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In most Mediterranean climate (MedClim) regions around the world, global climate models (GCMs) consistently project drier futures. In California, however, projections of changes in annual precipitation are inconsistent. Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over each of the five MedClm regions globally and helps disentangle their causes. MedClim regions, except California, are expected to dry via decreased frequency of winter precipitation. Frequencies of extreme precipitation, however, are projected to increase over the two MedClim regions of the Northern Hemisphere where projected warming is strongest. The increase in heavy and extreme precipitation is particularly robust over California, where it is only partially offset by projected decreases in low-medium intensity precipitation. Over the Mediterranean Basin, however, losses from decreasing frequency of low-medium-intensity precipitation are projected to dominate gains from intensifying projected extreme precipitation. MedClim regions are projected to become more sub-tropical, i.e. made dryer via pole-ward expanding subtropical subsidence. California’s more nuanced hydrological future reflects a precarious balance between the expanding subtropical high from the south and the south-eastward extending Aleutian low from the north-west. These dynamical mechanisms and thermodynamic moistening of the warming atmosphere result in increased horizontal water vapor transport, bolstering extreme precipitation events.

A new set of CMIP6 data downscaled using the localized constructed analogs (LOCA) statistical method has been produced, covering central Mexico through southern Canada at 6-km resolution. Output from 27 CMIP6 Earth system models is included, with up to 10 ensemble members per model and 3 SSPs (245, 370, and 585). Improvements from the previous CMIP5 downscaled data result in higher daily precipitation extremes, which have significant societal and economic implications. The improvements are accomplished by using a precipitation training dataset that better represents daily extremes and by implementing an ensemble bias correction that allows a more realistic representation of extreme high daily precipitation values in models with numerous ensemble members. Over southern Canada and the CONUS exclusive of Arizona (AZ) and New Mexico (NM), seasonal increases in daily precipitation extremes are largest in winter (~25% in SSP370). Over Mexico, AZ, and NM, seasonal increases are largest in autumn (~15%). Summer is the outlier season, with low model agreement except in New England and little changes in 5-yr return values, but substantial increases in the CONUS and Canada in the 500-yr return value. One-in-100-yr historical daily precipitation events become substantially more frequent in the future, as often as once in 30–40 years in the southeastern United States and Pacific Northwest by the end of the century under SSP 370. Impacts of the higher precipitation extremes in the LOCA version 2 downscaled CMIP6 product relative to the LOCA downscaled CMIP5 product, even for similar anthropogenic emissions, may need to be considered by end-users.

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.

Daily precipitation in California has been projected to become less frequent even as precipitation extremes intensify, leading to uncertainty in the overall response to climate warming. Precipitation extremes are historically associated with Atmospheric Rivers (ARs). Sixteen global climate models are evaluated for realism in modeled historical AR behavior and contribution of the resulting daily precipitation to annual total precipitation over Western North America. The five most realistic models display consistent changes in future AR behavior, constraining the spread of the full ensemble. They, moreover, project increasing year-to-year variability of total annual precipitation, particularly over California, where change in total annual precipitation is not projected with confidence. Focusing on three representative river basins along the West Coast, we show that, while the decrease in precipitation frequency is mostly due to non-AR events, the increase in heavy and extreme precipitation is almost entirely due to ARs. This research demonstrates that examining meteorological causes of precipitation regime change can lead to better and more nuanced understanding of climate projections. It highlights the critical role of future changes in ARs to Western water resources, especially over California.

Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM’s mean climate change signal, with differences of up to 2°C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile matching (EDCDFm) bias correction preserves GCM changes in mean daily maximum temperature but not precipitation. An extension to EDCDFm termed PresRat is introduced, which generally preserves the GCM changes in mean precipitation. Another problem is that GCMs can have difficulty simulating variance as a function of frequency. To address this, a frequency-dependent bias correction method is introduced that is twice as effective as standard bias correction in reducing errors in the models’ simulation of variance as a function of frequency, and it does so without making any locations worse, unlike standard bias correction. Last, a preconditioning technique is introduced that improves the simulation of the annual cycle while still allowing the bias correction to take account of an entire season’s values at once.

Recently the Southwest has experienced a spate of dryness, which presents a challenge to the sustainability of current water use by human and natural systems in the region. In the Colorado River Basin, the early 21st century drought has been the most extreme in over a century of Colorado River flows, and might occur in any given century with probability of only 60%. However, hydrological model runs from downscaled Intergovernmental Panel on Climate Change Fourth Assessment climate change simulations suggest that the region is likely to become drier and experience more severe droughts than this. In the latter half of the 21st century the models produced considerably greater drought activity, particularly in the Colorado River Basin, as judged from soil moisture anomalies and other hydrological measures. As in the historical record, most of the simulated extreme droughts build up and persist over many years. Durations of depleted soil moisture over the historical record ranged from 4 to 10 years, but in the 21st century simulations, some of the dry events persisted for 12 years or more. Summers during the observed early 21st century drought were remarkably warm, a feature also evident in many simulated droughts of the 21st century. These severe future droughts are aggravated by enhanced, globally warmed temperatures that reduce spring snowpack and late spring and summer soil moisture. As the climate continues to warm and soil moisture deficits accumulate beyond historical levels, the model simulations suggest that sustaining water supplies in parts of the Southwest will be a challenge.

