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Western U.S. (WUS) rainfall and snowpack vary greatly on interannual and decadal timescales. This combined with their importance to water resources makes future projections of these variables highly societally relevant. Previous studies have shown that precipitation events in the WUS are influenced by the timing, positioning, and duration of extreme integrated water vapor transport (IVT) events (e.g., atmospheric rivers) along the coast. We investigate end-of-21st-century projections of WUS precipitation and IVT in a collection of regional climate models (RCMs) from the North American Coordinated Regional Downscaling Experiment (NA-CORDEX). Several of the NA-CORDEX RCMs project a decrease in cool season precipitation at high elevation (e.g., across the Sierra Nevada) with a corresponding increase in the Great Basin of the U.S. We explore the larger-scale controls on this terrain-related precipitation change in a subset of the NA-CORDEX RCMs through an examination of IVT-events. Projected changes in frequency and duration of IVT-events depend on the event's extremity: by the end of the century extreme IVT-events increase in frequency whereas moderate IVT-events decrease in frequency. Furthermore, in the future, total precipitation across the WUS generally increases during extreme IVT-events, whereas total precipitation from moderate IVT-events decreases across higher elevations. Thus, we argue that the mean cool season precipitation decreases at high elevations and increases in the Great Basin are largely determined by changes in moderate IVT-events which are projected to be less frequent and bring less high-elevation precipitation. [ABSTRACT FROM AUTHOR]

Accurate quantitative precipitation estimates (QPEs) at high spatial and temporal resolution are difficult to obtain in regions of complex terrain due to the large spatial heterogeneity of orographically enhanced precipitation, sparsity of gauges, precipitation phase variations, and terrain effects that impact the quality of remotely sensed estimates. The large uncertainty of QPE in these regions also makes the evaluation of high-resolution quantitative precipitation forecasts (QPFs) challenging, as it can be difficult to choose a reference QPE that is reliable at both high and low elevations. In this paper we demonstrate a methodology to combine information from multiple high-resolution hourly QPE products to evaluate QPFs from NOAA's High-Resolution Rapid Refresh (HRRR) model in a region of Northern California. The methodology uses the quantiles of monthly QPE distributions to determine a range of hourly precipitation that correspond to "good," "possible," "underestimated," or "overestimated" QPFs. In this manuscript, we illustrate the use of the methodology to evaluate QPFs for seven atmospheric river events that occurred during the 2016–17 wet season in Northern California. Because the presence of frozen precipitation is often not captured by traditional QPE products, we evaluate QPFs both for all precipitation, and with likely frozen precipitation excluded. The methodology is shown to provide useful information to evaluate model performance while taking into account the uncertainty of available QPE at various temporal and spatial scales. The potential of the technique to evaluate changes between model versions is also shown. [ABSTRACT FROM AUTHOR]

Uncertainties in gridded and regional climate estimates of precipitation are large at high elevations, where observations are sparse and spatial variability is substantial. We explore these uncertainties for water year 2008 across California's Sierra Nevada in 10 datasets: 6 regional climate downscalings generated using the weather research and forecasting (WRF) model at convection-permitting resolution with differing lateral boundary conditions and microphysical parameterizations, and four gauge-based, interpolation-gridded precipitation datasets. Precipitation from these 10 datasets is evaluated against 95 snow pillows and a precipitation dataset inferred from stream gauges using a Bayesian inference method. During water year 2008, the gridded datasets tend to underestimate frozen precipitation on the windward slope of the Sierra Nevada, particularly in the vicinity of Yosemite National Park. The WRF simulations with single-moment microphysics tend to overestimate precipitation throughout much of the region, whereas the WRF simulations with double-moment microphysics tend to better agree with both the snow pillows and inferred precipitation estimates, although they somewhat overestimate the windward/leeside precipitation contrast in the northern Sierra Nevada. WRF simulations, in particular those with single-moment microphysics, better distinguish spatial patterns of wet-versus-dry pillows and watersheds over the water year than the gridded estimates. Our results suggest treating gauge-based datasets as 'truth' may give a misleading representation of model accuracy, since these gauge-based datasets often have issues of their own. [ABSTRACT FROM AUTHOR]

The Bay Area of California and surrounding region receives much of its annual precipitation during the October–March wet season, when atmospheric river events bring periods of heavy rain that challenge water managers and may exceed the capacity of storm sewer systems. The complex terrain of this region further complicates the situation, with terrain interactions that are not currently captured in most operational forecast models and inadequate precipitation measurements to capture the large variability throughout the area. To improve monitoring and prediction of these events at spatial and temporal resolutions of interest to area water managers, the Bay Area Advanced Quantitative Precipitation Information project was developed. To quantify improvements in forecast precipitation, model validation studies require a reference dataset to compare against. In this paper we examine 10 gridded, high-resolution (≤10 km, hourly) precipitation estimates to assess the uncertainty of high-resolution quantitative precipitation estimates (QPE) in areas of complex terrain. The products were linearly interpolated to 3-km grid spacing, which is the resolution of the operational forecast model to be validated. Substantial differences exist between the various products at accumulation periods ranging from hourly to annual, with standard deviations among the products exceeding 100% of the mean. While the products seem to agree fairly well on the timing of precipitation, intensity estimates differ, sometimes by an order of magnitude. The results highlight both the need for additional observations and the need to account for uncertainty in the reference dataset when validating forecasts in this area. [ABSTRACT FROM AUTHOR]

