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Warm temperature exposure during winter has reportedly resulted in the apparent negation of chilling in several fruit species. This study was conducted to investigate the floral and vegetative response of two pistillate kiwifruit cultivars to intermittent warm temperature interruption during chilling accumulation. Dormant 1-year-old canes of Actinidia chinensis ‘AU Golden Dragon’ and Actinidia deliciosa ‘AU Fitzgerald’ were collected in December 2018 and 2019 (334 and 360 chilling units, respectively), shortly after leaf abscission. Canes were cut to 10 nodes after removing the first six basal nodes, placed in jars filled with distilled water, and transferred to respective chilling treatments. Treatments included continuous chilling (CC) (in addition to base chilling) at 1-week (168 chilling units) increments (0–5 weeks) and chilling exposure at the same increments with intermittent warm temperature (WT). For the WT treatments, each week of chilling was followed by 3 days of exposure to warm conditions. Chilling and warm temperature exposure were simulated by 7/4°C and 25/17.2 °C (day/night) air temperatures, respectively, using separate climate-controlled growth chambers. After treatments, canes were forced in a third chamber at 21.1 to 25.0°C with light-emitting diode lighting. Vegetative budbreak, floral bud number (from here on defined as floral response), and floral development stage were recorded for each cane at 2-day intervals. For ‘AU Golden Dragon’, WT did not result in any reduced floral response at any of the observed chilling levels. However, lower mean floral response was observed with WT, as compared with CC for ‘AU Fitzgerald’ at 5 weeks of chilling over the 2 years (P = 0.05). WT also lessened the effect of apical dominance with respect to vegetative/floral response to node position for both cultivars. Chilling type had no significant effect on vegetative response in either cultivar. Estimated chilling requirements (CC) in this experiment were similar to those reported previously for these cultivars. Results suggest that A. chinensis cultivars may respond more favorably than A. deliciosa to the erratic winter temperature patterns experienced in the southeastern United States. [ABSTRACT FROM AUTHOR]

The surface and air temperature gradient (TS00 − Tair) drives the development of the convective boundary layer and the occurrence of clouds and precipitation. However, its variability is still poorly understood due to the lack of high-quality observations. This study fills in this gap by investigating the diurnal to decadal variability in TS00 − Tair from 2002 to 2022 based on hourly observations collected at over 100 stations of the U.S. Climate Reference Network. It is found that TS00 − Tair reaches its maximum at noon with an average of 6.85°C over the contiguous United States, which decreases to 4.28°C when the soil moisture exceeds 30%. The daily minimum of TS00 − Tair has an average of −2.08°C, which generally occurs in the early evening but is postponed as the cloud fraction decreases. Moreover, while existing studies have used the near-surface soil temperature, such as the 5-cm soil temperature (TS05), to calculate TS05 − Tair, we find that TS00 − Tair and TS05 − Tair have opposite diurnal cycles, and their amplitudes differed drastically. The daily minimum of TS00 − Tair has a significant decreasing trend (−0.50° ± 0.007°C decade−1) from 2002 to 2022 due to Tair increasing at a higher rate than TS00 during the nighttime. The occurrence frequency of near-surface stable conditions (TS00 − Tair < 0) increases significantly, and the frequency of unstable conditions (TS00 − Tair > 0) decreases notably throughout the year except for winter. When it is stable, the magnitude of TS00 − Tair tends to decrease while the TS00 − Tair tends to increase when it is unstable, which is consistent with the drying condition caused by the precipitation deficit. This study provides the first observational evidence on how TS00 − Tair responds to warming. Significance Statement: The impact of global warming on surface-air temperature gradients is a crucial scientific issue that needs to be addressed. These gradients determine changes in cloud and precipitation, affecting water resources. However, traditional surface temperature measurements from weather stations are of high uncertainty due to direct exposure to the insolation. Satellite retrieval of surface temperature is limited by the availability of clear sky conditions, with low accuracy for temperature gradient calculations. Despite their importance, high-accuracy data of land surface temperature are still lacking. To address this issue, the U.S. Climate Reference Network (USCRN) uses infrared radiometers to continuously monitor surface temperature with high accuracy and sampling frequency. This study reports on surface-air temperature gradients at more than 100 U.S. stations, providing insight into diurnal to decadal variability over the contiguous United States. The study also highlights the significant difference between the land surface temperature–air temperature gradient and soil temperature–air temperature gradient. [ABSTRACT FROM AUTHOR]

Many cold water‐dependent aquatic organisms are experiencing habitat and population declines from increasing water temperatures. Identifying mechanisms which drive local and regional stream thermal regimes facilitates restoration at ecologically relevant scales. Stream temperatures vary spatially and temporally both within and among river basins. We developed a modeling process to identify statistical relationships between drivers of stream temperature and covariates representing landscape, climate, and management‐related processes. The modeling process was tested in three study areas of the Pacific Northwest United States during the growing season (May [start], August [warmest], September [end]). Across all months and study systems, covariates with the highest relative importance represented the physical landscape (elevation [1st], catchment area [3rd], main channel slope [5th]) and climate covariates (mean monthly air temperature [2nd] and discharge [4th]). Two management covariates (groundwater use [6th] and riparian shade [7th]) also had high relative importance. Across the growing season (for all basins), local reach slope had high relative importance in May, but transitioned to a regional main channel slope covariate in August and September. This modeling process identified regionally similar and locally unique relationships among drivers of stream temperature. High relative importance of management‐related covariates suggested potential restoration actions for each system. [ABSTRACT FROM AUTHOR]

This study investigates the performance of the latter NCEP Unified Forecast System (UFS) Coupled Model prototype simulations (P5–P8) during boreal summer 2011–17 in regard to coupled land–atmosphere processes and their effect on model bias. Major land physics updates were implemented during the course of model development. Namely, the Noah land surface model was replaced with Noah-MP and the global vegetation dataset was updated starting with P7. These changes occurred along with many other UFS improvements. This study investigates UFS's ability to simulate observed surface conditions in 35-day predictions based on the fidelity of model land surface processes. Several land surface states and fluxes are evaluated against flux tower observations across the globe, and segmented coupling processes are also diagnosed using process-based multivariate metrics. Near-surface meteorological variables generally improve, especially surface air temperature, and the land–atmosphere coupling metrics better represent the observed covariance between surface soil moisture and surface fluxes of moisture and radiation. Moreover, this study finds that temperature biases over the contiguous United States are connected to the model's ability to simulate the different balances of coupled processes between water-limited and energy-limited regions. Sensitivity to land initial conditions is also implicated as a source of forecast error. Above all, this study presents a blueprint for the validation of coupled land–atmosphere behavior in forecast models, which is a crucial model development task to assure forecast fidelity from day one through subseasonal time scales. [ABSTRACT FROM AUTHOR]

Prior research evaluating snowfall conditions and temporal trends in the United States often acknowledges the role of various synoptic-scale weather systems in governing snowfall variability. While synoptic classifications have been performed in other regions of North America in applications to snowfall, there remains a need for enhanced understanding of the atmospheric mechanisms of snowfall in the central United States. Here we conduct a novel synoptic climatological investigation of the weather systems responsible for snowfall in the central United States from 1948 to 2021 focused on their identification and the quantification of associated snowfall totals and events. Ten unique synoptic weather types (SWTs) were identified, each resulting in distinct regions of enhanced snowfall across the study domain aligning with regions of sufficiently cold air temperatures and forcing mechanisms. While a substantial proportion of seasonal snowfall is attributed to SWTs associated with surface troughs and/or midlatitude cyclones, in portions of the southeastern and western study domain, as much as 70% of seasonal snowfall occurs during systems with high pressure centers as the domain's synoptic-scale forcing. Easterly flow, potentially resulting in topographic uplift from high pressure to east of the domain, was associated with between 15% and 25%of seasonal snowfall in Nebraska and South Dakota. On average, 64.8% of the SWT occurrences resulted in snowfall within the study region, ranging between 40.1%and 93.5%by SWT. Synoptic climatological investigations provide valuable insights into the unique weather systems that generate hydroclimatic variability. SIGNIFICANCE STATEMENT: By evaluating the weather patterns that are responsible for snowfall in the central United States, key insights can be gained into how and why snowfall varies and potentially changes over space and time. Using an approach that categorizes weather patterns based on their similarities, here 10 unique snowfall-producing weather patterns are identified and analyzed from 1948 to 2021. Each pattern resulted in different snowfall amounts across the central United States, varying substantially spatially and within the calendar year. Approximately 65% of the time that these weather patterns occur, snowfall is observed in the region. The majority of snowfall-producing weather patterns are associated with low pressure systems, but in some regions up to 70% of snowfall is associated with instances of high pressure in which winds can cause upward motions associated with topography. [ABSTRACT FROM AUTHOR]

