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Climate change is escalating the threat of heat stress to global public health, with the majority of humans today facing increasingly severe and prolonged heat waves. Accurate weather data reflecting the complexity of measuring heat stress is crucial for reducing the impact of extreme heat on health worldwide. Previous studies have employed Heat Index (HI) and Wet Bulb Globe Temperature (WBGT) metrics to understand extreme heat exposure, forming the basis for heat stress guidelines. However, systematic comparisons of meteorological and climate data sets used for these metrics and the related parameters, like air temperature, humidity, wind speed, and solar radiation crucial for human thermoregulation, are lacking. We compared three heat measures (HImax, WBGTBernard, and WBGTLiljegren) approximated from gridded weather data sets (ERA5‐Land, PRISM, Daymet) with ground‐based data, revealing strong agreement from HI and WBGTBernard (R2 0.76–0.95, RMSE 1.69–6.64°C). Discrepancies varied by Köppen‐Geiger climates (e.g., Adjusted R2 HImax 0.88–0.95, WBGTBernard 0.79–0.97, and WBGTLiljegren 0.80–0.96), and metrological input variables (Adjusted R2Tmax 0.86–0.94, Tmin 0.91–0.94, Wind 0.33, Solarmax 0.38, Solaravg 0.38, relative humidity 0.51–0.74). Gridded data sets can offer reliable heat exposure assessment, but further research and local networks are vital to reduce measurement errors to fully enhance our understanding of how heat stress measures link to health outcomes. Plain Language Summary: Extreme heat threatens human health. Rising intensity and duration of heat days expose more to hot environments. To understand how extreme heat affects human health, it is important to use accurate weather information and measures that reflect people's actual experience of the heat. Heat Index (HI) and Wet Bulb Globe Temperature (WBGT) are commonly used heat stress metrics that are widely used to set exposure guidelines and policies. However, there have been limited comparisons between daily heat measures and weather variables. In this study, we compared three heat measures (HI, WBGTBernard, and WBGTLiljegren) derived from three widely used gridded weather data sets (ERA5‐Land, PRISM, and Daymet) with ground‐based weather observations. The heat measures calculated from both the gridded weather data and the station data showed a reasonably strong agreement. However, the differences varied depending on the climate types. Gridded weather data sets can provide a reliable approach to assessing heat exposure and impacts based on meteorological variables to produce heat measures. However, further research and the establishment of local ground station networks are necessary to reduce measurement errors in exposure and improve accuracy. This will help us better understand the relationship between heat measures and their impact on health outcomes. Key Points: Compared heat stress measures using gridded data sets and in situ data from 17 institutions across 42 states in the contiguous USObserved variations in heat measures and weather variables align with Köppen‐Geiger climate classificationsInstalling more Wet Bulb Globe Temperature‐measuring stations in diverse microclimates is key to better heat exposure prevention strategies [ABSTRACT FROM AUTHOR]

Vapor pressure deficit (VPD) is the difference between saturation and actual water vapor pressures and is driven by interactions between air temperature and humidity. Globally, VPD observations indicate drying of the atmosphere, while air temperature (T) and relative humidity (RH) have changed asymmetrically during daytime versus nighttime. However, whether daytime or nighttime T (Tday and Tnight, respectively) and RH (RHday and RHnight, respectively) have been more important to VPD change is unknown, and so is the seasonal variation of this importance. This research determines the relative contribution of Tday, Tnight, RHday, and RHnight to VPD change observed during 1981–2021 across the conterminous United States. Tday contributed 41% to driving a VPD increase of 2.1 standard deviations (SD), followed by contributions of 25%, 22%, and 12% from RHday, RHnight, and Tnight, respectively. Regions with significant VPD increase have seen increase in Tday (by 1 SD) and Tnight (by 0.9 SD) and a decrease in RHday (by 1 SD) and RHnight (by 3.4 SD). Diurnal asymmetry in warming and drying trends was true for most months, with greater rates of change during the nighttime than daytime. Tday was the dominant driver of the annual mean VPD rise for 70% of the counties, followed by RHday (18%), RHnight (11%), and Tnight (1%). We conclude that warming and drying during the days and nights together explain increased VPD across the US