NOAA National Weather Service Western Region

Abstract A new method for automatic detection of atmospheric rivers (ARs) is developed and applied to an atmospheric reanalysis, yielding an extensive catalog of ARs land‐falling along the west coast of North America during 1948–2017. This catalog provides a large array of variables that can be used to examine AR cases and their climate‐scale variability in exceptional detail. The new record of AR activity, as presented, validated and examined here, provides a perspective on the seasonal cycle and the interannual‐interdecadal variability of AR activity affecting the hydroclimate of western North America. Importantly, AR intensity does not exactly follow the climatological pattern of AR frequency. Strong links to hydroclimate are demonstrated using a high‐resolution precipitation data set. We describe the seasonal progression of AR activity and diagnose linkages with climate variability expressed in Pacific sea surface temperatures, revealing links to Pacific decadal variability, recent regional anomalies, as well as a generally rising trend in land‐falling AR activity. The latter trend is consistent with a long‐term increase in vapor transport from the warming North Pacific onto the North American continent. The new catalog provides unprecedented opportunities to study the climate‐scale behavior and predictability of ARs affecting western North America.

Abstract In 2006, the National Centers for Environmental Prediction (NCEP) implemented the Real-Time Mesoscale Analysis (RTMA) in collaboration with the Earth System Research Laboratory and the National Environmental, Satellite, and Data Information Service (NESDIS). In this work, a description of the RTMA applied to the 5-km resolution conterminous U.S. grid of the National Digital Forecast Database is given. Its two-dimensional variational data assimilation (2DVAR) component used to analyze near-surface observations is described in detail, and a brief discussion of the remapping of the NCEP stage II quantitative precipitation amount and NESDIS Geostationary Operational Environmental Satellite (GOES) sounder effective cloud amount to the 5-km grid is offered. Terrain-following background error covariances are used with the 2DVAR approach, which produces gridded fields of 2-m temperature, 2-m specific humidity, 2-m dewpoint, 10-m U and V wind components, and surface pressure. The estimate of the analysis uncertainty via the Lanczos method is briefly described. The strength of the 2DVAR is illustrated by (i) its ability to analyze a June 2007 cold temperature pool over the Washington, D.C., area; (ii) its fairly good analysis of a December 2008 mid-Atlantic region high-wind event that started from a very weak first guess; and (iii) its successful recovery of the finescale moisture features in a January 2010 case study over southern California. According to a cross-validation analysis for a 15-day period during November 2009, root-mean-square error improvements over the first guess range from 16% for wind speed to 45% for specific humidity.

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.

Abstract Although atmospheric rivers (ARs) typically weaken following landfall, those that penetrate inland can contribute to heavy precipitation and high-impact weather within the interior of western North America. In this paper, the authors examine the evolution of ARs over western North America using trajectories released at 950 and 700 hPa within cool-season ARs along the Pacific coast. These trajectories are classified as coastal decaying, inland penetrating, or interior penetrating based on whether they remain within an AR upon reaching selected transects over western North America. Interior-penetrating AR trajectories most frequently make landfall along the Oregon coast, but the greatest fraction of landfalling AR trajectories that eventually penetrate into the interior within an AR is found along the Baja Peninsula. In contrast, interior-penetrating AR trajectories rarely traverse the southern “high” Sierra. At landfall, interior-penetrating AR trajectories are associated with a more amplified flow pattern, more southwesterly (vs westerly) flow along the Pacific coast, and larger water vapor transport (qυ). The larger initial qυ of interior-penetrating AR trajectories is due primarily to larger initial water vapor q and wind speed υ for those initiated at 950 and 700 hPa, respectively. Inland- and interior-penetrating AR trajectories maintain large qυ over the interior partially due to increases in υ that offset decreases in q, particularly in the vicinity of topographical barriers. Therefore, synoptic conditions and trajectory pathways favoring larger initial qυ at the coast, limited water vapor depletion by orographic precipitation, and increases in υ over the interior are keys to differentiating interior-penetrating from coastal-decaying ARs.