This paper investigates the sensitivity of golfers' performance to meteorological conditions at the men's US Masters tournament over the 40-year period 1980–2019. The mean and standard deviation of round scores are related to local temperature, humidity, wind speed and direction, and concurrent and antecedent precipitation. Mean scores are more dependent on weather conditions than the variability of scores in a given round. The best predictor of mean scores is the wet-bulb temperature in rounds one and two, and the zonal wind speed in rounds three and four. Across both sets of rounds (1 and 2, and 3 and 4), the wet-bulb temperature is a better predictor of mean scores than the air temperature, which implies that atmospheric moisture content affects scores. In general, golfers take fewer shots and so perform better in warmer and calmer conditions. The synergestic effect of several weather variables explains over 44% of the variance in mean scores. Mean meteorological conditions during play are a much better predictor of the players' average performance than the standard deviation of the weather variables. The golfers' performance becomes more variable in cooler conditions with a wider range of scores. Precipitation during play and the dampness of the ground (as quantified by rainfall up to ten days before play) do not have a consistent and statistically significant effect on the competitors' performance. In short, this paper demonstrates that golf scores are dependent on weather conditions. [ABSTRACT FROM AUTHOR]

Summary: Drylands of the southwestern United States are rapidly warming, and rainfall is becoming less frequent and more intense, with major yet poorly understood implications for ecosystem structure and function. Thermography‐based estimates of plant temperature can be integrated with air temperature to infer changes in plant physiology and response to climate change. However, very few studies have evaluated plant temperature dynamics at high spatiotemporal resolution in rainfall pulse‐driven dryland ecosystems.We address this gap by incorporating high‐frequency thermal imaging into a field‐based precipitation manipulation experiment in a semi‐arid grassland to investigate the impacts of rainfall temporal repackaging.All other factors held constant, we found that fewer/larger precipitation events led to cooler plant temperatures (1.4°C) compared to that of many/smaller precipitation events. Perennials, in particular, were 2.5°C cooler than annuals under the fewest/largest treatment.We show these patterns were driven by: increased and consistent soil moisture availability in the deeper soil layers in the fewest/largest treatment; and deeper roots of perennials providing access to deeper plant available water. Our findings highlight the potential for high spatiotemporal resolution thermography to quantify the differential sensitivity of plant functional groups to soil water availability. Detecting these sensitivities is vital to understanding the ecohydrological implications of hydroclimate change. [ABSTRACT FROM AUTHOR]

Extreme climate events are societally harmful and have increased in frequency and intensity in recent decades. Indices based on temperature and precipitation are a valuable way to quantify climate extremes. Certain indices are defined relative to percentiles, which are dependent on a climatological baseline period. In this study, indices computed using temperature and precipitation from the Modern Era Retrospective Analysis for Research and Applications, Version 2 are calculated using percentiles from three baseline periods: 1981–2010, 1991–2020 and 1981–2020. Updating the baseline period from 1981 to 2010 to 1991–2020 leads to significant changes in the quantification of temperature and precipitation extremes over the United States over 1980–2021. Using the later baseline period indicates more cold extremes, fewer warm extremes, and fewer but more intense precipitation extremes throughout the US, with regional variation. Changing the baseline period can mislead the public and decision makers, potentially undermining the appropriate response to climate‐related health risks. Plain Language Summary: Indices computed using 2‐m air temperature and precipitation are used to represent extreme climate events such as heat waves, cold waves, heavy precipitation, and drought. Some indices are defined relative to percentile‐based thresholds, which are computed using a baseline climatology period. The baseline climatology is typically a thirty‐year period and is updated every ten years. This study examines how updating the baseline climatology period from 1981–2010 to 1991–2020 affects the quantification of climate extremes in the United States over 1980–2021. In general, since the 1991–2020 period is warmer than 1981–2010 throughout the United States, there are fewer warm extremes detected and more cold extremes detected when it is used as the baseline. The differences are most notable in the southwest and northeast United States. The changes in the precipitation indices vary throughout the country, but in certain parts of the southern and central United States, updating the baseline period leads to the detection of fewer but heavier extreme precipitation events. It is important to communicate the choice of baseline climatology period to prevent misinterpretation of the extreme climate indices and the comparison of different studies. Key Points: Updating the baseline period from 1981–2010 to 1991–2020 leads to significant changes in percentile‐based extreme climate indices in the USTemperature indices show generally increased cold extremes and decreased warm extremes across the US when the baseline period is updatedFor precipitation indices, the later baseline period indicates fewer but more intense extreme events in the south and central US [ABSTRACT FROM AUTHOR]

Taxon–environment relationships can elucidate a taxon's tolerance or sensitivity to specific environmental conditions. We use a joint species distribution modeling framework to quantify relationships between ∼1700 benthic macroinvertebrate assemblages in streams and rivers across the contiguous United States and several environmental gradients that are susceptible to human alteration (e.g., nutrients, salinity, physical habitat, and climate). We found that the predicted occurrence probability for sampling units where a taxon actually occurs was 0.15 to 0.24 greater than the predicted occurrence probability for sampling units where a taxon does not occur, and a relatively large percentage (32–58%) responded to gradients of substrate diameter, mean summer air temperature, or total P. At the assemblage level, genus richness could change along environmental gradients by as many as 5 to 17 taxa depending on the ecoregion. Often, the largest change in genus richness was associated with sediment diameter. We also investigated whether a suite of traits (i.e., clinger, scraper, pollution tolerance, and thermal optima) were related to a genus' association with an environmental gradient and found that some traits are positively related to an organism's occurrence along one environmental gradient but negatively related to its occurrence along another. For example, in several ecoregions, thermal preference was positively related to mean summer air temperature but negatively related to nutrient concentrations. Collectively, our results showcase a multivariate approach for modeling biotic assemblages that can integrate multiple sources of information (i.e., environmental factors, biological traits, phylogenetic relationships, and co-occurrences) that are routinely collected by biomonitoring programs. [ABSTRACT FROM AUTHOR]

The ability of high-resolution mesoscale models to simulate near-surface and subsurface meteorological processes is critical for representing land-atmosphere feedback processes. The High-Resolution Rapid Refresh (HRRR) model is a 3-km numerical weather prediction model that has been used operationally since 2014. In this study, we evaluated the HRRR over the contiguous United States from 1 January 2021 to 31 December 2021. We compared the 1-, 3-, 6-, 12-, 18-, 24-, 30-, and 48-h forecasts against observations of air and surface temperature, shortwave radiation, and soil temperature and moisture from the 114 stations of the U.S. Climate Reference Network (USCRN) and evaluated the HRRR's performance for different geographic regions and land cover types. We found that the HRRR well simulated air and surface temperatures, but underestimated soil temperatures when temperatures were subfreezing. The HRRR had the largest overestimates in shortwave radiation under cloudy skies, and there was a positive relationship between the shortwave radiation mean bias error (MBE) and air temperature MBE that was stronger in summer than winter. Additionally, the HRRR underestimated soil moisture when the values exceeded about 0.2 m³ m-3, but overestimated soil moisture when measurements were below this value. Consequently, the HRRR exhibited a positive soil moisture MBE over the drier areas of the western United States and a negative MBE over the eastern United States. Although caution is needed when applying conclusions regarding HRRR's biases to locations with subgrid-scale land cover variations, general knowledge of HRRR's biases will help guide improvements to land surface models used in high-resolution weather forecasting models. [ABSTRACT FROM AUTHOR]

