Atmospheric Rivers Precipitation Research Articles

Synoptic and planetary-scale dynamics modulate antarctic atmospheric river precipitation intensity

Although rare, atmospheric rivers substantially influence the interannual variability of Antarctic surface mass balance. Here we use MERRA-2 reanalysis to identify characteristics unique to atmospheric river environments by comparing (1) Analog (environments that feature high-low pressure couplets, similar to Atmospheric River environments, but no Atmospheric River), (2) Atmospheric River, and (3) Top Atmospheric River (highest precipitation) timesteps during 1980–2019 around Antarctica. We find significant differences between Atmospheric River and Analog environments including more intense and poleward-shifted mid-tropospheric geopotential height couplets as well as larger atmospheric moisture anomalies. We find similar significant enhancement in synoptic-scale dynamic drivers of Top Atmospheric Rivers compared to all Atmospheric River environments, but no significant difference in local integrated water vapor anomalies. Instead, our results highlight the importance of large-scale dynamic drivers during Top Atmospheric River timesteps, including amplified Rossby waves excited by tropical convection.

Atmospheric Rivers are Responsible for Cyclicity in Sierra Nevada Precipitation

Abstract Cool-season (November–March) precipitation contributes critically to California’s water resources and flood risk. In the Sierra Nevada, approximately half of cool-season precipitation is derived from a small proportion of storms classified as atmospheric rivers (ARs). The frequency and intensity of ARs are highly variable from year to year and unreliable climate teleconnections limit forecasting. However, previous research provides intriguing evidence of cycles with biennial (2.2 years) and decadal (10–20 years) periodicities in Sierra Nevada cool-season precipitation, suggesting it is not purely stochastic. To identify the source of this cyclicity, we decompose daily precipitation records (1949–2022) into contributions from ARs versus non-ARs, as well as into variations in frequency and intensity. We find that the biennial and decadal spectral peaks in Sierra Nevada precipitation totals are entirely due to precipitation delivered by ARs, and primarily due to variations in the frequency of days with AR precipitation. While total non-AR precipitation correlates with sea surface temperature (SST) and atmospheric pressure patterns associated with the El Niño–Southern Oscillation, AR precipitation shows no consistent remote teleconnections at any periodicity. Supporting this finding, atmospheric simulations forced by observed SSTs do not reproduce the biennial or decadal precipitation variations identified in observations. These results, combined with the lack of long-term stable cycles in previously published tree-ring reconstructions, suggest that the observed biennial and decadal quasi-cyclicity in Sierra Nevada precipitation is unreliable as a forecasting tool. Significance Statement In California’s Sierra Nevada, where most of the state’s above-ground water resources originate, cool-season precipitation totals exhibited year-to-year and decadal cyclicity over the past century. Long-range forecasts are notoriously unskillful in this region, so nonrandom cycles would be intriguing to water managers challenged to simultaneously minimize flood and drought risk. Over 1949–2022, precipitation cycles were driven by variations in the number of atmospheric river (AR) storms per year even though ARs account for just half of total precipitation. These findings bring us a step closer to understanding the causes of precipitation cyclicity, but we find no evidence that the cycles were underpinned by larger-scale ocean–atmosphere circulations so we caution against relying on continued cycles into the future.

Performance of New Near-Real-Time PERSIANN Product (PDIR-Now) for Atmospheric River Events over the Russian River Basin, California

