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1. Global Assessment of Compound Climate Extremes and Exposures of Population, Agriculture, and Forest Lands Under Two Climate Scenarios

   https://doi.org/10.1029/2024EF004845  

   Schillerberg, Tayler_A; Tian, Di (September 2024, Earth's Future)

   Abstract Climate change is expected to increase the global occurrence and intensity of heatwaves, extreme precipitation, and flash droughts. However, it is not well understood how the compound heatwave, extreme precipitation, and flash drought events will likely change, and how global population, agriculture, and forest will likely be exposed to these compound events under future climate change scenarios. This research uses eight CMIP6 climate models to assess the current and future global compound climate extreme events, as well as population, agriculture, and forestry exposures to these events, under two climate scenarios, Shared Socioeconomic Pathways (SSP), SSP1‐2.6 and SSP5‐8.5 for three time periods: early‐, mid‐, and late‐ 21st century. Climate extremes are derived for heatwaves, extreme precipitation, and flash droughts using locational‐dependent thresholds. We find that compound heatwaves and flash drought events result in the largest increases in exposure of populations, agriculture, and forest lands, under SSP5‐8.5 late‐century projections of sequential heatwaves and flash droughts. Late‐century projections of sequential heatwaves and flash droughts show hot spots of exposure increases in population exposure greater than 50 million person‐events in China, India, and Europe; increases in agriculture land exposures greater than 90 thousand km²‐events in China, South America, and Oceania; and increase in forest land exposure greater than 120 thousand km²‐events in Oceania and South America regions when compared to the historical period. The findings from this study can be potentially useful for informing global climate adaptations. 

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2. Spatial patterns of extreme precipitation and their changes under ~ 2 °C global warming: a large-ensemble study of the western USA

   https://doi.org/10.1007/s00382-022-06214-3  

   Rupp, David E; Hawkins, Linnia R; Li, Sihan; Koszuta, Matthew; Siler, Nicholas (October 2022, Climate Dynamics)

   Extreme precipitation events are expected to increase in magnitude in response to global warming, but the magnitude of the forced response may vary considerably across distances of ~ 100 km or less. To examine the spatial variability of extreme precipitation and its sensitivity to global warming with high statistical certainty, we use a large (16,980 years), initial-condition ensemble of dynamically downscaled global climate model simulations. Under approximately 2 °C of global warming above a recent baseline period, we find large variability in the change (0 to > 60%) of the magnitude of very rare events (from 10 to 1000-year return period values of annual maxima of daily precipitation) across the western United States. Western (and predominantly windward) slopes of coastal ranges, the Cascades, and the Sierra Nevada typically show smaller increases in extreme precipitation than eastern slopes and bordering valleys and plateaus, but this pattern is less evident in the continental interior. Using the generalized extreme value shape parameter to characterize the tail of the precipitation distribution (light to heavy tail), we find that heavy tails dominate across the study region, but light tails are common on the western slopes of mountain ranges. The majority of the region shows a tendency toward heavier tails under warming, though some regions, such as plateaus of eastern Oregon and Washington, and the crest of the Sierra Nevada, show a lightening of tails. Spatially, changes in long return-period precipitation amounts appear to partially result from changes in the shape of the tail of the distribution. 

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3. Anthropogenic Influence on Recent Severe Autumn Fire Weather in the West Coast of the United States

   https://doi.org/10.1029/2021GL095496  

   Hawkins, Linnia R.; Abatzoglou, John T.; Li, Sihan; Rupp, David E. (February 2022, Geophysical Research Letters)

   Abstract Extreme wind‐driven autumn wildfires are hazardous to life and property, due to their rapid rate of spread. Recent catastrophic autumn wildfires in the western United States co‐occurred with record‐ or near‐record autumn fire weather indices that are a byproduct of extreme fuel dryness and strong offshore dry winds. Here, we use a formal, probabilistic, extreme event attribution analysis to investigate the anthropogenic influence on extreme autumn fire weather in 2017 and 2018. We show that while present‐day anthropogenic climate change has slightly decreased the prevalence of strong offshore downslope winds, it has increased the likelihood of extreme fire weather indices by 40% in areas where recent autumn wind‐driven fires have occurred in northern California and Oregon. The increase was primarily through increased autumn fuel aridity and warmer temperatures during dry wind events. These findings illustrate that anthropogenic climate change is exacerbating autumn fire weather extremes that contribute to high‐impact catastrophic fires in populated regions of the western US. 

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4. Climate models capture key features of extreme precipitation probabilities across regions

   https://doi.org/10.1088/1748-9326/abd351  

   Martinez-Villalobos, Cristian; Neelin, J. David (January 2021, Environmental Research Letters)

   Abstract Quantitative simulation of precipitation in current climate has been an ongoing challenge for global climate models. Despite serious biases in correctly simulating probabilities of extreme rainfall events, model simulations under global warming scenarios are routinely used to provide estimates of future changes in these probabilities. To minimize the impact of model biases, past literature tends to evaluate fractional (instead of absolute) changes in probabilities of precipitation extremes under the assumption that fractional changes would be more reliable. However, formal tests for the validity of this assumption have been lacking. Here we evaluate two measures that address properties important to the correct simulation of future fractional probability changes of precipitation extremes, and that can be assessed with current climate data. The first measure tests climate model performance in simulating the characteristic shape of the probability of occurrence of daily precipitation extremes and the second measure tests whether the key parameter governing the scaling of this shape is well reproduced across regions and seasons in current climate. Contrary to concerns regarding the reliability of global models for extreme precipitation assessment, our results show most models lying within the current range of observational uncertainty in these measures. Thus, most models in the Coupled Model Intercomparison Project Phase 6 ensemble pass two key tests in current climate that support the usefulness of fractional measures to evaluate future changes in the probability of precipitation extremes. 

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5. A generic risk assessment framework to evaluate historical and future climate-induced risk for rainfed corn and soybean yield in the U.S. Midwest

   Zhou, W. (August 2021, Weather and climate extremes)

   null (Ed.)

   Fluctuations in temperature and precipitation are expected to increase with global climate change, with more frequent, more intense and longer-lasting extreme events, posing greater challenges for the security of global food production. Here we proposed a generic framework to assess the impact of climate-induced crop yield risk under both current and future scenarios by combining a stochastic model for synthetic climate generation with a well-validated statistical crop yield model. The synthetic climate patterns were generated using the extended Empirical Orthogonal Function method based on historically observed and projected climate conditions. We applied our framework to assess the corn and soybean yield risk in the U.S. Midwest for historical and future climate conditions. We found that: (1) in the U.S. Midwest, about 45% and 40% of the interannual variability in corn and soybean yield, respectively, can be explained by the climate; (2) the risk level is higher in the southwest and northwest regions of the U.S. Midwest corresponding to 25% yield reduction for both corn and soybean compared to other regions; (3) the severity for the 1988 and 2012 major droughts quantified by our method represent 21-year and 30-year events for corn, and 7-year and 12-year events for soybean, respectively; (4) the crop yield risk will increase under a future climate scenario (i.e., Representative Concentration Pathway 8.5 or RCP 8.5 at 2050) compared with the current climate condition, with averaged yield decreases and yield variability increases for both corn and soybean. The framework and the results of this study enable applications for risk management policies and practices for the agriculture sectors. 

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