Most climate models still suffer large warm and dry summer biases in the central United States (CUS). As a solution, we improved cumulus parameterization to represent 1) the lifting effect of small-scale rising motions associated with Great Plains low-level jets and midtropospheric perturbations by defining the cloud base at the level of condensation, 2) the constraint of the cumulus entrainment rate depending on the boundary layer depth, and 3) the temperature-dependent cloud-to-rainwater conversion rate. These improvements acted to (i) trigger mesoscale convective systems in unfavorable environmental conditions to enhance total rainfall amount, (ii) lower cloud base and increase cloud depth to increase low-level clouds and reduce surface shortwave radiation, (iii) suppress penetrative cumuli from shallow boundary layers to remedy the overestimation of precipitation frequency, and (iv) increase water detrainment to form sufficient cirrus clouds and balanced outgoing longwave radiation. Much of these effects were nonlocal and nonlinear, where more frequent but weaker convective rainfall led to stronger (and sometimes more frequent) large-scale precipitation remotely. Together, they produced consistently heavier precipitation and colder temperature with a realistic atmospheric energy balance, essentially eliminating the CUS warm and dry biases through robust physical mechanisms. [ABSTRACT FROM AUTHOR]

Evidence of the physical and economic impacts of climate change is a critical input to policy development and decision making. The potential magnitude of climate change damages, where, when, and to whom those damages may occur across the country, the types of impacts that will be most damaging, and the ability of adaptation to reduce potential risks are all important and interconnected. This study utilizes the reduced-complexity model, Framework for Evaluating Damages and Impacts (FrEDI), to rapidly assess economic and physical impacts of climate change in the contiguous United States (U.S.). Results from FrEDI show that net national damages increase overtime, with mean climate-driven damages estimated to reach $2.9 trillion USD (95% CI: $510 billion to $12 trillion) annually by 2090. Climate-driven damages are largest for the health category, with the majority of damages in this category from the valuation estimates of premature mortality attributable to climate-driven changes in extreme temperature and air quality (O3 and PM2.5). Results from FrEDI also show that climate-driven damages vary by geographical region, with the Southeast experiencing the largest annual damages per capita (mean: $9,300 per person annually, 95% CI: $1,800-$37,000 per person annually), whereas the smallest damages per capita are expected in the Southwest region (mean: $6,300 per person annually, 95% CI: $840-$27,000 per person annually). Climate change impacts may also broaden existing societal inequalities, with Black or African Americans disproportionately affected by additional premature mortality from changes in air quality. This work significantly advances our understanding of the impacts from climate change to the U.S., in what U.S. regions impacts are happening, what sectors are being impacted, and which population groups being impacted the most. [ABSTRACT FROM AUTHOR]

Streams and rivers are major sources of greenhouse gases (GHGs) to the atmosphere, as carbon and nitrogen are converted and outgassed during transport. Although our understanding of drivers of individual GHG fluxes has improved with numerous site‐specific studies and global‐scale compilations, our ability to parse out interrelated physical and biogeochemical drivers of gas concentrations is limited by a lack of consistently collected, temporally continuous samples of GHGs and their associated drivers. We present a first analysis of such a dataset collected by the National Ecological Observatory Network across 27 streams and rivers across ecoclimatic domains of the United States. Average concentrations of CO2 ranged from 36.9 ± 0.88 to 404 ± 33 μmol L−1, CH4 from 0.003 ± 0.0003 to 4.99 ± 0.72 μmol L−1, and N2O from 0.015 to 0.04 μmol L−1 and spanned ranges of previous global compilations. Both CO2 and CH4 were strongly affected by physical drivers including mean air temperature and stream slope, as well as by dissolved oxygen and total nitrogen concentrations. N2O was exclusively correlated with total nitrogen concentrations. Results suggested that potential for gas exchange dominated patterns in gas concentrations at the site level, but contributions of in‐stream aerobic and anaerobic metabolism, and groundwater also likely varied across sites. The highest gas concentrations as well as highest variability occurred in low‐gradient, warmer, and nonperennial systems. These results are a first step in providing unprecedented, continuous estimates of GHG flux constrained by temporally variable physical and biogeochemical drivers of GHG production. [ABSTRACT FROM AUTHOR]

Climate change is altering species' habitats, phenology, and behavior. Although sexual behaviors impact population persistence and fitness, climate change's effects on sexual signals are understudied. Climate change can directly alter temperature-dependent sexual signals, cause changes in body size or condition that affect signal production, or alter the selective landscape of sexual signals. We tested whether temperature-dependent mating calls of Mexican spadefoot toads (Spea multiplicata) had changed in concert with climate in the southwestern United States across 22 years. We document increasing air temperatures, decreasing rainfall, and changing seasonal patterns of temperature and rainfall in the spadefoots' habitat. Despite increasing air temperatures, spadefoots' ephemeral breeding ponds have been getting colder at most elevations, and male calls have been slowing as a result. However, temperature-standardized call characters have become faster, and male condition has increased, possibly due to changes in the selective environment. Thus, climate change might generate rapid, complex changes in sexual signals with important evolutionary consequences. [ABSTRACT FROM AUTHOR]

Surface air temperatures in the southeastern United States that did not change from the climatological mean from 1900 to 2000 have increased since the year 2000. Analyzed herein are factors modulating the surface air temperatures in the region for a 20-yr period (2000–19) using space- and surface-based observations, and output from a reanalysis model. The 20-yr period is segregated into two decades, 2000–09 and 2010–19, corresponding to different tropospheric chemical regimes. Changes in seasonal and decadal averages are examined. The later decade experienced higher average surface air temperatures with significant warming during summer and fall seasons. Decadal and seasonal averages of cloud properties, column water vapor, rain rates, and top-of-atmosphere outgoing longwave radiation did not exhibit statistically significant differences between the two decades. The region experienced strong warm and moist advection during the winter months and very weak advection during the summer months. The later decade exhibited higher low-level moisture advection during the winter months than the earlier decade with insignificant changes in the temperature advection between the two decades. The later decade had significantly lower aerosol dry and liquid water mass during all seasons, along with lower aerosol optical depth, higher single scattering albedo, and lower top-of-the-atmosphere outgoing shortwave radiation during cloud-free conditions in the summer season. Collectively, these results suggest that changes in the aerosol direct radiative forcing are responsible for warming during summer months that experience weak advection and highlight seasonal differences in the temperature controlling mechanisms in the region. [ABSTRACT FROM AUTHOR]

In this study, we investigate both the changes of tropical cyclone (TC) rainfall hazard in the United States under climate change and the relative importance of the factors that cause the changes. We find that under the SSP5 8.5 scenario, the 100‐year TC rainfall level can increase by up to 320% along the U.S. coastline by the end of this century. The influence of TC rainfall‐producing ability increase is more significant than the influence of TC frequency increase on the increase of the 100‐year TC rainfall level (up to 180% vs. 60% increase). Among the different physical drivers for the increase in storm rainfall‐producing ability, the increase of TC intensity is the leading factor, followed by changes in TC duration and atmospheric temperature. The projected increase of TC rainfall hazard is robust against the uncertainty in the TC frequency projection. Plain Language Summary: Rainfall associated with landfalling tropical cyclones (TC) can cause extreme flooding and landslides, which are hazardous for coastal and inland areas. We project that by the end of the 21st century, TC rainfall hazard in the United States will increase by as much as 320% compared to its current value. The increase in TC rainfall hazard can be caused by two factors: more TCs making impact and TCs becoming more capable of producing rainfall in the future. The increased ability for TCs to produce rainfall is linked to increased TC intensity and duration as well as a warmer and more humid atmosphere in the future. Though uncertainties exist in the projected trend of future TC landfall frequency, TC rainfall hazard is very likely to increase due to the significant increase in TC rainfall‐producing ability. Key Points: U.S. landfalling tropical cyclone (TC) rainfall hazard will increase in the future due to increased TC landfalling frequency and TC rainfall‐producing abilityStorm intensity change is the leading factor for TC rainfall‐producing ability to increaseThe projected increase of TC rainfall hazard is robust against the uncertainty in TC frequency projection [ABSTRACT FROM AUTHOR]

