Extreme events are of interest worldwide given their potential for substantial impacts on social, ecological, and technical systems. Many climate‐related extreme events are increasing in frequency and/or magnitude due to anthropogenic climate change, and there is increased potential for impacts due to the location of urbanization and the expansion of urban centers and infrastructures. Many disciplines are engaged in research and management of these events. However, a lack of coherence exists in what constitutes and defines an extreme event across these fields, which impedes our ability to holistically understand and manage these events. Here, we review 10 years of academic literature and use text analysis to elucidate how six major disciplines—climatology, earth sciences, ecology, engineering, hydrology, and social sciences—define and communicate extreme events. Our results highlight critical disciplinary differences in the language used to communicate extreme events. Additionally, we found a wide range in definitions and thresholds, with more than half of examined papers not providing an explicit definition, and disagreement over whether impacts are included in the definition. We urge distinction between extreme events and their impacts, so that we can better assess when responses to extreme events have actually enhanced resilience. Additionally, we suggest that all researchers and managers of extreme events be more explicit in their definition of such events as well as be more cognizant of how they are communicating extreme events. We believe clearer and more consistent definitions and communication can support transdisciplinary understanding and management of extreme events.

Heat waves are an important type of extreme climate event and directly result in more than 130 deaths per year across the United States. Heat waves have been described by several attributes and combinations which constitute various event typologies. Attributes of heat waves from 10 cities are analyzed over the period 1950–2016 to understand how these attributes determine variability in local heat waves and how climate change affects heat waves across the United States. This study uses eight definitions to differentiate heat waves and tests for temporal trends in key properties of heat waves over the period 1950–2016. At least five harmful attributes of heat waves have increased simultaneously for Dallas, Miami, New York, Phoenix, and Portland.Miami showed the greatest change in heat wave season length, frequency, and timing over the study period. Surprisingly, the greatest mean heat wave intensities above daily thresholds were for Bismarck, ND (+8.2 °C) and Syracuse, NY (+6.5 °C). Similar results across Baltimore, MD, Colorado Springs, CO, Dallas, TX, Des Moines, IA, Miami, FL, New York, NY, Phoenix, AZ, and Portland, OR, are presented to clarify the many quantitative differences in heat wave attributes and variance in quantification approaches across climates. This work explores the nexus of quantitative description and social construction of heat waves through the lens of the various regional metrics to describe heat waves. Ultimately, this assessment will guide the development of various strategies to help communities understand and prepare for heat resilience based on local heat wave components.

Streamflow monitoring in the Colorado River Basin (CRB) is essential to ensure diverse needs are met, especially during periods of drought or low flow. Existing stream gage networks, however, provide a limited record of past and current streamflow. Modeled streamflow products with more complete spatial and temporal coverage (including the National Water Model [NWM]), have primarily focused on flooding, rather than sustained drought or low flow conditions. Objectives of this study are to (1) evaluate historical performance of the NWM streamflow estimates (particularly with respect to droughts and seasonal low flows) and (2) identify characteristics relevant to model inputs and suitability for future applications. Comparisons of retrospective flows from the NWM to observed flows from the United States Geological Survey stream gage network over 22 years in the CRB reveal a tendency for underestimating low flow frequency, locations with low flows, and the number of years with low flows. We found model performance to be more accurate for the Upper CRB and at sites with higher precipitation, snow percent, baseflow index, and elevations. Underestimation of low flows and variable model performance has important implications for future applications: inaccurate evaluations of historical low flows and droughts, and less reliable performance outside of specific watershed/stream conditions. This highlights characteristics on which to focus future model development efforts.

The widespread increase in global temperature is driving more frequent and more severe local heatwaves within the contiguous United States (CONUS). General circulation models (GCMs) show increasing, but spatially uneven trends in heatwave properties. However, the wide range of model outputs raises the question of the suitability of this method for indicating the future impacts of heatwaves on human health and well-being. This work examines the fitness of 32 models from CMIP5 and their ensemble median to predict a set of heatwave descriptors across the CONUS, by analyzing their capabilities in the simulation of historical heatwaves during 1950–2005. Then, we use a multi-criteria decision-making tool and rank the overall performance of each model for 10 locations with different climates. We found GCMs have different capabilities in the simulation of historical heatwave characteristics. In addition, we observed similar performances for GCMs over the areas with a partially similar climate. The ensemble model showed better performance in simulation of historical heatwave intensity in some locations, while other individual GCMs represented heatwave time-related components more similar to observations. These results are a step towards the use of contemporary weather models to guide heatwave impact predictions.

Global population is experiencing more frequent, longer, and more severe heat waves due to global warming and urbanization. Episodic heat waves increase mortality and morbidity rates and demands for water and energy. Urban managers typically assess heat wave risk based on heat wave hazard, population exposure, and vulnerability, with a general assumption of spatial uniformity of heat wave hazard. We present a novel analysis that demonstrates an approach to determine the spatial distribution of a set of heat wave properties and hazard. The analysis is based on the Livneh dataset at a 1/16-degree resolution from 1950 to 2009 in Maricopa County, Arizona, USA. We then focused on neighborhoods with the most frequent, severe, earlier, and extended periods of heat wave occurrences. On average, the first heat wave occurs 40 days earlier in the eastern part of the county; the northeast part of this region experiences 12 days further extreme hot days and 30 days longer heat wave season than other regions of the area. Then, we applied a multi-criteria decision-making (MCDM) tool (TOPSIS) to evaluate the total hazard posed by heat wave components. We found that the northern and central parts of the metropolitan area are subject to the greatest heat wave hazard and that individual heat wave hazard components did not necessarily indicate heat hazard. This approach is intended to support local government planning for heat wave adaptation and mitigation strategies, where cooling centers, heat emergency water distribution networks, and electrical energy delivery can be targeted based on current and projected local heat wave characteristics.