In mountain terrain, well-configured high-resolution atmospheric models are able to simulate total annual rain and snowfall better than spatial estimates derived from in situ observational networks of precipitation gauges, and significantly better than radar or satellite-derived estimates. This conclusion is primarily based on comparisons with streamflow and snow in basins across the western United States and in Iceland, Europe, and Asia. Even though they outperform gridded datasets based on gauge networks, atmospheric models still disagree with each other on annual average precipitation and often disagree more on their representation of individual storms. Research to address these difficulties must make use of a wide range of observations (snow, streamflow, ecology, radar, satellite) and bring together scientists from different disciplines and a wide range of communities. [ABSTRACT FROM AUTHOR]

Wintertime precipitation poses many observational and forecasting challenges, especially in the complex topography of the western United States where radar beam blockage and difficulty siting in situ observations yields more sparse observations than in the eastern United States. Uncertainty in western U.S. winter precipitation is known to be high, so much so that some studies have found model simulated precipitation to produce similar or better large-scale estimates of annual precipitation than gridded observational products during climatologically anomalous years. This study evaluates high-resolution gridded precipitation estimates from Multi-Radar Multi-Sensor (MRMS) and Stage IV as well as forecasts from NOAA's High-Resolution Rapid Refresh (HRRR) model in the Colorado Rocky Mountains. Gridded precipitation estimates and forecasts are compared with in situ SNOTEL measurements for two seasons of wintertime precipitation. The influence of forecast length, lead time, and model elevation on seasonal precipitation predictions from the HRRR are investigated. Additional comparisons are made with the relatively dense network of observations deployed in Colorado's East River Watershed during the Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaign. Gridded products and forecasts are found to underestimate cold-season precipitation by 25%–65% relative to in situ and aircraft measurements, with longer forecast periods and lead times (6–24 h) having smaller biases (25%–30%) than shorter forecast periods and lead times (55%–65%). The assessment of multiple years of observations indicates that these biases are related more to the data and methods used to create the gridded products and forecasts than to precipitation characteristics. Significance Statement: In the mountainous western United States, it is very challenging to both observe and forecast wintertime precipitation, yet snowfall plays an important role in providing the region's annual water supply. This study aims to increase our understanding of the biases in observations and forecasts of snowfall in the Colorado Rocky Mountains, which can in turn impact forecasts of water availability for the ensuing warm season. In this study we find high-resolution gridded precipitation estimates and forecasts to underestimate cold-season precipitation when compared with in situ observing stations, with longer-range forecasts (e.g., daily) being the least biased. These findings were consistent over two years of study and have broad implications for the hydrologic modeling and water management communities. [ABSTRACT FROM AUTHOR]

The Russian River in northern California is an important hydrological resource that typically depends on a few significant precipitation events per year, often associated with atmospheric rivers (ARs), to maintain its annual water supply. Because of the highly variable nature of annual precipitation in the region, accurate quantitative precipitation estimates (QPEs) are necessary to drive hydrologic models and inform water management decisions. The basin's location and complex terrain present a unique challenge to QPEs, with sparse in situ observations and mountains that inhibit remote sensing by ground radars. Gridded multisensor QPE datasets can fill in the gaps but are susceptible to both the errors and uncertainties from the ingested datasets and uncertainties due to interpolation methods. In this study a dense network of independently operated rain gauges is used to evaluate gridded QPE from the Multi-Radar Multi-Sensor (MRMS) during 44 precipitation events occurring during the 2015/16 and 2016/17 wet seasons (October–March). The MRMS QPE products matched the gauge estimates of precipitation reasonably well in approximately half the cases but failed to capture the spatial distribution and intensity of the rainfall in the remaining cases. ERA-Interim reanalysis data suggest that the differences in performance are related to synoptic-scale patterns and AR landfall location. These synoptic-scale differences produce different rainfall distributions and influence basin-scale winds, potentially creating regions of small-scale precipitation enhancement or suppression. Data from four profiling radars indicated that a larger fraction of the precipitation in poorly captured events occurred as shallow stratiform rain unobserved by radar. [ABSTRACT FROM AUTHOR]

Gridded spatiotemporal maps of precipitation are essential for hydrometeorological and ecological analyses. In the United States, most of these datasets are developed using the Cooperative Observer (COOP) network of ground-based precipitation measurements, interpolation, and the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) to map these measurements to places where data are not available. Here, we evaluate two daily datasets gridded at ° resolution against independent daily observations from over 100 snow pillows in California's Sierra Nevada from 1990 to 2010. Over the entire period, the gridded datasets performed reasonably well, with median total water-year errors generally falling within ±10%. However, errors in individual storm events sometimes exceeded 50% for the median difference across all stations, and in many cases, the same underpredicted storms appear in both datasets. Synoptic analysis reveals that these underpredicted storms coincide with 700-hPa winds from the west or northwest, which are associated with post-cold-frontal flow and disproportionately small precipitation rates in low-elevation valley locations, where the COOP stations are primarily located. This atmospheric circulation leads to a stronger than normal valley-to-mountain precipitation gradient and underestimation of actual mountain precipitation. Because of the small average number of storms (<10) reaching California each year, these individual storm misses can lead to large biases (~20%) in total water-year precipitation and thereby significantly affect estimates of statewide water resources. [ABSTRACT FROM AUTHOR]

