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Changes in precipitation patterns with climate change could have important impacts on human and natural systems. Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) report trends in daily precipitation patterns over the last five decades in the western United States, focusing on meteorological drought. They report that dry intervals (calculated at the annual or seasonal level) have increased across much of the southwestern U.S., with statistical assessment suggesting the results are statistically robust. However, Zhang et al. (2021, https://doi.org/10.1029/2020gl092293) preprocess their annual (or seasonal) averages to compute 5‐year moving window averages before using established statistical techniques for trend analysis that assume independence about some fixed trend. Here we show that the moving window preprocessing violates that independence assumption and inflates the statistical significance of their trend estimates. This raises questions about the robustness of their results. We conclude by discussing the difficulty of adjusting for spatial structure when assessing time trends in a regional context. Plain Language Summary: A recent paper reports trends in drought in the western United States, in particular increases in drought in the southwestern United States, based on changes in the lengths of time intervals without precipitation. In this "comment" we note that the preprocessing approach used in the paper artificially increases the apparent statistical signal in the data and caution that the evidence for the trends reported is not as strong as presented in the paper. We conclude by discussing the difficulty of estimating trends in a statistically rigorous fashion across multiple weather stations. Key Points: Statistical uncertainty about trends in droughts in the southwestern US is larger than reported in a recent GRL letter [ABSTRACT FROM AUTHOR]

Paciorek and Wehner raise important questions around our use of the Mann‐Kendall nonparametric trend test on smoothed data for analyzing long‐term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p‐values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends). Plain Language Summary: Our colleagues Drs. Paciorek and Wehner have raised concerns about our paper (Zhang et al., 2021, https://doi.org/10.1029/2020gl092293), which showed widespread increases in the duration of drought events over the last five decades in the western United States. They point out that our decision to smooth the data using a moving average inflated the number of weather stations at which the trends toward longer droughts were deemed significant by a statistical test. We agree with them on this point, and we have recomputed all our results using unsmoothed data to determine the impacts. We find that for most stations and regions, trend magnitudes remained largely unchanged, with many stations nearby one another often suggesting similar trends. Finally, we agree with Paciorek and Wehner that there is a lack of statistical methods to test such coherent regional patterns, and we caution that over‐reliance on p‐values limits the power of regional data to identify important climate trends. Key Points: We agree that smoothing to 5‐year moving windows introduced serial correlation into time series of annual statistics of daily rainfall data, inflating the number of weather stations individually showing significant trends (p < 0.05) with the Mann‐Kendall testRecomputation with unsmoothed values produced substantially the same dry intervals trend magnitude and direction at most stations individually and had only minimal impacts on dry interval trends computed for National Ecological Observatory Network domains using the Regional Kendall testNo perfect statistical approach leverages the capacity of coherent regional patterns among spatially correlated weather stations, and an over‐reliance on p‐values as a binary (significant vs. insignificant) determinant of trends limits the power of regional data [ABSTRACT FROM AUTHOR]

A mass‐conserving method to downscale precipitation from global climate models (GCMs) using sub‐grid‐scale topography and modeled 700‐mb wind direction is presented. Runoff is simulated using a stand‐alone hydrological model, with this and several other methods as inputs, and compared to runoff simulated using historical observations over the western contiguous United States. Results suggest the mitigation of grid‐scale biases is more critical than downscaling for some regions with large wet biases (e.g., the Great Basin and Upper Colorado). In other regions (e.g., the Pacific Northwest) the new method produces more realistic sub‐grid‐scale variability in runoff compared to unadjusted GCM output and a simpler downscaling method. The presented method also brings the runoff centroid timing closer to that simulated with observations for all subregions examined. Plain Language Summary: Due to limitations in computing power which necessitates coarse spatial resolution, climate models do not include many details on mountains and their impact on precipitation. For this reason, it is difficult to estimate the impact of climate change on the availability of water for human consumption in places like the western United States, where mountain snowpack is an important source of water. This paper presents a way to adjust precipitation estimates from climate models by using some simple statistics about nearby mountains and valleys. The adjusted precipitation is then used in a hydrologic model to calculate the runoff that is simulated with different precipitation inputs. Results show that in most cases, the precipitation adjustment improves estimates of the resultant runoff relative to simulations with observed precipitation. The main exceptions are in very dry areas where the climate model produces far too much precipitation. With further work, the proposed adjustment may be integrated into the climate model itself to make it easier for those managing water resources (e.g., controlling reservoir levels) to use the model output to plan and adapt to climate change. Key Points: A mass‐conserving method for downscaling orographic precipitation improves modeled runoff from the CESM2Considering upwind topography further improves modeled runoff compared to simpler adjustmentsNot tuning to individual model grid points makes this method more generalizable than many existing statistical downscaling methods [ABSTRACT FROM AUTHOR]

This paper analyzes the effects of pore pressure rate for a spring‐block system that is a simple model of a laboratory experiment. Pore pressure is increased at a constant rate in a remote reservoir, and slip is governed by rate and state friction. The frequency of rapid slip events increases with the increase of a nondimensional pressure rate that is the ratio of the time scale of frictional sliding to that for pressure increase. As the pressure rate increases, the more rapid increase of pore pressure on the slip surface quickly stabilizes slip events due to rate and state friction. Rate and state and pressure rate effects interact in a limited range of pressure rate and diffusivity. This range includes pressure rates and diffusivities representative of recent laboratory experiments. Plain Language Summary: Recent field observations have identified fluid injection as an important factor in causing the dramatic increase of earthquakes in the central United States, and recent laboratory experiments have observed effects of fluid pressure rate on frictional sliding. This paper studies a simple model of a laboratory experiment: a block resting on a frictional surface and pulled by a spring. The frictional resistance to sliding depends on the rate and history of sliding. Fluid pressure is increased at a constant rate at a distance remote from the surface. The paper calculates the types and characteristics of rapid slip events and their dependence on the pressure rate and how fast fluid can diffuse from the reservoir to the frictional surface. Key Points: Rapid slip events occur during the duration of a representative experiment in a limited range of pressure rate and diffusivityAbove a certain pressure rate slip events are strongly damped by a rapid decrease of effective stressInteraction between fluid diffusion and pressure rate affects the type, frequency, and magnitude of slip events [ABSTRACT FROM AUTHOR]

Catchments are complex systems containing channel networks and hillslopes. Channel networks interact with hillslopes and are pathways for transporting water, sediment, and nutrients. Understanding the branching and flux transport patterns of channel networks is critical for predicting the response of catchments to external forcing such as climate and tectonics. However, factors creating complexities in catchments are not fully understood. Here, we propose a new framework based on multiscale entropy approach to evaluate complexity of catchments using two different representations of channel networks. First, we investigate the structural complexity using the width‐function, which characterizes the spatial arrangement of channels. Second, we utilize the incremental area‐function along the main channel to study the functional complexity that captures the patterns of transport of fluxes. Our analysis reveals stronger controls of topological connectivity on the functional complexity than on structural complexity, indicating unchannelized surface (hillslope) contribution to the increase of heterogeneity in transport processes. Plain Language Summary: Catchments are complex natural landscape systems that contain hillslopes and channel networks. Understanding and quantifying features and processes that result in catchment complexity is important for predicting their response to changing human and climatic conditions. In this paper, we use an entropy‐based approach to explore the role of channel network and hillslope toward the contribution to catchment's complexity. Based on 40 natural catchments with minimum human impact across the United States in different climatic and geologic conditions, our results show that hillslopes add significant complexity to the catchments and suggest the amount of hillslope information one needs to account for in accurate predictive modeling of hydrologic processes at the catchment scale. Key Points: Topology controls structural and functional complexityFunctional complexity is higher than structural complexity due to contribution from hillslope processesScale of peak difference between the impact of topology on functional and structural complexity indicates the average hillslope length scale [ABSTRACT FROM AUTHOR]

Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar‐induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower‐level observations and process‐based modeling, we find highly linear gross primary production (GPP):SIF relationships for C4 crops, while C3 crops show some saturation of GPP at high light when SIF continues to increase. C4 crops yield higher GPP:SIF ratios (30–50%) primarily because SIF is most sensitive to the light reactions (does not account for photorespiration). Scaling to the satellite, we compare SIF from the TROPOspheric Monitoring Instrument (TROPOMI) against tower‐derived GPP and county‐level crop statistics. Temporally, TROPOMI SIF strongly agrees with GPP observations upscaled across a corn and soybean dominated cropland (R2 = 0.89). Spatially, county‐level TROPOMI SIF correlates with crop productivity (R2 = 0.72; 0.86 when accounting for planted area and C3/C4 contributions), highlighting the potential of SIF for reliable crop monitoring. Plain Language Summary: Crop monitoring is essential for ensuring food security, but reliable, instantaneous production estimates at the global scale are lacking. The monitoring of crop production in a changing climate is of paramount importance to sustainable food security. Accurate estimates of crop production are dependent on adequately quantifying crop photosynthesis. Our paper demonstrates that solar‐induced chlorophyll fluorescence (SIF), an emission of red to far‐red light from chlorophyll is highly correlated with crop photosynthesis. We show that a new high spatial resolution satellite SIF data set is highly correlated with crop productivity in the United States, which is benchmarked by the United States Department of Agriculture county‐level crop statistics. These results will improve the understanding of crop production and carbon flux over agricultural lands, as well as provide an accurate, large‐scale, and timely monitoring method for global crop production estimates. Key Points: The photosynthetic pathway (C3, C4) impacts the relationship between CO2 uptake and SIF, which helps to interpret satellite signalsTROPOMI SIF agrees well with the seasonality of crop gross primary production (GPP) when accounting for C3/C4 fractionationTROPOMI SIF is highly correlated with USDA reported crop productivity at the county scale [ABSTRACT FROM AUTHOR]