Abstract Most heavy precipitation events and extreme flooding over the U.S. Pacific coast can be linked to prevalent atmospheric river (AR) conditions. Thus, reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for water management and early warning systems of flooding and landslides over these regions. At the same time, high-quality near-real-time measurements of AR precipitation remain challenging due to the complex topographic features of land surface and meteorological conditions of the region: specifically, orographic features occlude radar measurements while infrared-based algorithms face challenges, differentiating between both cold brightband (BB) precipitation and the warmer nonbrightband (NBB) precipitation. It should be noted that the latter precipitation is characterized by greater orographic enhancement. In this study, we evaluate the performance of a recently developed near-real-time satellite precipitation algorithm: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain Rate-Now (PDIR-Now). This model is primarily dependent on infrared information from geostationary satellites as input; consequently, PDIR-Now has the advantage of short data latency, 15–60-min delay between observation to precipitation product delivery. The performance of PDIR-Now is analyzed with a focus on AR-related events for cases dominated by NBB and BB precipitation over the Russian River basin. In our investigations, we utilize S-band (3-GHz) precipitation profilers with Joss/Parsivel disdrometer measurements at the Middletown and Santa Rosa stations to classify BB and NBB precipitation events. In general, our analysis shows that PDIR-Now is more skillful in retrieving precipitation rates over both BB and NBB events across the topologically complex study area as compared to PERSIANN-Cloud Classification System (CCS). Also, we discuss the performance of well-known operational near-real-time precipitation products from 2017 to 2019. Conventional categorical and volumetric categorical indices, as well as continuous statistical metrics, are used to show the differences between various high-resolution precipitation products such as Multi-Radar Multi-Sensor (MRMS).

Ocean Surface Salinity Response to Atmospheric River Precipitation in the California Current System

Abstract Atmospheric rivers (ARs) result in precipitation over land and ocean. Rainfall on the ocean can generate a buoyant layer of freshwater that impacts exchanges between the surface and the mixed layer. These “fresh lenses” are important for weather and climate because they may impact the ocean stratification at all time scales. Here we use in situ ocean data, collocated with AR events, and a one-dimensional configuration of a general circulation model, to investigate the impact of AR precipitation on surface ocean salinity in the California Current System (CCS) on seasonal and event-based time scales. We find that at coastal and onshore locations the CCS freshens through the rainy season due to AR events, and years with higher AR activity are associated with a stronger freshening signal. On shorter time scales, model simulations suggest that events characteristic of CCS ARs can produce salinity changes that are detectable by ocean instruments (≥0.01 psu). Here, the surface salinity change depends linearly on rain rate and inversely on wind speed. Higher wind speeds (U > 8 m s−1) induce mixing, distributing freshwater inputs to depths greater than 20 m. Lower wind speeds (U ≤ 8 m s−1) allow freshwater lenses to remain at the surface. Results suggest that local precipitation is important in setting the freshwater seasonal cycle of the CCS and that the formation of freshwater lenses should be considered for identifying impacts of atmospheric variability on the upper ocean in the CCS on weather event time scales. Significance Statement Atmospheric rivers produce large amounts of rainfall. The purpose of this study is to understand how this rain impacts the surface ocean in the California Current System on seasonal and event time scales. Our results show that a greater precipitation over the rainy season leads to a larger decrease in salinity over time. On shorter time scales, these atmospheric river precipitation events commonly produce a surface salinity response that is detectable by ocean instruments. This salinity response depends on the amount of rainfall and the wind speed. In general, higher wind speeds will cause the freshwater input from rain to mix deeper, while lower wind speeds will have reduced mixing, allowing a layer of freshwater to persist at the surface.

Atmospheric rivers in CMIP5 climate ensembles downscaled with a high-resolution regional climate model