Using quarterly temperature and employment data between 1990 and 2021, this paper uncovers nuanced evidence on the impact of seasonal temperature within US counties: higher winter temperature increases private sector employment growth while higher summer temperature decreases it. The impacts of higher temperature in milder seasons, fall and spring, are statistically insignificant. Moreover, the negative impact of higher summer temperature persists while the positive impact of higher temperature in the winter is more short-lived. The negative effects of a hotter summer are pervasive and persistent in many sectors: most significantly in "Construction" and "Leisure and Hospitality" but also in "Trade, Transport, and Utilities" and "Financial Activities". In contrast, the positive effects of a warmer winter are less pervasive. The employment effect of a hotter summer has been more severe in recent decades. [ABSTRACT FROM AUTHOR]

In June of 2021 the Southwest United States experienced a record‐breaking heatwave. This heatwave came at a time when the region was in severe drought. As drought alters the surface energy budget in ways that affect lower atmosphere temperature and circulations, it is possible that the combined drought‐heat event was a cascading climate hazard, in which preexisting drought exacerbated the heatwave. We apply satellite observation and numerical experiments with the Weather Research and Forecasting (WRF) model to test for land‐atmosphere feedbacks during the heatwave consistent with drought influence. We find a modest positive drought‐heat effect, as WRF simulations that include the drought have marginally higher air temperatures than those that exclude the initial drought conditions, with more substantial effects in wetter, forested areas. Evidence of drought‐heat‐drought‐coupled feedbacks was similarly modest in our simulations, as accounting for drought preconditioning led to a small reduction in simulated precipitation in the region. Plain Language Summary: In June 2021 the Southwest United States was hit by a record‐breaking heatwave at the same time as a severe drought. In this study, we look into the response of both events effect on one another. The WRF computer model is designed to test the observed events besides the use of satellite images during the same time. We find a small positive response between the two events that was more considerable over wetter and green regions. We also find a decrease in rainfall over the study region as a response to the drought‐heatwave conditions. Key Points: The record‐setting 2021 US heatwave struck at a time when surface conditions were anomalously dry, bright, and barren due to droughtSatellite observations indicate that drought led to anomalous land‐atmosphere fluxesModel simulations also indicate a small but systematic positive feedback of drought on heat [ABSTRACT FROM AUTHOR]

I use data on 187 counties in the United States from 2001 to 2017 to examine local variation in the timing of the excess mortality hump, which is the period in adolescence and young adulthood when mortality rates spike in young men due to an increase in risk-taking behaviors believed to result from a surge of testosterone production and subsequent aggressive, impulsive behaviors. Using an ecological framework, I contend that certain features of the local environment will elevate testosterone production and stunt brain development, leading to behaviors that elevate the risk of death at younger ages. To explore this proposition, I assess the association between the age at the peak of the excess mortality hump in a county and local environmental conditions in that county. I find that the age at the peak of the excess mortality hump is younger in counties where the average annual temperature is high and in counties where air quality is poor. [ABSTRACT FROM AUTHOR]

Longleaf pine (Pinus palustris Mill.) forests are an important ecosystem in the southeastern United States, with high economic and ecological value. It is necessary to study the climate variation within its range in order to understand the effects of climate change on longleaf pine forests. In this study, past climate data at three sites within the longleaf pine range were used to detect climate variation. The results indicated no dramatic change in solar radiation at the three sites. There were high variations in annual air temperature at the three sites. The trend of annual air temperature change depended on the time scale and start/end time. The annual air temperature generally increased from the 1960s at three sites. However, from 1901 to 2020, the trend of increasing annual air temperature was not consistent. The annual precipitation and the standardized precipitation-evapotranspiration index were relatively stable, with variation at the three sites. The regimes of annual and monthly air temperature and precipitation were not shifted based on the analysis of multiscale entropy. The climate niche of longleaf pine forests based on long-term climate data was broader than previously found. These results may be helpful to understand the interactions of the atmosphere and growth of longleaf pine forest and develop relevant management strategies. [ABSTRACT FROM AUTHOR]

Surface meteorological analyses are an essential input (termed "forcing") for hydrologic modeling. This study investigated the sensitivity of different hydrologic model configurations to temporal variations of seven forcing variables (precipitation rate, air temperature, longwave radiation, specific humidity, shortwave radiation, wind speed, and air pressure). Specifically, the effects of temporally aggregating hourly forcings to hourly daily average forcings were examined. The analysis was based on 14 hydrological outputs from the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model for the 671 Catchment Attributes and Meteorology for Large-Sample Studies (CAMELS) basins across the contiguous United States (CONUS). Results demonstrated that the hydrologic model sensitivity to temporally aggregating the forcing inputs varies across model output variables and model locations. We used Latin hypercube sampling to sample model parameters from eight combinations of three influential model physics choices (three model decisions with two options for each decision, i.e., eight model configurations). Results showed that the choice of model physics can change the relative influence of forcing on model outputs and the forcing importance may not be dependent on the parameter space. This allows for model output sensitivity to forcing aggregation to be tested prior to parameter calibration. More generally, this work provides a comprehensive analysis of the dependence of modeled outcomes on input forcing behavior, providing insight into the regional variability of forcing variable dominance on modeled outputs across CONUS. [ABSTRACT FROM AUTHOR]

The Cross-track Infrared Sounder (CrIS) is a Michelson-type Fourier Transform Spectrometer. The CrIS flight module 2 instrument was launched into orbit on November 18, 2017, onboard the NOAA-20 satellite as part of the United States (US) Joint Polar Satellite System (JPSS). The CrIS instrument measures the top-of-atmosphere upwelling spectral radiance in the thermal infrared (IR) spectrum. These measurements provide critical information for medium-range weather forecasting, and the retrieval of atmospheric profiles of temperature, water vapor, and other trace gases. The instrument noise equivalent radiance differential (NEdN) estimates are used by the weather forecasting systems, the trace gas atmospheric retrieval algorithms, and for trending the health and stability of the instrument over time. The current operational NEdN estimate is calculated using instrument observations from the deep space (DS) view and the internal calibration target (ICT). Two alternative methodologies are described here based on the principal component analysis (PCA) of an ensemble of calibrated Earth scene (ES) spectra. The NEdN calculation methods show that the instrument meets the specifications with a margin for all 27 detectors with an exception of one midwave IR (MWIR) field-of-view (FOV) 9, which is borderline. The PCA analysis shows that warmer ES spectra have higher noise, known as scene shot, for the short-wave IR (SWIR) band. Using the PCA analysis, the NEdN for the long-wave IR FOV 5 is 30% higher than the NEdN calculated by the operational algorithm. Correlated noise is also found due to the effect of the instrument self-apodization correction. [ABSTRACT FROM AUTHOR]

Forecasts from NOAA's Global Forecast System (GFS) and the High‐Resolution Rapid Refresh (HRRR) weather models are matched to surface observations for the winter season of November 2019 to March 2020 at 210 airports across the United States. The 2‐m temperature errors, conditioned on observed weather conditions such as cloud cover amount and wind speed, are used to determine the nature of systematic model biases. We observe a strong diurnal cycle in 2‐m temperature errors in the GFS in conditions with ≤50% and ≤25% sky cover, with a 1°C warm bias at night and a 2°C cold bias during the day. The HRRR, which uses a different set of physical parameterizations, does not have a clear diurnal cycle in errors under the same conditions. These results highlight the utility of weather‐conditional comparisons across the diurnal cycle to diagnose sources of model weaknesses and to target model improvements. Plain Language Summary: We evaluate the output from weather forecast models compared to observations at 210 airports across the United States during the November 2019 to March 2020 winter season. We focus on near‐surface air temperature errors in the Global Forecast System (GFS) and High‐Resolution Rapid Refresh (HRRR) weather models for different times of day and subsets of observed weather conditions. The GFS is 1°C too warm at night and 2°C too cold during the day in conditions with ≤50% and ≤25% cloud cover. The daily high and low temperatures have smaller errors in the HRRR model, which has different algorithms than the GFS model. Model refinement and development efforts would benefit from a focus on accurate representation of the diurnal cycle of temperatures as this basic characteristic of weather can reveal strengths and weaknesses in the model physics. Key Points: National Oceanic and Atmospheric Administration (NOAA)'s global forecast system (GFS) model struggles to adequately represent the diurnal cycle of temperatures under observed conditions of ≤50% and 25% cloud coverNOAA's high‐resolution rapid refresh (HRRR) model uses a different physics suite and does not have a strong diurnal cycle of temperature errors under the same conditionsExamination of errors using similar weather conditions helps to constrain the portion of model physics that can yield larger forecast errors [ABSTRACT FROM AUTHOR]