Drought has affected much of the western United States since about the year 2000, including the Upper Colorado River Basin (UCRB). Using a time series of UCRB streamflow derived from a tree‐ring based reconstruction of UCRB streamflow for the years 1 CE through 1905 CE, together with naturalized UCRB streamflow values for 1906 CE through 2021 CE, we identify 51 drought events, including the 2000–2021 drought. Although the recent 2000–2021 drought has been relatively severe, it is not the most severe of the UCRB drought events we identified. Results also indicate that natural variability combined with projected climate warming can result in UCRB drought events that are more severe than any drought since 1 CE. Plain Language Summary: A long and severe drought has affected much of the western United States since about the year 2000 CE, including the Upper Colorado River Basin (UCRB). Comparing this drought to past UCRB droughts (during 1 CE through 2021 CE), we find that the 2000–2021 drought is not the most severe UCRB drought. The results also suggest that natural variability combined with projected climate warming could result in UCRB drought events that are more severe than any drought since 1 CE. Key Points: We identify 51 drought events for the years 1 CE through 2021 CE for the Upper Colorado River Basin (UCRB)Twelve of the 51 UCRB droughts we identify were more severe than the 2000–2021 droughtNatural variability and/or a 1°C temperature increase can trigger UCRB droughts that are more severe than the 2000–2021 drought [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) that undergo rapid intensification (RI) before landfall are notoriously difficult to predict and have caused tremendous damage to coastal regions in the United States. Using downscaled synthetic TCs and physics‐based models for storm tide and rain, we investigate the hazards posed by TCs that rapidly intensify before landfall under both historical and future mid‐emissions climate scenarios. In the downscaled synthetic data, the percentage of TCs experiencing RI is estimated to rise across a significant portion of the North Atlantic basin. Notably, future climate warming causes large increases in the probability of RI within 24 hr of landfall. Also, our analysis shows that RI events induce notably higher rainfall hazard levels than non‐RI events with equivalent TC intensities. As a result, RI events dominate increases in 100‐year rainfall and storm tide levels under climate change for most of the US coastline. Plain Language Summary: Tropical cyclones (TCs) that rapidly intensify (RI) before hitting land are typically hard to predict and cause immense destruction. We used synthetic TCs downscaled from global climate models and physics‐based hazard models to examine the dangers posed by these RI storms in historical and future climates. The TC simulation shows that, as the climate warms, the number of TCs undergoing rapid intensification could rise substantially in the North Atlantic region. Additionally, the likelihood of rapid intensification within 24 hr of landfall significantly increases. These TCs are much riskier, particularly in terms of heavy rainfall, even when compared to equally strong TCs that did not rapidly intensify. Consequently, 100‐year rainfall and storm tide levels will greatly increase under climate change, largely due to the increase of RI events in the future. Key Points: Future climate warming causes large increases in the probability of rapid intensification (RI) within 24 hr of landfallRI events show notably higher rainfall hazard levels than non‐RI events even with equivalent TC intensityChanges in RI events dominate future increases in 100‐year rainfall and storm tide levels for most of the US coastline [ABSTRACT FROM AUTHOR]

High‐resolution regional climate model (RCM) simulations of global warming consistently predict larger percentage increases in precipitation in the lee of midlatitude mountain ranges than on their windward slopes, indicating a weakening of the orographic rain shadow. This redistribution of precipitation could have profound consequences for water resources and ecosystems, but its underlying mechanisms are unknown. Here we show that rain‐shadow weakening is just one manifestation of a more general decrease in the influence of orography on precipitation under global warming. We introduce a simple model of precipitation change based on this principle, and find that it agrees well with an ensemble of high‐resolution simulations performed over the western United States. We argue that diminished orographic influence can be explained by the unique vertical structure of orographically forced ascent, which tends to maximize in the lower atmosphere where condensation is thermodynamically less sensitive to warming. Plain Language Summary: Mountains supply about half of the fresh water used by humans globally and often regulate the seasonal cycle of stream flows by accumulating snowpack during the wet season and releasing it over the dry season. Regional simulations tend to predict large future changes in the spatial pattern of precipitation in mountainous regions, but the reasons for these changes are not well understood. Here we show that the predicted patterns of precipitation change in the western US can be explained by a simple mechanism that causes the influence of mountains to weaken with increasing temperatures. We introduce a simple model of precipitation change based on this effect, and show that its predictions closely match those of far more sophisticated regional simulations of future warming over the western US. Key Points: Orographic influence on precipitation is reduced in simulations of global warmingFractional precipitation change scaled by warming is reproducible with a simple model [ABSTRACT FROM AUTHOR]

Data‐driven methods have been extensively applied to predict atmospheric compositions. Here, we explore the capability of a deep learning (DL) model to make ozone (O3) predictions across continents in China, the United States (US) and Europe. The DL model was trained and validated with surface O3 observations in China and the US in 2015–2018. The DL model was applied to predict hourly surface O3 over three continents in 2015–2022. Compared to baseline simulations using GEOS‐Chem (GC) model, our analysis exhibits mean biases of 2.6 and 4.8 μg/m3 with correlation coefficients of 0.94 and 0.93 (DL); and mean biases of 3.7 and 5.4 μg/m3 with correlation coefficients of 0.95 and 0.92 (GC) in Europe in 2015–2018 and 2019–2022, respectively. The comparable performances between DL and GC indicate the potential of DL to make reliable predictions over spatial and temporal domains where a wealth of local observations for training is not available. Plain Language Summary: Machine learning techniques have been extensively applied in the field of atmospheric science. It provides an efficient way of integrating data and predicting atmospheric compositions. Here, we explore the capability of a deep learning (DL) model to make ozone (O3) predictions across continents in China, the United States (US) and Europe. The DL model was trained and validated with surface O3 observations in China and the US in 2015–2018. We then applied the DL model to predict surface O3 concentrations in China, the US and Europe in 2015–2022. Our analysis exhibits comparable performances between DL and chemical transport models for surface O3 predictions in Europe. This indicates the potential of DL models to extend predictions across spatial and temporal domains. Key Points: Deep learning exhibits acceptable capabilities of spatial and temporal extrapolations for surface O3 predictionsComparable performances between deep learning and GEOS‐Chem models with respect to independent O3 observationsGood performance of deep learning for rapid hourly O3 predictions [ABSTRACT FROM AUTHOR]

Accurate assessment of changes in water availability with changing climate is vital for effective mitigation and adaptation. In this research, we employ a parsimonious Budyko curve method to evaluate changes in water availability under low‐ (SSP126) and high‐emission (SSP585) scenarios for 331 river basins in the contiguous United States. We also assess the relative role of changes in precipitation (∆P) and potential evapotranspiration (∆PET) with changing climate on the increase in water availability vulnerability. Results highlight that around 43% (28%) of basins are projected to experience increased vulnerability to changing climate in high‐emission (low‐emission) scenarios. Sub‐humid basins are most often impacted, while arid and semi‐arid basins exhibit lower sensitivity to changes. Intriguingly, ∆PET emerges as the dominant control on vulnerability, surpassing ∆P, particularly under SSP585 scenario. The analysis prompts water managers to focus on long‐term mitigation planning and scientists to further constraint climate and water budget forecasts in affected basins. Plain Language Summary: Assessment of changes in water availability because of the changing climate is useful for mitigation and adaptation planning. In this study, water availability change in river basins in the contiguous United States is assessed. Which basins will become more vulnerable in terms of reduced water availability in the future climate and how the vulnerability changes within different aridity zones is studied. The study presents a novel methodology to assess and quantify whether the changes in potential evapotranspiration or precipitation are the main driver of future water vulnerability. We find that vulnerability increase due to an increase in potential evapotranspiration to be large. From the different aridity zones, sub‐humid basins are projected to most often experience an increase in vulnerability. Key Points: Changes in water availability under climate change scenarios are evaluatedSub‐humid basins are most often impactedVulnerability increase is large due to increase in Potential Evapotranspiration [ABSTRACT FROM AUTHOR]

Runoff‐generated debris flows are a potentially destructive and deadly response to wildfire until sufficient vegetation and soil‐hydraulic recovery have reduced susceptibility to the hazard. Elevated debris‐flow susceptibility may persist for several years, but the controls on the timespan of the susceptible period are poorly understood. To evaluate the connection between vegetation recovery and debris‐flow occurrence, we calculated recovery for 25 fires in the western United States using satellite‐derived leaf area index (LAI) and compared recovery estimates to the timing of 536 debris flows from the same fires. We found that the majority (>98%) of flows occurred when LAI was less than 2/3 of typical prefire values. Our results show that total vegetation recovery is not necessary to inhibit runoff‐generated flows in a wide variety of regions in the western United States. Satellite‐derived vegetation data show promise for estimating the timespan of debris‐flow susceptibility. Plain Language Summary: Debris flows caused by excessive surface‐water runoff during intense rainfall can be a deadly and destructive hazard in mountainous areas after wildfire. In some cases, debris flows have only occurred in the burned area in the weeks to months after the fire, while, in other cases, debris flows occurred over several years. Though the recovery of vegetation is important for stabilizing sediment and reducing debris‐flow likelihood, uncertainty remains about how much recovery is needed to inhibit debris flows and about how much time is needed to reach this level of recovery. Knowing for how long debris flows are likely to be a hazard is important for managing risks to residents and infrastructure. To investigate this issue, we assembled a data set of 536 debris flows from the western United States and used satellite‐derived vegetation data to calculate the recovery condition of the burned area when each debris flow occurred. We found that the vast majority of the debris flows initiated when the burned area had not yet reached two‐thirds of its prefire vegetation condition. Burned areas that were slower to recover tended to experience debris flows over more protracted timescales. Key Points: Majority (>98%) of western United States postfire debris flows occurred when leaf area index was less than 2/3 of typical prefire valuesTotal recovery of vegetation not necessary to inhibit debris flowsRemotely sensed postfire vegetation state useful to evaluate elevated debris‐flow susceptibility with time [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]

Cloud‐to‐ground lightning with minimal rainfall ("dry" lightning) is a major wildfire ignition source in the western United States (WUS). Although dry lightning is commonly defined as occurring with <2.5 mm of daily‐accumulated precipitation, a rigorous quantification of precipitation amounts concurrent with lightning‐ignited wildfires (LIWs) is lacking. We combine wildfire, lightning and precipitation data sets to quantify these ignition precipitation amounts across ecoprovinces of the WUS. The median precipitation for all LIWs is 2.8 mm but varies with vegetation and fire characteristics. "Holdover" fires not detected until 2–5 days following ignition occur with significantly higher precipitation (5.1 mm) compared to fires detected promptly after ignition (2.5 mm), and with cooler and wetter environmental conditions. Further, there is substantial variation in precipitation associated with promptly‐detected (1.7–4.6 mm) and holdover (3.0–7.7 mm) fires across ecoprovinces. Consequently, the widely‐used 2.5 mm threshold does not fully capture lightning ignition risk and incorporating ecoprovince‐specific precipitation amounts would better inform WUS wildfire prediction and management. Plain Language Summary: Cloud‐to‐ground lightning with minimal rainfall, also known as "dry lightning," is a major wildfire ignition source in the western United States (WUS). Typically, daily‐accumulated precipitation of less than 2.5 mm is used to identify dry lightning occurrence. However, there is limited knowledge of (a) the true precipitation amounts that occur with lightning‐ignited wildfires (LIWs), and (b) how these amounts vary across different landscapes and vegetation types. We combine wildfire, lightning and precipitation data sets to quantify these ignition precipitation amounts across different regions of the WUS. Although we find a 2.8 mm median ignition precipitation for all LIWs, we show that "holdover" fires not detected until 2–5 days following ignition occur with significantly higher precipitation (5.1 mm) compared to fires detected promptly after ignition (2.5 mm). Holdover fires also occur with cooler and wetter environmental conditions. Further, ignition precipitation amounts associated with promptly‐detected and holdover fires vary substantially across ecoprovinces. Consequently, the widely‐used 2.5 mm threshold does not fully capture lightning ignition risk. WUS wildfire prediction and management could be improved through incorporating ecoprovince‐specific precipitation amounts and accounting for differing characteristics of holdover fires. Key Points: The widely‐used 2.5 mm daily precipitation threshold to define "dry" lightning does not fully capture fire ignition risk across the WUSIgnition precipitation amounts range from 1.7 to 7.7 mm depending on ecoprovince and whether the fire was promptly‐detected or a holdoverHoldover fires occur when conditions are cooler and wetter compared to promptly‐detected fires [ABSTRACT FROM AUTHOR]

