Precipitation regime change in Western North America: The role of Atmospheric Rivers

Role of atmospheric rivers in shaping long term Arctic moisture variability

Atmospheric rivers (ARs) reaching high-latitudes in summer contribute to the majority of climatological poleward water vapor transport into the Arctic. This transport has exhibited long term changes over the past decades, which cannot be entirely explained by anthropogenic forcing according to ensemble model responses. Here, through observational analyses and model experiments in which winds are adjusted to match observations, we demonstrate that low-frequency, large-scale circulation changes in the Arctic play a decisive role in regulating AR activity and thus inducing the recent upsurge of this activity in the region. It is estimated that the trend in summertime AR activity may contribute to 36% of the increasing trend of atmospheric summer moisture over the entire Arctic since 1979 and account for over half of the humidity trends in certain areas experiencing significant recent warming, such as western Greenland, northern Europe, and eastern Siberia. This indicates that AR activity, mostly driven by strong synoptic weather systems often regarded as stochastic, may serve as a vital mechanism in regulating long term moisture variability in the Arctic.

Spatial diversity of atmospheric moisture transport and climate teleconnections over Indian subcontinent at different timescales

Regional weather and climate are generally impacted by global climatic phenomenon's. Understanding the impact of global climate phenomenon's on an atmospheric branch of the hydrological cycle is crucial to make advances in skillful precipitation forecast. The present study adopts a multiscale approach based on wavelets for unravelling the linkages between teleconnections and atmospheric moisture transport over homogeneous regions of Indian sub-continent. We investigated linkages between atmospheric moisture transport quantified as monthly integrated water vapor transport (IVT) during 1951-2022 over selected homogeneous regions and eight large scale climate oscillations using wavelet and global wavelet coherence. Our results indicate significant heterogeneity in linkages across different regions and across multiple timescales. In particular, the Indian Ocean Dipole (IOD) influence monthly IVT at intra-annual to inter-annual scale over all regions. The El Niño-Southern Oscillation (ENSO) have strong connection to monthly IVT at inter-annual scale whereas over west central region both IOD and ENSO strongly influence IVT at inter-decadal scale. While the Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation have an impact on IVT in the north-east and southern regions, the Arctic Oscillation and North Atlantic oscillation have a strong inter-annual connection to IVT, majorly in the northwest and hilly regions. Overall, the methodology offers an effective approach for capturing the dynamics of atmospheric moisture transport in time-frequency space and provide a practical reference for prediction of atmospheric moisture transport linked precipitation over different regions of Indian subcontinent.

Temporal compounding increases economic impacts of atmospheric rivers in California

Temporally compounding atmospheric river (AR) events cause severe flooding and damage in California. However, the contribution of temporal compounding to AR-induced loss has yet to be systematically quantified. We show that the strongest ARs are more likely to be part of sequences, which are periods of elevated hydrologic hazard associated with temporally clustered ARs. Sequences increase the likelihood of flood-related impacts by 8.3% on AR days and 5.4% on non-AR days, and across two independent loss datasets, we find that ARs within sequences have over three times higher expected losses compared to ARs outside of sequences. Expected losses also increase when the preceding AR is higher intensity, when time since the preceding AR is shorter, and when an AR is the second or later event within a sequence. We conclude that temporal compounding is a critical source of information for predicting an AR's potential consequences.

Power spectral estimate for discrete data

The identification of cycles in periodic signals is a ubiquitous problem in time series analysis. Many real-world datasets only record a signal as a series of discrete events or symbols. In some cases, only a sequence of (non-equidistant) times can be assessed. Many of these signals are furthermore corrupted by noise and offer a limited number of samples, e.g., cardiac signals, astronomical light curves, stock market data, or extreme weather events. We propose a novel method that provides a power spectral estimate for discrete data. The edit distance is a distance measure that allows us to quantify similarities between non-equidistant event sequences of unequal lengths. However, its potential to quantify the frequency content of discrete signals has so far remained unexplored. We define a measure of serial dependence based on the edit distance, which can be transformed into a power spectral estimate (EDSPEC), analogous to the Wiener-Khinchin theorem for continuous signals. The proposed method is applied to a variety of discrete paradigmatic signals representing random, correlated, chaotic, and periodic occurrences of events. It is effective at detecting periodic cycles even in the presence of noise and for short event series. Finally, we apply the EDSPEC method to a novel catalog of European atmospheric rivers (ARs). ARs are narrow filaments of extensive water vapor transport in the lower troposphere and can cause hazardous extreme precipitation events. Using the EDSPEC method, we conduct the first spectral analysis of European ARs, uncovering seasonal and multi-annual cycles along different spatial domains. The proposed method opens new research avenues in studying of periodic discrete signals in complex real-world systems.