This manuscript documents numerical modeling experiments based on a January 2010 atmospheric river (AR) event that caused extreme precipitation in Arizona. The control experiment (CNTL), using the Weather Research and Forecasting (WRF) Model with 3-km grid spacing, agrees well with observations. Sensitivity experiments in which 1) model grid spacing decreases sequentially from 81 to 3 km and 2) upstream terrain is elevated are used to assess the sensitivity of interior precipitation amounts and horizontal water vapor fluxes to model grid resolution and height of Baja California terrain. The drying ratio, a measure of airmass drying after passage across terrain, increases with Baja's terrain height and decreases with coarsened grid spacing. Subsequently, precipitation across Arizona decreases as the Baja terrain height increases, although it changes little with coarsened grid spacing. Northern Baja's drying ratio is much larger than that of southern Baja. Thus, ARs with a southerly orientation, with water vapor transports that can pass south of the higher mountains of northern Baja and then cross the Gulf of California, can produce large precipitation amounts in Arizona. Further experiments are performed using a linear model (LM) of orographic precipitation for a central-Arizona-focused subdomain. The actual incidence angle of the AR (211°) is close to the optimum angle for large region-mean precipitation. Changes in region-mean precipitation amounts are small (~6%) owing to AR angle changes; however, much larger changes in basin-mean precipitation of up to 33% occur within the range of physically plausible AR angles tested. Larger LM precipitation sensitivity is seen with the Baja-terrain-modification experiments than with AR-angle modification. [ABSTRACT FROM AUTHOR]

Five 915-MHz wind profilers and GPS receivers across California's northern Central Valley (CV) and adjacent Sierra foothills and coastal zone, in tandem with a 6-km-resolution gridded reanalysis dataset generated from the Weather Research and Forecasting Model, document key spatiotemporal characteristics of Sierra barrier jets (SBJs), landfalling atmospheric rivers (ARs), and their interactions. Composite kinematic and thermodynamic analyses are based on the 13 strongest SBJ cases observed by the Sloughhouse profiler between 2009 and 2011. The analyses show shallow, cool, south-southeasterly (i.e., Sierra parallel) flow and associated water vapor transport strengthening with time early in the 24-h compositing period, culminating in an SBJ core at <1 km above ground over the eastern CV. The SBJ core increases in altitude up the Sierra's windward slope and poleward toward the north end of the CV, but it does not reach the westernmost CV. Above the developing SBJ, strengthening southwesterly flow descends temporally in response to the landfalling AR. The moistening SBJ reaches maximum intensity during the strongest AR flow aloft, at which time the core of the AR-parallel vapor transport slopes over the SBJ. The inland penetration of the AR through the San Francisco Bay gap in the coastal mountains contributes to SBJ moistening and deepening. The SBJ subsequently weakens with the initial cold-frontal period aloft, during which the shallow flow shifts to southwesterly and the heaviest precipitation falls in the Sierra foothills. An orographic precipitation analysis quantitatively links the Sierra-perpendicular (nearly AR parallel) vapor fluxes to enhanced precipitation along the Sierra's windward slope and the SBJ-parallel fluxes to heavy precipitation at the north end of the CV. [ABSTRACT FROM AUTHOR]

The frequency and character of Southern California's Santa Ana wind events are investigated within a 12-km-resolution downscaling of late-20th and mid-21st century time periods of the National Center for Atmospheric Research Community Climate System Model global climate change scenario run. The number of Santa Ana days per winter season is approximately 20% fewer in the mid 21st century compared to the late 20th century. Since the only systematic and sustained difference between these two periods is the level of anthropogenic forcing, this effect is anthropogenic in origin. In both time periods, Santa Ana winds are partly katabatically-driven by a temperature difference between the cold wintertime air pooling in the desert against coastal mountains and the adjacent warm air over the ocean. However, this katabatic mechanism is significantly weaker during the mid 21st century time period. This occurs because of the well-documented differential warming associated with transient climate change, with more warming in the desert interior than over the ocean. Thus the mechanism responsible for the decrease in Santa Ana frequency originates from a well-known aspect of the climate response to increasing greenhouse gases, but cannot be understood or simulated without mesoscale atmospheric dynamics. In addition to the change in Santa Ana frequency, we investigate changes during Santa Anas in two other meteorological variables known to be relevant to fire weather conditions-relative humidity and temperature. We find a decrease in the relative humidity and an increase in temperature. Both these changes would favor fire. A fire behavior model accounting for changes in wind, temperature, and relative humidity simultaneously is necessary to draw firm conclusions about future fire risk and growth associated with Santa Ana events. While our results are somewhat limited by a relatively small sample size, they illustrate an observed and explainable regional change in climate due to plausible mesoscale processes. [ABSTRACT FROM AUTHOR]