Abstract. Atmospheric rivers (ARs) are important drivers of hazardous precipitation levels and are often associated with intense floods. So far, the response of ARs to climate change in Europe has been investigated using global climate models within the CMIP5 framework. However, the spatial resolution of those models (1–3∘) is too coarse for an adequate assessment of local to regional precipitation patterns. Using a regional climate model with 0.22∘ resolution, we downscaled an ensemble consisting of 1 ERA-Interim (ERAI) reanalysis data hindcast simulation, 9 global historical, and 24 climate scenario simulations following greenhouse gas emission scenarios RCP2.6, RCP4.5, and RCP8.5. The performance of the climate model to simulate AR frequencies and AR-induced precipitation was tested against ERAI. Overall, we find a good agreement between the downscaled CMIP5 historical simulations and ERAI. However, the downscaled simulations better represented small-scale spatial characteristics. This was most evident over the terrain of the Iberian Peninsula, where the AR-induced precipitation pattern clearly reflected prominent east–west topographical elements, resulting in zonal bands of high and low AR impact. Over central Europe, the models simulated a smaller propagation distance of ARs toward eastern Europe than obtained using the ERAI data. Our models showed that ARs in a future warmer climate will be more frequent and more intense, especially in the higher-emission scenarios (RCP4.5, RCP8.5). However, assuming low emissions (RCP2.6), the related changes can be mostly mitigated. According to the high-emission scenario RCP8.5, AR-induced precipitation will increase by 20 %–40 % in western central Europe, whereas mean precipitation rates increase by a maximum of only 12 %. Over the Iberian Peninsula, AR-induced precipitation will slightly decrease (∼6 %) but the decrease in the mean rate will be larger (∼15 %). These changes will lead to an overall increased fractional contribution of ARs to heavy precipitation, with the greatest impact over the Iberian Peninsula (15 %–30 %) and western France (∼15 %). Likewise, the fractional share of yearly maximum precipitation attributable to ARs will increase over the Iberian Peninsula, the UK, and western France. Over Norway, average AR precipitation rates will decline by −5 % to −30 %, most likely due to dynamic changes, with ARs originating from latitudes > 60∘ N decreasing by up to 20 % and those originating south of 45∘ N increasing. This suggests that ARs over Norway will follow longer routes over the continent, such that additional moisture uptake will be impeded. By contrast, ARs from >60∘ N will take up moisture from the North Atlantic before making landfall over Norway. The found changes in the local AR pathway are probably driven by larger-scale circulation changes such as a change in dominating weather regimes and/or changes in the winter storm track over the North Atlantic.

Atmospheric River Precipitation Enhanced by Climate Change: A Case Study of the Storm That Contributed to California's Oroville Dam Crisis

AbstractAn increasingly volatile hydroclimate increases California's reliance on precipitation from atmospheric rivers (ARs) for water resources. Here, we simulate the AR that contributed to the Oroville Dam crisis in early February 2017 under global climate conditions representing preindustrial, present‐day, mid‐, and late‐21st century environments. This event consisted of two distinct AR pulses: the first snowy, westerly, and cool followed by a southwesterly and warm pulse resulting in copious rain‐on‐snow. We estimate that climate change to date results in ∼11% and ∼15% increase in precipitation over the Feather River Basin in Northern California for the first and second pulses, respectively, with late‐21st century enhancements upwards of ∼21% and ∼59%, respectively. Although both pulses were enhanced by the imposed climate changes, the thermodynamic response and subsequent precipitation increases were most substantial during the second pulse. The disparate changes demonstrated here highlight that not all ARs will respond similarly in a warmer world.

Evaluation of a Reanalysis‐Driven Configuration of WRF4 Over the Western United States From 1980 to 2020

AbstractDynamical downscaling remains a powerful tool for studying regional climate processes, and the genesis of high‐resolution historical and future climate data. This technique is particularly important over areas of complex terrain, such as the western United States (WUS), where global models are especially limited in representing regional climate. After identifying a suite of WRF options that best simulate snow and precipitation for an average water year (2010) over the WUS, we evaluate the performance of the dynamically downscaled European Centre for Medium‐range Weather Forecasting's fifth Reanalysis (ERA5) from 1980 to 2020 on 45‐km, 9‐km, and two 3‐km grids. We find that by decreasing the horizontal grid spacing within WRF, improvements to Sierra Nevada and Northern Rocky Mountain snow, Santa Ana and Diablo winds, and coastal meteorology occur. For landfalling atmospheric rivers (ARs), the downscaled reanalysis simulates greater upstream integrated vapor transport (IVT) than ERA5. However, WRF skillfully simulates the positioning of the IVT and the timing and magnitude of AR precipitation. This potential IVT bias, in conjunction with increasing resolution, leads to a wet precipitation bias across the Sierra Nevada in the 3‐km experiment. This conclusion is supported by streamflow analysis, although we note that the bias in the 3‐km experiment can also be explained by in situ undercatch issues. Meanwhile, the 9‐km experiment is more biased than the 3‐km experiment across the Northern Rocky Mountains compared to in situ measured SWE and precipitation, indicating a geographic sensitivity to biases.