Oceanic and terrestrial origin of precipitation over 50 major world river basins: Implications for the occurrence of drought

The terrestrial and oceanic origins of precipitation over 50 major river basins worldwide were investigated for the period 1980-2018. For this purpose, we used a Lagrangian approximation that calculates the humidity that results in precipitation from the entire ocean area (ocean component of the precipitation, PLO) and the entire land area (land component, PLT) as well as the sum of both components (Lagrangian precipitation, PL). PL and its components were highly correlated with precipitation over the basins, where PLT accounted for >50 % of the PL in most of them. This confirmed the importance assigned by previous studies to terrestrial recycling of precipitation and moisture transport within the continents. However, the amount of PLO in almost all North American river basins was highlighted. The assessment of drought conditions through the Standardized Precipitation Index (SPI) at a temporal scale of 1- and 3-months revealed the number of drought episodes that affected each river basin, especially the Amazon, Congo, and Nile, because of the lower number of episodes but higher average severity and duration. A direct relationship between the severity of drought episodes and the respective severity computed on the oceanic and terrestrial SPI series was also found for the majority of basins. This highlights the influence of the severity of the SPI of oceanic origin for most basins in North America. However, for certain basins, we found an inverse relationship between the severity of drought and the associated severity according to the SPI of oceanic or terrestrial origin, thus highlighting the principal drought attribution. Additionally, a copula analysis provided new information that illustrates the estimated conditional probability of drought for each river basin in relation to the occurrence of drought conditions of oceanic or terrestrial origin, which revealed the possible main driver of drought severity in each river basin.

A comprehensive meta-analysis of the impacts of intensified drought and elevated CO2 on forage growth

Forage crops are used worldwide as key feed sources for dairy systems. However, their productivity and quality are limited due to intensified drought events, elevated carbon dioxide (CO₂), and their interaction with climate change, with consequences for the security of animal husbandry and the agricultural economy. Although studies have quantified the impacts of such stresses on forage growth, these impacts have been less systematically investigated in a global context due to differences among various forage groups, regional microclimates, and environmental factors. Herein we employed nine forage growth-related variables involving three perspectives, i.e., photosynthetic parameters, production, and quality, from research articles published between 1990 and 2021 via a meta-analysis. A linear mixed-effect model was then used to explore the quantitative relationship between these factors in a restricted dataset. Decreasing trends in all four photosynthetic parameters were detected across different eco-geographical regions with increasing drought stress. The maximum decrease in DMY occurred in the Mediterranean, with 52.8% under drought conditions. Globally, eCO₂ significantly increased photosynthetic rate (P_n) and instantaneous water use efficiency (WUE_i) by 40.8% and 62.1%, respectively, which also had positive effects on forage dry matter yield (DMY) (+25.1%), especially for forage in Northern Europe. However, this stress would significantly decrease forage quality by decreasing crude protein (CP) (-19.7%) and nitrogen content (N content) (-13.5%). These negative impacts would be aggravated under the co-occurrence of drought and eCO₂, including a significant increase in WUE_i (+111.1%) and a decrease in DMY (-12.3%). Gramineae showed a more sensitive response to drought stress in photosynthetic parameters and DMY than Leguminosae, but the latter exhibited a better response in photosynthetic parameters and production under eCO₂. Our analysis provides a consensus concerning how the growth parameters of forage have changed under environmental stresses.

Uncovering social and environmental factors that increase the burden of climate-sensitive diarrheal infections on children

Climate-sensitive infectious diseases are an issue of growing concern due to global warming and the related increase in the incidence of extreme weather and climate events. Diarrhea, which is strongly associated with climatic factors, remains among the leading causes of child death globally, disproportionately affecting populations in low- and middle-income countries (LMICs). We use survey data for 51 LMICs between 2000 and 2019 in combination with gridded climate data to estimate the association between precipitation shocks and reported symptoms of diarrheal illness in young children. We account for differences in exposure risk by climate type and explore the modifying role of various social factors. We find that droughts are positively associated with diarrhea in the tropical savanna regions, particularly during the dry season and dry-to-wet and wet-to-dry transition seasons. In the humid subtropical regions, we find that heavy precipitation events are associated with increased risk of diarrhea during the dry season and the transition from dry-to-wet season. Our analysis of effect modifiers highlights certain social vulnerabilities that exacerbate these associations in the two climate zones and present opportunities for public health intervention. For example, we show that stool disposal practices, child feeding practices, and immunizing against the rotavirus modify the association between drought and diarrhea in the tropical savanna regions. In the humid subtropical regions, household's source of water and water disinfection practices modify the association between heavy precipitation and diarrhea. The evidence of effect modification varies depending on the type and duration of the precipitation shock.