Abstract Atmospheric rivers (ARs) are long and narrow corridors of enhanced vertically integrated water vapor (IWV) and IWV transport (IVT) within the warm sector of extra tropical cyclones that can produce heavy precipitation and flooding in regions of complex terrain, especially along the U.S. West Coast. Several field campaigns have investigated ARs under the CalWater program of field studies. The first field phase of CalWater during 2009–11 increased the number of observations of precipitation and aerosols, among other parameters, across California and sampled ARs in the coastal and near-coastal environment, whereas the second field phase of CalWater during 2014–15 observed the structure and intensity of ARs and aerosols in the coastal and offshore environment over the northeast Pacific. This manuscript highlights the forecasts that were prepared for the CalWater field campaign in 2015, and the development and use of an “AR portal” that was used to inform these forecasts. The AR portal contains archived and real-time deterministic and probabilistic gridded forecast tools related to ARs that emphasize water vapor concentrations and water vapor flux distributions over the eastern North Pacific, among other parameters, in a variety of formats derived from the National Centers for Environmental Prediction (NCEP) Global Forecast System and Global Ensemble Forecast System. The tools created for the CalWater 2015 field campaign provided valuable guidance for flight planning and field activity purposes, and they may prove useful in forecasting ARs and better anticipating hydrometeorological extremes along the U.S. West Coast.

Abstract Recent and historical events illustrate the vulnerabilities of the U.S. west to extremes in precipitation that result from a range of meteorological phenomena. This vision provides an approach to mitigating impacts of such weather and water extremes that is tailored to the unique meteorological conditions and user needs of the Western U.S. in the 21st Century. It includes observations for tracking, predicting, and managing the occurrence and impacts of major storms and is informed by a range of user‐requirements, workshops, scientific advances, and technological demonstrations. The vision recommends innovations and enhancements to existing monitoring networks for rain, snow, snowmelt, flood, and their hydrometeorological precursor conditions, including radars to monitor winds aloft and precipitation, soil moisture sensors, stream gages, and SNOTEL enhancements, as well as entirely new observational tools. Key limitations include monitoring the fuel for heavy precipitation, storms over the eastern Pacific, precipitation distributions, and snow and soil moisture conditions. This article presents motivation and context, and describes key components, an implementation strategy, and expected benefits. This document supports a Resolution of the Western States Water Council for addressing extreme events.

Abstract Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Abstract Although several mountain ranges surround the Great Salt Lake (GSL) of northern Utah, the extent to which orography modifies GSL-effect precipitation remains largely unknown. Here the authors use observational and numerical modeling approaches to examine the influence of orography on the GSL-effect snowstorm of 27 October 2010, which generated 6–10 mm of precipitation (snow-water equivalent) in the Salt Lake Valley and up to 30 cm of snow in the Wasatch Mountains. The authors find that the primary orographic influences on the event are 1) foehnlike flow over the upstream orography that warms and dries the incipient low-level air mass and reduces precipitation coverage and intensity; 2) orographically forced convergence that extends downstream from the upstream orography, is enhanced by blocking windward of the Promontory Mountains, and affects the structure and evolution of the lake-effect precipitation band; and 3) blocking by the Wasatch and Oquirrh Mountains, which funnels the flow into the Salt Lake Valley, reinforces the thermally driven convergence generated by the GSL, and strongly enhances precipitation. The latter represents a synergistic interaction between lake and downstream orographic processes that is crucial for precipitation development, with a dramatic decrease in precipitation intensity and coverage evident in simulations in which either the lake or the orography are removed. These results help elucidate the spectrum of lake–orographic processes that contribute to lake-effect events and may be broadly applicable to other regions where lake effect precipitation occurs in proximity to complex terrain.