Identifying regions that mediate regional propagation of atmospheric perturbations is important to assessing the susceptibility and resilience of complex hydroclimate systems. Detecting the regional gateways through causal inference, can help unravel the interplay of physical processes and inform projections of future changes. In this study, we characterize the causal interactions among nine climate regions in the contiguous United States using long‐term (1901–2018) precipitation data. The constructed causal networks reveal the cross‐regional propagation of precipitation perturbations. Results show that the Ohio Valley region acts as an atmospheric gateway for precipitation and moisture transport in the U.S., which is largely regulated by the regional convective uplift. The findings have implications for improving predicative capacity of hydroclimate modeling of regional precipitation. Plain Language Summary: Successful detection of causality in complex systems is important to unraveling the underlying mechanisms of system dynamics. The dynamic interactions in Earth's climate system are often nonlinear, weakly or moderately coupled, and essentially non‐separable, which renders conventional approaches of causal inference, such as statistical correlation or Granger causality, infeasible or ineffective. Here we applied the convergent cross mapping method to detect causal influence among different climate regions in the contiguous U.S. in response to precipitation perturbations. The results of our study show that the Ohio Valley region, as an atmospheric convergence zone, acts as a regional gateway and mediator for the long‐term precipitation perturbations in the U.S. The temporal evolution of causal effect and susceptibility exhibits superposition of climate variability at various time scales, highlighting the impact of prominent climate variabilities such as El Niño–Southern Oscillation on the dynamics of causality. Key Points: We use the convergent cross mapping algorithm (CCM), based on embedding theory, for causality inference in this studyCCM is used to detect causal influence in precipitation perturbations among different climate regions of USThe Ohio Valley region emerges as a causal gateway of moisture transport and propagation of regional precipitation anomalies in the US [ABSTRACT FROM AUTHOR]

During the last ice age, the western United States was covered by large lakes, sustained partly by higher levels of precipitation. Increased rainfall was driven by the atmospheric circulation associated with the presence of large North American ice sheets, yet Pleistocene lakes generally reached their highstands not at glacial maximum but during deglaciation. Prior modeling studies, however, showed nearly monotonic drying since the last glacial maximum. Here I show that iTraCE, a new transient climate simulation of the last deglaciation, reproduces a robust peak in winter rainfall over the Great Basin near 16 ka. The simulated peak is driven by a transient strengthening and southward shift of the midlatitude jet. While meltwater forcing is an important driver of changes to the North Pacific Jet, changing orbital conditions and rising atmospheric CO2 also shift the jet south and contribute to wetter conditions over the western US during deglaciation. Plain Language Summary: At the height of the last ice age, the western United States was covered by large lakes such as Lake Bonneville and Lake Lahontan that required more rainfall to be sustained. It is believed that the 3–4 km thick North American ice sheet over Canada acted as an obstacle to the atmospheric flow, forcing storms to be deflected southward over the southwestern US and bringing more winter rain. While wet conditions during glacial maximum are attributable to the presence of a large ice sheet, why does geological evidence indicate that most lakes attained their maximum size not when the ice sheet was at it largest, but rather when the ice sheet was already melting? Here, I use climate simulations to show that other factors, such as changes to Earth's tilt and temperature, in conjunction with changes in ocean circulation, caused a temporary further increase in rainfall that explains lake expansions during the deglaciation. Key Points: Geological evidence indicates many lakes over the western United States reached highstands during the last deglaciationiTraCE, a transient simulation of the last deglaciation, shows wetter conditions at 16 ka than at 20 ka and compares well to proxy evidenceOrbital conditions, rising atmospheric CO2, and meltwater flux all contribute to lake expansions inferred during Heinrich Stadial 1 [ABSTRACT FROM AUTHOR]

Hydroclimate variability of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly through the teleconnection to El Niño/Southern Oscillation (ENSO), which is expected to be altered by climate change. Natural variability in this teleconnection has not been robustly quantified, complicating the detection of anthropogenic climate change. Here, we use a linear inverse model (LIM) to quantify natural variability in the ENSO‐SWUS teleconnection. The LIM yields realistic teleconnection patterns with century‐scale variability comparable to simulations from the Last Millennium Ensemble project and the Climate Model Intercomparison Project Phases 5 and 6. The variability quantified by the LIM illuminates two aspects of our understanding of ENSO and its impacts: the inherent statistics of the observable system can produce century‐long periods with a wide range of correlations to SWUS hydroclimate, including nonsignificant correlations, and thus that detecting changes in ENSO‐related hydroclimate variability is challenging in a changing climate. Plain Language Summary: The El Niño/Southern Oscillation (ENSO) affects weather and climate across the globe through teleconnections. For example, when sea surface temperatures in the tropical Pacific Ocean are warmer than normal (e.g., during an El Niño), higher than normal precipitation is typically observed in the southwest United States (SWUS). However, because we have temporally limited observations of climate, we do not know how often El Niños actually bring more rain to the SWUS. Assessing this natural variability is difficult with commonly used approaches from the climate sciences. Here, we use a statistical model to emulate the characteristics of ENSO teleconnections from observations. Doing so demonstrates that there is considerable natural variability in the ENSO teleconnection to the SWUS. This suggests that even though ENSO and its impact on weather and climate are expected to change due to climate change, detecting such changes will be difficult. Key Points: A linear inverse model is used to quantify the natural variability in the El Niño/Southern Oscillation‐southwest United States (ENSO‐SWUS) teleconnection, and it suggests considerable intrinsic variabilityThis natural variability demonstrates that detecting anthropogenic changes in the ENSO‐SWUS hydroclimate teleconnection will be difficultCMIP6 shows an improvement in modeling the ENSO‐SWUS teleconnection, but uncertainty remains in the projected future climate [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]

Structural hydrologic connections, formed by the coaction of tectonic and climatic processes, facilitate the transfer of matter across Earth's surface. Large‐scale analysis of hillslope connectivity controls is lacking, thus limiting our understanding of the drivers of extremes, like floods and landslides, and benefits, like wetlands. Here, we model hillslope connectivity using the Index of Connectivity, at 10‐m resolution for the contiguous United States. We show the dominance of tectonic drivers, like river steepness (ρ = 0.84) and seismic activity (ρ = 0.48), over climatic drivers, like precipitation (ρ = −0.31) and aridity (ρ = −0.07), in controlling the strength of connectivity. Highly connected basins were associated with landslide occurrence (ρ = 0.69) while poorly connected basins had greater wetland density (ρ = −0.50). Lastly, we share our results in an open access data portal for land managers to leverage structural connectivity maps in their respective study domains. Plain Language Summary: Hillslopes are critical landscape features that intercept, store, and route water, from its source as rainfall to its fate as river discharge. The strength of this routing is a function of climatic and tectonic forces, but their relative importance to hillslope connectivity is uncertain. We simulated the Index of Connectivity, a topographic analogue for structural connectivity, for 75 billion locations in contiguous United States (CONUS), across a range of climatic and tectonic settings. At the CONUS‐scale, we found that hillslope connectivity is largely driven by tectonic forces, including uplift and seismic activity, and that highly connected hillslopes are more susceptible to landslides while poorly connected hillslopes promote wetland development. We provide a web data portal to serve as a tool for stakeholders to visualize and leverage structural connectivity data in their respective study areas. Key Points: Hillslope connectivity shows high spatial variability across the United StatesTectonics is a primary control of the strength of structural hillslope connectivityOpen access data portal of connectivity maps created for stakeholders [ABSTRACT FROM AUTHOR]

Short‐duration precipitation extremes (PE) increase at a rate of around 7%/K explained by the Clausius‐Clapeyron relationship. Previous studies show uncertainty in the extreme precipitation‐temperature relationship (scaling) due to various thermodynamic/dynamic factors. Here, we show that uncertainty may arise from the choice of data and methods. Using hourly precipitation (PPT) and daily dewpoint temperature (DPT) across 2,905 locations over the United States, we found higher scaling for quality‐controlled data, all locations showing positive (median 6.2%/K) scaling, as compared to raw data showing positive (median 5.3%/K) scaling over 97.5% of locations. We found higher scaling for higher measurement precision of PPT (0.25 mm: median 7.8%/K; 2.54 mm: median 6.6%/K). The method that removes seasonality in PPT and DPT gives higher (with seasonality: median 6.2%/K; without seasonality: median 7.2%/K) scaling. Our results demonstrate the importance of quality‐controlled, high‐precision observations and robust methods in estimating accurate scaling for a better understanding of PE change with warming. Plain Language Summary: Studies based on precipitation observations and climate models provide evidence of an increase in short‐duration precipitation extremes both over recent decades and into the future. To understand how precipitation extremes relate to warming, the common practice is to establish the statistical relationship between extreme precipitation and temperature referred to as scaling. Theory and observations suggest that extreme precipitation increases with a rate of around 7% per one‐degree rise in temperature. However, variations in the scaling rate can be observed using different sources of data, data quality, and different scaling calculation methods. Here, we demonstrate the importance of improving the quality of the data, using fine precision precipitation measurements, and robust scaling methods to estimate accurate scaling rates. Our results have implications for understanding the changes in the occurrence of extreme precipitation with warming and therefore potential changes in the risk of flash floods. Key Points: We estimated scaling rates from hourly observed precipitation and daily dewpoint temperature over the conterminous continental United StatesWe highlight the importance of quality‐controlled, high precision observations and robust statistical methods in estimating accurate scalingOur results have implications for a better understanding of change in extreme precipitation and flash floods with warming [ABSTRACT FROM AUTHOR]

This study evaluates the validity of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) in scaling extreme precipitation with temperature (termed scaling factor, SF). To this end, we use Hadley‐Integrated Surface Database (HadISD) data set at 1‐hourly, 6‐hourly, and 24‐hourly scales between 2000 and 2020 over the contiguous United States (CONUS) as a reference data set. Our findings reveal that IMERG can capture changes in precipitation extremes with the temperature at 6‐hourly, and 24‐hourly scales, especially over dry regions. The difference between IMERG's SF and HadISD's SF at 6‐hourly scale is less than 0.3%/°C in dry areas. However, IMERG underestimates SF in wet regions, especially at 1‐hourly scale, up to ∼5%/°C. It is found that IMERG's performance is dependent on temperature, particularly at 1‐hourly scale. IMERG overestimates extreme precipitations when temperatures are below 5°–11°C while the opposite is true at higher temperatures, indicating the need for considering temperature in adjusting IMERG. Plain Language Summary: Understanding the scaling rate of precipitation extremes with temperature can help to estimate precipitation extremes under global warming. However, we do not have in situ precipitation data in many parts of the world to monitor changes in precipitation extremes with temperature. The remotely sensed precipitation data sets that are available globally with high spatio‐temporal resolution might be excellent resources to use for this purpose. To discover that, in this study, we evaluated the performance of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) as one of the newest precipitation data sets for scaling extreme precipitation with temperature over the contiguous United States. We compared IMERG's results with Hadley‐Integrated Surface Database results at 1‐hourly, 6‐hourly, and 24‐hourly scales. Results indicate IMERG has a considerable performance at 6‐hourly and 24‐hourly time scales. Key Points: Integrated Multi‐satellite Retrievals for Global Precipitation Measurement (IMERG) represents well the relationship between precipitation extremes and temperature at 6‐hourly and daily scalesIMERG's scaling factors in dry areas are closer to the observations than in wet regionsIMERG overestimates (underestimates) hourly precipitation extremes at low (high) temperatures [ABSTRACT FROM AUTHOR]

