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Detection and attribution studies generally examine individual climate variables such as temperature and precipitation. Thus, we lack a strong understanding of climate change impacts on correlated climate extremes and compound events, which have become more common in recent years. Here we present a monthly‐scale compound warm and dry attribution study, examining CMIP6 climate models with and without the influence of anthropogenic forcing. We show that most regions have experienced large increases in concurrent warm and dry months in historical simulations with human emissions, while no coherent change has occurred in historical natural‐only simulations without human emissions. At the global scale, the likelihood of compound warm‐dry months has increased 2.7 times due to anthropogenic emissions. With this multivariate perspective, we highlight that anthropogenic emissions have not only impacted individual extremes but also compound extremes. Due to amplified risks from multivariate extremes, our results can provide important insights on the risks of associated climate impacts. Plain Language Summary: Most climate change studies tend to explore changes in individual climate variables such as temperature or precipitation. Due to this, we currently do not possess a strong understanding of the multiple changes that can occur simultaneously under human‐driven climate change. Here we present how the simultaneous occurrence of warm and dry months have increased significantly under modeled climate conditions with human emissions, especially relative to modeled climate conditions without human emissions. We highlight that at the global scale, the occurrence of simultaneously warm and dry months has increased 2.7 times under the presence of human emissions. Since the simultaneous occurrence of extreme climate conditions can produce devastating impacts, this study provides an important perspective on the large‐scale multivariate changes that have emerged as a result of human‐driven climate change. Key Points: Using CMIP6 model output, we attribute large increases in concurrent warm and dry months across the globe to anthropogenic activitiesDue to anthropogenic forcing, the global likelihood of warm‐dry months has increased by 2.7 times in land areas between 60°N–60°SWarm‐dry concurrences show largest increases in the tropics and subtropics (Central and South America, Africa, and East and Southeast Asia) [ABSTRACT FROM AUTHOR]

Most attribution studies tend to focus on the impact of anthropogenic forcing on individual variables. However, studies have already established that many climate variables are interrelated, and therefore, multidimensional changes can occur in response to climate change. Here, we propose a multivariate method which uses copula theory to account for underlying climate conditions while attributing the impact of anthropogenic forcing on a given climate variable. This method can be applied to any relevant pair of climate variables; here we apply the methodology to study high temperature exceedances given specified precipitation conditions (e.g., hot droughts). With this method, we introduce a new conditional probability ratio indicator, which communicates the impact of anthropogenic forcing on the likelihood of conditional exceedances. Since changes in temperatures under droughts have already accelerated faster than average climate conditions in many regions, quantifying anthropogenic impacts on conditional climate behavior is important to better understand climate change. Plain Language Summary: Most studies investigating human impacts on climate conditions focus on characterizing changes in individual variables such as precipitation or temperature. However, since many climate conditions are interconnected, these individual variables do not comprehensively represent the many changes that can occur in response to human activity. Here, we introduce a method that takes into account underlying climate conditions while quantifying the impact of human activity on a given climate variable. This method can be used to study pairs of climate variables and here we provide an example application to examine high temperature occurrences during dry precipitation conditions using climate models. For example, we show that regions such as the Amazon have a 4.1 times higher likelihood of experiencing high temperatures under dry climate conditions as a result of human activity. Given our knowledge of future climate change, we anticipate that the relationships between key climate variables may continue to change, which makes the study of human impacts on conditional climate behavior important for a more complete understanding of climate change. Key Points: We propose a multivariate method to conduct an attribution analysis of one variable conditioned on another related climate variableWe show how this method can be applied to high temperature exceedances given specified precipitation conditionsLand regions between 60°N and 60°S show increased risk of conditional temperature extremes under dry conditions due to anthropogenic forcing [ABSTRACT FROM AUTHOR]

