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Atmospheric rivers (ARs) significantly impact the hydrological cycle and associated extremes in western continental regions. Recent studies suggest ARs also influence water resources and extremes in continental interiors. AR detection tools indicate that AR conditions are relatively frequent in areas east of the Rocky Mountains. The origin of these ARs, whether from synoptic‐scale waves or mesoscale processes, is unclear. This study uses meteorological composite maps and transects of AR conditions during the four seasons. The analysis reveals that ARs east of the Rockies are associated with long‐wave, baroclinic Rossby waves. This result demonstrates that eastern North American ARs are dynamically similar to their western coastal counterparts, though mechanisms for vertical moisture flux differ between the two. These findings provide a foundation for understanding future climate change and ARs in this region and offer new methods for evaluating climate model simulations. Plain Language Summary: Atmospheric rivers (ARs) are a weather pattern that brings high amounts of atmospheric water and winds in a relatively narrow region. ARs are typically considered a "west coast" phenomenon, largely because the majority of the scientific research on ARs has focused on ARs in western coastal regions: particularly the western United States (US). ARs occur in continental interiors, but there has been some debate about whether these ARs represent the same type of weather as those in western coastal regions. This paper uses two objective methods for identifying ARs and finds times when ARs are present in three locations in the eastern half of the US: Norman, OK, Bloomington, IN, and Washington, DC. Examination of weather conditions during these AR times shows remarkable similarity to conditions associated with west coast ARs. This gives strong evidence that ARs do occur in the eastern half of the US. This result is important because it suggests that ARs may be important for water resources and extreme weather in the eastern half of the US, just as they are in the western US. This result also suggests that ARs may be important for water resources and extremes in other continental interiors. Key Points: Atmospheric rivers (ARs) east of the Rockies are associated with baroclinic wavesWestern coastal ARs and eastern/midwest ARs are dynamically similarSynoptic‐scale uplift, combined with convective instability, provide efficient mechanisms for generating precipitation [ABSTRACT FROM AUTHOR]

The research on the trends of mountainous aridity and the issue of elevation‐dependent aridity (EDA) has long been hindered by limitations in data validity. In this study, we present global monthly merged data sets of Vapor Pressure Deficit and Aridity Index (AI) from 1960 to 2020, aiming to detect and attribute elevation‐dependent patterns of atmospheric and soil aridity in six representative high mountainous areas worldwide. Our findings reveal that most of the mountainous regions experienced significant aridification after the 1970s (p < 0.05). The Rocky Mountains and Ethiopian Highlands are identified as the most vulnerable areas, with both atmospheric and soil aridity increasing by 13% across all elevation gradients. Significant humidification has been observed only in High Asian Regions at 4,000 m above sea level with an approximate decrease of 11% in soil AI. In both temporal and spatial patterns, soil aridity exhibits stronger heterogeneity compared to atmospheric aridity, with certain regions and seasons showing humidification, despite the overall aridification trend. Elevation‐dependent aridity is observed in two‐thirds of the mountains, but whether high altitude alleviates or amplifies aridity depends on the pattern of precipitation changes at different elevations. The rise in air temperature is the primary driving factor for soil and atmospheric aridification, contributing to over 50% of each. In two‐thirds of the regions, changes in precipitation exacerbate soil aridity. Simulations show that human activities are closely related to the ongoing prolonged atmospheric aridification. This study contributes to a comprehensive understanding of global mountainous aridity evolution projected under climate change. Plain Language Summary: Due to limitations in data validity, the conclusions regarding mountainous aridity changes and related elevation‐dependent aridity issues have often been contradictory. To address this issue, we generated a comprehensive data set of drought indices by integrating observed and simulated data, covering the period from 1960 to 2020. Our analysis revealed that the 1970s marked a significant turning point for aridity patterns in mountainous regions globally. Since then, except for the High Asian Regions, both soil and atmospheric aridity have exhibited a rapid increase in mountainous areas worldwide, with the most severe aridification observed in the Rocky Mountains and Ethiopian Highlands. We also identified a certain relationship between the severity of aridification and elevation gradients, although it is not a straightforward relationship where higher elevations necessarily experience more severe aridification. Importantly, our attribution analysis suggests that human activities may impact the observed atmospheric aridification in mountainous regions on a global scale. Key Points: The period from 1970 to 1980 witnessed a significant shift from humidification to aridification in most mountainous regions worldwideThe relationship between changes in precipitation and elevation gradients shapes the distinct patterns of elevation‐dependent aridityProlonged atmospheric aridification in mountainous regions may not be solely attributed to natural variability [ABSTRACT FROM AUTHOR]