croplands and that climate stressors during days and nights should be viewed independently due to their crop‐specific impacts that vary spatially and seasonally. Core Ideas: Vapor pressure deficit (VPD) has increased by 2.1 standard deviations during 1981–2021 in conterminous United States.Daytime or daily maximum air temperature (Tday), daytime or daily minimum relative humidity (RHday), nighttime or daily maximum relative humidity (RHnight), and nighttime or daily minimum air temperature contributed 41%, 25%, 22%, and 12% to annual mean VPD trend.Strong asymmetric warming and drying, that is, greater trends during daytime than nighttime.Relative contribution of drivers toward VPD trends changed substantially during the year.VPD rise during July and August was attributed equally to Tday, RHday, and RHnight. [ABSTRACT FROM AUTHOR]

Amid reports from western US wildland fire managers that, compared to when many started their careers, fires are burning longer throughout the day before reducing in intensity overnight, we examined decadal changes in nighttime vapor pressure deficits over the western United States with a focus on the summer fire season. We calculated changes using a recently updated observation‐assimilating reanalysis (ERA5) available at hourly resolution over the 1980–2019 period. Analysis identifies the proximate cause (atmospheric temperature vs. moisture content) of the observed changes and the extent to which they have been captured in climate model simulations. Increases in nighttime vapor pressure deficits of >50% in 40 years are evident over foothills of mountains ranges adjacent to arid plateaus. The largest observed increases greatly exceed the forced climate‐model response. Correlation analysis reveals a broad link between the variability of western US summer‐nighttime vapor pressure deficit and the Pacific Decadal Oscillation. Plain Language Summary: Western US wildland fire managers have reported that fires are burning longer into the night and increasing in intensity earlier in the morning compared to when many started their careers. Increasing nighttime vapor pressure deficit—a measure of the drying power of air—is widely suspected to be responsible for these perceived changes in fire behavior. It is also suspected that human‐caused increases in nighttime temperatures are responsible. We used a recently released observation‐based data set to quantify the extent to which nighttime vapor pressure deficits have changed over the last 40 years and determine the proximate cause for the observed changes (particularly whether temperature effects on their own can explain them). We also explored how well the observed changes are captured in climate model simulations. Results highlight large increases in nighttime vapor pressure deficit over the foothills of mountain ranges next to arid plateaus, where the observation‐based increases greatly exceed the climate model projections, and both temperature and humidity play a role in driving the observed changes. Key Points: Nighttime vapor pressure deficit increased >50% in 40 years over the foothills of the Sierra Nevada and Rocky MountainsSaturation vapor pressure increases caused by rising temperatures and decreases in actual vapor pressure account for these changesThe magnitudes of the changes in the observation‐based records greatly exceed those projected by climate forecast models [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) play a crucial role in the hydroclimate of the U.S. west coast. While the impact of large‐scale sea surface temperature (SST) patterns on ARs is well recognized, the specific roles of local SST on ARs have not been systematically investigated. This study analyzed the landfalling ARs from two regional climate simulations that differ only in the local SST. With local SST warming, AR frequency increases across the U.S. west coast, with comparable contributions from the spatial expansion of ARs and emergence of new ARs. AR landfalling area, inland intrusion distance, and intensity also increase, with landfalling area showing the largest sensitivity. Although local SST warming only increases the AR moisture by ∼0.4%/K, AR‐related precipitation increases by 3%/K, demonstrating the important impact of local SST warming on intensifying storms. Hence, local SST is important for accurate depiction of ARs and their precipitation in the western United States. Plain Language Summary: Atmospheric rivers (ARs) have important effects on extreme precipitation and flooding in the U.S. west coast. Local sea surface temperature (SST) may intensify ARs and their impacts by changing atmospheric temperature and moisture. This study compares two regional climate simulations of the western United States that differ only in