California is regularly impacted by floods and droughts, primarily as a result of too many or too few atmospheric rivers (ARs). This study analyzes a two-decade-long hourly precipitation dataset from 176 California weather stations and a 3-hourly AR chronology to report variations in rainfall events across California and their association with ARs. On average, 10-40 and 60-120 hours of rainfall in southern and northern California, respectively, are responsible for more than half of annual rainfall accumulations. Approximately 10-30% of annual precipitation at locations across the state is from only one large storm. On average, northern California receives 25-45 rainfall events annually (40-50% of which are AR-related). These events typically have longer durations and higher event-precipitation totals than those in southern California. Northern California also receives more AR landfalls with longer durations and stronger Integrated Vapor Transport (IVT). On average, ARs contribute 79%, 76%, and 68% of extreme-rainfall accumulations (i.e., top 5% events annually) in the north coast, northern Sierra, and Transverse Ranges of southern California, respectively. The San Francisco Bay Area terrain gap in the California Coast Range allows more AR water vapor to reach inland over the Delta and Sacramento Valley, and thus, influences precipitation in the Delta’s catchment. This is particularly important for extreme precipitation in the northern Sierra Nevada, including river basins above Oroville Dam and Shasta Dam. This study highlights differences between rainfall and AR characteristics in coastal versus inland northern California, differences that largely determine the regional geography of flood risks and water-reliability. These analyses support water resource, flood, levee, wetland, and ecosystem management within the catchment of the San Francisco estuary system by describing regional characteristics of ARs and their influence on rainfall on an hourly timescale.

Atmospheric rivers (ARs) are increasingly recognized globally as an important weather phenomenon associated with extreme precipitation. There is a substantial body of literature indicating that ARs are responsible for a large fraction of wet-season precipitation on western coasts (Rutz et al. 2019) and that they can cause large changes in snowpack (both positive and negative; Guan et al. 2010; Chen et al. 2019). Individual ARs and collections of ARs can bring large amounts of precipitation that drive floods and other storm-related hazards (Ralph et al. 2006, 2019a). ARs are a significant factor for water and associated water systems in the vicinity of western coasts (Gao et al. 2016; Ralph et al. 2019b). It is increasingly evident that they have major impacts on the energy and water budgets of the cryosphere: including mountains (Chen et al. 2019) and high-latitude regions (Gorodetskaya et al. 2014). These research advances hinge on technical advances in tracking ARs in observations, reanalyses, and climate model simulations and on understanding uncertainties associated with different tracking methods. In parallel with the recent increase in research activity around ARs, an increasing number of research groups have developed unique methods for tracking ARs (Shields et al. 2019).

Abstract Although smaller lakes are known to produce lake-effect precipitation, their influence on the precipitation climatology of lake-effect regions remains poorly documented. This study examines the contribution of lake-effect periods (LEPs) to the 1998–2009 cool-season (16 September–15 May) hydroclimate in the region surrounding the Great Salt Lake, a meso- β -scale hypersaline lake in northern Utah. LEPs are identified subjectively from radar imagery, with precipitation (snow water equivalent) quantified through the disaggregation of daily (i.e., 24 h) Cooperative Observer Program (COOP) and Snowpack Telemetry (SNOTEL) observations using radar-derived precipitation estimates. An evaluation at valley and mountain stations with reliable hourly precipitation gauge observations demonstrates that the disaggregation method works well for estimating precipitation during LEPs. During the study period, LEPs account for up to 8.4% of the total cool-season precipitation in the Great Salt Lake basin, with the largest contribution to the south and east of the Great Salt Lake. The mean monthly distribution of LEP precipitation is bimodal, with a primary maximum from October to November and a secondary maximum from March to April. LEP precipitation is highly variable between cool seasons and is strongly influenced by a small number of intense events. For example, at a lowland (mountain) station in the lake-effect-precipitation belt southeast of the Great Salt Lake, just 12 (13) events produce 50% of the LEP precipitation. Although these results suggest that LEPs contribute modestly to the hydroclimate of the Great Salt Lake basin, infrequent but intense events have a profound impact during some cool seasons.