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state. Significance Statement: Not all forecasts are created equal. Even before a given forecast is produced, the nature of its initial conditions may indicate that it will prove more accurate than corresponding forecasts started at other times. We address here how the character of the soil moisture at the beginning of a forecast may provide such information. We find that under certain conditions, when the initial state of the soil is wet, the bias in the forecast is reduced and, to a lesser extent, the random error in the forecast is also reduced. Knowing ahead of time when to put more trust into a forecast should be of substantial benefit to forecast end-users. [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]

Epidemiological studies have yielded conflicting results regarding climate and incident SARS-CoV-2 infection, and seasonality of infection rates is debated. Moreover, few studies have focused on COVD-19 deaths. We studied the association of average ambient temperature with subsequent COVID-19 mortality in the OECD countries and the individual United States (US), while accounting for other important meteorological and non-meteorological co-variates. The exposure of interest was average temperature and other weather conditions, measured at 25 days prior and 25 days after the first reported COVID-19 death was collected in the OECD countries and US states. The outcome of interest was cumulative COVID-19 mortality, assessed for each region at 25, 30, 35, and 40 days after the first reported death. Analyses were performed with negative binomial regression and adjusted for other weather conditions, particulate matter, sociodemographic factors, smoking, obesity, ICU beds, and social distancing. A 1 °C increase in ambient temperature was associated with 6% lower COVID-19 mortality at 30 days following the first reported death (multivariate-adjusted mortality rate ratio: 0.94, 95% CI 0.90, 0.99, p = 0.016). The results were robust for COVID-19 mortality at 25, 35 and 40 days after the first death, as well as other sensitivity analyses. The results provide consistent evidence across various models of an inverse association between higher average temperatures and subsequent COVID-19 mortality rates after accounting for other meteorological variables and predictors of SARS-CoV-2 infection or death. This suggests potentially decreased viral transmission in warmer regions and during the summer season. [ABSTRACT FROM AUTHOR]

Increased heat-wave frequency across the United States has led to the need for improved predictability of heat-wave events. A detailed understanding of land–atmosphere interactions and the relationship between soil moisture and temperature extremes could provide useful information for prediction. This study identifies, for many locations, a threshold of soil moisture below which there is an increase in the sensitivity of atmospheric temperature to declining soil moisture. This shift to a hypersensitive regime causes the atmosphere to be more susceptible to atmospherically driven heat-wave conditions. The soil moisture breakpoint where the regime shift occurs is estimated using segmented regression applied to observations and reanalysis data. It is shown that as the soil gets drier, there is a concomitant change in the rate of decrease in latent heat flux and increase in sensible heat flux leading to a strong positive feedback of increased air temperature near the surface, which further dries out the soil. Central, southwestern, and southeastern parts of the United States seem to have regions of clear regime shifts, while the eastern part of the United States generally does not get dry enough to reveal significant breakpoints. Sensible heat flux is seen to be a primary driver of this increased temperature sensitivity aided by the drop in latent heat flux. An investigation of flux tower sites verifies the breakpoint–flux relationships found in reanalysis data. Accurate estimation of these breakpoints can contribute to improved heat-wave prediction. [ABSTRACT FROM AUTHOR]

Climate change is causing rapid warming and altered precipitation patterns in mountain watersheds, both of which influence the timing of ice breakup in mountain lakes. To enable predictions of ice breakup in the future, we analyzed a dataset of mountain lake ice breakup dates derived from remote sensing and historical downscaled climate data. We evaluated drivers of ice breakup, constructed a predictive statistical model, and developed projections of mountain lake ice breakup date with global climate models. Using Random Forest analysis, we determined that winter and spring cumulative snow fraction (portion of precipitation falling as snow) and air temperature are the strongest predictors of ice breakup on mountain lakes. Interactions between precipitation, cumulative winter air temperature and lake surface area indicate that shifts in air temperature and precipitation affect smaller lakes (< 2 km²) more than larger lakes (> 2-10 km²). A linear mixed effects model (RMSE of 18 d), applied with an ensemble of 15 global climate models, projected that end-of-century ice breakup in mountain lakes will be earlier by 25 ± 4 and 61 ± 5 (mean ± SE) days for representative concentration pathways 4.5 and 8.5, respectively. [ABSTRACT FROM AUTHOR]

Polarimetric radar observations from the NEXRAD WSR-88D operational radar network in the contiguous United States, routinely available since 2013, are used to reveal three prominent microphysical signatures in landfalling tropical cyclones: 1) hydrometeor size sorting within the eyewall convection, 2) vertical displacement of the melting layer within the inner core, and 3) dendritic growth layers within stratiform regions of the inner core. Size sorting signatures within eyewall convection are observed with greater frequency and prominence in more intense hurricanes, and are observed predominantly within the deep-layer environmental wind shear vector-relative quadrants that harbor the greatest frequency of deep convection (i.e., downshear and left-of-shear). Melting-layer displacements are shown that exceed 1 km in altitude compared to melting-layer altitudes in outer rainbands and are complemented by analyses of archived dropsonde data. Dendritic growth and attendant snow aggregation signatures in the inner core are found to occur more often when echo-top altitudes are low (≤10 km MSL), nearer the −15°C isotherm commonly associated with dendritic growth. These signatures, uniquely observed by polarimetric radar, provide greater insight into the physical structure and thermodynamic characteristics of tropical cyclones, which are important for improving rainfall estimation and the representation of tropical cyclones in numerical models. [ABSTRACT FROM AUTHOR]

Operational cost of producing lettuce (Lactuca sativa) during the winter in greenhouses is high in the northern regions of the United States due to the addition of supplemental lighting (SL) and heating. Crop productivity in greenhouses should increase to offset high operational costs and maintain profits. Factors including SL composition, heating efficiency, suitability of production systems (PS), and cultivar performance can affect crop productivity. Research-based information on optimizing the above environmental- and production-related factors is limited. This information is critical for growers to make informed decisions and increase profits during winter hydroponic production.We evaluated the interactive effects of SL composition, solution temperature, PS, and cultivar treatments on lettuce shoot dry weight (SDW, g·m-2) and shoot water content (SWC, %) in a greenhouse maintained at suboptimal air temperature (13.7 8C) using a split-plot design. There were three light treatments (sunlight without SL, sunlight + narrow-spectrum SL at nighttime, and sunlight + full-spectrum SL at nighttime), two solution temperature levels [heated (18.8 8C) and unheated (13.2 8C)], two hydroponic PS [constant flood technique (CFT) and nutrient film technique (NFT)], and eight cultivars included in the study. Results indicated that 1) a narrow-spectrum SL at nighttime in combination with heated solution resulted in maximum SDW of lettuce, 2) the SDW and SWC (major determinant of economic yield) increase between the heated and unheated solution temperature treatments was higher in the CFT than in the NFT, and 3) the positive effects of using heated solution were seen mainly in the green-color cultivars. Our research identified the optimal spectral composition of nighttime SL, tested the positive effects of alternate heating methods using heated solution on plant growth under suboptimal air temperature conditions, compared the suitability of two hydroponic PS for lettuce production, and quantified yield potential of several lettuce cultivars in hydroponic production during winter. Growers can use our research findings to make informed decisions about their investment and to maximize hydroponic lettuce productivity and profits during winter. [ABSTRACT FROM AUTHOR]