Atmospheric River Precipitation Contributed to Rapid Increases in Surface Height of the West Antarctic Ice Sheet in 2019

AbstractEstimating the relative contributions of the atmospheric and dynamic components of ice‐sheet mass balance is critical for improving projections of future sea level rise. Existing estimates of changes in Antarctic ice‐sheet height, which can be used to infer changes in mass, are only accurate at multiyear time scales. However, NASA's Ice, Cloud, and land Elevation Satellite‐2 (ICESat‐2) laser altimetry mission now allows us to accurately measure changes in ice‐sheet height at subannual time scales. Here, we use ICESat‐2 data to estimate height changes over Antarctica between April 2019 and June 2020. These data show widespread increases in surface height over West Antarctica during the 2019 austral winter. Using climate reanalysis data, we show that 41% of increases in height during winter were from snow accumulation via extreme precipitation events—63% of these events were associated with landfalling atmospheric rivers (ARs) which occurred only 5.1% of the time.

Atmospheric rivers in high-resolution simulations of the Paleocene Eocene Thermal Maximum (PETM)

Atmospheric rivers (ARs) and related precipitation are analyzed in high resolution climate simulations during the Eocene using a sophisticated Earth System Model framework. Simulations are conducted across different forcing scenarios spanning the transition from the cooler Late Paleocene period to the Paleocene Eocene Thermal Maximum (PETM), testing both greenhouse gas and orbital sensitivities. AR metrics are compiled and compared across the various simulations and shown to reflect underlying storm tracks where changes in the low-level jet are the primary forcing mechanism for landfall location. Precipitation attributable to ARs is characterized by intensity and amount and compared to total precipitation. Generally, AR precipitation intensity is predominantly moderate, however, this varies by forcing scenario, region, and latitudinal location depending on location of the storm tracks. Extreme rates exist particularly for elevated greenhouse gases and an orbital configuration that maximizes Northern Hemisphere summer insolation. Three regions are diagnosed for landfalling ARs: Western North America, Europe, and Australia. Proxy evidence from the Pyrenees is directly compared to modelled European streamflow and suggests that precipitation produced by ARs can potentially explain the proxy hydrological signal.

Examination of Global Midlatitude Atmospheric River Lifecycles Using an Object‐Oriented Methodology

AbstractTracking atmospheric rivers (ARs) across their lifecycles is a field of recent interest with a multitude of emerging methodologies. The CONNected‐objECT (CONNECT) algorithm is adapted for the tracking of global midlatitude AR lifecycles and associated precipitation by implementing a seeded region growing segmentation algorithm, creating the AR‐CONNECT algorithm. To facilitate the permissiveness of the methodology, AR‐CONNECT is without hard‐coded geometric criteria yet is still shown to extract synoptic‐scale elongated objects >99.99% of the time. One of the consequences of the methodology is the ability to occasionally track atmospheric water vapor anomalies before evolving into AR geometries, effectively tracking AR genesis further back than other studies. With the aid of subdaily satellite‐derived rain data, we investigate the climatology, trends, and patterns of AR lifecycles from 1983–2016 and compare with other AR tracking studies. We find that AR frequency, genesis, and terminus locations are in generally good agreement with other AR tracking methodologies, though with key differences, and that AR frequencies in each hemisphere are determined by the number of AR hotspots. Furthermore, we uncover evidence that certain AR characteristics, such as frequency, areal extent, and duration, show evidence of increasing trends. Midlatitude precipitation uncovered by AR‐CONNECT shows contributions up to 50% over land and 65% over the ocean. Trend analysis of AR precipitation shows an increase in precipitation associated with ARs propagated by the Southern Jet Stream and ARs that traverse over the Sahara Desert, among others, but is determined not to be a driver of changes in global precipitation.

Sensitivity of Atmospheric River Vapor Transport and Precipitation to Uniform Sea Surface Temperature Increases.