Abstract Atmospheric River Reconnaissance (AR Recon) is a targeted campaign that complements other sources of observational data, forming part of a diverse observing system. AR Recon 2021 operated for ten weeks from January 13 to March 22, with 29.5 Intensive Observation Periods (IOPs), 45 flights and 1142 successful dropsondes deployed in the northeast Pacific. With the availability of two WC-130J aircraft operated by the 53 rd Weather Reconnaissance Squadron (53 WRS), Air Force Reserve Command (AFRC) and one National Oceanic and Atmospheric Administration (NOAA) Aircraft Operations Center (AOC) G-IVSP aircraft, six sequences were accomplished, in which the same synoptic system was sampled over several days. The principal aim was to gather observations to improve forecasts of landfalling atmospheric rivers on the U.S. West Coast. Sampling of other meteorological phenomena forecast to have downstream impacts over the U.S. was also considered. Alongside forecast improvement, observations were also gathered to address important scientific research questions, as part of a Research and Operations Partnership. Targeted dropsonde observations were focused on essential atmospheric structures, primarily atmospheric rivers. Adjoint and ensemble sensitivities, mainly focusing on predictions of U.S. West Coast precipitation, provided complementary information on locations where additional observations may help to reduce the forecast uncertainty. Additionally, Airborne Radio Occultation (ARO) and tail radar were active during some flights, 30 drifting buoys were distributed, and 111 radiosondes were launched from four locations in California. Dropsonde, radiosonde and buoy data were available for assimilation in real-time into operational forecast models. Future work is planned to examine the impact of AR Recon 2021 data on model forecasts.

What: A two-day workshop with participants from various U.S. federal agencies/programs, national and international universities, and U.S. national laboratories met to discuss progress with the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). ARTMIP aims to quantify the uncertainty in AR climatology, precipitation, and related impacts that arise from a wide range of AR tracking methods

The western United States is a preferred location for persistent midtropospheric long-wavelength ridges at the planetary scale. This greatly affects the character of synoptic-scale disturbances that move through the region, and results in an increased importance of mesoscale process and their interaction with the complex terrain of the area. This article discusses some of the important large scale, synoptic-scale, and mesoscale factors as background for the following series of papers on specific western United States terrain-influenced forecast problems.

Abstract When hazardous weather is forecast, communicating probabilistic information (PI) can improve trust, confidence, and understanding of forecast information, resulting in improved decision-making by emergency managers and public audiences. With probabilistic forecast tools modernizing forecast operations, the National Weather Service is calling on regional offices to increase the use of PI. However, communicating PI can be challenging since the information is intrinsically more complex than single-value deterministic forecasts that do not include a measure of uncertainty. We suggest that effective PI visualization not only includes the PI graphic but also communicates potential impacts and issues preventative guidance to limit exposure to weather-related hazards. Decision support tools like PI benefit from, if not require, effective visual communication that capitalizes on the efficiency of the visual system to extract information, decrease the time to interpret information, and increase the understanding of uncertainties. Furthermore, PI visuals need to be accessible to disabled and neurodivergent audiences. To enhance the visual communication of PI, we synthesize literature from graphic design and social science to identify guiding principles for effective visual communication and provide a one-page printout quick guide. To showcase how forecasters can incorporate guiding principles in the local context, we provide examples built from readily usable templates to demonstrate how probabilistic forecast information extracted from tools like the National Blend of Models can be used to enhance the visual communication of PI to support more informed decision-making.

Abstract Winter storms are disruptive to society and the economy, and they often cause significant injuries and deaths. Innovations in winter storm forecasting have occurred across the value chain over the past two decades, from physical understanding, to observations, to model forecasts, to postprocessing, to forecaster knowledge and interpretation, to products and services, and ultimately to decision support. These innovations enable more accurate and consistent forecasts, which are increasingly being translated into actionable information for decision-makers. This paper reviews the current state of winter storm forecasting in the context of the U.S. National Weather Service operations and describes a potential future state. Given predictability limitations, a key challenge of winter storm forecasting has been characterizing uncertainty and communicating the forecast in ways that are understandable and useful to decision-makers. To address this challenge, particular focus is placed on establishing a probabilistic framework, with probabilistic hazard information serving as a foundation for winter storm decision support services. The framework is guided by social science research to ensure effective communication of risk to meet users’ needs. Solutions to gaps impeding progress in winter storm forecasting are highlighted, including better understanding of mesoscale phenomenon, the need for better ensemble calibration, a rigorous and consistent database of observed impacts, and linking multiparameter probabilities (e.g., probability of intense snowfall rates at rush hour) with users’ information needs and decisions.