Winter climate warming is rapidly leading to changes in snow depth and soil temperatures across mid‐ and high‐latitude ecosystems, with important implications for survival and distribution of species that overwinter beneath the snow. Amphibians are a particularly vulnerable group to winter climate change because of the tight coupling between their body temperature and metabolic rate. Here, we used a mechanistic microclimate model coupled to an animal biophysics model to predict the spatially explicit effects of future climate change on the wintering energetics of a freeze‐tolerant amphibian, the Wood Frog (Lithobates sylvaticus), across its distributional range in the eastern United States. Our below‐the‐snow microclimate simulations were driven by dynamically downscaled climate projections from a regional climate model coupled to a one‐dimensional model of the Laurentian Great Lakes. We found that warming soil temperatures and decreasing winter length have opposing effects on Wood Frog winter energy requirements, leading to geographically heterogeneous implications for Wood Frogs. While energy expenditures and peak body ice content were predicted to decline in Wood Frogs across most of our study region, we identified an area of heightened energetic risk in the northwestern part of the Great Lakes region where energy requirements were predicted to increase. Because Wood Frogs rely on body stores acquired in fall to fuel winter survival and spring breeding, increased winter energy requirements have the potential to impact local survival and reproduction. Given the geographically variable and intertwined drivers of future under‐snow conditions (e.g., declining snow depths, rising air temperatures, shortening winters), spatially explicit assessments of species energetics and risk will be important to understanding the vulnerability of subnivium‐adapted species. [ABSTRACT FROM AUTHOR]

Initial-condition large ensembles with ensemble sizes ranging from 30 to 100 members have become a commonly used tool for quantifying the forced response and internal variability in various components of the climate system. However, there is no consensus on the ideal or even sufficient ensemble size for a large ensemble. Here, we introduce an objective method to estimate the required ensemble size that can be applied to any given application and demonstrate its use on the examples of global mean near-surface air temperature, local temperature and precipitation, and variability in the El Niño–Southern Oscillation (ENSO) region and central United States for the Max Planck Institute Grand Ensemble (MPI-GE). Estimating the required ensemble size is relevant not only for designing or choosing a large ensemble but also for designing targeted sensitivity experiments with a model. Where possible, we base our estimate of the required ensemble size on the pre-industrial control simulation, which is available for every model. We show that more ensemble members are needed to quantify variability than the forced response, with the largest ensemble sizes needed to detect changes in internal variability itself. Finally, we highlight that the required ensemble size depends on both the acceptable error to the user and the studied quantity. [ABSTRACT FROM AUTHOR]

The frequency of heat waves (defined as daily temperature exceeding the local 90th percentile for at least three consecutive days) during summer in the United States is examined for daily maximum and minimum temperature and maximum apparent temperature, in recent observations and in 10 CMIP5 models for recent past and future. The annual average percentage of days participating in a heat wave varied between approximately 2% and 10% in observations and in the model's historical simulations during 1979-2005. Applying today's temperature thresholds to future projections, heatwave frequencies rise to more than 20% by 2035-40. However, given the models' slight overestimation of frequencies and positive trend rates during 1979-2005, these projected heat-wave frequencies should be regarded cautiously. The models' overestimations may be associated with their higher daily autocorrelation than is found in observations. Heat-wave frequencies defined using apparent temperature, reflecting both temperature and atmospheric moisture, are projected to increase at a slightly (and statistically significantly) faster rate than for temperature alone. Analyses show little or no changes in the day-to-day variability or persistence (autocorrelation) of extreme temperature between recent past and future, indicating that the future heat-wave frequency will be due predominantly to increases in standardized (using historical period statistics) mean temperature and moisture content, adjusted by the local climatological daily autocorrelation. Using nonparametric methods, the average level and spatial pattern of future heat-wave frequency is shown to be approximately predictable on the basis of only projected mean temperature increases and local autocorrelation. These model-projected changes, even if only approximate, would impact infrastructure, ecology, and human well-being. [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]

The United States Great Lakes Region (USGLR) is a critical geographic area for future bioenergy production. Switchgrass (Panicum virgatum) is widely considered a carbon (C)‐neutral or C‐negative bioenergy production system, but projected increases in air temperature and precipitation due to climate change might substantially alter soil organic C (SOC) dynamics and storage in soils. This study examined long‐term SOC changes in switchgrass grown on marginal land in the USGLR under current and projected climate, predicted using a process‐based model (Systems Approach to Land‐Use Sustainability) extensively calibrated with a wealth of plant and soil measurements at nine experimental sites. Simulations indicate that these soils are likely a net C sink under switchgrass (average gain 0.87 Mg C ha−1 year−1), although substantial variation in the rate of SOC accumulation was predicted (range: 0.2–1.3 Mg C ha−1 year−1). Principal component analysis revealed that the predicted intersite variability in SOC sequestration was related in part to differences in climatic characteristics, and to a lesser extent, to heterogeneous soils. Although climate change impacts on switchgrass plant growth were predicted to be small (4%–6% decrease on average), the increased soil respiration was predicted to partially negate SOC accumulations down to 70% below historical rates in the most extreme scenarios. Increasing N fertilizer rate and decreasing harvest intensity both had modest SOC sequestration benefits under projected climate, whereas introducing genotypes better adapted to the longer growing seasons was a much more effective strategy. Best‐performing adaptation scenarios were able to offset >60% of the climate change impacts, leading to SOC sequestration 0.7 Mg C ha−1 year−1 under projected climate. On average, this was 0.3 Mg C ha−1 year−1 more C sequestered than the no adaptation baseline. These findings provide crucial knowledge needed to guide policy and operational management for maximizing SOC sequestration of future bioenergy production on marginal lands in the USGLR. [ABSTRACT FROM AUTHOR]

Monthly tropical sea surface temperature (SST) data are used as predictors to make statistical forecasts of cold season (November–March) precipitation and temperature for the contiguous United States. Through the use of the combined-lead sea surface temperature (CLSST) model, predictive information is discovered not just in recent SSTs but also from SSTs up to 18 months prior. We find that CLSST cold season forecast anomaly correlation skill is higher than that of the North American Multimodel Ensemble (NMME) and the SEAS5 model from the European Centre for Medium-Range Weather Forecasts (ECMWF) when averaged over the United States for both precipitation and 2-m air temperature. The precipitation forecast skill obtained by CLSST in parts of the Intermountain West is of particular interest because of its implications for water resources. In those regions, CLSST dramatically improves the skill over that of the dynamical model ensembles, which can be attributed to a robust statistical response of precipitation in this region to SST anomalies from the previous year in the tropical Pacific. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this article was to investigate and report the implementation of evidence-based design (EBD) principles relating to user controls into hospital renovation projects. Background: Progress requires the application of the most recent knowledge and technology. When it comes to the design and construction of healthcare facilities, the latest knowledge comes in the form of EBD research. EBD is the process of basing decisions about the built environment on credible research to achieve the best possible outcomes. The desired outcomes of EBD recommendations include improvements to enhance user control. User control factors include the individual control over bed position, air temperature, lights, sound, and natural light. Method: A list of recommendations from existing EBD literature related to user controls was compiled. Construction documents from 30 recent healthcare facility renovation projects across the United States were obtained and analyzed. Implementation levels for the EBD categories of user controls were reported. Results: The findings indicate relatively extensive industry use of EBD principles relating to user control of temperature, lights, and natural lighting. Conclusions: The findings indicate that EBD recommendations related to user controls are being adopted in practice at consistently high levels. These findings also reveal that there are still areas of potential improvement which could inform those who influence or determine building design, codes, standards, and guidelines. The results are helpful to owners, designers, and contractors by providing a glimpse into how well the industry is recognizing and implementing known best practices. The findings likewise introduce new opportunities for further research which could lead to additional improvement in the healthcare facilities of the future. [ABSTRACT FROM AUTHOR]

