###### Abstract  
This study investigates the influence of meteorological parameters such as temperature and precipitation on gross primary production (GPP) in the continental United States (CONUS) during boreal summer using satellite-based temperature and precipitation indices and GPP data at various scales (i.e., pixel, county, and state levels). The strong linear relationship between temperature and precipitation indices is presented around the central United States, particularly in the Great Plains, where the year-to-year variation of GPP is very sensitive to meteorological conditions. This sensitive GPP variation is mostly attributable to the semi-arid climate in the Great Plains, where crop productivity and temperature are closely related. The more specific information for the regionality of the relationships across the variables manifests itself at higher resolutions. The impact of the summer meteorological condition on the annual crop yield is particularly significant. Maize and soybean yields show a strong correlation with both Temperature Condition Index (TCI) and Precipitation Condition Index (PCI) in the Great Plains, with a relatively higher relationship with TCI than PCI, which is consistent with the relationship compared with GPP. This study suggests that in-depth investigations into the relationship between maize and soybean yields and the climate are required. The region-dependent relationship between GPP and meteorological conditions in our study would guide agricultural decision making in the future climate. Keywords:regional climate; crop productivity; crop yield; gross primary production; temperature; precipitation +
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The influence of regional climate conditions on crop yield can be attributed primarily to soil moisture variations, which result mostly from the interaction between temperature and precipitation. The anomalously high temperature and low precipitation during the growing season have been regarded as the main drivers creating unfavorable conditions for crop growth [4; 14]. Excessively high temperatures in the growing season can decrease crop yield exponentially [15; 16], cause pollen sterility, and reduce seed sets [6; 17]. Prolonged lack of precipitation leads to a decrease in soil moisture that harms crop growth [18; 19], indicating that the influence of these climatic factors can intensify under drought conditions [6]. As mentioned in [PERSON] et al. [18], two-three months before harvesting (July and August for maize and soybean) is the most important period because maize silking and soybean blooming occur during that season. Obviously, it is hard to demonstrate which climate condition is most responsible for crop yield variation, because (i) regional temperature and precipitation in boreal summer are highly correlated and (ii) the relative importance of the climate conditions depends on the regional characteristics. The analysis in this paper seeks to resolve the above-mentioned aspects to provide detailed information about the role of climate conditions in US agriculture. Although many observational station data and the census of agriculture are available in the continental United States (CONUS) at national and state levels, they are still insufficient to represent the relationship between regional crop yield and climate conditions. What is required is an understanding of the relationships between crop yields and climate variability at finer spatiotemporal scales (e.g., county level and pixel level) [20]. Local-scale climate conditions usually demand spatiotemporally continuous high-resolution data to understand the effect on crop yield. Satellite-derived data provide spatiotemporally continuous climate conditions (e.g., precipitation, land surface temperature (LST), and soil moisture) covering large areas at relatively high resolution. Therefore, satellite data are useful for analyzing the influence of climate conditions on crop yield at local and regional scales.