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Abstract Warm temperatures due to increases of greenhouse gas emissions have changed temperature distribution patterns especially for their extremes, which negatively affect crop yields. However, the assessment of these negative impacts remains unclear when surface precipitation patterns are shifted. Using a statistical model along with 23,944 county-year maize-yield data during 1981–2020 in the US Corn Belt, we found that the occurrence of timely precipitation reduced the sensitivity of maize yields to extreme heat by an average of 20% during the growing season with variations across phenological periods. Spatially across the US corn belt, maize in the northern region exhibited more significant benefits from timely precipitation compared to the southern region, despite the pronounced negative effects of extreme heat on yields in cooler regions. This study underscores the necessity of incorporating timely precipitation as a pivotal factor in estimating heat effects under evolving climates, offering valuable insights into complex climate-related challenges. 

Precipitation recycling, where evapotranspiration (ET) from the land surface contributes to precipitation within the same region, is a critical component of the water cycle. This process is especially important for the US Corn Belt, where extensive cropland expansions and irrigation activities have significantly transformed the landscape and affected the regional climate. Previous studies investigating precipitation recycling typically relied on analytical models with simplifying assumptions, overlooking the complex interactions between groundwater hydrology and agricultural management. In this study, we use high-resolution climate models coupled with an explicit water vapor tracer algorithm to quantify the impacts of shallow groundwater, dynamic crop growth, and irrigation on regional precipitation recycling in the US Corn Belt. We find that these coupled groundwater–crop–irrigation processes reduce surface temperatures and increase the growing season precipitation. The increase in precipitation is attributed to a significant enhancement of the precipitation recycling ratio from 14 to 18%. This enhanced precipitation recycling is stronger in a dry year than normal and wet years, depending on both large-scale moisture transport and local ET. Our study underscores the critical role of groundwater hydrology and agricultural management in altering the regional water cycle, with important implications for regional climate predictions and food and water security. 

Unprecedented precipitation deficits in the 2022–2023 growing season across the primary wheat-producing region in the United States caused delays in winter wheat emergence and poor crop growth. Using an integrated approach, we quantitatively unraveled a 37% reduction in wheat production as being attributable to both per–harvested acre yield loss and severe crop abandonment, reminiscent of the Dust Bowl years in the 1930s. We used random forest machine learning and game theory analytics to show that the main driver of yield loss was spring drought, whereas fall drought dominated abandonment rates. Furthermore, results revealed, across the US winter wheat belt, the La Niña phase of the El Niño Southern Oscillation (ENSO), increased abandonment rates compared to the El Niño phase. These findings underscore the necessity of simultaneously addressing crop abandonment and yield decline to stabilize wheat production amid extreme climatic conditions and provide a holistic understanding of global-scale ENSO dynamics on wheat production.