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Abstract
In support of the 2004 North American Monsoon Experiment (NAME) field campaign, NOAA established and maintained a field site about 100 km north of Mazatlán, Mexico, consisting of wind profilers, precipitation profilers, surface upward–downward-looking radiometers, and a 10-m meteorological tower to observe the environment within the North American monsoon. Three objectives of this NOAA project are discussed in this paper: 1) to observe the vertical structure of precipitating cloud systems as they passed over the NOAA profiler site, 2) to estimate the vertical air motion and the raindrop size distribution from near the surface to just below the melting layer, and 3) to better understand the microphysical processes associated with stratiform rain containing well-defined radar bright bands.
To provide a climatological context for the profiler observations at the field site, the profiler reflectivity distributions were compared with Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity distributions from the 2004 season over the NAME domain as well as from the 1998–2005 seasons. This analysis places the NAME 2004 observations into the context of other monsoon seasons. It also provides a basis for evaluating the representativeness of the structure of the precipitation systems sampled at this location. The number of rain events observed by the TRMM PR is dependent on geography; the land region, which includes portions of the Sierra Madre Occidental, has more events than the coast and gulf regions. Conversely, from this study it is found that the frequencies of occurrence of stratiform rain and reflectivity profiles with radar bright bands are mostly independent of region. The analysis also revealed that the reflectivity distribution at each height has more year-to-year variability than region-to-region variability. These findings suggest that in cases with a well-defined bright band, the vertical profile of the reflectivity relative to the height of the bright band is similar over the gulf, coast, and land regions.
Abstract
In support of the 2004 North American Monsoon Experiment (NAME) field campaign, NOAA established and maintained a field site about 100 km north of Mazatlán, Mexico, consisting of wind profilers, precipitation profilers, surface upward–downward-looking radiometers, and a 10-m meteorological tower to observe the environment within the North American monsoon. Three objectives of this NOAA project are discussed in this paper: 1) to observe the vertical structure of precipitating cloud systems as they passed over the NOAA profiler site, 2) to estimate the vertical air motion and the raindrop size distribution from near the surface to just below the melting layer, and 3) to better understand the microphysical processes associated with stratiform rain containing well-defined radar bright bands.
To provide a climatological context for the profiler observations at the field site, the profiler reflectivity distributions were compared with Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity distributions from the 2004 season over the NAME domain as well as from the 1998–2005 seasons. This analysis places the NAME 2004 observations into the context of other monsoon seasons. It also provides a basis for evaluating the representativeness of the structure of the precipitation systems sampled at this location. The number of rain events observed by the TRMM PR is dependent on geography; the land region, which includes portions of the Sierra Madre Occidental, has more events than the coast and gulf regions. Conversely, from this study it is found that the frequencies of occurrence of stratiform rain and reflectivity profiles with radar bright bands are mostly independent of region. The analysis also revealed that the reflectivity distribution at each height has more year-to-year variability than region-to-region variability. These findings suggest that in cases with a well-defined bright band, the vertical profile of the reflectivity relative to the height of the bright band is similar over the gulf, coast, and land regions.
Abstract
Two vertically pointing S-band radars (coastal and inland) were operated in western Washington during two winters to monitor brightband snow-level altitudes. Similar snow-level characteristics existed at both sites, although the inland site exhibited lower snow levels by ~70 m because of proximity to cold continental air, and snow-level altitude changes were delayed there by several hours owing to onshore translation of weather systems. The largest precipitation accumulations and rates occurred when the snow level was largely higher than the adjacent terrain. A comparison of these observations with long-term operational radiosonde data reveals that the radar snow levels mirrored climatological conditions. The inland radar data were used to assess the performance of nearby operational freezing-level forecasts. The forecasts possessed a lower-than-observed bias of 100–250 m because of a combination of forecast error and imperfect representativeness between the forecast and observing points. These forecast discrepancies increased in magnitude with higher observed freezing levels, thus representing the hydrologically impactful situations where a greater fraction of mountain basins receive rain rather than snow and generate more runoff than anticipated. Vertical directional wind shear calculations derived from wind-profiler data, and concurrent surface temperature data, reveal that most snow-level forecast discrepancies occurred with warm advection aloft and low-level cold advection through the Stampede Gap. With warm advection, forecasts were too high (low) for observed snow levels below (above) 1.25 km MSL. An analysis of sea level pressure differences across the Cascades indicated that mean forecasts were too high (low) for observed snow levels below (above) 1.25 km MSL when higher pressure was west (east) of the range.