Filaments of intense vapor transport called atmospheric rivers (ARs) are responsible for the majority of poleward vapor transport in the midlatitudes. Despite their importance to the hydrologic cycle, there remain many unanswered questions about changes to ARs in a warming climate. In this study we perform a series of escalating uniform SST increases (+2, +4, and +6K, respectively) in the Community Atmosphere Model version 5 in an aquaplanet configuration to evaluate the thermodynamic and dynamical response of AR vapor content, transport, and precipitation to warming SSTs. We find that AR column integrated water vapor (IWV) is especially sensitive to SST and increases by 6.3–9.7% per degree warming despite decreasing relative humidity through much of the column. Further analysis provides a more nuanced view of AR IWV changes: Since SST warming is modest compared to that in the midtroposphere, computing fractional changes in IWV with respect to SST results in finding spuriously large increases. Meanwhile, results here show that AR IWV transport increases relatively uniformly with temperature and at consistently lower rates than IWV, as modulated by systematically decreasing low‐level wind speeds. Similarly, changes in AR precipitation are related to a compensatory relationship between enhanced near‐surface moisture and damped vertical motions.

Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products

AbstractAtmospheric rivers (ARs) play an important role in the total annual precipitation regionally and globally, delivering precious freshwater to many arid/semiarid regions. On the other hand, they may cause intense precipitation and floods with huge socioeconomic effects worldwide. In this study, we investigate AR‐related precipitation using 18 years (2001–2018) of globally gridded AR locations derived from Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2). AR precipitation features are explored regionally and seasonally using remote sensing (Integrated Multi‐satellitE Retrievals for GPM version 6 [IMERG V6], daily Global Precipitation Climatology Project version 1.3 [GPCP V1.3], bias‐adjusted CPC Morphing Technique version 1 [CMORPH V1], and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks [PERSIANN‐CDR]) and reanalysis (MERRA‐2 and ECMWF Reanalysis 5th Generation [ERA5]) precipitation products. The results show that most of the world (except the tropics) experience more intense precipitation from AR‐related events compared to non‐AR events. Over the oceans (especially the Southern Ocean), the contribution of ARs to the total precipitation and extreme events is larger than over land. However, some coastal areas over land are highly affected by ARs (e.g., the western and eastern United States and Canada, Western Europe, North Africa, and part of the Middle East, East Asia, and eastern South America and part of Australia). Although spatial correlations for pairs of IMERG/CMORPH and GPCP/PERSIANN‐CDR are fairly high, considerable discrepancies are shown in their estimation of AR‐related events (i.e., overall IMERG and CMORPH show a higher fraction of AR‐related precipitation). It was found that the degree of consistency between reanalysis and satellite‐based products is highly regionally dependent, partly due to the uneven distribution of in situ measurements.

Precipitation characteristics related to atmospheric rivers in East Asia

AbstractPrecipitation related to atmospheric rivers (ARs) is critical in shaping climate and extreme hydrologic events in the mid‐latitude coastal regions, making it a recent topic of intense research. This study has analysed the AR climatology, AR‐precipitation characteristics and their regional variations in East Asia (EA) for 1979–2015 using an AR inventory based on vertically‐integrated water‐vapour transport and AR geometry. The AR frequency over EA varies seasonally with highest (lowest) frequency in summer (winter). The AR frequency peaks in the coastal regions of the mid‐latitude western North Pacific (WNP), then decreases rapidly away from the region towards higher/lower latitudes and inlands. ARs are related to 30–60% of the annual precipitation in EA with maximum in summer; secondary peaks occur in spring in eastern China, Korea and southern Japan, and in winter for the southern China coast. Calculating the AR precipitation on days of partial AR occurrences from daily precipitation data is a key source of uncertainties in the AR‐precipitation fraction in this study. The AR days are substantially more related to heavy precipitation than non‐AR days for all seasons and regions. Seasonal cycle of AR frequency over EA and the WNP follows the northward march of the main rainband from spring to mid‐summer, but is decoupled from it from late summer to winter as the North Pacific storm track migrates into the Eastern North Pacific. The annual cycle of AR frequency and AR precipitation varies regionally; Japan and southern China adjacent to WNP show high (low) frequency of weak‐ (heavy‐) precipitating ARs in early spring (late fall) with highly frequent heavy‐precipitating ARs in summer while the mid‐latitude coastal regions, eastern China and Korea, show low frequency of heavy‐precipitating ARs in early fall with highly frequent heavy‐precipitating ARs in mid‐summer.

