Subseasonal Clustering of Atmospheric rivers over the western United States

The serial occurrence of atmospheric rivers (ARs) along the US West Coast can lead to prolonged and exacerbated hydrologic impacts, threatening flood-control and water-supply infrastructure due to soil saturation and diminished recovery time between storms. Here a statistical approach for quantifying subseasonal temporal clustering among extreme events is applied to a 41-year (1979–2019) wintertime AR catalog across the western United States (US). Observed AR occurrence, compared against a randomly distributed AR timeseries with the same average event density, reveals temporal clustering at a greater-than-random rate across the western US with a distinct geographical pattern. Compared to the Pacific Northwest, significant AR clusters over the northern Coastal Range of California and Sierra Nevada are more frequent and occur over longer time periods. Clusters along the California Coastal Range typically persist for 2 weeks, are composed of 4–5 ARs per cluster, and account for over 85% of total AR occurrence. Across the northwest Coast-Cascade Ranges, clusters account for ∼50% of total AR occurrence, typically last 8–10 days, and contain 3–4 individual AR events. Based on precipitation data from a high-resolution dynamical downscaling of reanalysis, the fractions of total and extreme hourly precipitation attributable to AR clusters are largest along the northern California coast and in the Sierra Nevada. Interannual variability among clusters highlights their importance for determining whether a particular water year is anomalously wet or dry. The mechanisms behind this unusual clustering are unclear and require further research

Assessment of Observational Uncertainty in Extreme Precipitation Over the Continental United States

An extreme precipitation categorization scheme, developed to temporally and spatially visualize and track the multi-scale variability of extreme precipitation climatology, is introduced over the continental United States and used as the basis for an observational dataset intercomparison. The categorization scheme groups three-day precipitation totals exceeding 100 mm into five precipitation categories, or P-Cats . To assess observational uncertainty across a range of precipitation measurement approaches, we compare in situ station data from the Global Historical Climatology Network-Daily (GHCN-D), satellite derived data from the Tropical Rainfall Measuring Mission (TRMM), gridded station data from the Parameter-elevation Regression on Independent Slopes Model (PRISM), global reanalysis from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA 2), and regional reanalysis from the North American Regional Reanalysis (NARR). While all datasets capture the principal spatial patterns of extreme precipitation climatology, results show considerable variability across the five-platform suite in P-Cat frequency, spatial extent, and magnitude. Higher resolution datasets, PRISM and TRMM, most closely resemble GHCN-D and capture a greater frequency of high-end totals relative to lower resolution products, NARR and MERRA-2. When all datasets are regridded to a common coarser grid, differences persist with datasets originally constructed at a high resolution maintaining the highest frequency and magnitude of P-Cats. Potential future applications of this scheme include tracking change in P-Cats over space and time, climate model evaluation, and assessment of model projected change

Regional Characteristics and Variability of Extreme Precipitation and Atmospheric Rivers in Past, Present, and Future Climates Over the Contiguous United States

This dissertation examines the regional and seasonal variability of extreme precipitation and atmospheric rivers (ARs) across the contiguous United States (CONUS) in past, present, and future climates. An extreme precipitation categorization scheme, designed to monitor and track the multi-scale variability of extreme precipitation, is applied to a range of precipitation measurement products as an assessment of observational uncertainty. To investigate the importance of ARs across the CONUS, an objective AR identification algorithm is applied to global reanalysis to identify and characterize AR characteristics regionally over the observational record. Projected change in AR day frequency, geometry, intensity, and associated precipitation is quantified in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) under the Shared Socioeconomic Pathway 585 (SSP 585) high-end emissions warming scenario. Extreme precipitation most commonly occurs across the mountains of the western US in the winter and over the southeastern US in the summer and fall, associated with ARs and tropical systems, respectively. Observational uncertainty assessment results reveal historical precipitation measurement approaches, including in situ, satellite-derived, gridded in situ, and reanalysis, capture the principal spatial patterns of extreme precipitation climatology, with considerable variability in event frequency, spatial extent, and magnitude. Higher native resolution products most closely resemble in-situ observations, capturing a greater frequency of high-end multi-day totals relative to lower resolution products, even after rescaling, implying a systematic resolution-related bias. Within the observational record, ARs are most frequent in the fall and winter in the West, spring in the Great Plains, and fall in the Midwest and Northeast, showing regional and seasonal variability in basic geometry and IVT. Linked AR precipitation characteristics suggest that a substantial proportion of extreme events are associated with ARs over many parts of the CONUS, including the eastern US, characterized by seasonally-varying moisture transport patterns and lifting mechanisms. Analysis of change between five CMIP6 model historical simulations and future projections, under the SSP585 warming scenario, suggests notable increases in AR day frequency, intensity, and geometry by the end of the 21st century (2071-2100). Projections indicate ARs will comprise a greater share of the total climatological precipitation that falls CONUS-wide, as well as an increasing percentage of the occurrence of the top 5% of multi-day extremes. The findings from this dissertation aim to identify and quantify uncertainty in the regional-scale variability of extreme precipitation and associated meteorological mechanisms among observations and global climate model projections. Future climate change impacts studies require an improved dynamical and physical process-based understanding of extreme precipitation. Results from this dissertation can further support future investigation into the spatiotemporal variability of the underlying synoptic scale weather patterns (i.e., meteorological characteristics and dynamical processes) associated with enhanced precipitation formation during an AR

