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Many agricultural regions in China are likely to become appreciably wetter or drier as the global climate warming increases. However, the impact of these climate change patterns on the intensity of soil greenhouse gas (GHG) emissions (GHGI, GHG emissions per unit of crop yield) has not yet been rigorously assessed. By integrating an improved agricultural ecosystem model and a meta‐analysis of multiple field studies, we found that climate change is expected to cause a 20.0% crop yield loss, while stimulating soil GHG emissions by 12.2% between 2061 and 2090 in China's agricultural regions. A wetter‐warmer (WW) climate would adversely impact crop yield on an equal basis and lead to a 1.8‐fold‐ increase in GHG emissions relative to those in a drier‐warmer (DW) climate. Without water limitation/excess, extreme heat (an increase of more than 1.5°C in average temperature) during the growing season would amplify 15.7% more yield while simultaneously elevating GHG emissions by 42.5% compared to an increase of below 1.5°C. However, when coupled with extreme drought, it would aggravate crop yield loss by 61.8% without reducing the corresponding GHG emissions. Furthermore, the emission intensity in an extreme WW climate would increase by 22.6% compared to an extreme DW climate. Under this intense WW climate, the use of nitrogen fertilizer would lead to a 37.9% increase in soil GHG emissions without necessarily gaining a corresponding yield advantage compared to a DW climate. These findings suggest that the threat of a wetter‐warmer world to efforts to reduce GHG emissions intensity may be as great as or even greater than that of a drier‐warmer world. Plain Language Summary: Both climate observations and projections suggest that warmer temperatures will intensify convective precipitation, resulting in drier regions becoming drier and wetter regions becoming wetter. By integrating an improved agricultural ecosystem model and a meta‐analysis of multiple field studies, this study has investigated the effects of drier‐warmer (DW) and wetter‐warmer (WW) climates on crop yield and soil greenhouse gas emissions in China. Our findings indicate that the cost of greenhouse gas emissions in a wetter‐warmer world for crop production could be as high as or even higher than in a drier‐warmer world. Moreover, this study suggests that effective climate mitigation practices need to account for the combined effects of extreme climate changes and nitrogen addition on greenhouse gas emissions and crop production. Therefore, China would need to exert considerably more effort in a future with warmer and wetter conditions to achieve its greenhouse gas emission reduction targets. Key Points: Climate change would cause a 20% crop yield loss and an increase of 12.2% in soil greenhouse gas (GHG) emissions between 2061 and 2090A Wetter‐Warmer climate would cause a more significant crop yield loss and about double the GHG emissions of a Drier‐Warmer climateNitrogen fertilizer‐induced GHG emissions in a Wetter‐Warmer climate would increase 37.9% compared to those in a Drier‐Warmer climate [ABSTRACT FROM AUTHOR]

To aid California's water sector to better understand and manage future climate extremes, we present a method for creating a regionally consistent ensemble of plausible daily future climate and streamflow scenarios that represent natural climate variability captured in a network of tree‐ring chronologies, and then embed anthropogenic climate change trends within those scenarios. We use 600 years of paleo‐reconstructed weather regimes to force a stochastic weather generator, which we develop for five subbasins in the San Joaquin Valley of California. To assess the compound effects of climate change, we create temperature series that reflect projected scenarios of warming and precipitation series that have been scaled to reflect thermodynamically driven shifts in the distribution of daily precipitation. We then use these weather scenarios to force hydrologic models for each of the five subbasins. The paleo‐forced streamflow scenarios highlight periods in the region's past that produce flood and drought extremes that surpass those in the modern record and exhibit large non‐stationarity through the reconstruction. Variance decomposition is employed to characterize the contribution of natural variability and climate change to variability in decision‐relevant metrics related to floods and drought. Our results show that a large portion of variability in individual subbasin and spatially compounding extreme events can be attributed to natural variability, but that anthropogenic climate changes become more influential at longer planning horizons. The joint importance of climate change and natural variability in shaping extreme floods and droughts is critical to resilient water systems planning and management in the San Joaquin. Plain Language Summary: California experiences cycles of floods and droughts that can be driven by both natural variability and climate change. The specific role these drivers play in impacting extremes is uncertain, but can influence how to best plan and manage regional water systems for future extremes. To better quantify the role of these drivers, we introduce a framework that utilizes a 600‐year tree‐ring reconstruction to create long sequences of plausible future weather and streamflow for key basins in the San Joaquin Valley. We find that a large portion of variability in extremes can be attributed to natural variability at shorter planning horizons, but that human‐driven climate changes are influential at longer planning horizons (>30 years). Furthermore, decision‐makers' perceptions of important drivers can be skewed depending on the specific definitions used to analyze floods and droughts, which can present significant challenges for adaptation planning and infrastructure development tied to tracking hydroclimate variables. This study also illustrates the vast variability in extremes that the region has experienced over the past 600 years and highlights the pitfalls of defining risk based on a limited historical record. Key Points: We introduce a framework to create 600‐year ensembles of future weather and streamflow for basins in the San Joaquin ValleyWe discover vast variability and non‐stationarity in flood and drought extremes in the region over the past 600 yearsThe joint importance of climate change and natural variability in shaping floods and droughts is critical to water systems planning [ABSTRACT FROM AUTHOR]

