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Narrow cold‐frontal rainbands (NCFRs) produce short‐duration, high‐intensity precipitation associated with flash flooding and debris flows in Southern California, including the extremely destructive 2018 Montecito event. This manuscript presents the first known catalog of NCFR events in this region during winter seasons 1995–2020. A manual approach was used to identify NCFRs in radar imagery, supported by rain gauges and atmospheric reanalysis products. In total, 94 NCFRs were observed, with an average of three landfalling events occurring per water year. Propagation and impacts of these NCFRs were also investigated. Composite analyses of synoptic conditions reveal similarities across events; however, individual NCFRs exist on a spectrum of atmospheric conditions, precipitation intensity, and associated hazards. This regional record serves as a control dataset for the development of an objective identification algorithm and supports the evaluation and improvement of forecasting procedures. Methods established here are transferrable to other mid‐latitude regions with limited radar coverage. Plain Language Summary: Narrow cold‐frontal rainbands produce short‐duration (<1‐hr), high‐intensity precipitation associated with flash floods and debris flows in Southern California, including the extremely destructive 2018 Montecito event. Prior research describes development, predictability, and associated hazards of these bands, though no known long‐term record of their occurrence and climatological characteristics exists within the United States. This study provides the first known catalog of narrow cold‐frontal rainbands during the winter seasons of 1995–2020 in Southern California, and explores characteristics of these features such as frequency, movement, and the large‐scale meteorology that drives them. Events were documented manually using rain gauge observations, radar data, and output from atmospheric models. In total, 94 rainbands were documented during the study period, with an average of three landfalling events occurring in Southern California per water year. The intensity and impacts across the recorded events varied, though common weather patterns, including strengthening cyclones near the California coast, were associated with the documented events. This catalog supports weather forecasting efforts as well as the future development of an automated detection algorithm. Key Points: Southern California experienced 94 narrow cold‐frontal rainbands over 26 water years from 1995 to 2020Common synoptic conditions associated with narrow cold‐frontal rainband development include a deepening cyclone off of the California coastFuture work can focus on the development of automated detection algorithms for NCFR identification using radar, and improved forecasting [ABSTRACT FROM AUTHOR]

Rainfall intensity-duration (ID) thresholds are commonly used to assess flash flood potential downstream of burned watersheds. High-intensity and/or long-duration rainfall is required to generate flash floods as landscapes recover from fire, but there is little guidance on how thresholds change as a function of time since burning. Here, we force a hydrologic model with radar-derived precipitation to estimate ID thresholds for post-fire flash floods in a 41.5 km2 watershed in southern California, USA. Prior work in this study area constrains temporal changes in hydrologic model parameters, allowing us to estimate temporal changes in ID thresholds. Results indicate that ID thresholds increase by more than a factor of 2 from post-fire year 1 to post-fire year 5. Thresholds based on averaging rainfall intensity over durations of 30-60 minutes perform better than those that average rainfall intensity over shorter time intervals. Moreover, thresholds based on the 75th percentile of radar-derived rainfall intensity over the watershed perform better than thresholds based on the 25th or 50th percentile of rainfall intensity. Results demonstrate how hydrologic models can be used to estimate changes in ID thresholds following disturbance and provide guidance on the rainfall metrics that are best suited for predicting post-fire flash floods. [ABSTRACT FROM AUTHOR]

Conventional observations of atmospheric rivers (ARs) over the northeastern Pacific Ocean are sparse. Satellite radiances are affected by the presence of clouds and heavy precipitation, which impact their distribution in the lower atmosphere and in precipitating areas. The goal of this study is to document a data gap in existing observations of ARs in the northeastern Pacific, and to investigate how a targeted field campaign called AR Reconnaissance (AR Recon) can effectively fill this gap. When reconnaissance data are excluded, there is a gap in AR regions from near the surface to the middle troposphere (below 450 hPa), where most water vapor and its transport are concentrated. All-sky microwave radiances provide data within the AR object, but their quality is degraded near the AR core and its leading edge, due to the existence of thick clouds and precipitation. AR Recon samples ARs and surrounding areas to improve downstream precipitation forecasts over the western United States. This study demonstrates that despite the apparently extensive swaths of modern satellite radiances, which are critical to estimate large-scale flow, the data collected during 15 AR Recon cases in 2016, 2018, and 2019 supply about 99% of humidity, 78% of temperature, and 45% of wind observations in the critical maximum water vapor transport layer from the ocean surface to 700 hPa in ARs. The high-vertical-resolution dropsonde observations in the lower atmosphere over the northeastern Pacific Ocean can significantly improve the sampling of low-level jets transporting water vapor to high-impact precipitation events in the western United States. [ABSTRACT FROM AUTHOR]