It has been found that a decreased fraction of precipitation falling as snow in a warmer climate significantly affects streamflow. Here, based on observations from 631 catchments over the contiguous United States, we proposed a framework to investigate the first‐order and second‐order hydro‐climatic relationships between annual streamflow and snowfall fraction. Results show that in addition to the mean annual streamflow, the interannual streamflow variability will also decrease with lower snowfall fraction in the context of warming. The positive relationship between streamflow variability and snowfall fraction may result from the asymmetric hydrological effects of snowfall in the wet and dry years. To our knowledge, it is the first attempt to detect the role of snowfall on the streamflow variability. This study provides new understandings of the second‐order hydro‐climatic effects, and these findings will facilitate decisions for water resource management in a changing climate. Plain Language Summary: With persistent global warming, more precipitation will land on the earth's surface as rainfall instead of snowfall. The observed evidence has shown that the precipitation phase shift (PPS) would reduce mean annual streamflow, leading to less water resources available for human utilization. However, the impacts of this PPS on the interannual variability of river flows have yet to be understood. Here, we employ a parsimonious model to show that both the mean annual streamflow and interannual streamflow variability would decrease concurrently due to temperature rising. We show observed evidence that the snowfall leads to streamflow increases in the wet year and decreases in the dry year. This asymmetric hydrological effect of snowfall results in higher interannual streamflow variability in the snowy regions. These findings contribute to the understanding of the possible changes in hydrological processes at snow‐affected catchments under a changing climate. Key Points: An observation‐driven approach was developed to investigate the second‐order relationship between streamflow and snowfall fractionBoth the mean annual streamflow and interannual streamflow variability will decrease with less snowfall fraction in the context of warmingThe asymmetric effects of snowfall fraction on streamflow in the wet and dry years amplify the interannual streamflow variability [ABSTRACT FROM AUTHOR]

It has been known that the southwestern United States (US) has experienced a drying trend during spring as climate warms. Less is known about the projected increase of summer precipitation in the region and its physical mechanisms. By using climate model simulations and moisture budget analysis, we show that in contrast to the spring, the changes of moisture gradient and wind convergence both cause increasing precipitation during summer. The change of the moisture gradient is featured by larger increase of water vapor along the western coast than inland, thus causing enhanced moisture advection in the future climate. The change of the wind convergence is caused by the maximum jet weakening over the continental US near the latitudes of the region, which leads to enhanced moisture convergence. Plain Language Summary: Precipitation in the southwestern United States (US) is projected to decrease in the spring but increase in the summer under climate warming. It has been known that the spring dry is caused by enhanced zonal drying advection. Here, we performed moisture budget analysis using climate model simulations and found that in contrast to the spring, the moisture gradient change and the wind convergence change both increase the precipitation in the summer. There is more moisture increase along the western coast than inland in the summer. Hence the westerly brings more moisture into the southwestern US and increases precipitation. There is more wind convergence with warming during summer in the southwestern US, which induces more moisture convergence and hence more precipitation. Such wind convergence increase is associated with the maximum jet weakening over land near the southwestern US. Spring drying and summer wetting in the southwestern US demonstrate how different changes of atmospheric dynamics and thermodynamics in different seasons determine the precipitation change. Key Points: Precipitation decreases during spring but increases during summer in the southwestern United States in response to warmingEnhanced zonal moisture advection causes moisture convergence in the summerStronger wind convergence associated with jet weakening is mainly responsible for the summer precipitation increase [ABSTRACT FROM AUTHOR]

High‐amplitude ridges can enforce heat‐trapping systems that persist through an entire season, contributing to drought events. However, the impacts of day‐to‐day weather system changes at the meso‐ and synoptic‐scale are also important, albeit less well studied. We identify five weather types (WTs) from 500‐hPa geopotential height anomalies. These categories include WT4, which represents ridges and associated dry and warm anomalies, and WT3, which characterizes troughs and associated wetter‐ and colder‐than‐normal conditions and is the largest contributor to precipitation in the western U.S. While no discernable trend is evident for WT4 conditions, WT3 conditions have undergone a distinctive decrease in frequency at both annual and seasonal scales, thus a general drying trend across the west during this time period may be more significantly associated with fewer troughs rather than more ridges. Attribution analysis reveals that this decrease in wetter and colder weather is a likely result of anthropogenic forcing. Plain Language Summary: While it is well known that large, persistent areas of high pressure can trap heat in a region for an entire season, contributing to droughts, the impacts of day‐to‐day weather system changes at smaller scales have remained less studied. In this study, we learned that dry‐ and hot‐weather‐inducing ridge conditions did not significantly change during a period of generalized drying between 1980 and 2018. What did change during those years was the pattern of troughs, which are associated with wetter‐ and colder‐than‐normal conditions; these conditions became less common during those years. This trend is likely to have occurred in response to human‐caused factors. Key Points: No discernable trend is evident for dry‐ and warm‐weather‐inducing ridge conditionsTrough conditions‐the largest contributor to annual precipitation in the western U.S.‐have undergone a distinctive decrease in frequencyThe decreasing trend in western troughs is likely to have occurred in response to external forcing rather than natural forcing alone [ABSTRACT FROM AUTHOR]

Inorganic salts present in the atmosphere may affect the composition and abundance of secondary organic aerosol. Here, we quantify the effects of salt identity, salt concentration (ionic strength), and solution pH on the partitioning of ambient water‐soluble organic gases (WSOCg) at a site in the eastern United States. The experimental pH (pH = 1–6) and ionic strengths (10−3–101 mol kg−1) span a wide range of conditions found in atmospheric particles, clouds, and fog droplets. Chloride salts (NaCl, NH4Cl, and KCl) exhibit a strong salting‐out effect at all ionic strengths >0.005 mol kg−1 and pH = 1.8–6. In contrast, sulfate salts (Na2SO4, (NH4)2SO4, and K2SO4) induce both salting‐in and salting‐out behaviors, depending on ionic strength and pH. These results suggest that monovalent cations have minimal effect, while ionic strength, pH, and anion identity exert strong effects on the partitioning of ambient organic gases in the atmosphere. Plain Language Summary: The presence of salts in atmospheric aerosols, fogs, and clouds may change the amount of dissolved organic compounds. This may lead to changes in their physical and chemical properties, and chemical reactions that produce lower‐volatility organic compounds (secondary organic aerosol, SOA). Inorganic salts can both enhance ("salting‐in") or inhibit ("salting‐out") the partitioning of organic gases to aqueous solutions relative to that in pure water, though their importance in the atmosphere is largely unconstrained at present. We performed ambient air sampling to measure the effects of salt identity, salt concentration, and solution pH on the absorption of VOCs into aqueous solutions. A wide range of pH (pH = 1–6) and salt concentrations (ionic strength = 10−3–101 mol kg−1) representative of atmospheric particles, clouds, and fog droplets were studied. Chloride salts (NaCl, NH4Cl, and KCl) exert strong salting‐out effects at all ionic strengths >0.005 mol kg−1 and pH = 1.8–6, while sulfate salts (Na2SO4, (NH4)2SO4, and K2SO4) exhibit both salting‐in or salting‐out behavior based on the salt concentration and solution pH. It was also found that anions induced strong salting effects, while singly charged cations showed minimal salting effects. Key Points: Anion identity, pH, and ionic strength strongly affect the partitioning of ambient organic gases in aerosol, fog, and cloud waterMonovalent cations do not have a significant effect on the salting behavior of ambient organic gasesChloride salts always induce salting‐out, while sulfate salts exert both salting‐in or salting‐out, depending on pH and ionic strength [ABSTRACT FROM AUTHOR]

The western United States experienced a record‐breaking wildfire season in 2020. This study quantifies the contribution of wildfire emissions to the exceedances of health‐based National Ambient Air Quality Standard (NAAQS) for fine particles (PM2.5) by comparing two CMAQ simulations, with and without wildfire emissions. During August to October 2020, western wildfires contributed 23% of surface PM2.5 in the contiguous US (CONUS), with a larger contribution in Pacific Coast (43%) and Mountain Region (42%). Consequently, wildfires were the primary contributor to the 3,720 observed exceedances. The wildfire influence peaked on September 14th, 2020, when 273 exceedances were recorded and wildfire emissions contributed 41%, 81%, and 72% to surface PM2.5 concentrations in the CONUS, Pacific Coast, and Mountain Region, respectively. Our finding highlights the predominating influence of wildfires on air quality, and potentially human health, that is expected to grow with increasing fire activities, while anthropogenic emissions decrease. Plain Language Summary: In the summer of 2020, the western United States experienced a record‐breaking number of wildfires. We looked into the effects of these wildfires on air quality, through the lens of the exceedances of health‐based National Ambient Air Quality Standards (NAAQS) for fine particles (PM2.5), which are associated with the bulk of health risks posed by air pollution. We found that in 2020, the western wildfires contributed 23% of surface PM2.5 pollution during August to October in the contiguous United States. The contribution is much bigger in the Pacific Coast (43%) and the Mountain Region (42%). Consequently, the wildfires were the primary contributor to the 3,720 exceedances of PM2.5 NAAQS. Our finding highlights the dominating influence of wildfire emissions on air quality and potentially on human health. Key Points: Wildfire emissions contribute 23% of surface PM2.5 concentration in the contiguous United States during the summer of 2020Wildfires were the primary contributor to the 3,720 exceedances of National Ambient Air Quality Standard for PM2.5 during the 2020 summerOur finding highlights the predominating influence of wildfires on air quality during the 2020 wildfire season [ABSTRACT FROM AUTHOR]

Constructing an accurate, continental, in‐situ‐based, kilometer‐scale, long‐term record of the precipitation field and its spatiotemporal changes remains a significant challenge. Here, we determine the extreme‐value behavior of the NEXRAD Stage IV radar‐based quantitative precipitation estimate. We find that the climatology of 5‐year daily return values in the contiguous United States East of the Rocky Mountains shows only slight variability on spatial scales smaller than ~100 km. In light of this finding, we test whether rain‐gauge‐only daily precipitation data sets can produce accurate extreme‐value behavior at spatial scales finer than the spacing between gauges. We find that the 5‐year daily return values are accurate at locations far from rain gauges only if the interpolation between gauges is carried out appropriately for extremes. Precipitation statistics derived from in‐situ rain gauge data are therefore of sufficient spatial resolution to faithfully capture daily extremes over much of the eastern United States. Plain Language Summary: Accurate measurement of the amount of precipitation that falls within a given region and time period is crucial for environmental modeling, climate change research, and resource and risk management. For all of those applications, it is desirable to understand not only how much precipitation falls on average, but also how much precipitation falls during an extreme event, such as a severe storm. Using data from weather radar, we show that certain statistical properties of extreme rainfall are highly correlated on spatial scales up to 100 km over the eastern United States. This means that rain gauge networks, which have typical intergauge spacings of roughly 30 km over the eastern United States, are dense enough to accurately measure these statistical properties. However, it is imperative to interpolate between the rain gauge measurements in a way that explicitly captures extremes if the application of interest requires capturing extremes accurately. Our research represents a step toward constructing an accurate, continental‐scale, long‐term, high‐resolution precipitation data set. Key Points: The 5‐years return values of extreme rainfall vary only minimally on spatial scales smaller than 100 kmThe gauge‐only Mountain Mapper algorithm underestimates 5‐year return values far from the locations of rain gaugesThe Risser et al. (2019) algorithm represents these statistics more accurately than Mountain Mapper over the majority of contiguous United States [ABSTRACT FROM AUTHOR]