Watershed memory amplified the Oroville rain-on-snow flood of February 2017

Mountain snowpacks are transitioning to experience less snowfall and more rainfall as the climate warms, creating more persistent low- to no-snow conditions. This precipitation shift also invites more high-impact rain-on-snow (ROS) events, which have historically yielded many of the largest and most damaging floods in the western United States. One such sequence of events preceded the evacuation of 188,000 residents below the already-damaged Oroville Dam spillway in February 2017 in California's Sierra Nevada. Prior studies have suggested that snowmelt during ROS dramatically amplified reservoir inflows. However, we present evidence that snowmelt may have played a smaller role than previously documented (augmenting terrestrial water inputs by 21%). A series of hydrologic model experiments and subdaily snow, soil, streamflow, and hydrometeorological measurements demonstrate that direct, "passive" routing of rainfall through snow, and increasingly efficient runoff driven by gradually wetter soils can alternatively explain the extreme runoff totals. Our analysis reveals a crucial link between frequent winter storms and a basin's hydrologic response-emphasizing the role of soil moisture "memory" of within-season storms in priming impactful flood responses. Given the breadth in plausible ROS flood mechanisms, this case study underscores a need for more detailed measurements of soil moisture along with in-storm changes to snowpack structure, extent, energy balance, and precipitation phase to address ROS knowledge gaps associated with current observational limits. Sharpening our conceptual understanding of basin-scale ROS better equips water managers moving forward to appropriately classify threat levels, which are projected to increase throughout the mid-21st century.

The climate change mitigation potential of annual grasslands under future climates

Composted manure and green waste amendments have been shown to increase net carbon (C) sequestration in rangeland soils and have been proposed as a means to help lower atmospheric CO₂ concentrations. However, the effect of climate change on soil organic C (SOC) stocks and greenhouse gas emissions in rangelands is not well understood, and the viability of climate change mitigation strategies under future conditions is even less certain. We used a process-based biogeochemical model (DayCent) at a daily time step to explore the long-term effects of potential future climate changes on C and greenhouse gas dynamics in annual grassland ecosystems. We then used the model to explore how the same ecosystems might respond to climate change following compost amendments to soils and determined the long-term viability of net SOC sequestration under changing climates. We simulated net primary productivity (NPP), SOC, and greenhouse gas fluxes across seven California annual grasslands with and without compost amendments. We drove the DayCent simulations with field data and with site-specific daily climate data from two Earth system models (CanESM2 and HadGEM-ES) and two representative concentration pathways (RCP4.5 and RCP8.5) through 2100. NPP and SOC stocks in unamended and amended ecosystems were surprisingly insensitive to projected climate changes. A one-time amendment of compost to rangeland acted as a slow-release organic fertilizer and increased NPP by up to 390-814 kg C ha^-1  year^-1 across sites. The amendment effect on NPP was not sensitive to Earth system model or emissions scenario and endured through the end of the century. Net SOC sequestration amounted to 1.96 ± 0.02 Mg C ha^-1 relative to unamended soils at the maximum amendment effect. Averaged across sites and scenarios, SOC sequestration peaked 22 ± 1 years after amendment and declined but remained positive throughout the century. Though compost stimulated nitrous oxide (N₂ O) emissions, the cumulative net emissions (in CO₂ equivalents) due to compost were far less than the amount of SOC sequestered. Compost amendments resulted in a net climate benefit of 69.6 ± 0.5 Tg CO₂ e 20 ± 1 years after amendment if applied to similar ecosystems across the state, amounting to 39% of California's rangeland. These results suggest that the biogeochemical benefits of a single amendment of compost to rangelands in California are insensitive to climate change and could contribute to decadal-scale climate change mitigation goals alongside emissions reductions.