Water management and flood control are major challenges in the western United States. They are heavily influenced by atmospheric river (AR) storms that produce both beneficial water supply and hazards; for example, 84% of all flood damages in the West (up to 99% in key areas) are associated with ARs. However, AR landfall forecast position errors can exceed 200 km at even 1-day lead time and yet many watersheds are <100 km across, which contributes to issues such as the 2017 Oroville Dam spillway incident and regularly to large flood forecast errors. Combined with the rise of wildfires and deadly post-wildfire debris flows, such as Montecito (2018), the need for better AR forecasts is urgent. Atmospheric River Reconnaissance (AR Recon) was developed as a research and operations partnership to address these needs. It combines new observations, modeling, data assimilation, and forecast verification methods to improve the science and predictions of landfalling ARs. ARs over the northeast Pacific are measured using dropsondes from up to three aircraft simultaneously. Additionally, airborne radio occultation is being tested, and drifting buoys with pressure sensors are deployed. AR targeting and data collection methods have been developed, assimilation and forecast impact experiments are ongoing, and better understanding of AR dynamics is emerging. AR Recon is led by the Center for Western Weather and Water Extremes and NWS/NCEP. The effort's core partners include the U.S. Navy, U.S. Air Force, NCAR, ECMWF, and multiple academic institutions. AR Recon is included in the "National Winter Season Operations Plan" to support improved outcomes for emergency preparedness and water management in the West. [ABSTRACT FROM AUTHOR]

Ice nucleating particles (INP) have been found to influence the amount, phase, and efficiency of precipitation from winter storms, including atmospheric rivers. Warm INP, those that initiate freezing at temperatures warmer than −10°C, are thought to be particularly impactful because they can create primary ice in mixed-phase clouds, enhancing precipitation efficiency. The dominant sources of warm INP during atmospheric rivers, the role of meteorology in modulating transport and injection of warm INP into atmospheric river clouds and the impact of warm INP on mixed-phase cloud properties are not well-understood. Time-resolved precipitation samples were collected during an atmospheric river in Northern California, USA during winter 2016. Precipitation was collected at two sites, one coastal and one inland, that are separated by less than 35km. The sites are sufficiently close that airmass sources during this storm were almost identical, but the inland site was exposed to terrestrial sources of warm INP while the coastal site was not. Warm INP were more numerous in precipitation at the inland site by an order of magnitude. Using FLEXPART dispersion modelling and radar-derived cloud vertical structure, we detected influence from terrestrial INP sources at the inland site, but did not find clear evidence of marine warm INP at either site. We episodically detected warm INP from long-range transported sources at both sites. By extending the FLEXPART modelling using a meteorological reanalysis, we demonstrate that long-range transported warm INP are observed only when the upper tropospheric jet provided transport to cloud tops. Using radar-derived hydrometeor classifications, we demonstrate that hydrometeors over the terrestrially-influenced inland site were more likely to be in the ice phase for cloud temperatures between 0°C and −10°C. We thus conclude that terrestrial and long-range transported aerosol were important sources of warm INP during this atmospheric river. Meteorological details such as transport mechanism and cloud structure were important in determining warm INP source strength and injection temperature, and ultimately the impact of warm INP on mixed phase cloud properties. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) account for more than 90% of the total meridional water vapor flux in midlatitudes, and 25-50% of the annual precipitation in the coastal western United States. In this study, reflectivity profiles from the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM-DPR) are used to evaluate precipitation and temperature characteristics of ARs over the western coast of North America and the eastern North Pacific Ocean. Evaluation of GPM-DPR bright-band height using a network of ground-based vertically pointing radars along the West Coast demonstrated exceptional agreement, and comparison with freezing level height from reanalyses over the eastern North Pacific Ocean also consistently agreed, indicating that GPM-DPR can be used to independently validate freezing level in models. However, precipitation comparison with gridded observations across the western United States indicated deficiencies in GPM-DPR's ability to reproduce the spatial distribution of winter precipitation, likely related to sampling frequency. Over the geographically homogeneous oceanic portion of the domain, sampling frequency was not problematic, and significant differences in the frequency and intensity of precipitation between GPM-DPR and reanalyses highlighted biases in both satellite-observed and modeled AR precipitation. Reanalyses precipitation rates below the minimum sensitivity of GPM-DPR accounted for a 20% increase in total precipitation, and 25% of radar-derived precipitation rates were greater than the 99th percentile precipitation rate in reanalyses. Due to differences in the proportions of precipitation in convective, stratiform bright-band, and non-bright-band conditions, AR conditions contributed nearly 10% more to total precipitation in GPM-DPR than reanalyses. [ABSTRACT FROM AUTHOR]

Winter westerly disturbances (WWD) are the primary climatic influence within High Mountain Asia during the boreal winter. Here we investigate variations and changes in WWD over the period 1979-2010 and relationships with heavy (85th percentile) precipitation in the Karakoram/western Himalaya (KH) and central Himalaya (CH) using multiple datasets. We show that heavy precipitation events occurring in the KH and CH are often spatiotemporally independent, suggesting differing behavior of WWD affecting each region. The wavelet power spectrum of 200 hPa geopotential height anomalies is used to characterize the frequency and magnitude of individual disturbances and to distinguish synoptic scale variability through time. Our analysis exhibits an enhancement in the strength and frequency of WWD in the KH and indicates an increase in local heavy precipitation events. In contrast, the CH is observed to experience weakening influence of these disturbances and consequently, a decrease in heavy precipitation. Furthermore, we investigate multi-annual variability of WWD and teleconnections with some known modes of climate variability affecting central Asia, including the Arctic Oscillation, Eurasian/Polar Pattern, the El Niño Southern Oscillation, and the Siberian High. Although there is clear evidence that these modes affect circulation and precipitation in High Mountain Asia, their competing influences on WWD are complex and non-linear. These results suggest that a thorough understanding of WWD and their spatiotemporal variations are crucial to improve our knowledge of the hydrologic cycle within High Mountain Asia as well as our ability to project the future status of Asia's water resources. [ABSTRACT FROM AUTHOR]