Abstract
Two vertically pointing S-band radars (coastal and inland) were operated in western Washington during two winters to monitor brightband snow-level altitudes. Similar snow-level characteristics existed at both sites, although the inland site exhibited lower snow levels by ~70 m because of proximity to cold continental air, and snow-level altitude changes were delayed there by several hours owing to onshore translation of weather systems. The largest precipitation accumulations and rates occurred when the snow level was largely higher than the adjacent terrain. A comparison of these observations with long-term operational radiosonde data reveals that the radar snow levels mirrored climatological conditions. The inland radar data were used to assess the performance of nearby operational freezing-level forecasts. The forecasts possessed a lower-than-observed bias of 100–250 m because of a combination of forecast error and imperfect representativeness between the forecast and observing points. These forecast discrepancies increased in magnitude with higher observed freezing levels, thus representing the hydrologically impactful situations where a greater fraction of mountain basins receive rain rather than snow and generate more runoff than anticipated. Vertical directional wind shear calculations derived from wind-profiler data, and concurrent surface temperature data, reveal that most snow-level forecast discrepancies occurred with warm advection aloft and low-level cold advection through the Stampede Gap. With warm advection, forecasts were too high (low) for observed snow levels below (above) 1.25 km MSL. An analysis of sea level pressure differences across the Cascades indicated that mean forecasts were too high (low) for observed snow levels below (above) 1.25 km MSL when higher pressure was west (east) of the range.
Abstract
An evaluation of Weather Surveillance Radar-1988 Doppler (WSR-88D) KMUX and KDAX radar quantitative precipitation estimation (QPE) over a site in California’s northern Sonoma County is performed and rain type climatology is presented. This site is next to the flood-prone Russian River basin and, because of the mountainous terrain and remoteness from operational radars, is generally believed to lack adequate coverage. QPE comparisons were conducted for multiyear observations with concurrent classification of rainfall structure using measurements from a gauge and an S-band profiler deployed at the location of interest. The radars were able to detect most of the brightband (BB) rain, which contributed over half of the total precipitation. For this rain type hourly radar-based QPE obtained with a default vertical profile of reflectivity correction provided results with errors of about 50%–60%. The operational radars did not detect precipitation during about 30% of the total rainy hours with mostly shallow nonbrightband (NBB) rain, which, depending on the radar, provided ~(12%–15%) of the total precipitation. The accuracy of radar-based QPE for the detected fraction of NBB rain was rather poor with large negative biases and characteristic errors of around 80%. On some occasions, radars falsely detected precipitation when observing high clouds, which did not precipitate or coexisted with shallow rain (less than 10% of total accumulation). For heavier rain with a significant fraction of BB hourly periods, radar QPE for event totals showed relatively good agreement with gauge data. Cancelation of errors of opposite signs contributed, in part, to such agreement. On average, KDAX-based QPE was biased low compared to KMUX.
Abstract
An evaluation of Weather Surveillance Radar-1988 Doppler (WSR-88D) KMUX and KDAX radar quantitative precipitation estimation (QPE) over a site in California’s northern Sonoma County is performed and rain type climatology is presented. This site is next to the flood-prone Russian River basin and, because of the mountainous terrain and remoteness from operational radars, is generally believed to lack adequate coverage. QPE comparisons were conducted for multiyear observations with concurrent classification of rainfall structure using measurements from a gauge and an S-band profiler deployed at the location of interest. The radars were able to detect most of the brightband (BB) rain, which contributed over half of the total precipitation. For this rain type hourly radar-based QPE obtained with a default vertical profile of reflectivity correction provided results with errors of about 50%–60%. The operational radars did not detect precipitation during about 30% of the total rainy hours with mostly shallow nonbrightband (NBB) rain, which, depending on the radar, provided ~(12%–15%) of the total precipitation. The accuracy of radar-based QPE for the detected fraction of NBB rain was rather poor with large negative biases and characteristic errors of around 80%. On some occasions, radars falsely detected precipitation when observing high clouds, which did not precipitate or coexisted with shallow rain (less than 10% of total accumulation). For heavier rain with a significant fraction of BB hourly periods, radar QPE for event totals showed relatively good agreement with gauge data. Cancelation of errors of opposite signs contributed, in part, to such agreement. On average, KDAX-based QPE was biased low compared to KMUX.