Patterns and Drivers of Atmospheric River Precipitation and Hydrologic Impacts across the Western United States

AbstractAtmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.

Evaluation of physical parameterizations for atmospheric river induced precipitation and application to long-term reconstruction based on three reanalysis datasets in Western Oregon

Dynamically downscaled precipitation is often used for evaluating sub-daily precipitation behavior on a watershed-scale and for the input to hydrological modeling because of its increasing accuracy and spatiotemporal resolution. Despite these advantages, physical parameterizations in regional models and systematic biases due to the dataset used for boundary conditions greatly influence the quality of downscaled precipitation data. The present paper aims to evaluate the performance and the sensitivities of physical parameterizations of the Weather Research and Forecasting (WRF) model to simulate extreme precipitation associated with atmospheric rivers (ARs) over the Willamette watershed in Oregon. Also investigated was whether the optimized WRF configuration for extreme events can be used for long-term reconstruction using different boundary condition datasets. Three reanalysis datasets, the Twentieth Century Reanalysis version 2c (20CRv2c), the European Center for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA20C), and the Climate Forecast System Reanalysis (CFSR), which have different spatial resolutions and dataset periods, were used to simulate precipitation at 4 km resolution. Sensitivity analyses showed that AR precipitation is most sensitive to the microphysics parameterization. Among 13 microphysics schemes investigated, the Goddard and the Stony-Brook University schemes performed the best regardless of the choice of reanalysis. Reconstructed historical precipitation with the optimized configuration showed better accuracies during the wet season than the dry season. With respect to simulations with CFSR, it was found that the optimized configuration for AR precipitation can be used for long-term reconstruction with small biases. However, systematic biases in the reanalysis datasets may still lead to uncertainties in downscaling precipitation in a different season with a single configuration.

How well were the early 2017 California Atmospheric River precipitation events captured by satellite products and ground‐based radars?

In January and February of 2017, California experienced multiple heavy storms that caused serious destruction of facilities and economic loss, although it also helped to reduce water storage deficit due to prolonged drought in previous years. These extreme precipitation events were mainly associated with Atmospheric Rivers (ARs) and brought about 174 km3 of water to California according to ground observations. This article evaluates the performance of six commonly used satellite‐based precipitation products (IMERG, 3B42RT, PERSIANN, CCS, CMORPH and GSMaP), as well as ground‐based radar products (Radar‐only and Radar‐lgc) in capturing the ARs precipitation rate and distribution. It is found that precipitation maps from all products present heavy precipitation in January and February, with more consistent observations over ocean than land. Though large uncertainties exist in quantitative precipitation estimation (QPE) over land, the ensemble mean of different remote‐sensing precipitation products over California is consistent with gauge measurements. Among the six satellite‐based products, IMERG correlates the best with gauge observations both in the detection and quantification of precipitation, but it is not the best product in terms of root‐mean‐square error or bias. Compared to satellite products, ground weather radar shows better precipitation detectability and estimation skill. However, neither radar nor satellite QPE products have good performances in quantifying the peak precipitation intensity during the extreme events, suggesting that further advancement in quantification of extremely intense precipitation associated with ARs in the western United States is needed.

Influence of atmospheric rivers on vegetation productivity and fire patterns in the southwestern U.S.