Clumped isotope paleothermometry using pedogenic carbonates is a powerful tool for investigating past climate changes. However, location‐specific seasonal patterns of precipitation and soil moisture cause systematic biases in the temperatures they record, hampering comparison of data across large areas or differing climate states. To account for biases, more systematic studies of carbonate forming processes are needed. We measured modern soil temperatures within the San Luis Valley of the Rocky Mountains and compared them to paleotemperatures determined using clumped isotopes. For Holocene‐age samples, clumped isotope results indicate carbonate accumulated at a range of temperatures with site averages similar to the annual mean. Paleotemperatures for late Pleistocene‐age samples (ranging 19–72 ka in age) yielded site averages only 2°C lower, despite evidence that annual temperatures during glacial periods were 5–9°C colder than modern. We use a 1D numerical model of soil physics to support the idea that differences in hydrologic conditions in interglacial versus glacial periods promote differences in the seasonal distribution of soil carbonate accumulation. Model simulations of modern (Holocene) conditions suggest that soil drying under low soil pCO2 favors year‐round carbonate accumulation in this region but peaking during post‐monsoon soil drying. During a "glacial" simulation with lowered temperatures and added snowpack, more carbonate accumulation shifted to the summer season. These experiments show that changing hydrologic regimes could change the seasonality of carbonate accumulation, which in this study blunts the use of clumped isotopes to quantify glacial‐interglacial temperature changes. This highlights the importance of understanding seasonal biases of climate proxies for accurate paleoenvironmental reconstruction. Plain Language Summary: Reconstructing the amount of temperature change associated with past climate changes for individual regions is important for understanding their climate vulnerability. Carbonate minerals developed naturally in desert soils record past temperatures in the numbers of their rare isotopes, called clumped isotopes. However, the temperature recorded in soil minerals is linked to the time of year they form, which varies greatly from winter to summer, so understanding the timing is key to interpreting past climate. We measured underground temperatures in the southern Rocky Mountains, compared them to mineral temperatures from young soils, and found that they record mean annual soil temperature. In contrast, temperatures recorded by soil minerals during the last ice age were only 2°C colder than young soil temperatures, despite evidence that ice age air temperatures were 5–9°C colder. We performed numerical modeling to predict the seasonal timing of soil carbonate accumulation under interglacial and glacial climate states and found that carbonate likely forms year‐round during interglacial states but forms during the summertime under glacial conditions due to delayed melting of snow under colder temperatures. This lowers the difference between glacial and interglacial temperatures, which is important to account for when quantifying past climate change for the region. Key Points: Clumped isotope temperatures for soil carbonate are biased to different seasons in different regions and time periods depending on climateIn the San Luis Valley, USA, monitoring, modeling, and isotope results suggest carbonate accumulation throughout the year in the HoloceneIn the glacial late Pleistocene, clumped isotopes and soil modeling indicate longer snow cover shifted carbonate accumulation to the summer [ABSTRACT FROM AUTHOR]