The atmospheric conditions that lead to strong offshore surface winds in Southern California, commonly referred to as Santa Ana winds, are investigated using the North American Regional Reanalysis and a 12-year, 6-km resolution regional climate simulation of Southern California. We first construct an index to characterize Santa Ana events based on offshore wind strength. This index is then used to identify the average synoptic conditions associated with Santa Ana events—a high pressure anomaly over the Great Basin. This pressure anomaly causes offshore geostrophic winds roughly perpendicular to the region’s mountain ranges, which in turn cause surface flow as the offshore momentum is transferred to the surface. We find, however, that there are large variations in the synoptic conditions during Santa Ana conditions, and that there are many days with strong offshore flow and weak synoptic forcing. This is due to local thermodynamic forcing that also causes strong offshore surface flow: a large temperature gradient between the cold desert surface and the warm ocean air at the same altitude creates an offshore pressure gradient at that altitude, in turn causing katabatic-like offshore flow in a thin layer near the surface. We quantify the contribution of “synoptic” and “local thermodynamic” mechanisms using a bivariate linear regression model, and find that, unless synoptic conditions force strongly onshore winds, the local thermodynamic forcing is the primary control on Santa Ana variability. [ABSTRACT FROM AUTHOR]

Using a 6-km-resolution regional climate simulation of Southern California, the effect of orographic blocking on the precipitation climatology is examined. To diagnose whether blocking occurs, precipitating hours are categorized by a bulk Froude number. The precipitation distribution becomes much more spatially homogeneous as the Froude number decreases, and an inspection of winds confirms that this results from the increasing prevalence of orographic blocking. Low Froude (Froude approximately less than 1), blocked cases account for a large fraction of climatological precipitation, particularly at the coastline where more than half is attributable to blocked cases. Thus, the climatological precipitation–slope relationship seen in observations and in the simulation is a hybrid of blocked and unblocked cases. Simulated precipitation distributions are compared to those predicted by a simple linear model that includes only rainfall arising from direct forced topographic ascent. The agreement is nearly perfect for high Froude (Froude substantially larger than 1) cases but degrades dramatically as the index decreases; as blocking becomes more prevalent, the precipitation–slope relationship becomes continuously weaker than that predicted by the linear model. Because of its high fidelity during unblocked cases, it is surmised that blocking effects are the primary limitation preventing the linear model from accurately representing precipitation climatology and that the representation would be significantly improved during low Froude hours by the addition of a term to reduce the effective slope of the topography. These results suggest orographic blockingmay substantially affect climatological precipitation distributions in similarly configured coastal areas. [ABSTRACT FROM AUTHOR]

We examine the climatological diurnal cycle of surface air temperature in a 6 km resolution atmospheric simulation of Southern California from 1995 to the present. We find its amplitude and phase both have significant geographical structure. This is most likely due to diurnally-varying flows back and forth across the coastline and elevation isolines resulting from the large daily warming and cooling over land. Because the region’s atmosphere is generally stably stratified, these flow patterns result in air of lower (higher) potential temperature being advected upslope (downslope) during daytime (nighttime). This suppresses the temperature diurnal cycle amplitude at mountaintops where diurnal flows converge (diverge) during the day (night). The nighttime land breeze also advects air of higher potential temperature downslope toward the coast. This raises minimum temperatures in land areas adjacent to the coast in a manner analogous to the daytime suppression of maximum temperature by the cool sea breeze in these same areas. Because stratification is greater in the coastal zone than in the desert interior, these thermal effects of the diurnal winds are not uniform, generating spatial structures in the phase and shape of the temperature diurnal cycle as well as its amplitude. We confirm that the simulated characteristics of the temperature diurnal cycle as well as those of the associated diurnal winds are also found in a network of 30 observation stations in the region. This gives confidence in the simulation’s realism and our study’s findings. Diurnal flows are probably mainly responsible for the geographical structures in the temperature diurnal cycle in other regions of significant topography and surface heterogeneity, their importance depending partly on the degree of atmospheric stratification. [ABSTRACT FROM AUTHOR]

SIGNIFICANCE STATEMENT: Water is a limited and critical resource in the western United States. To protect water access for millions of people and ecosystems, and to preserve our ability to irrigate millions of acres of cropland, policymakers and water managers require advanced weather and water prediction systems. To improve these forecast systems in high-altitude complex terrain, the National Oceanic and Atmospheric Administration (NOAA) has deployed instrumentation in the East River watershed of the Upper Colorado River basin as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). SPLASH observations are being used to advance fundamental understanding of mountain weather and water and to advance predictive capabilities across weather and climate time scales. Water is a critical resource that causes significant challenges to inhabitants of the western United States. These challenges are likely to intensify as the result of expanding population and climate-related changes that act to reduce runoff in areas of complex terrain. To better understand the physical processes that drive the transition of mountain precipitation to streamflow, the National Oceanic and Atmospheric Administration has deployed suites of environmental sensors throughout the East River watershed of Colorado as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). This includes surface-based sensors over a network of five different observing sites, airborne platforms, and sophisticated remote sensors to provide detailed information on spatiotemporal variability of key parameters. With a 2-yr deployment, these sensors offer detailed insight into precipitation, the lower atmosphere, and the surface, and support the development of datasets targeting improved prediction of weather and water. Initial datasets have been published and are laying a foundation for improved characterization of physical processes and their interactions driving mountain hydrology, evaluation and improvement of numerical prediction tools, and educational activities. SPLASH observations contain a depth and breadth of information that enables a variety of atmospheric and hydrological science analyses over the coming years that leverage collaborations between national laboratories, academia, and stakeholders, including industry. [ABSTRACT FROM AUTHOR]