Abstract
S-band profiling (S-PROF) radar measurements from different southeastern U.S. Hydrometeorology Testbed sites indicated a frequent occurrence of rain that did not exhibit radar bright band (BB) and was observed outside the periods of deep-convective precipitation. This common nonbrightband (NBB) rain contributes ~15%–20% of total accumulation and is not considered as a separate rain type by current precipitation-segregation operational radar-based schemes, which separate rain into stratiform, convective, and, sometimes, tropical types. Collocated with S-PROF, disdrometer measurements showed that drop size distributions (DSDs) of NBB rain have much larger relative fractions of smaller drops when compared with those of BB and convective rains. Data from a year of combined DSD and rain-type observations were used to derive S-band-radar estimators of rain rate R, including those based on traditional reflectivity Z e and ones that also use differential reflectivity Z DR and specific differential phase K DP. Differences among same-type estimators for mostly stratiform BB and deep-convective rain were relatively minor, but estimators derived for the common NBB rain type were distinct. Underestimations in NBB rain-rate retrievals derived using other rain-type estimators (e.g., those for BB or convective rain or default operational radar estimators) for the same values of radar variables can be on average about 40%, although the differential phase-based estimators are somewhat less susceptible to DSD details. No significant differences among the estimators for the same rain type derived using DSDs from different observational sites were present despite significant separation and differing terrain. Identifying areas of common NBB rain could be possible from Z e and Z DR measurements.
Abstract
S-band profiling (S-PROF) radar measurements from different southeastern U.S. Hydrometeorology Testbed sites indicated a frequent occurrence of rain that did not exhibit radar bright band (BB) and was observed outside the periods of deep-convective precipitation. This common nonbrightband (NBB) rain contributes ~15%–20% of total accumulation and is not considered as a separate rain type by current precipitation-segregation operational radar-based schemes, which separate rain into stratiform, convective, and, sometimes, tropical types. Collocated with S-PROF, disdrometer measurements showed that drop size distributions (DSDs) of NBB rain have much larger relative fractions of smaller drops when compared with those of BB and convective rains. Data from a year of combined DSD and rain-type observations were used to derive S-band-radar estimators of rain rate R, including those based on traditional reflectivity Z e and ones that also use differential reflectivity Z DR and specific differential phase K DP. Differences among same-type estimators for mostly stratiform BB and deep-convective rain were relatively minor, but estimators derived for the common NBB rain type were distinct. Underestimations in NBB rain-rate retrievals derived using other rain-type estimators (e.g., those for BB or convective rain or default operational radar estimators) for the same values of radar variables can be on average about 40%, although the differential phase-based estimators are somewhat less susceptible to DSD details. No significant differences among the estimators for the same rain type derived using DSDs from different observational sites were present despite significant separation and differing terrain. Identifying areas of common NBB rain could be possible from Z e and Z DR measurements.
Abstract
Because knowledge of the melting level is critical to river forecasters and other users, an objective algorithm to detect the brightband height from profiles of radar reflectivity and Doppler vertical velocity collected with a Doppler wind profiling radar is presented. The algorithm uses vertical profiles to detect the bottom portion of the bright band, where vertical gradients of radar reflectivity and Doppler vertical velocity are negatively correlated. A search is then performed to find the peak radar reflectivity above this feature, and the brightband height is assigned to the altitude of the peak. Reflectivity profiles from the off-vertical beams produced when the radar is in the Doppler beam swinging mode provide additional brightband measurements. A consensus test is applied to subhourly values to produce a quality-controlled, hourly averaged brightband height. A comparison of radar-deduced brightband heights with melting levels derived from temperature profiles measured with rawinsondes launched from the same radar site shows that the brightband height is, on average, 192 m lower than the melting level. A method for implementing the algorithm and making the results available to the public in near–real time via the Internet is described. The importance of melting level information in hydrological prediction is illustrated using the NWS operational river forecast model applied to mountainous watersheds in California. It is shown that a 2000-ft increase in the melting level can triple run off during a modest 24-h rainfall event. The ability to monitor the brightband height is likely to aid in melting-level forecasting and verification.
Abstract
Because knowledge of the melting level is critical to river forecasters and other users, an objective algorithm to detect the brightband height from profiles of radar reflectivity and Doppler vertical velocity collected with a Doppler wind profiling radar is presented. The algorithm uses vertical profiles to detect the bottom portion of the bright band, where vertical gradients of radar reflectivity and Doppler vertical velocity are negatively correlated. A search is then performed to find the peak radar reflectivity above this feature, and the brightband height is assigned to the altitude of the peak. Reflectivity profiles from the off-vertical beams produced when the radar is in the Doppler beam swinging mode provide additional brightband measurements. A consensus test is applied to subhourly values to produce a quality-controlled, hourly averaged brightband height. A comparison of radar-deduced brightband heights with melting levels derived from temperature profiles measured with rawinsondes launched from the same radar site shows that the brightband height is, on average, 192 m lower than the melting level. A method for implementing the algorithm and making the results available to the public in near–real time via the Internet is described. The importance of melting level information in hydrological prediction is illustrated using the NWS operational river forecast model applied to mountainous watersheds in California. It is shown that a 2000-ft increase in the melting level can triple run off during a modest 24-h rainfall event. The ability to monitor the brightband height is likely to aid in melting-level forecasting and verification.