Flooding is one of the most devastating natural disasters causing significant economic losses. One of the dominant drivers of flood losses is heavy precipitation, with other contributing factors such as built environments and socio‐economic conditions superimposed to it. To better understand the risk profile associated with this hazard, we develop probabilistic models to quantify the future likelihood of fluvial flood‐related property damage exceeding a critical threshold (i.e., high property damage) at the state level across the conterminous United States. The model is conditioned on indicators representing heavy precipitation amount and frequency derived from observed and downscaled precipitation. The likelihood of high property damage is estimated from the conditional probability distribution of annual total property damage, which is derived from the joint probability of the property damage and heavy precipitation indicators. Our results indicate an increase in the probability of high property damage (i.e., exceedance of 70th percentile of observed annual property damage for each state) in the future. Higher probability of high property damage is projected to be clustered in the states across the western and south‐western United States, and parts of the U.S. Northwest and the northern Rockies and Plains. Depending on the state, the mean annual probability of high property damage in these regions could range from 38% to 80% and from 46% to 95% at the end of the century (2090s) under RCP4.5 and RCP8.5 scenarios, respectively. This is equivalent to 20%–40% increase in the probability compared to the historical period 1996–2005. Results show that uncertainty in the projected probability of high property damage ranges from 14% to 35% across the states. The spatio‐temporal variability of the uncertainty across the states and three future decades (i.e., 2050s, 2070s, and 2090s) exhibits nonstationarity, which is driven by the uncertainty associated with the probabilistic prediction models and climate change scenarios. Plain Language Summary: Floods create significant economic losses in the United States and many other places across the world. Floods and flood‐related losses are expected to change due to changes in heavy precipitation in a warmer climate. Inferring how (including when and where) flood‐related losses could change in the future is crucial because of significant implications for flood risk management, insurance, and infrastructure resilience. We develop probabilistic models to project the likelihood of (fluvial) flood‐related high property damage (annual total property damage exceeding a critical threshold) conditioning on precipitation indicators under two greenhouse gas emission scenarios. We estimate relatively higher probability of high property damage for the states across the western and south‐western U.S. and parts of the U.S. Northwest and the northern Rockies and Plains, where projected changes range from 46% to 95% for a high‐emission scenario. In these regions, future changes in the probability of high property damage compared to the historical period vary from 20% to 40%. Overall, our results identify regions with higher likelihood of high property damage in the future, and they are useful for developing long‐term planning and resource mobilization, adaptation, and insurance instruments. Key Points: Future likelihood of flood‐related property damage is quantified using probabilistic models conditioned on precipitation indicatorsIncrease in the probability of flood‐related property damage is projected toward the mid and end of the century across the USNonstationary uncertainties in the projected flood‐related property damage originate from the probabilistic models and climate scenarios [ABSTRACT FROM AUTHOR]

Increased wildfire activity and climate change have intensified disturbance regimes globally and have raised concern among scientists and land managers about the resilience of disturbed landscapes. Here we test the effects of climate, topographic variation and pre‐fire stand structure on regeneration in lodgepole pine (Pinus contorta var. latifolia) forests following high‐severity fire over the past seven decades.We surveyed lodgepole pine regeneration 8–67 years after eight high‐severity fires in western Colorado and southern Wyoming. We used dendroecological methods and machine learning to (a) identify temporal trends in post‐fire regeneration and (b) examine influences of climate on post‐fire regeneration, with focus on post‐fire establishment, initial post‐fire density and radial growth.All burned sites reached a median stocking density of ≥150 seedlings/ ha, but there was a large range of spatial heterogeneity, with regeneration being absent or scarce in many plots, implying a trend of increasing patchiness with likely cascading effects on subsequent patterns and processes. Our analysis indicated that (a) post‐fire regeneration is influenced by pre‐fire stand structure (stand age and density), elevation and post‐fire minimum temperature; (b) pre‐fire densities of >14,000 stems/ha promoted successful stocking (≥150 seedlings/ha) and reduced lag between the disturbance and initial regeneration; and (c) minimum post‐fire temperatures >−1.6°C reduced lag of initial regeneration and promoted initial radial growth.Synthesis. Our study demonstrates that lodgepole pine in high‐elevation forests are regenerating following fires under recent climatic trends, but that regeneration is affected by post‐fire climatic conditions. Importantly, forest patchiness may be increasing in a way that affects future ecological dynamics and may compromise the resilience of these systems. [ABSTRACT FROM AUTHOR]