Landscape Genomics to Enable Conservation Actions: The California Conservation Genomics Project

The California Conservation Genomics Project (CCGP) is a unique, critically important step forward in the use of comprehensive landscape genetic data to modernize natural resource management at a regional scale. We describe the CCGP, including all aspects of project administration, data collection, current progress, and future challenges. The CCGP will generate, analyze, and curate a single high-quality reference genome and 100-150 resequenced genomes for each of 153 species projects (representing 235 individual species) that span the ecological and phylogenetic breadth of California's marine, freshwater, and terrestrial ecosystems. The resulting portfolio of roughly 20 000 resequenced genomes will be analyzed with identical informatic and landscape genomic pipelines, providing a comprehensive overview of hotspots of within-species genomic diversity, potential and realized corridors connecting these hotspots, regions of reduced diversity requiring genetic rescue, and the distribution of variation critical for rapid climate adaptation. After 2 years of concerted effort, full funding ($12M USD) has been secured, species identified, and funds distributed to 68 laboratories and 114 investigators drawn from all 10 University of California campuses. The remaining phases of the CCGP include completion of data collection and analyses, and delivery of the resulting genomic data and inferences to state and federal regulatory agencies to help stabilize species declines. The aspirational goals of the CCGP are to identify geographic regions that are critical to long-term preservation of California biodiversity, prioritize those regions based on defensible genomic criteria, and provide foundational knowledge that informs management strategies at both the individual species and ecosystem levels.

Climate change contributions to future atmospheric river flood damages in the western United States

Atmospheric rivers (ARs) generate most of the economic losses associated with flooding in the western United States and are projected to increase in intensity with climate change. This is of concern as flood damages have been shown to increase exponentially with AR intensity. To assess how AR-related flood damages are likely to respond to climate change, we constructed county-level damage models for the western 11 conterminous states using 40 years of flood insurance data linked to characteristics of ARs at landfall. Damage functions were applied to 14 CMIP5 global climate models under the RCP4.5 "intermediate emissions" and RCP8.5 "high emissions" scenarios, under the assumption that spatial patterns of exposure, vulnerability, and flood protection remain constant at present day levels. The models predict that annual expected AR-related flood damages in the western United States could increase from $1 billion in the historical period to $2.3 billion in the 2090s under the RCP4.5 scenario or to $3.2 billion under the RCP8.5 scenario. County-level projections were developed to identify counties at greatest risk, allowing policymakers to target efforts to increase resilience to climate change.

Life history strategies of stream fishes linked to predictors of hydrologic stability

Life history theory provides a framework to understand environmental change based on species strategies for survival and reproduction under stable, cyclical, or stochastic environmental conditions. We evaluated environmental predictors of fish life history strategies in 20 streams intersecting a national park within the Potomac River basin in eastern North America. We sampled stream sites during 2018–2019 and collected 3801 individuals representing 51 species within 10 taxonomic families. We quantified life history strategies for species from their coordinates in an ordination space defined by trade‐offs in spawning season duration, fecundity, and parental care characteristic of opportunistic, periodic, and equilibrium strategies. Our analysis revealed important environmental predictors: Abundance of opportunistic strategists increased with low‐permeability soils that produce flashy runoff dynamics and decreased with karst terrain (carbonate bedrock) where groundwater inputs stabilize stream flow and temperature. Conversely, abundance of equilibrium strategists increased in karst terrain indicating a response to more stable environmental conditions. Our study indicated that fish community responses to groundwater and runoff processes may be explained by species traits for survival and reproduction. Our findings also suggest the utility of life history theory for understanding ecological responses to destabilized environmental conditions under global climate change.

Datasets for characterizing extreme events relevant to hydrologic design over the conterminous United States

Despite the close linkage between extreme floods and snowmelt, particularly through rain-on-snow (ROS), hydrologic infrastructure is mostly designed based on standard precipitation Intensity-Duration-Frequency curves (PREC-IDF) that neglect snow processes in runoff generation. For snow-dominated regions, such simplification could result in substantial errors in estimating extreme events and infrastructure design risk. To address this long-standing problem, we applied the Next Generation IDF (NG-IDF) technique to estimate design basis extreme events for different durations and return periods in the conterminous United States (CONUS) to distinctly represent the contribution of rain, snowmelt, and ROS events to the amount of water reaching the land surface. A suite of datasets were developed to characterize the magnitude, trend, seasonality, and dominant mechanism of extreme events for over 200,000 locations. Infrastructure design risk associated with the use of PREC-IDF was estimated. Accuracy of the model simulations used in the analyses was confirmed by long-term snow data at over 200 Snowpack Telemetry stations. The presented spatially continuous datasets are readily usable and instrumental for supporting site-specific infrastructure design.

