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Objective: To synthesize the methodologies of studies that evaluate the impacts of heat exposure on morbidity and mortality. Methods: Embase, MEDLINE, Web of Science, and Scopus were searched from date of inception until 1 March 2023 for English language literature on heat exposure and health outcomes. Records were collated, deduplicated and screened, and full texts were reviewed for inclusion and data abstraction. Eligibility for inclusion was determined as any article with climate‐related heat exposure and an associated morbidity/mortality outcome. Results: Of 13,136 records initially identified, 237 articles were selected for analysis. The scope of research represented 43 countries, with most studies conducted in China (62), the USA (44), and Australia (16). Across all studies, there were 141 unique climate data sources, no standard threshold for extreme heat, and 200 unique health outcome data sources. The distributed lag non‐linear model (DLNM) was the most common analytic method (48.1% of studies) and had high usage rates in China (68.9%) and the USA (31.8%); Australia frequently used conditional logistic regression (50%). Conditional logistic regression was most prevalent in case‐control studies (5 of 8 studies, 62.5%) and in case‐crossover studies (29 of 70, 41.4%). DLNMs were most common in time series studies (64 of 111, 57.7%) and ecological studies (13 of 20, 65.0%). Conclusions: This review underscores the heterogeneity of methods in heat impact studies across diverse settings and provides a resource for future researchers. Underrepresentation of certain countries, health outcomes, and limited data access were identified as potential barriers. Plain Language Summary: Climate change and global warming are major threats to public health, leading to increased illness and death worldwide due to rising temperatures. Heatwaves are becoming more frequent and severe, causing various health problems, particularly affecting low‐income and minority communities. Studying the link between heat and health requires diverse methods due to regional differences. Different study designs and analytical techniques have been used, but there is no consensus on the best approach. Factors like heat severity, duration, air quality, and humidity must be considered. However, defining extreme heat and determining the best metric for heat exposure remain debated. With climate change worsening, understanding previous research on heat‐related health impacts is crucial for future policies and adaptation strategies. This scoping review aims to address gaps in knowledge by examining the range of epidemiological approaches used to study the effects of extreme heat on health outcomes. Key Points: Distributed lag non‐linear models were widely used across various health outcomes and study designs, especially in time series studiesThere were disparities in research focus across different regions with regions like Africa and Oceania being underrepresentedAccess to public health data and standardized definitions for extreme heat remain significant challenges in heat impact studies [ABSTRACT FROM AUTHOR]

Characterizing changes in precipitation patterns over time is critical for hydrologically dependent fields like water resource management and agriculture. Here, we explore observed trends in interannual precipitation variability using a suite of metrics that describe changes in precipitation over time. We analyze daily in situ Global Historical Climatology Network precipitation data from 1970 to present over 17 internally consistent sub‐national United States domains using a regional Mann‐Kendall trend test. We find robustly increasing trends in annual mean precipitation and wet day frequency for most of the central and eastern U.S., but decreasing trends in the western U.S. Importantly, we identify widespread significant trends in interannual precipitation variability, with increasing variability in the southeast, decreasing variability in the far west, and mixed signals in the Rocky Mountains and north‐central U.S. Our results provide important context for water resource managers and a new observational standard for climate model performance assessments. Plain Language Summary: While many studies have examined how annual precipitation totals and precipitation frequency have changed, few examine the variability, or consistency, of year‐over‐year precipitation. We test for these trends in daily observations across 17 regions within the United States. We find changes in yearly precipitation variability for most regions, though results in the central U.S. are mixed. We also identify rising average annual precipitation and precipitation frequency for the central and eastern U.S. and falling average annual precipitation and frequency for the western U.S. Our results are important for agriculture and water resource management and can be compared against historical climate model simulations to determine how well they reproduce observations. Key Points: We find widespread robust changes in two measures of interannual precipitation variability across the United StatesWe detect increases (decreases) in annual mean precipitation and wet day frequency across the eastern (western) United StatesWe explore the interaction of changes in precipitation frequency and wet day precipitation intensity on interannual variability [ABSTRACT FROM AUTHOR]