Studies have quantified the contribution of tropical cyclones (TCs) toward seasonal precipitation, but limited analysis is available on TC contribution toward seasonal streamflow over the southeastern and southcentral (SESC) United States (U.S.). Using an extensive network of hydroclimatic data that consists of 233 TC tracks and daily precipitation and streamflow, we estimate TC contribution toward precipitation and streamflow during the hurricane season over the SESC U.S. We found that TCs account for 12% of seasonal streamflow and 6% of seasonal precipitation over the region. Florida, North Carolina, and Louisiana have the highest fractional occurrence of TC‐generated annual maximum precipitation (∼20%–32%) and streamflow (∼15%–27%). We also found the fractional occurrence of TCs associated with peak‐over threshold precipitation (streamflow) events ranges from 5% to 8% in coastal regions (10%–20% over FL and 5%–10% over coastal NC). Increased antecedent moisture results in increased TCs contribution to streamflow leading to different land‐surface responses for similar hurricane events. Plain Language Summary: While tropical cyclones cause major flooding over coastal areas of the eastern United States (U.S.), they are also an important source of moisture supply. Our analysis shows, on average, TCs contribute 6% of precipitation and 12% of streamflow during the hurricane season over the southeastern and southcentral (SESC) U.S. Our findings also show that TCs play a key role in generating annual extreme precipitation and streamflow over the SESC U.S. Key Points: Tropical cyclones account for 6% of the total seasonal precipitation and 12% of the total seasonal streamflow in the southeastern and southcentral United StatesFlorida, North Carolina, and Louisiana have the highest fractional occurrence of tropical cyclone (TC)‐generated annual maximum precipitation (∼20%–32%) and streamflow (∼15%–27%)Increased antecedent moisture leads to increased TC contribution resulting in increased land‐surface runoff for similar hurricane events [ABSTRACT FROM AUTHOR]

Cloud‐to‐ground strokes, narrow bipolar events, and energetic in‐cloud pulses are known classes of high peak‐current lightning processes that occur in thunderstorms. Here, we report one more distinct class of high peak‐current events observed exclusively over mountainous terrain, usually above 2,000 m altitude, in the continental Unites States. These events, which we call mountain‐top energetic pulses (MEPs), are bipolar pulses with negative radiated field polarities. MEPs are generated between the high mountain tops and compact overhead thunderclouds. Evidence supports the hypothesis that MEPs are produced by terrain‐initiated upward positive leaders propagating in high electric fields due to the proximity of the low negative charge regions of the thunderstorms. This scenario further suggests the possibility that MEPs are associated with downward terrestrial gamma‐ray flashes, and their high peak currents imply that they may produce elves. Plain Language Summary: Several distinct classes of high peak‐current lightning processes are known to occur in thunderstorms, such as cloud‐to‐ground (CG) strokes, narrow bipolar events (NBEs), and the recently revealed energetic in‐cloud pulses (EIPs). Here, we report on another type of high‐amplitude event that is generated almost always over mountainous terrain in the western United States. We term them mountain‐top energetic pulses, or MEPs, which produce only radiated fields of negative polarity. The low‐frequency radio waveform characteristics, associated lightning flash structures, as well as weather radar images of the storms suggest that MEPs occur during the propagation of upward, terrain‐initiated, positive polarity lightning leaders. MEPs seem to require several conditions, namely a high ground altitude, a relatively short distance between the ground and overhead cloud, and terrain that can enhance the local electric field. MEP‐producing processes are very different from CGs and NBEs but are similar to EIPs. It is known that positive EIPs are always or almost always associated with upward‐propagating terrestrial gamma‐ray flashes (TGFs). We conjecture that MEPs may be associated with downward‐propagating TGFs. And because of the transient high‐amplitude‐radiated electromagnetic fields, MEPs may also produce ionospheric optical emissions in the form of elves. Key Points: Document a type of highly energetic, negative field polarity lightning processes in the United States only over mountain areas (>2,800 MSL altitude)Measurements indicate that these pulses occur during the upward propagation of terrain‐initiated positive leadersTheir similarity to other processes suggests that they may be associated with terrestrial gamma‐ray flashes and elves [ABSTRACT FROM AUTHOR]

Droughts are complex phenomena that typically evolve slowly over time. They originate through interactions between the atmosphere and the land surface, but show delayed evolution as they cascade through soil moisture, surface, and groundwater supplies, sometimes resulting in prolonged and insidious impacts on regional hydrological systems. While previous studies have observed this cascade phenomenon at select in situ locations, the temporal characteristics of drought cascades have never been quantitatively estimated at large scales using primarily remote sensing techniques. Here, we use satellite observations of vapor pressure deficit, Precipitation, and terrestrial water storage, and reanalysis‐based estimates of column soil moisture to characterize cascade phenomena for four major US drought case studies. By mapping the time evolution through this suite of variables, we observe large‐scale behavior generally consistent with theory and are able to quantify emergent patterns in the evolution of drought signals that may support improved future predictability. Plain Language Summary: Droughts are slow‐building disasters that result in billions of dollars of losses every year. A better understanding of how long droughts take to propagate and persist depends on the ability to observe drying beneath the land surface, where drought effects reach deep to disturb soil moisture and groundwater stores that remain hidden to the naked eye. In this study, we used state‐of‐the‐art satellite observations to measure not only the surficial causes of drought, but also to characterize the beginning, ending, and severity of drought at depth in the soil column and in groundwater. For four major historical droughts in the United States, we find similar patterns in the timing of the drought cascade through the land surface that may be useful to tracking drought evolution more comprehensively in the future. Key Points: This study presents the first multievent analysis of drought cascades using satellite vapor pressure deficit (VPD), precipitation, terrestrial water storage (TWS), and reanalysis soil moistureWe find characteristic lag times in the propagation of drought onset, termination, and timing from precipitation to soil moisture and TWSOn average, it took 2.5 months for precipitation deficits at drought onset to propagate to soil moisture, and 8 months to propagate to TWS [ABSTRACT FROM AUTHOR]

Solar radiation is a fundamental driver of ecosystem productivity, but widespread estimates of light available for primary producers in rivers are lacking. We developed a model to predict light available for river primary producers and used it to estimate river primary production across the contiguous United States (CONUS). Successively accounting for riparian and water column processes improved predictions of primary production as a function of light. We calculated the ratio of river width to riparian tree height and used this metric to predict whether riparian zones or water column processes most limit productivity for over 2 million reaches. Water column processes limited productivity for 50% of the nation's river length and 80% of its surface area, with variations across ecoregions related to riparian forest cover. Our findings facilitate large‐scale predictions of stream and river ecosystem productivity, as well as understanding the processes controlling productivity across networks. Plain Language Summary: The conversion of solar energy to organic matter through photosynthesis is an important component of global carbon cycling. While there are global estimates of solar radiation at the Earth's surface, primary producers in rivers often only receive a small percentage of incoming light due to reductions from riparian shading, water depth, and water clarity. We developed a model to predict light available for river primary producers so that we could make estimates of productivity based solely on light. We predicted light and primary productivity for 173 rivers across the United States and also examined the degree to which riparian zones or water column processes limited productivity. Our model allowed us to make first approximations of productivity across many sites with varying conditions based solely on light availability. We also developed a metric to predict whether river productivity was most limited by riparian zones or water column processes and calculated this metric for over 2 million rivers in the United States. Our results suggested that riparian zones and water column process limit an equal percentage of river length nationally; however, these results varied across ecoregions and appear to be driven by changes in forest cover. Key Points: Riparian zones limit light availability, and thus primary productivity, until channel width is 1.7 times the height of riparian treesLight attenuation from water depth and clarity limit productivity for 50% of river length and 80% of river surface areaThe percentage of river length and surface area limited by riparian zones and water column processes varies across ecoregions [ABSTRACT FROM AUTHOR]

High‐speed video observations of two sprites with halo features were analyzed with concurrent measurements of broadband magnetic sferics. Both events were produced by positive cloud‐to‐ground (CG) strokes. Moreover, the halo features appeared less than 0.5 ms after the return stroke, and the first sprite elements followed within 1 and 3 ms, respectively, for the two cases. The persistent charge transfer in the causative stroke from long continuing current can maintain the continuous glowing of existing sprite elements, and also may aid the vertical development and enhanced luminescence of later sprite elements. The observations with electric field (E‐field) simulations by the transmission line model provide evidence that the induction component of the lightning‐induced E‐field contributes significantly to halo formation. Our results suggest additional measurements and analysis are needed to identify the specific role of induction E‐field in addition to the well‐known quasi‐electrostatic (QE) field in the lightning‐induced impact on the mesosphere. Plain Language Summary: We analyze two cases of sprite observations demonstrating the halo feature that were both produced by positive cloud‐to‐ground (CG) strokes over a mesoscale convective system in the central United States. The first event was the brightest sprites observed on that night, while the second event was a dancing sprite event containing three sprite elements all following a single +CG. The broadband (<1 Hz–400 kHz) lightning sferic signals recorded at various ranges are analyzed in comparison with the high‐speed and low‐light‐level video to reveal the detailed development and evolution of sprite events. The first case contains an elves, halo, and sprite elements; the second case includes a halo as well as three sprite elements. In both case, the halo features appeared less than 0.5 ms after the return stroke. From this observation with relatively high time resolution and the simulation of lightning‐induced electrical field (E‐field) change at the height of halo formation, we attribute the occurrence of halo to the induction E‐field from the initial portion (within 1 ms) of charge transfer in the causative stroke mainly. The continuous illumination of the existing sprite element and the time delay and vertical structure of following sprites are associated with the subsequent continuing current of causative strokes. Key Points: Two sprite events featured with halo were captured on the high‐speed video camera with coordinated broadband sferic dataIn both cases, the halo initiated within 0.5 ms after the causative return strokeThe induction component of lightning‐induced transient E‐field appears to make a considerable contribution to the halo formation [ABSTRACT FROM AUTHOR]