Measurement(s)	gridded precipitation
Technology Type(s)	weather station
Sample Characteristic - Environment	flood • snowmelt • hydrological process
Sample Characteristic - Location	contiguous United States of America

Increases in Future AR Count and Size: Overview of the ARTMIP Tier 2 CMIP5/6 Experiment

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.

Uncertainty in El Niño-like warming and California precipitation changes linked by the Interdecadal Pacific Oscillation

Marked uncertainty in California (CA) precipitation projections challenges their use in adaptation planning in the region already experiencing severe water stress. Under global warming, a westerly jet extension in the North Pacific analogous to the El Niño-like teleconnection has been suggested as a key mechanism for CA winter precipitation changes. However, this teleconnection has not been reconciled with the well-known El Niño-like warming response or the controversial role of internal variability in the precipitation uncertainty. Here we find that internal variability contributes > 70% and > 50% of uncertainty in the CA precipitation changes and the El Niño-like warming, respectively, based on analysis of 318 climate simulations from several multi-model and large ensembles. The Interdecadal Pacific Oscillation plays a key role in each contribution and in connecting the two via the westerly jet extension. This unifying understanding of the role of internal variability in CA precipitation provides critical guidance for reducing and communicating uncertainty to inform adaptation planning.

Climate change and extreme weather: A review focusing on the continental United States

Anthropogenic emissions of greenhouse gases are warming the Earth. It is likely that the greatest impacts of climate change on human and natural systems will come from increasingly frequent and severe extreme weather and climate events. Some increases in such extremes are already being detected, and this trend is projected to continue as Earth warms. Here we review the overarching climate drivers of increases in extreme weather and address the context in which extremes occur and the challenges of projecting future changes. The observational evidence for climate-driven increases in extremes and the implications of model projections are reviewed for heat and drought and several types of storms: tropical cyclones, midlatitude storms, and severe local weather, focusing on those changes most relevant to the continental United States. We emphasize the overall observed and modeled trends in extreme weather in which we have the greatest confidence, because they are consistent with our fundamental understanding of weather and climate. Despite remaining uncertainty about many details, especially in model-based projections, the signal of increasing extremes is sufficiently clear that it demands a robust human response, in limiting future emissions of greenhouse gases and in making our human systems more resilient to further changes that are inevitable as Earth continues to warm.Implications: By placing observed and projected changes in extreme weather in the context of our fundamental understanding of physics and statistics, this review makes it clear that these are significant and impactful changes that demand a robust human response.

A Review of Climate Change Impacts on the USA-Mexico Transboundary Santa Cruz River Basin

In the parched Upper Santa Cruz River Basin (USCRB), a binational USA–Mexico basin, the water resources depend on rainfall-triggered infrequent flow events in ephemeral channels to recharge its storage-limited aquifers. In-situ data from the basin highlight a year-round warming trend since the 1980s and a concerning decline in average precipitation (streamflow) from 1955–2000 to 2001–2020 by 50% (87.6%) and 17% (63%) during the winter and summer, respectively. Binational sustainable management of the basins water resources requires a careful consideration of prospective climatic changes. In this article we review relevant studies with climate projections for the mid-21st century of four weather systems that affect the region’s precipitation. First, the North American Monsoon (NAM) weather system accounts for ~60% of the region’s annual rainfall. The total NAM precipitation is projected to decline while heavy rainfall events are expected to intensify. Second, the frequency of the pacific cold fronts, the region’s prevalent source of winter precipitation, is projected to decline. Third, the frequency and intensity of future atmospheric rivers, a weather system that brings winter rainfall to the region, are projected to increase. Fourth, the frequency and intensity of large eastern pacific tropical cyclones (TC) are expected to increase. On rare occasions, remnants of TC make their way to the USCRB to cause storms with considerable impact on the region’s water resources. In contrast to the high confidence projections for the warming trend to persist throughout the mid-21st century, the precipitation projections of these four weather systems affecting the region encompass large uncertainties and studies have often reported contradicting trends. An added source of uncertainty is that the USCRB is located at the periphery of the four rain-bearing weather systems and small mesoscale changes in these weather systems may have accentuated impacts on their edges. Despite the high uncertainty in the projections of future precipitation, the early 21st century drying trend and the projected mid-21st century decline in precipitation events serve as a pressing call for planning and actions to attain sustainable water resources management that reliably satisfies future demands.