AbstractIn the southwestern U.S., the meteorological phenomenon known as atmospheric rivers (ARs) has gained increasing attention due to its strong connections to floods, snowpacks, and water supplies in the West Coast states. Relatively less is known about the ecological implications of ARs, particularly in the interior Southwest, where AR storms are less common. To address this gap, we compared a chronology of AR landfalls on the west coast between 1989 and 2011 and between 25°N and 42.5°N to annual metrics of the normalized difference vegetation index (NDVI; an indicator of vegetation productivity) and daily resolution precipitation data to assess influences of AR‐fed winter precipitation on vegetation productivity across the southwestern U.S. We mapped correlations between winter AR precipitation during landfalling ARs and (1) annual maximum NDVI and (2) area burned by large wildfires summarized by ecoregion during the same year as the landfalls and during the following year. Interannual variations of AR precipitation strongly influenced both NDVI and area burned by wildfire in some dryland ecoregions. The influence of ARs on dryland vegetation varied significantly depending on the latitude of landfall, with those ARs making landfall below 35°N latitude more strongly influencing these systems, and with effects observed as far as 1300 km from the landfall location. As climatologists' understanding of the synoptic patterns associated with the occurrence of ARs continues to evolve, an increased understanding of how AR landfalls, in aggregate, influence vegetation productivity and associated wildfire activity in dryland ecosystems may provide opportunities to better predict ecological responses to climate and climate change.

On the Quantification of Atmospheric Rivers Precipitation from Space: Composite Assessments and Case Studies over the Eastern North Pacific Ocean and the Western United States

Abstract Atmospheric rivers (ARs) are often associated with extreme precipitation, which can lead to flooding or alleviate droughts. A decade (2003–12) of landfalling ARs impacting the North American west coast (between 32.5° and 52.5°N) is collected to assess the skill of five commonly used satellite-based precipitation products [T3B42, T3B42 real-time (T3B42RT), CPC morphing technique (CMORPH), PERSIANN, and PERSIANN–Cloud Classification System (CCS)] in capturing ARs’ precipitation rate and pattern. AR detection was carried out using a database containing twice-daily satellite-based integrated water vapor composite observations. It was found that satellite products are more consistent over ocean than land and often significantly underestimate precipitation rate over land compared to ground observations. Incorrect detection of precipitation from IR-based methods is prevalent over snow and ice surfaces where microwave estimates often show underestimation or missing data. Bias adjustment using ground observation is found very effective to improve satellite products, but it also raises concern regarding near-real-time applicability of satellite products for ARs. The analysis using individual case studies (6–8 January and 13–14 October 2009) and an ensemble of AR events suggests that further advancement in capturing orographic precipitation and precipitation over cold and frozen surfaces is needed to more reliably quantify AR precipitation from space.

Characterization of extreme precipitation within atmospheric river events over California

Abstract. Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California. We have recently developed the TECA (Toolkit for Extreme Climate Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.

A Climatology of the Vertical Structure of Water Vapor Transport to the Sierra Nevada in Cool Season Atmospheric River Precipitation Events

Abstract This study presents the climatology of the vertical structure of water vapor flux above the Sierra Nevada during significant cool season (November–April) precipitation events. Atmospheric river (AR) and non-AR events are analyzed to better understand the effect of this structure on precipitation patterns. Daily measurements of cool season precipitation at seven weather stations around the Tahoe basin from 1974 to 2012 and NCEP/CPC gridded daily precipitation analysis along the Sierra crest for the period 1948–2012 are examined. NCEP–NCAR reanalysis and soundings from Oakland are used to look at upper atmospheric conditions, including the presence of vapor transport by low- and midlevel jets on storm days as well as upstream static stability in relation to significant precipitation events. Key findings are as follows: 1) ARs play a disproportionately large role in generating Tahoe basin precipitation during the cool season; 2) strong midlevel vapor transport needs to occur in tandem with low-level transport to achieve the most extreme 2-day precipitation in the Tahoe basin; 3) when low- to midlevel vapor transport is present on days with a defined AR, the local maximum in 2-day precipitation intensity decreases with distance from the Sierra crest, and on non-AR days, the relative increase in 2-day precipitation intensity due to low- and midlevel vapor transport does not vary based on distance from the Sierra crest; 4) AR and non-AR moisture fluxes are significantly modified by upstream static stability; and 5) understanding the impacts of ARs and their lower- and midlevel moisture flux structure are crucial components of the hydrometeorology in this region.