Linkages between atmospheric rivers and humid heat across the United States

The global increase in atmospheric water vapor due to climate change tends to heighten the dangers associated with both humid heat and heavy precipitation. Process-linked connections between these two extremes, particularly those which cause them to occur close together in space or time, are of special concern for impacts. Here we investigate how atmospheric rivers relate to the risk of summertime humid heat in the United States. We find that the hazards of atmospheric rivers and humid heat often occur in close proximity, most notably across the northern third of the United States. In this region, high levels of water vapor-resulting from the spatially organized horizontal moisture plumes that characterize atmospheric rivers-Act to amplify humid heat, generally during the transition from dry high-pressure ridge conditions to wet low-pressure trough conditions. In contrast, the US Southeast, Southwest, and Northwest tend to experience atmospheric rivers and humid heat separately, representing an important negative correlation of joint risk

A Climatology of Atmospheric Rivers and Associated Precipitation for the Seven US National Climate Assessment Regions

Motivated by a desire to understand the physical mechanisms involved in future anthropogenic changes in extreme temperature events, the key atmospheric circulation patterns associated with extreme daily temperatures over North America in the current climate are identified. The findings show that warm extremes at most locations are associated with positive 500-hPa geopotential height and sea level pressure anomalies just downstream with negative anomalies farther upstream. The orientation, physical characteristics, and spatial scale of these circulation patterns vary based on latitude, season, and proximity to important geographic features (i.e., mountains, coastlines). The anomaly patterns associated with extreme cold events tend to be similar to, but opposite in sign of, those associated with extreme warm events, especially within the westerlies, and tend to scale with temperature in the same locations. Circulation patterns aloft are more coherent across the continent than those at the surface where local surface features influence the occurrence of and patterns associated with extreme temperature days. Temperature extremes may be more sensitive to small shifts in circulation at locations where temperature is strongly influenced by mountains or large water bodies, or at the margins of important large-scale circulation patterns making such locations more susceptible to nonlinear responses to future climate change. The identification of these patterns and processes will allow for a thorough evaluation of the ability of climate models to realistically simulate extreme temperatures and their future trends

A Climatology Of Daily Synoptic Circulation Patterns And Associated Surface Meteorology Over Southern South America

Synoptic circulation patterns, defined as anomalies in sea level pressure (SLP), 500 hPa geopotential height (Z500), and 250 hPa wind speed (V250) and referred to as large-scale meteorological patterns (LSMPs), are characterized using the self-organizing maps approach over southern South America. Results show a wide range of possible LSMP types over a 37-year period of study. LSMP type variability can be summarized as a spectrum from patterns dominated by positive SLP and Z500 anomalies with a poleward displacement of the strongest 250 hPa winds, to patterns dominated by similar structures but with anomalies of opposite sign. The LSMPs found are connected with lower tropospheric temperature and wind, precipitation, and the frequency of atmospheric rivers (ARs). This highlights LSMPs more closely associated with anomalous and potentially impactful surface meteorology. Results show ARs as primary drivers of heavy precipitation over some of the region and connect their occurrence to driving synoptic dynamics. Two important low frequency modes of climate variability, the Southern Annular Mode (SAM) and the El Nino Southern Oscillation (ENSO), show some influence on the frequency of LSMP type, with the SAM more directly related to LSMP type modulation than ENSO. This comprehensive climatology of synoptic variability across southern South America has potential to aid in a mechanistic approach to studying climate change projections of temperature, precipitation, and AR frequency in climate models

Recreating the California New Year's Flood Event of 1997 in a Regionally Refined Earth System Model

Abstract: The 1997 New Year's flood event was the most costly in California's history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM‐E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events informs practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California‐focused RRM grids, with horizontal resolution refinement of 14 km down to 3.5 km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are better represented at finer horizontal resolutions resulting in better estimates of storm total precipitation and storm duration snowpack changes. Traditional time‐series and causal analysis frameworks are used to examine runoff sensitivities state‐wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time‐series shape, than forecast lead time, 2‐to‐4 days prior to the 1997 flood onset

Recreating the California New Year's Flood Event of 1997 in a Regionally Refined Earth System Model

Abstract The 1997 New Year's flood event was the most costly in California's history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM‐E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events informs practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California‐focused RRM grids, with horizontal resolution refinement of 14 km down to 3.5 km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are better represented at finer horizontal resolutions resulting in better estimates of storm total precipitation and storm duration snowpack changes. Traditional time‐series and causal analysis frameworks are used to examine runoff sensitivities state‐wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time‐series shape, than forecast lead time, 2‐to‐4 days prior to the 1997 flood onset