Lost in a sagebrush sea: comparative genetic assessment of an isolated montane population of Tamias amoenus

The montane sky islands of the Great Basin are characterized by unique, isolated habitats and communities that likely are vulnerable to extirpation with environmental change. A subspecies of yellow pine chipmunk, the Humboldt yellow pine chipmunk (Tamias amoenus celeris), is associated with the whitebark and limber pine forests of the Pine Forest Range (PFR) in Nevada. We sampled T. amoenus and least chipmunks (T. minimus) from the isolated PFR and compared genetic diversity between these populations and more “mainland” populations, including other subspecies of chipmunks. Given the high frequency of hybridization in Tamias, we tested for hybridization between T. amoenus and T. minimus in the PFR. We examined phylogenetic relationships, population divergence and diversity, and screened populations for a common pathogen, Borrelia hermsii, to gain insight into population health. We found T. amoenus of the PFR are closely related to T. amoenus in the Warner Mountains and Sierra Nevada, but maintain substantively lower genetic variation. Microsatellite analyses show PFR T. amoenus are highly genetically differentiated from other populations. In contrast, PFR T. minimus had higher genetic diversity that was comparable to the other T. minimus population we sampled. Pathogen screening revealed that T. amoenus carried higher pathogen loads than T. minimus in the PFR, although the prevalence of infection was similar to other Tamias populations. Our assessment of habitat associations suggests that the Humboldt yellow pine chipmunk almost entirely is restricted to the conifer systems of the PFR, while least chipmunks are prevalent in the other forests. Our work highlights the need for continued conservation and research efforts to identify how response to environmental change can be facilitated in isolated species and habitats.

Contrasting wet deposition composition between three diverse islands and coastal North American sites

This study examined spatial variations of precipitation accumulation and chemistry for six sites located on the West and East Coasts of the U.S., and one site each on the islands of Hawaii, Bermuda, and Luzon of the Philippines (specifically Manila). The nine coastal sites ranged widely in both mean annual precipitation accumulation, ranging from 40 cm (Mauna Loa, Hawaii) to 275 cm (Washington), and in terms of monthly profiles. The three island sites represented the extremes of differences in terms of chemical profiles, with Bermuda having the highest overall ion concentrations driven mainly by sea salt, Hawaii having the highestSO 4 2 - mass fractions due to the nearby influence of volcanic SO2 emissions and mid-tropospheric transport of anthropogenic pollution, and Manila exhibiting the highest concentration of non-marine ions (NH 4 + non-sea salt [nss]SO 4 2 - , nss Ca2+,NO 3 - , nss K+, nss Na+, nss Mg2+) linked to anthropogenic, biomass burning, and crustal emissions. The Manila site exhibited the most variability in composition throughout the year due to shifting wind directions and having diverse regional and local pollutant sources. In contrast to the three island sites, the North American continental sites exhibited less variability in precipitation composition with sea salt being the most abundant constituent followed by some combination ofSO 4 2 - ,NO 3 - , andNH 4 + . The mean-annual pH values ranged from 4.88 (South Carolina) to 5.40 (central California) withNH 4 + exhibiting the highest neutralization factors for all sites except Bermuda where dust tracer species (nss Ca2+) exhibited enhanced values. The results of this study highlight the sensitivity of wet deposition chemistry to regional considerations, elevation, time of year, and atmospheric circulations.

The impact of climate change induced alterations of streamflow and stream temperature on the distribution of riparian species

Distributions of riparian species will likely shift due to climate change induced alterations in temperature and rainfall patterns, which alter stream habitat. Spatial forecasting of suitable habitat in projected climatic conditions will inform management interventions that support wildlife. Challenges in developing forecasts include the need to consider the large number of riparian species that might respond differently to changing conditions and the need to evaluate the many different characteristics of streamflow and stream temperature that drive species-specific habitat suitability. In particular, in dynamic environments like streams, the short-term temporal resolution of species occurrence and streamflow need to be considered to identify the types of conditions that support various species. To address these challenges, we cluster species based on habitat characteristics to select habitat representatives and we evaluate regional changes in habitat suitability using short-term, temporally explicit metrics that describe the streamflow and stream temperature regime. We use stream-specific environmental predictors rather than climatic variables. Unlike other studies, the stream-specific environmental predictors are generated from the time that species were observed in a particular reach, in addition to long term trends, to evaluate habitat preferences. With species occurrence data from local monitoring surveys and streamflow and stream temperature modeled from downscaled Coupled Model Intercomparison Project - Phase 5 (CMIP5) climate projections, we predict change in habitat suitability at the end-of-century. The relative importance of hydrology and stream temperature varied by cluster. High altitudinal, cold water species' distributions contracted, while lower elevation, warm water species distributions expanded. Modeling with short-term temporally explicit environmental metrics did produce different end-of-century projections than using long-term averages for some of the representative species. These findings can help wildlife managers prioritize conservation efforts, manage streamflow, initiate monitoring of species in vulnerable clusters, and address stressors, such as passage barriers, in areas projected to be suitable in future climate conditions.

Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA)

This study investigates the historical climatology and future projected change of atmospheric rivers (ARs) and precipitation for the Middle East and North Africa (MENA) region. We use a suite of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5, historical and RCP8.5 scenarios) and other observations to estimate AR frequency and mean daily precipitation. Despite its arid-to-semi-arid climate, parts of the MENA region experience strong ARs, which contribute a large fraction of the annual precipitation, such as in the mountainous areas of Turkey and Iran. This study shows that by the end of this century, AR frequency is projected to increase (~20–40%) for the North Africa and Mediterranean areas (including any region with higher latitudes than 35 N). However, for these regions, mean daily precipitation (i.e., regardless of the presence of ARs) is projected to decrease (~15–30%). For the rest of the MENA region, including the Arabian Peninsula and the Horn of Africa, minor changes in AR frequency (±10%) are expected, yet mean precipitation is projected to increase (~50%) for these regions. Overall, the projected sign of change in AR frequency is opposite to the projected sign of change in mean daily precipitation for most areas within the MENA region.

Significant increase of global anomalous moisture uptake feeding landfalling Atmospheric Rivers

One of the most robust signals of climate change is the relentless rise in global mean surface temperature, which is linked closely with the water-holding capacity of the atmosphere. A more humid atmosphere will lead to enhanced moisture transport due to, among other factors, an intensification of atmospheric rivers (ARs) activity, which are an important mechanism of moisture advection from subtropical to extra-tropical regions. Here we show an enhanced evapotranspiration rates in association with landfalling atmospheric river events. These anomalous moisture uptake (AMU) locations are identified on a global scale. The interannual variability of AMU displays a significant increase over the period 1980-2017, close to the Clausius-Clapeyron (CC) scaling, at 7 % per degree of surface temperature rise. These findings are consistent with an intensification of AR predicted by future projections. Our results also reveal generalized significant increases in AMU at the regional scale and an asymmetric supply of oceanic moisture, in which the maximum values are located over the region known as the Western Hemisphere Warm Pool (WHWP) centred on the Gulf of Mexico and the Caribbean Sea.

Increasing atmospheric temperatures are expected to have various impacts on the global water cycle. Here, the authors show that there is an intensification of atmospheric rivers, that causes enhanced evapotranspiration and thus atmospheric moisture uptake in many regions of the world.

Future precipitation increase from very high resolution ensemble downscaling of extreme atmospheric river storms in California

Precipitation extremes will likely intensify under climate change. However, much uncertainty surrounds intensification of high-magnitude events that are often inadequately resolved by global climate models. In this analysis, we develop a framework involving targeted dynamical downscaling of historical and future extreme precipitation events produced by a large ensemble of a global climate model. This framework is applied to extreme "atmospheric river" storms in California. We find a substantial (10 to 40%) increase in total accumulated precipitation, with the largest relative increases in valleys and mountain lee-side areas. We also report even higher and more spatially uniform increases in hourly maximum precipitation intensity, which exceed Clausius-Clapeyron expectations. Up to 85% of this increase arises from thermodynamically driven increases in water vapor, with a smaller contribution by increased zonal wind strength. These findings imply substantial challenges for water and flood management in California, given future increases in intense atmospheric river-induced precipitation extremes.