Abstract
A new S-band vertical profiler with a coupler option for extending the dynamic range of the radar’s receiver is discussed. The added dynamic range allows the profiler to record radar reflectivity measurements in moderate to heavy precipitation that otherwise would not have been possible with this system because of receiver saturation. The radar hardware, signal processor, and operating software are based on existing S-band and UHF profiler technology. Results from a side-by-side comparison with a calibrated Ka-band radar are used to determine the calibration and sensitivity of the S-band profiler. In a typical cloud profiling mode of operation, the sensitivity is −14 dBZ at 10 km. Examples taken from a recent field campaign are shown to illustrate the profiler’s ability to measure vertical velocity and radar reflectivity profiles in clouds and precipitation, with particular emphasis on the benefit provided by the coupler technology.
Abstract
A new S-band vertical profiler with a coupler option for extending the dynamic range of the radar’s receiver is discussed. The added dynamic range allows the profiler to record radar reflectivity measurements in moderate to heavy precipitation that otherwise would not have been possible with this system because of receiver saturation. The radar hardware, signal processor, and operating software are based on existing S-band and UHF profiler technology. Results from a side-by-side comparison with a calibrated Ka-band radar are used to determine the calibration and sensitivity of the S-band profiler. In a typical cloud profiling mode of operation, the sensitivity is −14 dBZ at 10 km. Examples taken from a recent field campaign are shown to illustrate the profiler’s ability to measure vertical velocity and radar reflectivity profiles in clouds and precipitation, with particular emphasis on the benefit provided by the coupler technology.
Abstract
During winter 2016/17, California experienced numerous heavy precipitation events linked to land-falling atmospheric rivers (ARs) that filled reservoirs and ended a severe, multiyear drought. These events also caused floods, mudslides, and debris flows, resulting in major socioeconomic disruptions. During 2–11 February 2017, persistent heavy precipitation in the northern Sierra Nevada culminated in a rapid increase in the water level on Lake Oroville, necessitating the activation of an emergency spillway for the first time since the Oroville Dam was installed and forcing the evacuation of 188,000 people. The precipitation, which mostly fell as rain due to elevated freezing levels, was focused on the western slope of the Sierra Nevada in connection with orographic forcing linked to two successive ARs. Heavy rain fell on saturated soils and a snowpack produced by antecedent storms and thereby resulted in excessive runoff into Lake Oroville that led to a damaged spillway and complicated reservoir operations.
Abstract
During winter 2016/17, California experienced numerous heavy precipitation events linked to land-falling atmospheric rivers (ARs) that filled reservoirs and ended a severe, multiyear drought. These events also caused floods, mudslides, and debris flows, resulting in major socioeconomic disruptions. During 2–11 February 2017, persistent heavy precipitation in the northern Sierra Nevada culminated in a rapid increase in the water level on Lake Oroville, necessitating the activation of an emergency spillway for the first time since the Oroville Dam was installed and forcing the evacuation of 188,000 people. The precipitation, which mostly fell as rain due to elevated freezing levels, was focused on the western slope of the Sierra Nevada in connection with orographic forcing linked to two successive ARs. Heavy rain fell on saturated soils and a snowpack produced by antecedent storms and thereby resulted in excessive runoff into Lake Oroville that led to a damaged spillway and complicated reservoir operations.
Abstract
With funding provided by the 2012 Disaster Relief Act (Sandy Supplemental), NOAA’s Earth System Research Laboratory Physical Sciences Division has installed three Doppler wind-profiling radars and surface meteorology towers along the U.S. Gulf and southeast coasts to help detect and monitor landfalling tropical storms and other high-impact weather events. This same combination of instruments has been used to monitor landfalling atmospheric rivers on the U.S. West Coast. For this reason, we refer to the whole collection of instruments at each site as an Atmospheric River Observatory (ARO). These three new AROs supported by the Sandy Supplemental complement a fourth ARO deployed in coastal North Carolina as part of NOAA’s Hydrometeorology Testbed Southeast Pilot Study. These four AROs were installed in time to capture the 2014 hurricane season and will be operated through the 2015 hurricane season.