Wildfires in forest ecosystems have been well studied, while wildfires in rangelands ecosystems have received less attention. This study evaluated temporal trends of large wildfires on rangelands in western United States from 1984 to 2017, using the Monitoring Trends in Burn Severity product (captured wildfires ≥405 ha in size in western United States) and Autoregressive Integrated Moving Average analysis. The results showed a significant increase (more than fivefold) in area of rangeland burned by large wildfires, but generally no significant trends in proportions of areas burned at different levels of severity. The trends for all rangelands, in total area burned and in areas burned at different levels of severity, were most similar to the trends for herbaceous‐dominated rangelands but largely different from the trends for shrub‐dominated rangelands. These findings can aid in the development of management strategies for anticipating and reducing wildfire risk and enhancing rangeland conservation and sustainability. Plain Language Summary: Wildfires have become more frequent and larger in the western United States over the last 30 years. Burn severity, an indicator of fire effects on soil and vegetation, can help in assessing fire impacts on ecosystem structure and function. Many studies have explored burn severity of wildfires in forests, while less attention has been given to rangelands. In this study, we examined temporal trends of large wildfires (≥405 ha in size) on rangelands in western United States from 1984 to 2017, in terms of rangeland area burned and areas burned at different levels (low, moderate, and high) of severity using the Monitoring Trends in Burn Severity data. We also tested whether the trends were consistent in three rangeland ecosystem types: grass‐dominated, shrub‐dominated and tree‐dominated rangelands. The results showed a significant increase in rangeland areas burned over time, but the rate of increase was lower than that for forests. Furthermore, the trends for all rangeland burned were similar to the trends for grass‐dominated rangelands but different from the trends for shrub‐dominated rangelands. These findings can help policymakers and rangeland managers in developing strategies for anticipating and reducing wildfire risks and enhancing rangeland conservation and sustainability in western United States. Key Points: Significant increasing trends existed in area of rangeland burned, but the rate of increase on rangelands was lower than that for forestsRangeland area burned at low and moderate severity increased significantly, but no trend in proportion of area burned at specific severityTrends in areas burned and severity for all rangeland areas were more reflective of those for herbaceous‐dominated rangelands [ABSTRACT FROM AUTHOR]

This study explores the impacts of groundwater processes on the simulated land‐surface water balance and hydrometeorology. Observations are compared to multiscale Weather Research and Forecasting (WRF) simulations of three summer seasons: 2012, 2013, and 2014. Results show that a grid spacing of 3 km or smaller is necessary to capture small‐scale river and stream networks and associated shallow water tables, which supplies additional root‐zone water double that of simulations with 9‐km and 27‐km grid spacing and is critical to replenishing the depleted vegetation root zones and leads to 150 mm more evapotranspiration. Including groundwater processes in convection‐permitting models is effective to reduce: (1) 2‐m temperature warm biases from 5–6 to 2–3 °C and (2) the low precipitation bias by half. The additional groundwater supply to active soil flux in convection‐permitting simulations with groundwater for June‐August is nearly translated into the same amount of increased precipitation in the domain investigated. Plain Language Summary: Groundwater plays an important role in land‐atmosphere interactions. This study explores the impacts of groundwater processes on the model simulated land‐surface water balance and hydrometeorology. Observations are compared to multiscale Weather Research and Forecasting model simulations of summer seasons for three years: 2012, 2013, and 2014. Results show that high‐resolution modeling (with a grid spacing of 3 km or smaller) is necessary to capture small‐scale river and stream networks and associated shallow water tables, and supply crop and plant root‐zone water double that of low‐resolution simulations, which is critical to replenishing the depleted vegetation root zones and leads to 150 mm more evapotranspiration. Including groundwater processes in high‐resolution models is effective to reduce: (1) 2‐m temperature warm biases from 5–6 to 2–3 °C and (2) the low precipitation bias by half. The additional groundwater supply to active soil flux in high‐resolution simulations with groundwater for June‐August is nearly translated into the same amount of increased precipitation in the domain investigated. Key Points: Groundwater‐atmosphere nexus heavily depends on model resolution and is accelerated at convection‐permitting scalesConvection‐permitting simulations with groundwater effectively mitigates summer warm and dry biases in central United StatesThe amount of water transported from shallow water tables to plant root zones is nearly identical to the increased amount of precipitation [ABSTRACT FROM AUTHOR]

Monthly, high‐resolution (∼2 km) ammonia (NH3) column maps from the Infrared Atmospheric Sounding Interferometer (IASI) were developed across the contiguous United States and adjacent areas. Ammonia hotspots (95th percentile of the column distribution) were highly localized with a characteristic length scale of 12 km and median area of 152 km2. Five seasonality clusters were identified with k‐means++ clustering. The Midwest and eastern United States had a broad, spring maximum of NH3 (67% of hotspots in this cluster). The western United States, in contrast, showed a narrower midsummer peak (32% of hotspots). IASI spatiotemporal clustering was consistent with those from the Ammonia Monitoring Network. CMAQ and GFDL‐AM3 modeled NH3 columns have some success replicating the seasonal patterns but did not capture the regional differences. The high spatial‐resolution monthly NH3 maps serve as a constraint for model simulations and as a guide for the placement of future, ground‐based network sites. Plain Language Summary: Ammonia (NH3) contributes to the formation of particulate matter, which is known to degrade air quality and human health. The major source of NH3 is from agricultural activities, yet observational constraints on NH3 are limited, particularly at both monthly resolution and high spatial resolution. We have developed high spatial resolution (2 km) satellite maps of NH3 on a monthly scale in the United States. Areas with the highest NH3 are generally very localized with typical length scales of ∼12 km. The seasonal patterns varied dramatically based upon the underlying agricultural activities. These high‐resolution satellite maps can be used as observational constraints on the seasonalities and spatial patterns for modeling of atmospheric NH3. Key Points: High spatial resolution (2 km) maps of NH3 show that hotspots are highly localized with characteristic length scales of ∼12 kmLarge monthly variations of NH3 columns are observed with different seasonality patterns by region and type of agricultural activitiesSatellite NH3 maps provide insights for future ground‐based observational networks and constraints for model NH3 spatiotemporal patterns [ABSTRACT FROM AUTHOR]

Rapid drought intensification, or flash droughts, is often driven by anomalous atmospheric ridging and can cause severe and complex impacts on water availability and agriculture, but the full range of variability of such events in terms of intensity and frequency is unknown. New tree‐ring reconstructions of May–July mid‐tropospheric ridging and soil moisture anomalies back to 1500 CE in the central United States—a hotspot for flash drought—suggest that over the last five centuries, anomalies in these two variables combined to indicate flash‐drought conditions in ∼17% of years and exceptionally severe flash drought in ∼4% of years, similar to frequencies in recent decades. However, over one‐third of all inferred exceptional flash droughts occurred since 1900, suggesting the 20th century was highly flash‐drought prone. These results may guide future work to diagnose the roles of external, oceanic, and land‐surface forcing of warm‐season atmospheric circulation and hydroclimate over North America. Plain Language Summary: In 2012, the central United States experienced a "flash drought," when rapid soil drying due to persistently low precipitation totals and high temperatures in late spring and summer caused billions of dollars in damages and agricultural losses. Such events are difficult to forecast because flash droughts can develop in a matter of weeks, and only a handful of flash droughts have been observed in recent decades, giving high uncertainty as to their likelihood. Here, we use tree rings to create two independent annual records of central United States soil moisture and the principal atmospheric circulation pattern known to cause flash droughts that extend back to the year 1500. Taken together, these records provide a new five‐century perspective on these crucial components of flash drought and reveal for the first time the long‐term behavior of central United States flash droughts, including frequency and cyclicity of exceptional events. We find that the instrumental record is a good representation of the long‐term likelihood of flash droughts. This apparent agreement with long‐term average conditions is largely by chance; however, as the reconstructions indicate large century‐to‐century variations in flash‐drought frequency and magnitude over the past 500 years. Key Points: We developed tree‐ring reconstructions of central U.S. soil moisture and the atmospheric ridge that causes flash droughts back to 1500 CEObservations capture flash drought's long‐term probability distribution, but reconstructions reveal centennial fluctuations in variabilityCycles in reconstructed atmospheric ridging may aid diagnosis and prediction of flash drought on interannual to decadal time scales [ABSTRACT FROM AUTHOR]

The newly released simulations from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) provide an opportunity to re‐examine long‐term soil moisture trends. In this study, we assessed the historical simulation (1850–2014) of surface soil moisture from 18 general circulation models that are part of CMIP6 and compared them with model simulations from CMIP5 and NLDAS‐2, and in situ observations over CONUS. Our results show that for CONUS as a whole, there is no significant long‐term trend in soil moisture, but significant drying trends exist over medium‐term, short‐term, and near‐present periods based on the CMIP6. Our comparison of CMIP6 to NLDAS‐2 (1980–2014) and in situ observations (2004–2014) demonstrates that it more accurately captures soil moisture trends in CONUS than CMIP5. CMIP6 shows a significant wetting trend in the Northwest, Midwest, Northeast, and Southeast. There is greater agreement amongst the individual models in CMIP6 than CMIP5, but intermodel variability still exists. Plain Language Summary: Soil moisture is an important variable that affects both energy and water balance near land surface. Global climate models are commonly used to simulate historical and future soil moisture conditions. We analyzed soil moisture in the 0–10 cm soil layer from the newly released Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) to assess long‐term soil moisture trends (1850–2014) the contiguous United States. Significant increases in soil moisture were found in the Midwest, Northeast, Southeast, and Northwest. However, when considering all of the contiguous United States, there is no trend in soil moisture. This differs from CMIP5 which showed a significant drying trend in the United States. We validated the CMIP6 results by comparing them with the NLDAS‐2 land‐surface model (1980–2014) and in situ soil moisture observations (2004–2014). The comparison shows that CMIP6 is more accurate than CMIP5. There is still substantial variation among the individual models that comprise CMIP6; however, there is greater consensus amongst the CMIP6 models than CMIP5. Key Points: Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) shows significant long‐term soil moisture trends in the northern half of CONUS and Southeast, but not for CONUS as a wholeCMIP6 has less uncertainty and is better able to capture soil moisture trends than CMIP5Substantial model uncertainty remains in CMIP6 [ABSTRACT FROM AUTHOR]

Increases in burned area across the western United States (US) since the mid‐1980s have been widely documented and linked partially to climate factors, yet evaluations of trends in fire severity are lacking. Here we evaluate fire severity trends and their interannual relationships to climate for western US forests from 1985 to 2017. Significant increases in annual area burned at high severity (AABhs) were observed across most ecoregions, with an overall eightfold increase in AABhs across western US forests. The relationships we identified between the annual fire severity metrics and climate, as well as the observed and projected trend toward warmer and drier fire seasons, suggest that climate change will contribute to increased fire severity in future decades where fuels remain abundant. The growing prevalence of high‐severity fire in western US forests has important implications to forest ecosystems, including an increased probability of fire‐catalyzed conversions from forest to alternative vegetation types. Plain Language Summary: The physical and ecological effects of wildfire (hereafter fire severity) have important consequences in terms of soil erosion, carbon storage, forest succession, wildlife habitat, and human safety and infrastructure. This study evaluated changes in fire severity in western US forests from 1985 to 2017 and tested whether fire severity varied with fire‐season climate. Results show that area burned at high severity increased across most of the study area, with an overall eightfold increase in western US forests from 1985 to 2017. Furthermore, warmer and drier fire seasons corresponded with higher severity fire, indicating that continued climate change may result in increased fire severity in future decades. One potential consequence of greater area burned at high severity is an increased probability that forests will convert to alternative vegetation types. Our findings provide some guidance to managers as society struggles to better coexist with fire. For example, it may be possible to increase the prevalence of low‐ and moderate‐severity fire, sometimes referred to as "good fire", through thoughtful planning about where and when to implement a less aggressive fire suppression response. Similar to prescribed fires that promote forest resilience, unplanned fires that burn during less‐than‐extreme fire seasons have the potential to serve as effective "fuel treatments". Key Points: Area burned at high severity increased from 1985 to 2017 across most western US forests coincident with warmer and drier fire seasonsWarmer and drier fire seasons correspond to elevated fire severity and proportion burned at high severity across many western US forestsContinued climate change could result in more high‐severity fire where fuels remain abundant [ABSTRACT FROM AUTHOR]