A multimodel evaluation of the water vapor budget in atmospheric rivers

Atmospheric rivers (ARs) are narrow regions of strong horizontal water vapor transport that play important roles in the global water cycle, weather, and hydrology. Motivated by challenges in simulating ARs with state-of-the-art global models, this paper diagnoses model errors with a focus on relative contributions of moisture convergence, evaporation, and precipitation to AR column-integrated water vapor (IWV) budget. Using 20-year simulations by 24 global weather/climate models, budget terms are calculated for four AR sectors: postfrontal, frontal, prefrontal, and pre-AR, with biases assessed against two reanalysis products. The results indicate that each sector is unique in terms of the dominant water vapor balance, and that the terms exhibiting the largest intermodel spread are the same terms dominating the water vapor balance in each sector. Overall, simulated bulk AR characteristics (e.g., geometry, frequency, and intensity) are more sensitive to biases in IVT convergence and IWV tendency than to biases in evaporation and precipitation, although evaporation/precipitation biases do affect key AR bulk characteristics in selected sectors. The large intermodel spread (particularly for precipitation) and, in certain cases, discrepancies between the reanalysis references themselves (particularly for precipitation types) highlight the need for observational efforts that target better constraining AR processes in weather/climate models and reanalyses.

Advances in understanding large-scale responses of the water cycle to climate change

Globally, thermodynamics explains an increase in atmospheric water vapor with warming of around 7%/°C near to the surface. In contrast, global precipitation and evaporation are constrained by the Earth's energy balance to increase at ∼2-3%/°C. However, this rate of increase is suppressed by rapid atmospheric adjustments in response to greenhouse gases and absorbing aerosols that directly alter the atmospheric energy budget. Rapid adjustments to forcings, cooling effects from scattering aerosol, and observational uncertainty can explain why observed global precipitation responses are currently difficult to detect but are expected to emerge and accelerate as warming increases and aerosol forcing diminishes. Precipitation increases with warming are expected to be smaller over land than ocean due to limitations on moisture convergence, exacerbated by feedbacks and affected by rapid adjustments. Thermodynamic increases in atmospheric moisture fluxes amplify wet and dry events, driving an intensification of precipitation extremes. The rate of intensification can deviate from a simple thermodynamic response due to in-storm and larger-scale feedback processes, while changes in large-scale dynamics and catchment characteristics further modulate the frequency of flooding in response to precipitation increases. Changes in atmospheric circulation in response to radiative forcing and evolving surface temperature patterns are capable of dominating water cycle changes in some regions. Moreover, the direct impact of human activities on the water cycle through water abstraction, irrigation, and land use change is already a significant component of regional water cycle change and is expected to further increase in importance as water demand grows with global population.

Atmospheric rivers drive flood damages in the western United States

Atmospheric rivers (ARs) are extratropical storms that produce extreme precipitation on the west coasts of the world's major landmasses. In the United States, ARs cause significant flooding, yet their economic impacts have not been quantified. Here, using 40 years of data from the National Flood Insurance Program, we show that ARs are the primary drivers of flood damages in the western United States. Using a recently developed AR scale, which varies from category 1 to 5, we find that flood damages increase exponentially with AR intensity and duration: Each increase in category corresponds to a roughly 10-fold increase in damages. Category 4 and 5 ARs cause median damages in the tens and hundreds of millions of dollars, respectively. Rising population, increased development, and climate change are expected to worsen the risk of AR-driven flood damage in future decades.

Atmospheric rivers impact California's coastal water quality via extreme precipitation

Precipitation in California is projected to become more volatile: less frequent but more extreme as global warming pushes midlatitude frontal cyclones further poleward while bolstering the atmospheric rivers (ARs), which tend to produce the region's extreme rainfall. Pollutant accumulation and delivery to coastal waters can be expected to increase, as lengthening dry spells will be increasingly punctuated by more extreme precipitation events. Coastal pollution exposes human populations to high levels of fecal bacteria and associated pathogens, which can cause a variety of health impacts. Consequently, studying the impact of atmospheric rivers as the mechanism generating pulses of water pollution in coastal areas is relevant for public health and in the context of climate change. We aimed to quantify the links between precipitation events and water quality in order to explore meteorological causes as first steps toward effective early warning systems for the benefit of population health in California and beyond. We used historical gridded daily precipitation and weekly multiple fecal bacteria indicators at ~500 monitoring locations in California's coastal waters to identify weekly associations between precipitation and water quality during 2003-09 using canonical correlation analysis to account for the nested/clustered nature of longitudinal data. We then quantified, using a recently published catalog of atmospheric rivers, the proportion of coastal pollution events attributable to ARs. Association between precipitation and fecal bacteria was strongest in Southern California. Over two-thirds of coastal water pollution spikes exceeding one standard deviation were associated with ARs. This work highlights the importance of skillful AR landfall predictions in reducing vulnerability to extreme weather improving resilience of human populations in a varying and changing climate. Quantifying the impacts of ARs on waterborne diseases is important for planning effective preventive strategies for public health.