Traditional, mainstream definitions of drought describe it as deficit in water‐related variables or water‐dependent activities (e.g., precipitation, soil moisture, surface and groundwater storage, and irrigation) due to natural variabilities that are out of the control of local decision‐makers. Here, we argue that within coupled human‐water systems, drought must be defined and understood as a process as opposed to a product to help better frame and describe the complex and interrelated dynamics of both natural and human‐induced changes that define anthropogenic drought as a compound multidimensional and multiscale phenomenon, governed by the combination of natural water variability, climate change, human decisions and activities, and altered micro‐climate conditions due to changes in land and water management. This definition considers the full spectrum of dynamic feedbacks and processes (e.g., land‐atmosphere interactions and water and energy balance) within human‐nature systems that drive the development of anthropogenic drought. This process magnifies the water supply demand gap and can lead to water bankruptcy, which will become more rampant around the globe in the coming decades due to continuously growing water demands under compounding effects of climate change and global environmental degradation. This challenge has de facto implications for both short‐term and long‐term water resources planning and management, water governance, and policymaking. Herein, after a brief overview of the anthropogenic drought concept and its examples, we discuss existing research gaps and opportunities for better understanding, modeling, and management of this phenomenon. Plain Language Summary: This article reviews research and progress on the notion of anthropogenic drought broadly defined as drought events caused or intensified by human activities. Most commonly used drought definitions are based on deficit in hydrologic/meteorologic drivers such as precipitation and runoff. Within coupled human‐water systems, however, drought must be defined and understood as the complex and interrelated dynamics of both natural and human‐induced changes. This anthropogenic drought definition considers the full spectrum of dynamic feedbacks and processes (e.g., land‐atmosphere interactions and water and energy balance) within human‐nature systems. Ideally, anthropogenic drought and the corresponding human interactions should be incorporated in models that include land‐atmosphere interactions, water balance, and energy balance. In this article, we review existing research gaps and opportunities for better understanding, modeling, and management of this phenomenon. Key Points: Anthropogenic drought is primarily governed by the joint impacts of natural renewable water variability, climate change, and human decisionsAnthropogenic drought and water bankruptcy will become more ubiquitous under current development and climate change trajectoriesIdeally, human interactions should be incorporated in models that include land‐atmosphere interactions, water balance and energy balance [ABSTRACT FROM AUTHOR]

Abstract: Compound extremes correspond to events with multiple concurrent or consecutive drivers (e.g., ocean and fluvial flooding, drought, and heat waves) leading to substantial impacts such as infrastructure failure. In many risk assessment and design applications, however, multihazard scenarios of extremes and compound events are ignored. In this paper, we review the existing multivariate design and hazard scenario concepts and introduce a novel copula‐based weighted average threshold scenario for an expected event with multiple drivers. The model can be used for obtaining multihazard design and risk assessment scenarios and their corresponding likelihoods. The proposed model offers uncertainty ranges of most likely compound hazards using Bayesian inference. We show that the uncertainty ranges of design quantiles might be large and may differ significantly from one copula model to the other. We also demonstrate that the choice of marginal and copula functions may profoundly impact the multihazard design values. A robust analysis should account for these uncertainties within and between multivariate models that translate into multihazard design quantiles. [ABSTRACT FROM AUTHOR]

Climate change may affect ocean-driven coastal flooding regimes by both raising the mean sea level (msl) and altering ocean-atmosphere interactions. For reliable projections of coastal flood risk, information provided by different climate models must be considered in addition to associated uncertainties. In this paper, we propose a framework to project future coastal water levels and quantify the resulting flooding hazard to infrastructure. We use Bayesian Model Averaging to generate a weighted ensemble of storm surge predictions from eight climate models for two coastal counties in California. The resulting ensembles combined with msl projections, and predicted astronomical tides are then used to quantify changes in the likelihood of road flooding under representative concentration pathways 4.5 and 8.5 in the near-future (1998-2063) and mid-future (2018-2083). The results show that road flooding rates will be significantly higher in the near-future and mid-future compared to the recent past (1950-2015) if adaptation measures are not implemented. [ABSTRACT FROM AUTHOR]

Natural disasters often affect the most vulnerable countries/communities around the world. However, within the same countries/communities, the impact of natural disasters is far greater on disadvantaged populations. We investigate how wildfires affect asthma prevalence in different populations across California. Our results indicate that although there is no discernible relationship between wildfires and asthma prevalence for California's population as a whole, wildfires and asthma prevalence in Black and senior populations have a strong relationship. We believe there is an urgent need to make high‐resolution health‐related data publicly available for in‐depth analyses of climate change impacts on society and disadvantage communities Key Points: The impact of natural disasters is greater on disadvantaged and vulnerable populations with respect to the overall populationThere is a need to make high‐resolution health‐related data publicly available for in‐depth analyses of climate change impacts on society [ABSTRACT FROM AUTHOR]