based vegetation GPP responds better to drought climate than vegetation index-based GPP products, and is an excellent indicator to accurately and quickly reflect the process of drought impact on vegetation. Therefore, this study analyzed the response of GPP to drought based on SIF data simulation using a mega-drought as a case study. Drought indices are convenient tools with which to assess drought, such as the Standardized Precipitation Index (SPI) [10] and the Standardized Precipitation Evaporationaporation Index (SPEI), which rely on meteorological factors to assess drought and ignore the influence of surface factors on drought.