A series of precipitation events impacted the Pacific Northwest during the first two weeks of November 2006. This sequence was punctuated by a particularly potent inland-penetrating atmospheric river (AR) that produced record-breaking precipitation across the region during 5-7 November. The precipitation caused destructive flooding as far inland as Montana's Glacier National Park, 800 km from the Pacific Ocean. This study investigates the inland penetration of moisture during the event using a 4-1.33-km grid spacing configuration of the Weather Research and Forecasting (WRF) modeling system. A high-resolution simulation allowed an analysis of interactions between the strong AR and terrain features such as the Cascade Mountains and the Columbia River Gorge (CR Gorge). Moisture transport in the vicinity of the Cascades is assessed using various metrics. The most efficient pathway for moisture penetration was through the gap (i.e., CR Gap) between Mt. Adams and Mt. Hood, which includes the CR Gorge. While the CR Gap is a path of least resistance through the Cascades, most of the total moisture transport that survived transit past the Cascades overtopped the mountain barrier itself. This is due to the disparity between the length of the ridge (~800 km) and relatively narrow width of the CR Gap (~93 km). Moisture transport reductions were larger across the Washington Cascades and the southern-central Oregon Cascades than through the CR Gap. During the simulation, drying ratios through the CR Gap (9.3%) were notably less than over adjacent terrain (19.6%-30.6%). Drying ratios decreased as moisture transport intensity increased. [ABSTRACT FROM AUTHOR]

The data required to drive distributed hydrological models are significantly limited within mountainous terrain because of a scarcity of observations. This study evaluated three common configurations of forcing data: 1) one low-elevation station, combined with empirical techniques; 2) gridded output from the Weather Research and Forecasting Model (WRF); and 3) a combination of the two. Each configuration was evaluated within the heavily instrumented North Fork American River basin in California during October-June 2000-10. Simulations of streamflow and snowpack using the Distributed Hydrology Soil and Vegetation Model (DHSVM) highlighted precipitation and radiation as variables whose sources resulted in significant differences. The best source of precipitation data varied between years. On average, the WRF performed as well as the single station distributed using the Parameter Regression on Independent Slopes Model (PRISM). The average percent biases in simulated streamflow were 3% and 1%, for configurations 1 and 2, respectively, even though precipitation compared directly with gauge measurements was biased high by 6% and 17%, suggesting that gauge undercatch may explain part of the bias. Simulations of snowpack using empirically estimated longwave irradiance resulted in melt rates lower than those observed at high-elevation sites, while at lower elevations the same forcing caused significant midwinter melt that was not observed. These results highlight the complexity of how forcing data sources impact hydrology over different areas (high- versus low-elevation snow) and different time periods. Overall, results support the use of output from the WRF model over empirical techniques in regions with limited station data. [ABSTRACT FROM AUTHOR]

Understanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) are well-known producers of precipitation along the U.S. West Coast. Depending on their intensity, orientation, and location of landfall, some ARs penetrate inland and cause heavy rainfall and flooding hundreds of miles from the coast. Climate change is projected to potentially alter a variety of AR characteristics and impacts. This study examines potential future changes in moisture transport and precipitation intensity, type, and distribution for a high-impact landfalling AR event in the U.S. Pacific Northwest using an ensemble of high-resolution numerical simulations produced under projected future thermodynamic changes. Results indicate increased total precipitation in all future simulations, although there is considerable model spread in both domain-averaged and localized inland precipitation totals. Notable precipitation enhancements across inland locations such as Idaho’s Sawtooth Mountain Range are present in four out of six future simulations. The most marked inland precipitation increases are shown to occur by way of stronger and deeper moisture transport that more effectively crosses Oregon’s Coastal and Cascade mountain ranges, essentially “spilling over” into the Snake River Valley and fueling orographic precipitation in the Sawtooth Mountains. Moisture transport enhancements are shown to have both thermodynamic and dynamic contributions, with both enhanced absolute environmental moisture and localized lower- and midlevel dynamics contributing to amplified inland moisture penetration. Precipitation that fell as snow in the present-day simulation becomes rain in the future simulations for many mid- and high-elevation locations, suggesting potential for enhanced flood risk for these regions in future climate instances of similar events. [ABSTRACT FROM AUTHOR]

Given uncertainty in precipitation gauge-based gridded datasets over complex terrain, we use multiple streamflow observations as an additional source of information about precipitation, in order to identify spatial and temporal differences between a gridded precipitation dataset and precipitation inferred from streamflow. We test whether gridded datasets capture across-crest and regional spatial patterns of variability, as well as year-to-year variability and trends in precipitation, in comparison to precipitation inferred from streamflow. We use a Bayesian model calibration routine with multiple lumped hydrologic model structures to infer the most likely basin-mean, water-year total precipitation for 56 basins with long-term (>30 year) streamflow records in the Sierra Nevada mountain range of California. We compare basin-mean precipitation derived from this approach with basin-mean precipitation from a precipitation gauge-based, 1/16° gridded dataset that has been used to simulate and evaluate trends in Western United States streamflow and snowpack over the 20th century. We find that the long-term average spatial patterns differ: in particular, there is less precipitation in the gridded dataset in higher-elevation basins whose aspect faces prevailing cool-season winds, as compared to precipitation inferred from streamflow. In a few years and basins, there is less gridded precipitation than there is observed streamflow. Lower-elevation, southern, and east-of-crest basins show better agreement between gridded and inferred precipitation. Implied actual evapotranspiration (calculated as precipitation minus streamflow) then also varies between the streamflow-based estimates and the gridded dataset. Absolute uncertainty in precipitation inferred from streamflow is substantial, but the signal of basin-to-basin and year-to-year differences are likely more robust. The findings suggest that considering streamflow when spatially distributing precipitation in complex terrain may improve its representation, particularly for basins whose orientations (e.g., windward-facing) are favored for orographic precipitation enhancement. [ABSTRACT FROM AUTHOR]