This commentary discusses new advances in the predictability of east African rains and highlights the potential for improved early warning systems (EWS), humanitarian relief efforts, and agricultural decision‐making. Following an unprecedented sequence of five droughts, 23 million east Africans faced starvation in 2022, requiring >$2 billion in aid. Here, we update climate attribution studies showing that these droughts resulted from an interaction of climate change and La Niña. Then we describe, for the first time, how attribution‐based insights can be combined with the latest dynamical models to predict droughts at 8‐month lead‐times. We then discuss behavioral and social barriers to forecast use, and review literature examining how EWS might (or might not) enhance agro‐pastoral advisories and humanitarian interventions. Finally, in reference to the new World Meteorological Organization "Early Warning for All" Executive Action Plan, we conclude with a set of recommendations supporting actionable and authoritative climate services. Trust, urgency, and accuracy can help overcome barriers created by limitedfunding, uncertain tradeoffs, and inertia. Understanding how climate change is producing predictable climate extremes now, investing in African‐led EWS, and building better links between EWS and agricultural development efforts can support long‐term adaptation, reducing chronic needs for billions of dollars in reactive assistance. In Africa and beyond, climate change brings increasingly extreme sea surface temperature (SST) gradients. Using climate models, we can often see these extremes coming. Prediction, therefore, offers opportunities for proactive risk management and improved advisory services, if we can create effective societal linkages via cross‐silo collaborations. Plain Language Summary: Eastern East Africa is extremely food insecure. Millions of farmers and pastoralists rely on two meager rainy seasons that arrive twice a year. In the 13 seasons since late 2016, the region experienced eight droughts and three exceptionally wet seasons. Seven droughts were linked to very strong Pacific sea surface temperature (SST) gradients, which arose through an interaction between climate change and La Niña. Climate change will bring more extreme Pacific and Indian Ocean SST gradients. Here, for the first time, we show that these gradients can be very well predicted by the current generation of climate models. We then discuss how such information might be used to inform risk management, agriculture, and livestock management practices. The IGAD Climate Predictions and Applications Center, Ethiopian and Kenyan meteorological agencies, and other groups are providing increasingly accurate climate information. This creates opportunities for more proactive and effective agricultural and pastoral advisory services. Trust, urgency and accuracy can lower uncertainty, reduce risk aversion, and empower poor households and cash‐strapped institutions to act and innovate. Investing now in collaborative African climate systems, participatory advisory services and proactive risk management will help counter these threatening climate extremes. Key Points: Climate change and La Niña are producing extreme Pacific sea surface temperature (SST) gradients, which can be predicted very far in advanceThese Pacific SST forecasts provide robust opportunities for predicting well wet and dry outcomes in East AfricaTrust, urgency and accuracy can overcome barriers due to limited funding, uncertain tradeoffs, and inertia by improving advisory services [ABSTRACT FROM AUTHOR]

Climate change is affecting the agriculture, water, and energy sectors in East Africa and the impact is projected to increase in the future. To allow adaptation and mitigation of the impacts, we assessed the changes in climate and their impacts on hydrology and hydrological extremes in East Africa. We used outputs from seven CMIP‐6 Global Climate Models (GCMs) and 1981–2010 is used as a reference period. The output from GCMs are statistically downscaled using the Bias Correction‐Constructed Analogs with Quantile mapping reordering method to drive a high‐resolution hydrological model. The Variable Infiltration Capacity and vector‐based routing models are used to simulate runoff and streamflow across 68,300 river reaches in East Africa. The results show an increase in annual precipitation (up to 35%) in Ethiopia, Uganda, and Kenya and a decrease (up to 4.5%) in Southern Tanzania in the 2050s (2041–2070) and 2080s (2071–2100). During the long rainy season (March–May), precipitation is projected to be higher (up to 43%) than the reference period in Southern Ethiopia, Kenya, and Uganda but lower (up to −20%) in Tanzania. Large parts of Kenya, Uganda, Tanzania, and Southern Ethiopia show an increase in precipitation (up to 38%) during the short rainy season (October–December). Temperature and evapotranspiration will continue to increase in the future. Further, annual and seasonal streamflow and hydrological extremes (droughts and floods) are projected to increase in large parts of the region throughout the 21st century calling for site‐specific adaptation. Key Points: Precipitation, precipitation extremes, and temperature will increase in large parts of East Africa in the 21st centuryHydrological extremes (droughts and floods) will increase in the future in large parts of Ethiopia, Kenya, and TanzaniaSite‐specific adaptation measures are urgently required to minimize the adverse impact of hydroclimate extremes in East Africa [ABSTRACT FROM AUTHOR]

Water utilities' supply systems are vulnerable to several climate‐related hazards, including droughts, floods and cyclones. Here we propose a generally applicable framework for conducting multi‐hazard risk assessments of water supply systems and use it to quantify the impact of present and future climate extremes on the national water supply network in Jamaica. The proposed framework involves stress‐testing a model of the system with a large set of spatially coherent drought, cyclone and pluvial and fluvial flood events to calculate the number of water users whose supplies would be disrupted during an event, that is, the Customer disruption days (CDD). We estimate the total multi‐hazard annual expected disruption to be approximately 5 days per year per utility customer under present conditions. This is increased by a factor of between 2 and 2.5 when end‐of‐century climate scenarios are propagated through the model. Our analysis shows that more high probability drought events lead to greater CDD compared with asset damage events. However, extreme asset damage events, despite manifesting over shorter timescales (days) compared to drought events (months), can lead to more widespread CDD. This quantified risk framework would allow utility managers to compare the risk of both asset damage‐ and water shortage‐induced disruptions via a common, decision‐relevant metric. However, applications to other utilities would require tailored hazard modeling approaches. The proposed risk assessment is intended to inform prioritization of infrastructure investments, ranging from asset protection to drought mitigation projects, with the goal of enhancing water supply resilience in the face of a changing climate. Key Points: We propose a spatial multi‐hazard risk framework for analyzing present‐day and future climate risks to water usersWe propose the use of customer disruption days as a common metric for comparing different hazards impactsThe framework can be used by decision makers to prioritize investments across asset protection against flooding and cyclones, and drought mitigation options [ABSTRACT FROM AUTHOR]