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Abstract Individually, extreme humid heat and extreme precipitation events can trigger widespread socioeconomic impacts which disproportionately affect vulnerable populations. These impacts might become greater when both events occur in close temporal proximity, for example if emergency responses to heat stress casualties are hindered by flooded roads. Improved understanding of the probabilities and physical mechanisms associated with these events’ temporal compounding might uncover causal interrelationships offering avenues for improving early warning systems and projecting changes in a warmer climate. We explore sequential humid heat and rainfall relationships during the local summer season, identifying two classes of temporal relationships. We find that high wet bulb temperature (WBT) anomalies in most mid- to high-latitude and tropical regions are preceded by anomalously low precipitation. In contrast, hot and dry subtropical regions generally experience elevated WBTs during and, to a somewhat lesser extent, before extreme precipitation events. High WBT events are followed by positive precipitation anomalies in many land regions. 

Abstract Hot and dry conditions pose a substantial risk to global crops. The frequency of co-occurring heat and drought depends on land–atmosphere coupling, which can be quantified by the correlation between temperature and evapotranspiration (r(T, ET)). We find that the majority of global croplands have experienced declines inr(T, ET) over the past ∼40 years, indicating a shift to a more moisture-limited state. In some regions, especially Europe, the sign ofr(T, ET) has flipped from positive to negative, indicating a transition from energy-limitation to moisture-limitation and suggesting a qualitative shift in the local climate regime. We associate stronger declines inr(T, ET) with faster increases in annual maximum temperatures and larger declines in soil moisture and ET during hot days. Our results suggest that shifts towards stronger land–atmosphere coupling have already increased the sensitivity of crop yields to temperature in much of the world by 12%–37%, as hot days are not only hotter, but also more likely to be concurrently dry. 

Abstract The impact of extreme heat on crop yields is an increasingly pressing issue given anthropogenic climate warming. However, some of the physical mechanisms involved in these impacts remain unclear, impeding adaptation-relevant insight and reliable projections of future climate impacts on crops. Here, using a multiple regression model based on observational data, we show that while extreme dry heat steeply reduced U.S. corn and soy yields, humid heat extremes had insignificant impacts and even boosted yields in some areas, despite having comparably high dry-bulb temperatures as their dry heat counterparts. This result suggests that conflating dry and humid heat extremes may lead to underestimated crop yield sensitivities to extreme dry heat. Rainfall tends to precede humid but not dry heat extremes, suggesting that multivariate weather sequences play a role in these crop responses. Our results provide evidence that extreme heat in recent years primarily affected yields by inducing moisture stress, and that the conflation of humid and dry heat extremes may lead to inaccuracy in projecting crop yield responses to warming and changing humidity. 

Climate change necessitates a global effort to reduce greenhouse gas emissions while adapting to increased climate risks. This broader climate transition will involve large-scale global interventions including renewable energy deployment, coastal protection and retreat, and enhanced space cooling, all of which will result in CO 2 emissions from energy and materials use. Yet, the magnitude of the emissions embedded in these interventions remains unconstrained, opening the potential for underaccounting of emissions and conflicts or synergies between mitigation and adaptation goals. Here, we use a suite of models to estimate the CO 2 emissions embedded in the broader climate transition. For a gradual decarbonization pathway limiting warming to 2 °C, selected adaptation-related interventions will emit ∼1.3 GtCO 2 through 2100, while emissions from energy used to deploy renewable capacity are much larger at ∼95 GtCO 2 . Together, these emissions are equivalent to over 2 y of current global emissions and 8.3% of the remaining carbon budget for 2 °C. Total embedded transition emissions are reduced by ∼80% to 21.2 GtCO 2 under a rapid pathway limiting warming to 1.5 °C. However, they roughly double to 185 GtCO 2 under a delayed pathway consistent with current policies (2.7 °C warming by 2100), mainly because a slower transition relies more on fossil fuel energy. Our results provide a holistic assessment of carbon emissions from the transition itself and suggest that these emissions can be minimized through more ambitious energy decarbonization. We argue that the emissions from mitigation, but likely much less so from adaptation, are of sufficient magnitude to merit greater consideration in climate science and policy. 

Abstract US maize and soy production have increased rapidly since the mid-20th century. While global warming has raised temperatures in most regions over this time period, trends in extreme heat have been smaller over US croplands, reducing crop-damaging high temperatures and benefiting maize and soy yields. Here we show that agricultural intensification has created a crop-climate feedback in which increased crop production cools local climate, further raising crop yields. We find that maize and soy production trends have driven cooling effects approximately as large as greenhouse gas induced warming trends in extreme heat over the central US and substantially reduced them over the southern US, benefiting crops in all regions. This reduced warming has boosted maize and soy yields by 3.3 (2.7–3.9; 13.7%–20.0%) and 0.6 (0.4–0.7; 7.5%–13.7%) bu/ac/decade, respectively, between 1981 and 2019. Our results suggest that if maize and soy production growth were to stagnate, the ability of the crop-climate feedback to mask warming would fade, exposing US crops to more harmful heat extremes. 

Abstract Intensive crop growth can modify regional climate by partitioning energy to latent heating through transpiration, cooling growing season temperatures. Recent work shows that cooling associated with agriculture can dampen anthropogenic warming over breadbasket regions. However, it is unknown whether climate models reproduce crop influences on regional climate, and thus the future risk of extreme climate events over global breadbasket regions. We show that models overestimate growing season temperatures and underestimate evapotranspiration (ET) over global croplands, and that these differences increase with cropped area. We trace this warm and dry difference through each model's representation of the surface energy budget, showing that model differences in transpiration, leaf area index, and the ratio of transpiration to total ET drive the overall effect. While the implications of these model deficiencies for future projections are uncertain, they point to the importance of improving representations of crop‐climate processes to better assess breadbasket vulnerability to climate change.