The near-surface climate, including the atmosphere, ocean, sea ice, and land state and fluxes, in the initial version of the Regional Arctic System Model (RASM) are presented. The sensitivity of the RASM near-surface climate to changes in atmosphere, ocean, and sea ice parameters and physics is evaluated in four simulations. The near-surface atmospheric circulation is well simulated in all four RASM simulations but biases in surface temperature are caused by biases in downward surface radiative fluxes. Errors in radiative fluxes are due to biases in simulated clouds with different versions of RASM simulating either too much or too little cloud radiative impact over open ocean regions and all versions simulating too little cloud radiative impact over land areas. Cold surface temperature biases in the central Arctic in winter are likely due to too few or too radiatively thin clouds. The precipitation simulated by RASM is sensitive to changes in evaporation that were linked to sea surface temperature biases. Future work will explore changes in model microphysics aimed at minimizing the cloud and radiation biases identified in this work. [ABSTRACT FROM AUTHOR]

The Regional Arctic System Model (RASM) is a fully coupled, regional Earth system model applied over the pan-Arctic domain. This paper discusses the implementation of the Variable Infiltration Capacity land surface model (VIC) in RASM and evaluates the ability of RASM, version 1.0, to capture key features of the land surface climate and hydrologic cycle for the period 1979-2014 in comparison with uncoupled VIC simulations, reanalysis datasets, satellite measurements, and in situ observations. RASM reproduces the dominant features of the land surface climatology in the Arctic, such as the amount and regional distribution of precipitation, the partitioning of precipitation between runoff and evapotranspiration, the effects of snow on the water and energy balance, and the differences in turbulent fluxes between the tundra and taiga biomes. Surface air temperature biases in RASM, compared to reanalysis datasets ERA-Interim and MERRA, are generally less than 2°C; however, in the cold seasons there are local biases that exceed 6°C. Compared to satellite observations, RASM captures the annual cycle of snow-covered area well, although melt progresses about two weeks faster than observations in the late spring at high latitudes. With respect to derived fluxes, such as latent heat or runoff, RASM is shown to have similar performance statistics as ERA-Interim while differing substantially from MERRA, which consistently overestimates the evaporative flux across the Arctic region. [ABSTRACT FROM AUTHOR]

The upper Sacramento River watershed is vital to California's water supply and is susceptible to major floods. Orographic precipitation in this complex terrain involves both atmospheric rivers (ARs) and the Sierra barrier jet (SBJ). The south-southeasterly SBJ induces orographic precipitation along south-facing slopes in the Mt. Shasta-Trinity Alps, whereas landfalling ARs ascend up and over the statically stable SBJ and induce orographic precipitation along west-facing slopes in the northern Sierra Nevada. This paper explores the occurrence of extreme daily precipitation (EDP) in this region in association with landfalling ARs and the SBJ. The 50 wettest days (i.e., days with EDP) for water years (WYs) 2002-11 based on the average of daily precipitation from eight rain gauges known as the Northern Sierra 8-Station Index (NS8I) are compared to dates from an SSM/I satellite-based landfalling AR-detection method and dates with SBJ events identified from nearby wind profiler data. These 50 days with EDP accounted for 20% of all precipitation during the 10-WY period, or 5 days with EDP per year on average account for one-fifth of WY precipitation. In summary, 46 of 50 (92%) days with EDP are associated with landfalling ARs on either the day before or the day of precipitation, whereas 45 of 50 (90%) days with EDP are associated with SBJ conditions on the day of EDP. Forty-one of 50 (82%) days with EDP are associated with both a landfalling AR and an SBJ. The top 10 days with EDP were all associated with both a landfalling AR and an SBJ. [ABSTRACT FROM AUTHOR]

An analysis of atmospheric rivers (ARs) as defined by an automated AR detection tool based on integrated water vapor transport (IVT) and the connection to heavy precipitation in the southeast United States (SEUS) is performed. Climatological water vapor and water vapor transport fields are compared between the U.S. West Coast (WCUS) and the SEUS, highlighting stronger seasonal variation in integrated water vapor in the SEUS and stronger seasonal variation in IVT in the WCUS. The climatological analysis suggests that IVT values above ~500 kg m−1 s−1 (as incorporated into an objective identification tool such as the AR detection tool used here) may serve as a sensible threshold for defining ARs in the SEUS. Atmospheric river impacts on heavy precipitation in the SEUS are shown to vary on an annual cycle, and a connection between ARs and heavy precipitation during the nonsummer months is demonstrated. When identified ARs are matched to heavy precipitation days (>100 mm day−1), an average match rate of ~41% is found. Results suggest that some aspects of an AR identification framework in the SEUS may offer benefit in forecasting heavy precipitation, particularly at medium- to longer-range forecast lead times. However, the relatively high frequency of SEUS heavy precipitation cases in which an AR is not identified necessitates additional careful consideration and incorporation of other critical aspects of heavy precipitation environments such that significant predictive skill might eventually result. [ABSTRACT FROM AUTHOR]