To determine hydrologic changes in a warmer climate, we impose precipitation and potential evaporation (Eo) perturbations on hydrologic response functions constructed from precipitation and satellite soil moisture observations across the United States. Despite nonlinearities in the evaporation (E) and drainage (D) responses and opposing‐sign perturbations, changes in individual fluxes are superposable. Empirical frameworks (Budyko) can misrepresent changes in E/D partitioning by neglecting shifts/trends in hydrologic regime and subseasonal precipitation dynamics. E/D both increase to balance mean precipitation (P¯) increases, and increased Eo reduces soil moisture. E and D are generally more elastic to changes in P¯ than Eo. The results suggest that (1) the impacts of regional hydrologic perturbations may allow for simple superposition/scaling, (2) changes in timing/intensity of precipitation may have substantial impacts on mean moisture states and fluxes, and (3) changes to the distribution of surface moisture states are likely more relevant for E/D partitioning than common aridity indices. Plain Language Summary: We use satellite observations of soil moisture and expected increase in air temperature to determine how evaporation and soil drainage (to groundwater recharge and rivers/streamflow) will change in a warmer climate. The impacts of drier air, more rainfall, and more extreme rainfall (drier dry days and wetter wet days) can largely be considered separately and then added, which will help when predicting a specific location's water balance using scenarios from global climate models. In typical scenarios, soils are likely to dry, evaporation is likely to increase, and—when precipitation increases—drainage to groundwater/streams is likely to increase as well. Evaporation and drainage are relatively more sensitive to changes in precipitation and humidity in the Western United States than the East, and the Corn Belt is particularly susceptible to changes in precipitation intensity. Common methods of determining changes in evaporation and drainage, which neglect changes in soil moisture, may have large errors in global change scenarios. Key Points: Aridity indices (Budyko) fail to capture effects of daily dynamics and precipitation extremes on long‐term hydroclimate changeClimate perturbations to evaporation/drainage are superposable despite nonlinear flux mechanisms and mixed‐sign effectsLong‐term soil drying tied to trends in increased evaporation, decreased drainage to groundwater and streamflow [ABSTRACT FROM AUTHOR]

Many studies have examined the effects of climate warming on lake stability, but few have addressed environmental changes concomitant with climate change, such as alterations in water clarity and lake inflow. Although air temperature rise is a predominant factor linked to lake thermal characteristics, climate-driven changes at watershed scales can substantially alter lake clarity and inflow, exacerbating the effects of future air warming on lake thermal conditions. Without accounting for potential changes in clarity and inflow, future thermal predictions could be inaccurate. We employed the General Lake Model to simulate future thermal conditions (relative thermal resistance to mixing; RTRM) of small (< 12 ha) mountain lakes of the western United States by calibrating the model to a set of lakes in the Southern Rocky Mountains, USA. We found that after air temperature, alterations in inflow had the largest effect on lake thermal conditions, changes in wind had the least effect, and larger lakes experienced more than double the increase in lake stability than smaller lakes. Generally, clear, high inflow lakes had the lowest stability now, and in the future, while the largest overall increase in thermal stability occurred in larger lakes with low inflows and high turbidity. Assuming air temperature rise alone, summer stability of mountain lakes of the western United States was predicted to increase by 15–23% at + 2 °C air temperatures, and by 39–62% at + 5 °C air temperatures. When accounting for associated changes in clarity and inflow, lake stability was predicted to increase by 208% with + 2 °C air warming and 318% with at 5 °C air warming. Thus, ignoring the multivariate effects of climate change can substantially underestimate changes to mountain lake thermal and stratification regimes. Dimictic lakes may become more strongly stratified and polymictic lakes will experience more prolonged stratification. While predicted changes to lake temperatures may not be harmful to trout species that currently inhabit mountain lakes, longer and more intense stratification could cause indirect effects, such as hypoxia, that could reduce growth and survival of these organisms. [ABSTRACT FROM AUTHOR]

High air temperatures are a public health threat, causing 1300 deaths annually in the United States (US) along with heat-related morbidity and increased electricity consumption for air-conditioning (AC). Increasing tree canopy cover has been proposed as one way to reduce urban air temperatures. Here, we assemble tree cover and developed land-cover information for 97 US cities, housing 59 million people, and use regression relationships to analyze how much current urban tree cover reduces summer (JJA) air temperatures and associated heat-related mortality, morbidity, and electricity consumption. We find that 78% of urban dwellers are in neighborhoods with less than 20% tree cover. Some 15.0 million people (25% of total) experience a reduction of 0.5–1.0°C from tree cover, with another 7.9 million (13% of total) experiencing a reduction of greater than 1.0°C. Current relationships between temperature and health outcomes imply that urban tree cover helps avoid 245–346 deaths annually. Heat–mortality relationships in the 1980s, when a smaller fraction of US households had AC, imply a greater role in the past for urban tree cover in avoiding heat-related mortality. As AC availability has increased, the value of tree cover for avoiding heat-related mortality has decreased, while the value of tree cover for reducing electricity consumption likely has increased. Currently, for the 97 cities studied, the total annual economic value of avoided mortality, morbidity, and electricity consumption is an estimated $1.3–2.9 billion, or $21–49 annually per capita. Applying our results to the entire US urban population, we estimate urban tree cover annually supplies heat-reduction services worth $5.3–12.1 billion. [ABSTRACT FROM AUTHOR]

A major driver of wildlife responses to climate change will include non-genomic effects, like those mediated through parental behavior and physiology (i.e. parental effects). Parental effects can influence lifetime reproductive success and survival, and thus population-level processes. However, the extent to which parental effects will contribute to population persistence or declines in response to climate change is not well understood. These effects may be substantial for species that exhibit extensive parental care behaviors, like birds. Environmental temperature is important in shaping avian incubation behavior, and these factors interact to determine the thermal conditions embryos are exposed to during development, and subsequently avian phenotypes and secondary sex ratios. In this article, we argue that incubation behavior may be an important mediator of avian responses to climate change, we compare incubation strategies of two species adapted to different thermal environments nesting in extreme heat, and we present a simple model that estimates changes in egg temperature based on these incubation patterns and predicted increases in maximum daily air temperature. We demonstrate that the predicted increase in air temperature by 2100 in the central USA will increase temperatures that eggs experience during afternoon off-bouts and the proportion of nests exposed to lethal temperatures. To better understand how species and local adaptations and behavioral-plasticity of incubation behavior will contribute to population responses to climate change comparisons are needed across more avian populations, species, and thermal landscapes. [ABSTRACT FROM AUTHOR]

Heat index (HI) provides a proven indicator of heat stress and discomfort for the general public. The index takes the integrated effects of both temperature and humidity into account, and both factors are regulated by large-scale circulation patterns. This study examines the impacts of the North Atlantic Subtropical High (NASH) on HI over the conterminous United States (CONUS). The analysis suggests that the HI is primarily controlled by surface air temperature over the CONUS; but is negatively correlated with relative humidity in the western and Central US north of 40°N. In addition, winds contribute to the variation of HI in the Midwest and the southeastern US. By regulating these meteorological parameters, the movement of the NASH western ridge significantly impacts HI over the US, especially the Southeast. When the NASH western ridge is located northwest (NW) of its climatological mean position, abnormally high temperatures are observed due to fewer clouds and a precipitation deficit, leading to positive HI anomalies over the southeastern US. In contrast, when the western ridge is located in the southwest (SW), temperature decreases and HI anomaly becomes negative over the Southeast, even though relative humidity increases east of 100°W. NASH has a weaker impact on the HI when it is far from the North American continent, especially during southeast (SE) ridge years. In the future, CMIP5 models project an increase in HI over the entire CONUS, while NASH-induced HI will be weakened during the NW, SE and NE ridge years but strengthened when its ridge moves to the SW quadrant. These results suggest that future increases in heat stress are likely caused by climatological warming and NASH intensification. [ABSTRACT FROM AUTHOR]

Patterns of energy and available moisture can vary over small (<1 km) distances in mountainous terrain. Information on fuel and soil moisture conditions that resolves this variation could help to inform fire and drought management decisions. Here, we describe the development of TOPOFIRE, a web-based mapping system designed to provide finely resolved information on soil water balance, drought, and wildfire danger information for the contiguous United States. We developed 8-arc-second-resolution (~250 meter) daily historical, near real-time, and 4-day forecast radiation, temperature, humidity, and snow water equivalent data and used these grids to calculate a suite of drought and wildfire danger indices. Large differences in shortwave radiation and surface air temperature with aspect contribute to greater snow accumulation and delays in melt timing on north-facing slopes, delaying fuel conditioning on shaded slopes. These datasets will help advance our understanding of the role of topography in wildland fire spread and ecological effects. Integration with national programs like the Wildland Fire Assessment System, the Wildland Fire Decision Support System, and drought early warning systems could support more proactive management of wildland fires and refine the characterization of drought in mountainous regions of the United States. [ABSTRACT FROM AUTHOR]