Sea‐level dynamics, sediment availability, and marine energy are critical drivers of coastal wetland formation and persistence, but their roles as continental‐scale drivers remain unknown. We evaluated the timing and spatial variability of wetland formation from new and existing cores collected along the Atlantic and Gulf coasts of the United States. Most basal peat ages occurred after sea‐level rise slowed (after ~4,000 years before present), but predominance of sea‐level rise studies may skew age estimates toward older sites. Near‐coastal sites tended to be younger, indicating creation of wetlands through basin infilling and overwash events. Age distributions differed among regions, with younger wetlands in the northeast and southeast corresponding to European colonization and deforestation. Across all cores, wetland age correlated strongly with basal peat depth. Marsh age elucidates the complex interactions between sea‐level rise, sediment supply, and geomorphic setting in determining timing and location of marsh formation and future wetland persistence. Plain Language Summary: Marshes, a type of coastal wetland, form under stable, slow rates of sea‐level rise (SLR). Although many marshes along the East Coast of the United States formed after the most recent slowing of SLR (approximately 4,000–6,000 years ago), there is evidence that sediment erosion from colonial deforestation expanded marshes. This study uses sediment cores to determine when and where marshes formed to understand what drives modern marsh formation. We found that most marshes did form following SLR slowing after around 4,000 years ago. We also found evidence of marshes forming during European colonization in the northeastern and southeastern United States. Finally, we found recent formation of marshes closest to the coast, possibly driven by storm events and associated overwash. Through this study, we outline a novel way to easily determine marsh age and to better understand why marshes form through future research. Key Points: Marshes largely formed after SLR slowed (after 4,000 ybp). A second formation period occurred (~400 ybp), coinciding with land cover changeStudies that dated marshes to assess historic sea‐level rise had an older and less varied age distribution than other studiesCoastal marshes are younger nearer the coast and in regions where land use change may have delivered large amounts of sediment to the coast [ABSTRACT FROM AUTHOR]

Geomagnetic perturbations (BGEO) related to magnetospheric ultralow frequency (ULF) waves induce electric fields within the conductive Earth—geoelectric fields (EGEO)—that in turn drive geomagnetically induced currents. Though numerous past studies have examined ULF wave BGEO from a space weather perspective, few studies have linked ULF waves with EGEO. Using recently available magnetotelluric impedance and EGEO measurements in the contiguous United States, we explore the relationship between ULF waves and EGEO. We use satellite, ground‐based radar, BGEO, and EGEO measurements in a case study of a plasmaspheric virtual resonance (PVR), demonstrating that the PVR EGEO has significant spatial variation in contrast to a relatively uniform BGEO, consistent with spatially varying Earth conductivity. We further show ULF wave EGEO measurements during two moderate storms of ∼1 V/km. We use both results to highlight the need for more research characterizing ULF wave EGEO. Plain Language Summary: A variety of phenomena in the near‐Earth space environment produce disturbances in the magnetic field observed on the ground, including plasma waves in the ionized portion of the Earth's upper atmosphere. Though numerous studies have characterized magnetic disturbances related to waves with frequencies below a few hertz, few studies have addressed the electric fields they can induce in the Earth: geoelectric fields (EGEO). The latter are important because they drive potentially damaging electrical currents in power grids and other infrastructure. This study addresses the lack of constraints on wave EGEO fields by taking advantage of recently available models and measurements. The results show that extreme wave events can produce EGEO of significant amplitude, comparable to once‐per‐century values obtained in other studies. The results also indicate that more work is needed to characterize wave EGEO. Key Points: There are few measurements of ultralow frequency (ULF) wave geoelectric fields (EGEO), despite the hazard these fields can representA coordinated investigation of ULF waves and EGEO reveals significant spatial inhomogeneities in EGEO related to Earth conductivityMeasured storm time ULF wave EGEO amplitudes of ∼300–1000 mV/km suggest that they should be considered in future geoelectric hazard analysis [ABSTRACT FROM AUTHOR]

The 100th meridian is a conceptual arid‐humid divide that effectively bisects the continent of the United States into the humid east and arid west. Here, we examine the historical and future shifts of the 100th meridian from atmospheric, hydrologic, and agroecological perspectives. We find that the effective arid‐humid divide regarding vegetation greenness and runoff has been moving toward west with a mean shift of 0.73° (1982–2015) and 2.08° (1961–2010), respectively, suggesting decreased agroecological and hydrologic aridity in the region. For future periods, the agroecological divide shows a persistent westward movement, whereas eastward shifts of the 100th meridian are detected from the atmospheric and hydrologic perspectives. Nevertheless, the eastward movements of the atmospheric and hydrologic divide substantially slow down when the vegetation response to elevated atmospheric CO2 is accounted for. This finding demonstrates that CO2 fertilization on vegetation could largely alleviate the warming‐induced drying tendency around the 100th meridian region. Plain Language Summary: The 100th meridian is a conceptual arid‐humid divide in the physical climate and landscape of the central United States continent and has exerted a profound influence on human settlement and agriculture developments. Using climate projections and aridity index, a previous study reported an eastward movement of the 100th meridian, indicating an overall drying trend in the region. Here, we reexamine the historical and future shifts of the 100th meridian from the atmospheric, hydrologic, and agroecological perspectives. We find that the movements of the 100th meridian are strongly modified by the vegetation response to elevated atmospheric CO2 concentration that CO2 fertilization on vegetation could largely alleviate the warming‐induced drying tendency and effectively slows down the eastward movement of the arid‐humid divide. Key Points: Historical and future shifts of the 100th meridian from atmospheric, hydrologic, and agroecological perspectives are assessedObserved hydrologic and agroecological 100th meridian have been moving toward west over the past few decadesProjected agroecological divide moves toward west whereas hydrologic and atmospheric divides move toward east in the coming century [ABSTRACT FROM AUTHOR]

Analyses of wildfire‐climate relationships in North America were conducted using diverse independent observation and reanalysis data sets for the period 1984–2014. Results show that the western United States (WUS) has experienced the most robust increase in burned area, even though Alaska and western‐central Canada have comparable warming trends. In addition to warming, the WUS has been under the influence of multi‐decadal trends in tropospheric relative humidity deficit, reduced cloudiness, increased surface net insolation, and enhanced adiabatic warming and drying from increased tropospheric subsidence, as well as drying from enhanced offshore low‐level flow. These trends are found to be associated with a widening of the descending branch of the Hadley circulation, consistent with climate model projections under greenhouse gases warming. Due to the relative short (~30 years) data record, the aforementioned trend signals are likely also be affected by phase changes of natural interdecadal variability during the data period. Plain Language Summary: The increase in wildfires in the western United States (WUS) has been attributed to numerous factors, such as enhanced warming, drying, and ignitions by humans or nature and possibly amplified by a regional climate feedback. However, the mechanisms of the feedback are not well understood. Our observational analyses show that the increase in wildfires in the WUS is likely linked to a multi‐decadal drying trend in the subtropical troposphere associated with the expansion of the Hadley circulation under greenhouse‐gas warming. This circulation change induces a regional climate feedback, involving reduced relative humidity, fewer clouds, more downward surface insolation, warmer land surfaces, enhanced subsidence, and stronger offshore low‐level winds. This results in accelerated and sustained tropospheric warming and drying, exacerbating wildfires in the WUS. Results suggest that if actions to combat climate change are not taken soon, the WUS wildfire situation will likely worsen quickly. Key Points: Tropospheric warming and drying, induced by a regional climate feedback spurred on by the expansion of the Hadley circulation under global warming, enhance and sustain the recent long‐term increasing trend in large wildfires in the western United StatesDue to its unique climatology, western United States has the most robust long‐term large wildfire increasing trend in North America during 1984–2014Warming and drying by adiabatic compression of sinking air, and increased low level offshore, downslope winds play key roles [ABSTRACT FROM AUTHOR]

Heat waves have pronounced impacts on human health, ecosystems, and society. Heat waves have become more frequent and intense globally and are likely to intensify further in a warming climate. Across the United States there is a warming trend in average surface temperatures, but concordant increase in heat wave severity appears absent. Limitations in heat waves studies may be responsible for limited detection of a heat wave warming signal. We track daily spatiotemporal evolution of heat waves using geometric concepts and clustering algorithms to investigate how heat manifests on the land surface. We develop a spatial metric combining heat wave frequency, magnitude, duration, and areal extent. We find mixed trends in some individual heat wave characteristics across the United States during 1981–2018. However, exploration of the spatiotemporal evolution of combined heat wave characteristics shows considerable increases during this period and indicates a substantial increase in heat wave hazard across the United States. Plain Language Summary: Heat waves are detrimental to human health and the environment and are projected to intensify in the future. However, observed upward trends in heat wave severity have not previously been detected in some regions of the globe, including the United States. This study considers heat waves as spatiotemporal events allowing for detection of significant increases in severity and coverage across the United States. Our study outlines a novel approach that combines geometric concepts with a clustering algorithm to investigate how heat waves evolve. We track heat waves daily across the ground surface and capture the combination of frequency, magnitude, duration, and areal extent using a new index that provides a more complete picture of heat waves. Our results indicate significant increases in heat waves across the United States during the last four decades. Key Points: A new spatial metric tracks daily heat wave evolution finding a significant upward trend in heat wave severity and coverage 1981–2018The observed upward trend is not captured by examining individual heat wave characteristics such as frequency, magnitude, or durationFindings suggest a substantial increase in the heat wave burden across the United States during the last four decades [ABSTRACT FROM AUTHOR]