This work evaluates the fidelity of the polar marine Ekman layer in the Regional Arctic System Model (RASM) and Community Earth System Model (CESM) using sea-ice inertial oscillations as a proxy for ice-ocean Ekman transport. A case study is presented that demonstrates that RASM replicates inertial oscillations in close agreement with motion derived using the GPS. This result is obtained from a year-long case study pre-dating the recent decline in perennial Arctic sea ice, using RASM with sub-hourly coupling between the atmosphere, sea-ice and ocean components. To place this work in context, the RASM coupling method is applied to CESM, increasing the frequency of oceanic flux exchange from once per day in the standard CESM configuration, to every 30 min. For a single year simulation, this change causes a considerable increase in the median inertial ice speed across large areas of the Southern Ocean and parts of the Arctic sea-ice zone. The result suggests that processes associated with the passage of storms over sea ice (e.g. oceanic mixing, sea-ice deformation and surface energy exchange) are underestimated in Earth System Models that do not resolve inertial frequencies in their marine coupling cycle. [ABSTRACT FROM AUTHOR]

Two methods were used to identify the paths of moisture transport that reach the U.S. Intermountain West (IMW) during heavy precipitation events in winter. In the first, the top 150 precipitation events at stations located within six regions in the IMW were identified, and then back trajectories were initiated at 6-h intervals on those days at the four Climate Forecast System Reanalysis grid points nearest the stations. The second method identified the leading patterns of integrated water vapor transport (IVT) using the three leading empirical orthogonal functions of IVT over land that were first normalized by the local standard deviation. The top 1% of the associated 6-hourly time series was used to construct composites of IVT, atmospheric circulation, and precipitation. The results from both methods indicate that moisture originating from the Pacific that leads to extreme precipitation in the IMW during winter takes distinct pathways and is influenced by gaps in the Cascades (Oregon-Washington), the Sierra Nevada (California), and Peninsular Ranges (from Southern California through Baja California). The moisture transported along these routes appears to be the primary source for heavy precipitation for the mountain ranges in the IMW. The synoptic conditions associated with the dominant IVT patterns include a trough-ridge couplet at 500 hPa, with the trough located northwest of the ridge where the associated circulation funnels moisture from the west-southwest through the mountain gaps and into the IMW. [ABSTRACT FROM AUTHOR]

This study characterizes kinematic and thermodynamic structures of Sierra barrier jets (SBJs), atmospheric rivers (ARs), and their interaction over the period 14-16 February 2011 when a winter storm made landfall in northern California. A suite of scanning and profiling Doppler radars, rawinsondes, and GPS receivers is used to document these structures across the Central Valley and up the western Sierra slope to the crest along an ~200-km segment of the Sierra. The winter storm is grouped into two episodes, each having an AR that made landfall. Low-level winds in the SBJ observed during episode 1 were southeasterly and embedded in a stably stratified air mass. Along-barrier wind speeds U340 reached maximum values of 25-30 m s−1, as low as ~0.2 km MSL over the Central Valley, and as high as ~1.5 km MSL over the western Sierra slope. Southwesterly winds associated with the AR overlaid the SBJ along an interface that sloped upward from southwest to northeast with a southwestern extent at the western edge of the Central Valley. In contrast, low-level winds in the SBJ observed during episode 2 were more southerly and embedded in a less stable air mass. The U340 reached maximum values that were slightly weaker (~20-25 m s−1) and spread over a thicker layer that extended to higher levels over the western Sierra (~2.5 km MSL). Southwesterly winds associated with the AR overlaying the SBJ tilted upward from southwest to northeast with a steeper slope but did not extend as far southwest. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) are a dominant mechanism for generating intense wintertime precipitation along the U.S. West Coast. While studies over the past 10 years have explored the impact of ARs in, and west of, California's Sierra Nevada and the Pacific Northwest's Cascade Mountains, their influence on the weather across the intermountain west remains an open question. This study utilizes gridded atmospheric datasets, satellite imagery, rawinsonde soundings, a 449-MHz wind profiler and global positioning system (GPS) receiver, and operational hydrometeorological observing networks to explore the dynamics and inland impacts of a landfalling, flood-producing AR across Arizona in January 2010. Plan-view, cross-section, and back-trajectory analyses quantify the synoptic and mesoscale forcing that led to widespread precipitation across the state. The analyses show that a strong AR formed in the lower midlatitudes over the northeastern Pacific Ocean via frontogenetic processes and sea surface latent-heat fluxes but without tapping into the adjacent tropical water vapor reservoir to the south. The wind profiler, GPS, and rawinsonde observations document strong orographic forcing in a moist neutral environment within the AR that led to extreme, orographically enhanced precipitation. The AR was oriented nearly orthogonal to the Mogollon Rim, a major escarpment crossing much of central Arizona, and was positioned between the high mountain ranges of northern Mexico. High melting levels during the heaviest precipitation contributed to region-wide flooding, while the high-altitude snowpack increased substantially. The characteristics of the AR that impacted Arizona in January 2010, and the resulting heavy orographic precipitation, are comparable to those of landfalling ARs and their impacts along the west coasts of midlatitude continents. [ABSTRACT FROM AUTHOR]