Captive breeding programs are a valuable conservation strategy, particularly when integrated with research goals. Panamanian Harlequin frogs (genus Atelopus) serve as a case study for integrating captive breeding and research goals because they have experienced drastic chytridiomycosis-related declines and have large captive populations. Captive breeding efforts in Panama and the United States established secure ex-situ populations of Atelopus certus , A. glyphus , A. limosus , A. varius , and A. zeteki. Atelopus chiriquiensis is presumed to be extinct with no captive populations. The status of one undescribed species, Atelopus aff. limosus , has not been evaluated and no secure captive population has yet been established. Captive breeding efforts that produce a surplus of Atelopus are an important resource for research into collections management, disease mitigation, and adaptive management approaches for Atelopus reintroduction efforts. We reevaluated all Panamanian Atelopus species through the IUCN Redlist and compiled occurrence records for Panamanian Atelopus species to create a historical distribution map. We model Atelopus habitat suitability using Maxent and found annual mean air temperature to be the best predictor of Atelopus occurrence. The model will improve our knowledge of their likely spatial distribution and guide future conservation and reintroduction efforts. The recent proliferation of molecular tools, climate models, bio-banking, and reproductive technologies position us to address multiple applied and basic evolutionary questions such as: What factors cause differential disease outcomes? Do persisting populations have heritable traits associated with improved survivorship? Are there climatic refugia from disease? Ultimately, the answers to these questions will help us develop applied solutions and facilitate the reestablishment of self-sustaining wild populations. • Atelopus species have experienced severe chytridiomycosis-related declines. • This case study documents the wild and captive status of Atelopus in Panama. • Habitat models improve historical distribution maps and guide future efforts. • Captive breeding efforts prevent extinctions and are a valuable research resource. [ABSTRACT FROM AUTHOR]

The roles of planetary and synoptic-scale waves in extreme cold wave (ECW) events over the southeastern (SE) and northwestern (NW) United States (US) are studied using a spherical harmonic decomposition in conjunction with piecewise tendency diagnosis (PTD). Planetary waves and synoptic waves jointly work together to initiate ECW events. Notably, the planetary waves not only provide a direct contribution to circulation field enacting ECW events but also alter the background circulation field in such a manner that promotes synoptic waves growth via increases in regional barotropic deformation. The SE-ECW events, concurrent with the Northern Hemisphere annular mode (NAM) negative phase, feature high latitude intensification and subsequent southeastward movement of cold surface air temperature (SAT) anomalies. The planetary-scale pattern provides a sizable contribution to the total wave pattern on both sea level pressure (SLP) and upper level. Moreover, the negative NAM planetary anomaly acts to displace the jet equatorward and thereby increases the barotropic deformation of the synoptic-scale anomaly over southeastern US. PTD confirms that the planetary-scale barotropic deformation plays a key role in deepening the negative height anomaly with a secondary contribution from baroclinic growth. In contrast, NW-ECW events feature a regional SAT cold anomaly that intensified in situ in association with a quasi-stationary positive SLP anomaly with a substantial planetary-scale wave component. The upper level circulation is characterized by a pronounced anomalous ridge over the Gulf of Alaska and a northeast-southwest tilted negative height anomaly to its east. The negative height anomaly axis is orthogonal to the planetary-scale dilatation, result in a stronger planetary barotropic deformation of the incipient negative height anomaly. [ABSTRACT FROM AUTHOR]

Anticipated future increases in air temperature and regionally variable changes in precipitation will have direct and cascading effects on United States (U.S.) water quality. In this paper, and a companion paper by Coffey et al., we review technical literature addressing the responses of different water quality attributes to historical and potential future changes in air temperature and precipitation. The goal is to document how different attributes of water quality are sensitive to these drivers, to characterize future risk to inform management responses, and to identify research needs to fill gaps in our understanding. Here we focus on potential changes in streamflow, water temperature, and salt water intrusion (SWI). Projected changes in the volume and timing of streamflow vary regionally, with general increases in northern and eastern regions of the U.S., and decreases in the southern Plains, interior Southwest, and parts of the Southeast. Water temperatures have increased throughout the U.S. and are expected to continue to increase in the future, with the greatest changes in locations where high summer air temperatures occur together with low streamflow volumes. In coastal areas, especially the mid‐Atlantic and Gulf coasts, SWI to rivers and aquifers could be exacerbated by sea level rise, storm surges, and altered freshwater runoff. Management responses for reducing risks to water quality should consider strategies and practices robust to a range of potential future conditions. Research Impact Statement: Climate change effects on water quality will vary in different regional and watershed settings and could present a risk to human health and the environment. [ABSTRACT FROM AUTHOR]

In this paper we review the published, scientific literature addressing the response of nutrients, sediment, pathogens, and cyanobacterial blooms to historical and potential future changes in air temperature and precipitation. The goal is to document how different attributes of water quality are sensitive to these drivers, to characterize future risk, to inform management responses, and to identify research needs to fill gaps in our understanding. Results suggest that anticipated future changes present a risk of water quality and ecosystem degradation in many United States locations. Understanding responses is, however, complicated by inherent high spatial and temporal variability, interactions with land use and water management, and dependence on uncertain changes in hydrology in response to future climate. Effects on pollutant loading in different watershed settings generally correlate with projected changes in precipitation and runoff. In all regions, increased heavy precipitation events are likely to drive more episodic pollutant loading to water bodies. The risk of algal blooms could increase due to an expanded seasonal window of warm water temperatures and the potential for episodic increases in nutrient loading. Increased air and water temperatures are also likely to affect the survival of waterborne pathogens. Responding to these challenges requires understanding of vulnerabilities, and management strategies to reduce risk. Research Impact Statement: Climate change will have direct and cascading effects on water quality that vary in different regional and watershed settings, and could present a risk to human health and the environment. [ABSTRACT FROM AUTHOR]

Hydrologic intensity is often quantified using precipitation without directly incorporating atmospheric water demand. We develop a hydrologic intensity index called the surplus deficit intensity (SDI) index that accounts for variation in supply and demand. SDI is the standardized sum of standardized surplus intensity (mean of daily surplus when supply > demand) and deficit time (mean of consecutive days when demand > supply). Using an observational ensemble of global daily precipitation and atmospheric water demand during 1979–2017, we document widespread hydrologic intensification (SDI; +0.11 z‐score per decade) driven primarily by increased surplus intensity. Using a climate model ensemble of the United States, hydrologic intensification is projected for the mid‐21st century (+0.86 in z‐score compared to 1971–2000), producing greater apparent intensification when compared to an index that does not explicitly incorporate demand. While incorporating demand had a minor effect on observed hydrologic intensification, it doubles hydrological intensification for the mid‐21st century. Plain Language Summary: Increasing air temperatures have resulted in an intensification, or acceleration, of the terrestrial hydrologic cycle, which is defined as an increase of the water fluxes (precipitation and evapotranspiration) between the surface and the atmosphere. Efforts to quantify hydrologic intensification have traditionally only considered "supply" variables such as precipitation rates without considering "demand" that varies over space and time. For this work we develop a method to quantify hydrologic intensification using supply and demand. This approach shows widespread hydrologic intensification from 1979–2017 across much of the global land surface, which is expected to continue into the future. We additionally compare this new method to a previously developed method that uses only supply without explicitly incorporating demand. Incorporating demand results in a notable hydrologic intensification compared to methods that only use supply or a simplified representation of supply and demand. This work suggests that demand needs to be considered when quantifying hydrologic intensification. Key Points: We develop a hydrologic intensity metric that incorporates daily supply and demand using precipitation and reference evapotranspirationWidespread hydrologic intensification occurred over the past four decades and will continue into the futureAdding demand couples intensity metrics to ecohydrologic conditions and produces greater increases than metrics with static demand [ABSTRACT FROM AUTHOR]