Impacts modelers and stakeholders use publicly available data sets of downscaled climate projections to assess and design infrastructure for changes in future rainfall extremes. If differences across data sets exist, infrastructure resilience decisions could change depending on which single data set is used. We assess changes in U.S. rainfall extremes from 2044–2099 compared with 1951–2005 based on 227 projections under RCP4.5 and RCP8.5 from five widely used data sets. We show there are large differences in the change magnitude and its spatial structure between data sets. At the continental scale, the data sets show different increases, with high‐end extremes (e.g. 100‐year event) generally increasing more (between 10% and 50%) than low‐end extremes (e.g. 5‐year). These differences largely contribute to the overall uncertainty for small average recurrence intervals (ARIs) extremes (2‐ to 10‐year), while uncertainties due to short record length dominate large ARIs (25‐ to 100‐year). The results indicate that robust infrastructure planning should consider these uncertainties to enable resilient infrastructure under climate change. Plain Language Summary: Observed extreme rainfall magnitudes have increased since 1950, and climate model projections indicate that these increases will continue throughout the 21st century in many areas in the US. Adapting and designing infrastructure for climate change requires future extreme rainfall projections at high resolutions. Global climate model (GCM) output resolution is generally much coarser, and methods have been developed to create relevant climate information at regional scales. Multiple open data sets exist that provide downscaled projections of future rainfall extremes. We analyze changes in future daily extremes using five widely used data sets in climate change impacts assessments and decision making. We found large differences between data sets in how much and where extreme events will intensify by the end of the 21st century. This and other sources of uncertainty need to be considered when designing resilient infrastructure. Key Points: Extreme daily rainfall changes for the United States from five widely used public downscaled climate projection data sets are comparedLarge differences in magnitude and spatial patterns of projected extreme precipitation changes exist between data setsHigh‐end extremes (e.g., 100‐year event) increase 10–50 % faster than low‐end extremes (e.g., 2‐year event) at the continental scale [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) generate extreme precipitation with severe impacts across large coastal and inland areas, calling for accurate frequency estimation methods. Statistical approaches that take into account the physical mechanisms responsible for these extremes can help reduce the estimation uncertainty. Here we formulate a mixed‐population Metastatistical Extreme Value Distribution explicitly incorporating non‐TC and TC‐induced rainfall and evaluate its implications on long series of daily rainfall for six major U.S. urban areas impacted by these storms. We find statistically significant differences between the distributions of TC‐ and non‐TC‐related precipitation; moreover, including mixtures of distributions improves the estimation of the probability of extreme precipitation where TCs occur more frequently. These improvements are greater when rainfall aggregated over durations longer than one day are considered. Plain Language Summary: The accurate estimation of the frequency of extreme rainfall has broad implications in designing mitigation measures, policy making, risk management, geology/geomorphology, insurance and reinsurance, and water‐borne disease prevention and management. In many parts of the world tropical cyclones play a significant role in generating heavy rainfall, but the evaluation of their contribution to the frequency of extremes is problematic, due to the low number of tropical cyclones in the measured historical record. Here, we introduce a new statistical tool that explicitly includes tropical cyclone rainfall together with rainfall generated by other physical mechanisms and provides a way to maximize the information that can be extracted from available observations. When applied to locations on the U.S. eastern seaboard, we find that this method significantly improves estimates of extreme rainfall. Key Points: We study rainfall extremes from tropical cyclone (TC) and non‐TC rainfall mixtures at six U.S. locationsThe Metastatistical Extreme Value Distribution based on mixed populations outperforms single population formulationsThe advantage of considering different rainfall sources is greater for 3‐day cumulative rainfall [ABSTRACT FROM AUTHOR]

Water security is tightly connected with the food security, ecological health, and economic prosperity of a region. In this study, a comprehensive water security assessment based on water footprint concepts from 1995 to 2015 was performed for the counties located in the Contiguous States of the Unites States. The availability of blue water (e.g., surface water) is comparatively less in the western river basins, and most of the rainfed agricultural lands in the eastern United States were characterized by the lower levels of green water (e.g., root zone soil moisture) storage. This integrated assessment of the water security indicators can directly map the critical regions and reveal the dependence between human water consumption, crop water requirements and environmental flow. This analysis can be further extended to incorporate climate change and extreme drought events to inform specific locations (e.g., counties and watersheds) at which problems of water conflict are more likely to occur. Plain Language Summary: The spatial and temporal changes in climate variables (e.g., precipitation and temperature) control the water supply within a river basin. Concurrently, variability in sectorial water demands is determined by agricultural and human usage within a river basin. Therefore, it is important to integrate supply and demand components to investigate water security within a river basin. This study investigates the spatiotemporal variability of water security indicators such as blue water scarcity, green water scarcity, and Falkenmark Indicators across the major river basins of the continental United States. We provide a first‐ever assessment of water security based on climate and demand‐driven water availability based on the selected sectors for the 18 major river basins of the CONUS (Contiguous States of the Unites States). We believe that our findings will provide insight into water supply and demand and related water security components in the CONUS. The results of this analysis will be useful in developing regional water management programs as well as in identifying key vulnerable river basins in the CONUS. Key Points: Influence of hydroclimatic and anthropogenic factors on water security indicators are investigatedSignificant decrease of blue water availability is evident in the central and western river basinsCalifornia and Lower Colorado River basins are characterized by severe water scarcity and absolute water stress [ABSTRACT FROM AUTHOR]

Plant response to elevated CO2 concentration is known to increase leaf‐level water‐use efficiency through a reduction in stomatal opening. Recent studies have emphasized that increased plant water‐use efficiency can ameliorate the impact of drought due to climate change. However, there is a potentially counterbalancing impact due to the increased leaf area. We investigate long‐term trends (1951 to 2015) of observed streamflow in the Southeastern United States (SE US) and quantify the contribution of major drivers of streamflow changes using single factor climate modeling experiments from Community Land Model Version 5 (CLM5). The SE US streamflow observations do not exhibit a trend, which is in agreement with the CLM5 control experiment. Using the factorial set of CLM5 experiments, we find that increased leaf area under elevated CO2 leads to decreased runoff and completely counteracts increased runoff due to water‐use efficiency gains under elevated CO2 and land‐use change. Plain Language Summary: Understanding drivers of hydrological changes are societally important. Many studies have investigated the effects of climate change and land‐use change on the regional water cycle. However, the effect of plant response under elevated CO2 concentration is less known. Plant response can play two primary roles: (1) It can increase water availability due to increased water‐use efficiency, and (2) it can decrease water availability due to increased plant growth. The observations show no significant changes in water availability from 1951 to 2015 in the Southeastern United States (SE US). Climate modeling experiments show that plant growth under elevated CO2 concentration has negated the effect of increased water‐use efficiency on water availability in the SE US. Hence, we conclude that the plant growth, this seemingly less known and slowly moving driver, can play an important role in the water cycle changes at the regional scale. Key Points: Long‐term streamflow observations (1951 to 2015) do not exhibit a significant trend in the Southeastern United StatesIncreased leaf area or plant growth under elevated CO2 decreases runoff or streamflowPlant growth completely counteracts increased runoff due to water‐use efficiency gains under elevated CO2 [ABSTRACT FROM AUTHOR]

Upright convection can impact extratropical cyclone (ETC) precipitation and dynamics differently than isentropic ascent, but how often it occurs and how much it contributes to total precipitation within an ETC have not been systematically documented in previous literature. Herein, convection in ETCs is analyzed using ground‐based radar observations over the Eastern United States. Convection occupies 1%–5% of the precipitating region and constitutes 1%–15% of total cyclone precipitation. Furthermore, the location of convective activity occurs preferentially in the warm sector early in a cyclone's life cycle, and then as the storm evolves, more convection occurs along and behind the cold front. The precipitation rates in regions with convection are more likely to be stronger than those in other precipitating regions of the cyclone. However, the cyclones with the largest area‐average precipitation rates include only a small contribution from convection. Plain Language Summary: This research is motivated by the potential influence of convection on extratropical cyclone circulation. We utilize a newly derived dataset of upright convection and a cyclone‐tracking framework to quantify convective activity in extratropical cyclones over the United States, east of the Rocky Mountains. We find that upright convection only occupies a small portion of the precipitating region, and the relative contribution to total precipitation has relatively small variability as the cyclone evolves. We find that the location of convective activity occurs preferentially in the warm sector early in a cyclone's life cycle, and as the storm evolves, more convection occurs along and behind the cold front. We find that precipitation rates in regions with convection are more likely to be stronger than those in other precipitating regions of the cyclone. However, the cyclones with the largest area‐average precipitation rates include only a small contribution from convection. Key Points: Convection occurs in 1%–5% of precipitating regions of extratropical cyclones over eastern United States and contributes 1%–15% of total precipitationThe majority of upright convection occurs ahead of the cold front and disperses into other regions as the cyclone agesWhile convection produces larger rain rates, cyclones with greater total precipitation do not have a large convective contribution [ABSTRACT FROM AUTHOR]

We present multilayer observations and numerical simulations of gravity waves (GWs) generated by a series of Mesoscale Convective Systems over the midwestern United States. Strong semiconcentric GWs were observed and modeled, which couple from their tropospheric sources to the thermosphere, displaying strong nonlinearity indicated by instability, breaking, and formation of turbulent vortices. GWs in the stratosphere display a large range of horizontal scales from 34–400 km; however, the smaller wavelength waves break rapidly in the mesosphere and lower thermosphere. Larger‐scale (≥150 km) waves dominate in the thermosphere and display northwestward propagation at 200–300 km altitude, opposing the mean winds. Despite strong molecular viscosity and thermal conductivity in the thermosphere, steepened wave fronts, which may indicate nonlinearity, is identified in 630 nm airglow imagers. The agreement between model and data suggests new opportunities for data‐constrained simulations that span multilayer observables, including mesosphere and lower thermosphere‐region airglow not captured for this event. Key Points: Coherent gravity waves were observed above thunderstorms, in the stratosphere by AIRS and thermosphere by MANGOSimulations of waves generated by convective sources defined by radar data closely match the observations in scaleResults indicate that gravity waves may evolve nonlinearly well into the thermosphere and ionosphere [ABSTRACT FROM AUTHOR]

Fracture cementation is an important control on the recovery of prefailure levels of permeability and strength in faults. The timescales of this process, however, are almost entirely unknown from direct analysis of the rock record. We report U‐Th dating results that quantify rates of fracture cementation in syntectonic calcite veins from the Loma Blanca fault, New Mexico, USA. Measured rates vary from ~0.05 to 0.80 mm/ka and exhibit a power function correlation with minimum fracture apertures. We argue that this correlation is the result of crystal growth in a transport‐limited system, where cementation rates were proportional to rates of postseismic fluid flow in individual fractures. We further argue that such transport‐limited, flux‐dependent cementation necessarily leads to a heterogeneous distribution of permeability and strength recovery as fluids migrate through fault‐zone fracture networks. These heterogeneities may influence rupture propagations pathways and the continual development of fault‐zone architecture/complexity. Plain Language Summary: Fractures formed during earthquakes greatly increase the permeability of fault zones while decreasing their strength, thereby exerting a significant influence on the cycle of earthquakes in the crust. Permeability and strength, however, experience partial recovery during interseismic times, a process referred to as fault or fracture "healing." Precipitation of minerals within fractures is commonly cited as an important control on healing, but rates of this process are largely unknown. We present the results of a novel sampling approach which allowed us to estimate the rates of fracture cementation in a seismogenic fault in New Mexico, USA. Our results show that cementation rates are highly variable among individual fractures. Rates of fracture cementation are strongly correlated with the aperture (or width) of the original fracture during healing. We conclude that cementation rates that are dependent on rates of fluid flow through individual fractures following earthquakes, with the widest fractures accommodating more fluid flow and rapid healing. This suggests healing of faults during interseismic periods is spatially heterogeneous and continuously migrates as fracture networks evolve. Key Points: U‐Th dating was used to estimate the timescales of calcite cementation and healing/sealing in fault‐localized fracturesResults suggest that cementation rates are "flux dependent" and proportional to rates of postseismic fluid flow through fracturesThis dependency likely leads to heterogeneous distributions of postseismic recovery of permeability and strength in fault damage zones [ABSTRACT FROM AUTHOR]