Changes in wintertime 10 m winds due to the El Niño-Southern Oscillation are examined using a 6 km resolution climate simulation of Southern California covering the period from 1959 through 2001. Wind speed statistics based on regional averages reveal a general signal of increased mean wind speeds and wind speed variability during El Niño across the region. An opposite and nearly as strong signal of decreased wind speed variability during La Niña is also found. These signals are generally more significant than the better-known signals in precipitation. In spite of these regional-scale generalizations, there are significant sub-regional mesoscale structures in the wind speed impacts. In some cases, impacts on mean winds and wind variability at the sub-regional scale are opposite to those of the region as a whole. All of these signals can be interpreted in terms of shifts in occurrences of the region's main wind regimes due to the El Niño phenomenon. The results of this study can be used to understand how interannual wind speed variations in regions of Southern California are influenced by the El Niño phenomenon. [ABSTRACT FROM AUTHOR]

This study utilizes multiple decades of daily streamflow data gathered in four major watersheds in western Washington to determine the meteorological conditions most likely to cause flooding in those watersheds. Two are located in the Olympic Mountains and the other two in the western Cascades; and each has uniquely different topographic characteristics. The flood analysis is based on the maximum daily flow observed during each water year (WY) at each site [i.e., the annual peak daily flow (APDF)], with an initial emphasis on the 12 most recent water years between WY1998 and 2009, and then focusing on a 30-year interval between WY1980 and 2009. The shorter time period coincides with relatively complete passive microwave satellite coverage of integrated water vapor (IWV) over the Pacific basin. The combination of IWV imagery and streamflow data highlights a close link between landfalling atmospheric rivers (ARs) and APDFs (i.e., 46 of the 48 APDFs occurred with landfalling ARs). To complement this approach, the three-decade time series of APDFs, which correspond to the availability of the North American Regional Reanalysis (NARR) dataset, are examined. The APDFs occur most often, and are typically largest in magnitude, from November to January. The NARR is used to assess the composite meteorological conditions associated with the 10 largest APDFs at each site during this 30-year period. Heavy precipitation fell during the top 10 APDFs, and anomalously high composite NARR melting levels averaged ~1.9 km MSL, which is primarily above the four basins of interest. Hence, on average, mostly rain rather than snow fell within these basins, leading to enhanced runoff. The flooding on the four watersheds shared common meteorological attributes, including the presence of landfalling ARs with anomalous warmth, strong low-level water vapor fluxes, and weak static stability. There were also key differences that modulated the orographic control of precipitation. Notably, two watersheds experienced their top 10 APDFs when the low-level flow was southwesterly, while the other two basins had their largest APDFs with west-southwesterly flow. These differences arose because of the region's complex topography, basin orientations, and related rain shadowing. [ABSTRACT FROM AUTHOR]

This wind profiler–based study highlights key characteristics of the barrier jet along the windward slope of California’s Sierra Nevada. Between 2000 and 2007 roughly 10% of 100 000 hourly wind profiles, recorded at two sites, satisfied the sierra barrier jet (SBJ) threshold criteria described in the text. The mean magnitude of the terrain-parallel flow in the SBJ core (i.e., Vmax) was similar at both sites (∼17.5 m s−1) and at a comparable altitude, 500–1000 m above the surface. The cross-mountain wind speed was weak at the altitude of Vmax, consistent with blocked conditions. The seasonal cycle of SBJ occurrences showed a maximum during the cooler months and a minimum in summer. Additionally, the SBJ was stronger in winter than in summer. Because the warm-season (May–September) SBJs were different than their cool-season (October–April) counterparts and occurred during California’s dry season, they were not discussed in detail. An inventory of ∼250 cool-season SBJ cases from the two sites was generated (a case contains ≥8 consecutive SBJ profiles). Up to 60% of the nearby cool-season precipitation fell during SBJ cases, and these cases shifted the precipitation down the sierra’s windward slope and enhanced precipitation at the north end of the Central Valley (relative to non-SBJ conditions). The large number of cool-season SBJ cases was stratified by the mean strength and altitude of Vmax and by the case duration. Composite profiles of the along-barrier component for the top- and bottom-20 ranked cases in each of these three SBJ classes reveal stark differences in the magnitude and vertical positioning of the barrier jet. The three SBJ classes yielded uniquely different local precipitation characteristics in proximity to the wind profilers, with the strongest and longest-lived SBJs yielding the greatest precipitation. North American Regional Reanalysis plan-view composites were generated to explore the synoptic conditions responsible for, and to showcase the precipitation distributions associated with, the top- and bottom-20 ranked cases in each of the three classes of SBJs. The composite analyses yielded large contrasts between the SBJ classes that could prove useful in forecasting SBJs and their precipitation impacts. All SBJ classes occurred, on average, in the pre-cold-frontal environment of landfalling winter storms. [ABSTRACT FROM AUTHOR]