the local SST. Analysis shows that local SST warming increases the frequency of ARs across the U.S. west coast as ARs expand to cover larger areas and more ARs emerge with increasing moisture. AR landfalling area, inland intrusion distance, and intensity also increase. Although local SST warming only increases AR moisture by 0.4%/K, extreme precipitation associated with ARs increases by a much larger rate of 3%/K as SST warming intensifies storms. Hence, local SST has important effects on ARs and extreme precipitation in the western United States. Key Points: Local SST warming increases AR frequencies across the U.S. west coast by expanding AR spatial coverage and increasing AR occurrencesAR landfalling area, inland intrusion distance, and intensity all increase with local SST warming, and landfalling area increases the mostAlthough AR moisture increases only by 0.4%/K of local SST warming, extreme precipitation increases by 3%/K in the west coast [ABSTRACT FROM AUTHOR]

ABSTRACT Isobaric equivalent temperature ( TE) is the temperature that an air parcel would have if all associated water vapour were condensed and the resulting latent heat used to increase the temperature of the parcel. It is therefore an ideal metric for assessing changes in (1) total near-surface heat content associated with both temperature and moisture content and (2) the joint behaviour of temperature and humidity, which is relevant to both lower atmospheric stability and human heat stress during extreme temperature events. We present results from an analysis of 50 years (1961-2010) of daily TE and its temperature and moisture components at seven stations in the central United States. The annual means of daily TEmax and TEmin increased at all stations during the period of analysis with the largest changes occurring in TEmin, largely as a result of increasing minimum air temperature. At western locations significant increases in the annual mean TEmax were also observed, resulting from a combination of increases in Tmax and humidity. Despite small summer ( JJA) trends in maximum air temperature, summer TE trends were generally larger than their annual counterparts. The timing of the observed variations and the resulting spatial pattern are consistent with observed changes in meridional moisture flux associated with the Great Plains low-level jet. Heat waves in the region were found to be characterized by increasing TEmin, primarily resulting from increases in minimum air temperature. At western stations, heat waves were also characterized by increasing TEmax as a result of positive trends in humidity. In most cases, equivalent temperature provides a perspective on local environmental change that differs from what is provided by consideration of temperature alone. [ABSTRACT FROM AUTHOR]

Microclimatic data are required for many problems in pure and applied ecology. This data includes aboveground convective and radiative conditions as well as soil temperature and moisture. In cold regions, the connection between above‐ and belowground microclimates via snow cover is also critically important. Here I describe a data set of hourly microclimates for the continental United States, simulated from the years 1979 to 2017 across a grid of 2,287 locations approximately 60 km apart. The data were generated with the NicheMapR microclimate model, driven by 0.04° gridded daily meteorological forcing data (air temperature, wind speed, humidity, solar radiation, air pressure, and rainfall). The aboveground microclimate variables include horizontal plane solar radiation, solar zenith angle, sky temperature (from which downwelling longwave radiation can be computed), air temperature, relative humidity, and wind speed at 1 and 200 cm height, and snow depth. The belowground variables include soil temperature, pore humidity, soil moisture, and soil water potential for 0, 2.5, 5, 10, 15, 20, 30, 50, 100, and 200 cm belowground. The computations are for four shade levels (0%, 50%, 75%, and 90%). The predictions are validated against detailed soil temperature, soil moisture, and snow observations and show enhanced performance over existing microclimatic data for the United States. The data set can be used for a wide variety of applications, including the computation of heat and water budgets of organisms, the potential for vegetation growth, and the computation of stress and growth indices. The use of daily forcing data also allows assessments of the consequences of extreme events including heat waves and drought. Example applications are provided for computing plant growth potential, lizard egg development and body temperature, and mammalian energy and water requirements. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper. [ABSTRACT FROM AUTHOR]