## 1 Introduction
Thus, accurately assessing drought is difficult when these products are used. Under natural illumination, a part of the unused absorbed photosynthetically active radiation (APAR) is emitted by vegetation as fluorescence, and is referred to as solar-induced chlorophyll fluorescence (SIF) [18]. Recent studies have successfully extracted a global time-series of SIF from satellite observations [18; 19; 20]. SIF provides an alternative method for monitoring global vegetation from space, because it is different from traditional reflectance-based vegetation indices. SIF is directly related to the photosynthesis of vegetation and is likely to reflect rapid changes in the water stress of a canopy [21; 22]. The relationship between the gross primary production (GPP), APAR, and the light use efficiency (LUE) is as follows:  
\[GPP\ =\ APAR\ \times\ LUE \tag{1}\]  
\[SIF\ =\ APAR\ \times\ SIFyield\, \tag{2}\]  
where \(\text{SIF}_{\text{yield}}\) is the SIF emitted per photon absorbed [23]. According to Equation (2), if the ratio of \(\text{SIF}_{\text{yield}}\) and LUE remains relatively stable, which has been confirmed under moderate illumination [24], SIF will have a linear relationship with GPP [25]. A good consistency between space-borne SIF and flux-measured GPP has been found in different biomes [26], and the SIF-driven NPP model helps to improve the estimation of crop yield [27]. As with the LUE, SIF\({}_{\text{yield}}\) is sensitive to environmental stresses, such as water or heat stress [28; 29], so SIF is expected to respond rapidly to agricultural drought and to directly indicate drought-induced reductions of vegetation production. [PERSON] _et al._[28] used SIF extracted from the Greenhouse gases Observing Satellite (GOSAT) to evaluate the drought-induced reduction of forest production in Amazonia. [PERSON] _et al._[25] monitored the Russian drought in 2010 using SIF extracted from the Global Ozone Monitoring Instrument 2 (GOME-2) and found that drought-related declines in LUE and APAR produced losses in SIF and GPP. [PERSON] _et al._[30] also reported positive relationships between the SIF and soil water content (SWC) anomalies in Texas and the central Great Plains. However, the relationships between the widely used meteorological drought indices and satellite measurements of SIF have not been examined. Whether the lag between remotely-sensed vegetation parameters and precipitation also holds for SIF has not been confirmed. In addition, the spatiotemporal patterns of drought monitored by drought indices, the NDVI, and SIF have not been compared and discussed. Our objective in this study was to investigate satellite-measured SIF responses to drought by analyzing the relationship between various meteorological drought indices and SIF, and to examine whether SIF is more sensitive to short-term drought conditions than are reflectance-based VIs. Our study examined the feasibility of directly using satellite-measured SIF to monitor and assess drought. There was an extreme drought in the Great Plains of the USA in 2012, and we compared SIF and ground-based GPP among dry and humid years. We used SIF to monitor the drought during the summer of 2012, and applied a simple model to make an assessment of the drought-induced reduction of GPP throughout the Great Plains. We compared drought patterns derived from meteorological drought indices, SIF, and the NDVI, and discuss our results below.