The water resources of the western United States depend heavily on snowpack to store part of the wintertime precipitation into the drier summer months. A well-documented shift toward earlier runoff in recent decades has been attributed to 1) more precipitation falling as rain instead of snow and 2) earlier snowmelt. The present study addresses the former, documenting a regional trend toward smaller ratios of winter-total snowfall water equivalent (SFE) to winter-total precipitation (P) during the period 1949–2004. The trends toward reduced SFE are a response to warming across the region, with the most significant reductions occurring where winter wet-day minimum temperatures, averaged over the study period, were warmer than -5°C. Most SFE reductions were associated with winter wet-day temperature increases between 0° and +3°C over the study period. Warmings larger than this occurred mainly at sites where the mean temperatures were cool enough that the precipitation form was less susceptible to warming trends. The trends toward reduced SFE/Pratios were most pronounced in March regionwide and in January near the West Coast, corresponding to widespread warming in these months. While mean temperatures in March were sufficiently high to allow the warming trend to produce SFE/Pdeclines across the study region, mean January temperatures were cooler, with the result that January SFE/Pimpacts were restricted to the lower elevations near the West Coast. Extending the analysis back to 1920 shows that although the trends presented here may be partially attributable to interdecadal climate variability associated with the Pacific decadal oscillation, they also appear to result from still longer-term climate shifts.

Low‐level stratiform clouds modulate California's coastal climate during the warm season. Previous work describing the seasonal and daily variability of coastal low cloudiness (CLC) suggests that in July, August, and September southern California's CLC is under the influence of an additional driver, which has less impact in northern California. In this work, we introduce the link in which free‐tropospheric moisture dictated by North American Monsoon (NAM) processes can impact southern California CLC. We use in situ and remote sensing observations, as well as reanalysis and single column model simulations to identify and investigate this previously missing component. We find that monsoonal moisture advected by southeasterly flow from the core NAM region into southern California reduces CLC by diminishing cloud‐top longwave cooling. To add to an already complex brew of known factors influencing coastal cloudiness, another one is hereby introduced and should be accounted for in future work. Plain Language Summary Low‐altitude marine layer clouds shade and cool coastal California in spring and summer. When these clouds are low enough that the base of the cloud intercepts terrain (which is known as fog), they additionally add moisture to the landscape during a typically dry time of year in California. Future trends in coastal low cloudiness (CLC) are uncertain. Although CLC impact the whole coast of California and beyond, previous studies have exposed differences in seasonal and daily CLC behavior in southern and northern California. The North American Monsoon (NAM), which becomes active in the US Southwest in summer, brings rain and thunderstorms to the desert southwest. Coastal southern California is on the northwest edge of the NAM influence and typically does not receive much rain from NAM. In this study, we show how low altitude coastal cloud cover in southern California and northern Baja California can be diminished by higher altitude moisture from the NAM. Dry and stable air above the top of low clouds helps to maintain the cloud layer, and higher altitude moisture interrupts this process. To better understand how CLC varies and may change, an accounting of all key drivers of CLC behavior, including the NAM, is needed. Key Points An increase in free‐tropospheric moisture over coastal southern California in summer is attributed to the North American Monsoon (NAM) NAM moisture intrusions can diminish southern California coastal low cloudiness by decreasing longwave cloud‐top cooling These results link two iconic regional climate phenomena of the U.S. Southwest

California’s highly variable climate and growing water demands combine to pose both water-supply and flood-hazard challenges to resource managers. Recently important efforts to more fully integrate the management of floods and water resources have begun, with the aim of benefitting both sectors. California is shown here to experience unusually large variations in annual precipitation and streamflow totals relative to the rest of the US, variations which mostly reflect the unusually small average number of wet days per year needed to accumulate most of its annual precipitation totals (ranging from 5 to 15 days in California). Thus whether just a few large storms arrive or fail to arrive in California can be the difference between a banner year and a drought. Furthermore California receives some of the largest 3-day storm totals in the country, rivaling in this regard the hurricane belt of the southeastern US. California’s largest storms are generally fueled by landfalling atmospheric rivers (ARs). The fractions of precipitation and streamflow totals at stations across the US that are associated with ARs are documented here and, in California, contribute 20–50% of the state’s precipitation and streamflow. Prospects for long-lead forecasts of these fractions are presented. From a meteorological perspective, California’s water resources and floods are shown to derive from the same storms to an extent that makes integrated flood and water resources management all the more important.

As the climate evolves over the next century, the interaction of accelerating sea level rise (SLR) and storms, combined with confining development and infrastructure, will place greater stresses on physical, ecological, and human systems along the ocean-land margin. Many of these valued coastal systems could reach “tipping points,” at which hazard exposure substantially increases and threatens the present-day form, function, and viability of communities, infrastructure, and ecosystems. Determining the timing and nature of these tipping points is essential for effective climate adaptation planning. Here we present a multidisciplinary case study from Santa Barbara, California (USA), to identify potential climate change-related tipping points for various coastal systems. This study integrates numerical and statistical models of the climate, ocean water levels, beach and cliff evolution, and two soft sediment ecosystems, sandy beaches and tidal wetlands. We find that tipping points for beaches and wetlands could be reached with just 0.25 m or less of SLR (~ 2050), with > 50% subsequent habitat loss that would degrade overall biodiversity and ecosystem function. In contrast, the largest projected changes in socioeconomic exposure to flooding for five communities in this region are not anticipated until SLR exceeds 0.75 m for daily flooding and 1.5 m for storm-driven flooding (~ 2100 or later). These changes are less acute relative to community totals and do not qualify as tipping points given the adaptive capacity of communities. Nonetheless, the natural and human built systems are interconnected such that the loss of natural system function could negatively impact the quality of life of residents and disrupt the local economy, resulting in indirect socioeconomic impacts long before built infrastructure is directly impacted by flooding.