Today's winter weather headlines are based on the meteorological strength of an event with the assumption that stronger events produce larger public impacts. In reality, public impacts involve many factors, such as whether or not snow will accumulate on roads and affect traffic. Along with numerous environmental factors, decisions are further complicated by societal factors (e.g., timing of the commute). The National Weather Service (NWS) Strategic Plan calls for increased emphasis on decision support services (DSS) to our partners, especially during high-impact events. However, determining when events will produce high-impact conditions often remains a challenge. While forecasters should be aware of the relevant societal factors, they also need objective tools capable of integrating over the wide range of environmental factors that intersect in producing high-impact weather. This is particularly true in the case of road surface conditions, where complex interactions between temperature, moisture, and the road surface play a key role in determining what hazards might develop during wintry weather. Initial verification suggests that output from the Model of the Environment and Temperature of Roads (METRo) can provide useful information with regard to the timing and severity of hazardous road surface conditions, allowing NWS forecasters to more effectively highlight the impacts associated with impending meteorological events. This information enhances the DSS that the NWS is able to provide to government partners, local emergency management, and the public during high-impact winter weather events.

From 18 January to 23 January 2010, a series of winter storms impacted the western United States. During this period, a record-setting system produced severe convection, high winds, and heavy rain and snow on 21–22 January. The severe weather included tornadoes in California and gusts in excess of 40 m s−1 associated with an intense squall line affecting southeast California and Arizona. One of the primary impacts of the storms was a heavy precipitation event across Arizona. Rainfall amounts of 125–250 mm were recorded along the Mogollon Rim in central Arizona, while higher elevations in northern Arizona received 100–150 cm of snow, with one site setting the state's 24-h snowfall record. The heavy snow and high winds resulted in widespread power outages and paralyzed travel across portions of northern Arizona. All-time minimum pressure records were set across a large portion of the western United States from Oregon to Arizona. This was an extraordinary event that was well predicted. Standardized anomalies derived from the GFS Ensemble Forecast System (GEFS) indicated a potentially historic storm one week in advance. The forecast synoptic-scale anomalies were well correlated with high-impact weather across the western United States. This case demonstrates the utility of using standardized anomalies to increase situational awareness, which enables operational forecasters to provide decision makers with information regarding the potential significance of pending weather events. The event will also be utilized to demonstrate an anomaly-based situational awareness display for streamlining the identification, and analysis, of significant forecast anomalies.

An integrated warning team (IWT) approach to the provision of fire warnings (FRWs) for particularly dangerous wildfires has been developed and operationally demonstrated in select jurisdictions of Oklahoma and Texas. Such warnings provide initial public notification of wildfires that present an immediate threat to life and property and also influence protective actions by incident managers. This warning paradigm consists of a real-time interagency collaborative process between National Weather Service meteorologists and state forestry agency fire analysts based on shared knowledge of the fire environment and satellite-detected fire characteristics. To explore the viability of IWT FRW concepts elsewhere, analyses of decisional guidance thresholds for multiagency coordination and warning issuance timelines from operational demonstrations in Oklahoma and Texas are applied to data reviews of three western United States wildfire disasters. The retrospective test cases support possible warning issuance up to 55 minutes prior to the 8 November 2018 Camp Fire entering Paradise, California, and coincident with communitywide evacuations during the 30 December 2021 Marshall Fire near Boulder, Colorado. Retrospective analysis of the Kincade Fire (Sonoma County, California) on 27-28 October 2019 demonstrates potential application of IWT FRWs during a devastating run of an extended fire incident. These wildfire disasters exhibited environmental and remote sensing signals consistent with those used for successful IWT FRW demonstrations in Oklahoma and Texas. Evaluations of the IWT FRW paradigm for past fire disasters in the fire-prone American West may provide a framework for future collaborative multi-agency/disciplinary geo-targeted fire-scale warnings for dangerous and life-threatening wildfires.

In March 2020, the NOAA Snow Workshop brought together the snow observation and research communities from offices across NOAA’s National Weather Service (NWS), Oceanic and Atmospheric Research (OAR), and National Environmental Satellite, Data, and Information Service (NESDIS), along with subject matter experts from other agencies and organizations. While the organizing committee had planned for a 2-day workshop in College Park, Maryland, the workshop was adapted to a virtual format due to COVID-19 health and travel concerns.