Abstract
With funding provided by the 2012 Disaster Relief Act (Sandy Supplemental), NOAA’s Earth System Research Laboratory Physical Sciences Division has installed three Doppler wind-profiling radars and surface meteorology towers along the U.S. Gulf and southeast coasts to help detect and monitor landfalling tropical storms and other high-impact weather events. This same combination of instruments has been used to monitor landfalling atmospheric rivers on the U.S. West Coast. For this reason, we refer to the whole collection of instruments at each site as an Atmospheric River Observatory (ARO). These three new AROs supported by the Sandy Supplemental complement a fourth ARO deployed in coastal North Carolina as part of NOAA’s Hydrometeorology Testbed Southeast Pilot Study. These four AROs were installed in time to capture the 2014 hurricane season and will be operated through the 2015 hurricane season.
Abstract
Observations from northern California during the California Landfalling Jets (CALJET) experiment are used to examine the mean characteristics of precipitation and their variances as functions of synoptic and topographic regimes. Ten cases involving the landfall of extratropical cyclones are analyzed with radar and rain gauge data collected at two sites: one in the coastal mountains north of San Francisco (CZD) and the other in the Central Valley just west of Sacramento (KDAX). Aside from the melting-layer bright band, the most striking feature in the 10-case composite vertical profile of radar reflectivity at CZD was a distinct change in slope about 2.5 km above the bright band. This “shoulder” is thought to represent a change in the growth rate of hydrometeors. Although the bright band was quite distinct, about one-third of the profiles in the composite did not exhibit this feature. These nonbrightband (NBB) profiles had a low-level slope where reflectivity increased with decreasing altitude, a structure suggesting that collision–coalescence was the primary growth process. The relationship between surface rainfall rate and low-level radar reflectivity implies that all profiles were composed of larger numbers of small drops than expected from a Marshall–Palmer drop size distribution, a trend that was especially apparent for NBB profiles.
Synoptic variability of precipitation characteristics at CZD were examined by identifying five distinct regimes (cold sector, warm front, warm sector, cold front, and cool sector) based on a simplified conceptual model. The shoulder remained approximately 2.5 km above the bright band in each regime. Rainfall intensity was highest during the cold-frontal regime and NBB rainfall was most common during the warm-frontal, warm-sector, and cool-sector regimes. Topographic variability of precipitation characteristics was investigated by comparing results at CZD and KDAX. A shoulder structure located about 2.5 km above the bright band was also evident in the KDAX profiles, suggesting that this feature is related to large-scale dynamic, thermodynamic, and microphysical processes rather than orographic effects. The relationship between surface rainfall rate and low-level radar reflectivity near KDAX closely followed a trend expected for a Marshall–Palmer drop size distribution, implying the presence of relatively larger raindrops than observed at CZD and indicating that NBB rainfall occurs less frequently near KDAX.
Abstract
Observations from northern California during the California Landfalling Jets (CALJET) experiment are used to examine the mean characteristics of precipitation and their variances as functions of synoptic and topographic regimes. Ten cases involving the landfall of extratropical cyclones are analyzed with radar and rain gauge data collected at two sites: one in the coastal mountains north of San Francisco (CZD) and the other in the Central Valley just west of Sacramento (KDAX). Aside from the melting-layer bright band, the most striking feature in the 10-case composite vertical profile of radar reflectivity at CZD was a distinct change in slope about 2.5 km above the bright band. This “shoulder” is thought to represent a change in the growth rate of hydrometeors. Although the bright band was quite distinct, about one-third of the profiles in the composite did not exhibit this feature. These nonbrightband (NBB) profiles had a low-level slope where reflectivity increased with decreasing altitude, a structure suggesting that collision–coalescence was the primary growth process. The relationship between surface rainfall rate and low-level radar reflectivity implies that all profiles were composed of larger numbers of small drops than expected from a Marshall–Palmer drop size distribution, a trend that was especially apparent for NBB profiles.
Synoptic variability of precipitation characteristics at CZD were examined by identifying five distinct regimes (cold sector, warm front, warm sector, cold front, and cool sector) based on a simplified conceptual model. The shoulder remained approximately 2.5 km above the bright band in each regime. Rainfall intensity was highest during the cold-frontal regime and NBB rainfall was most common during the warm-frontal, warm-sector, and cool-sector regimes. Topographic variability of precipitation characteristics was investigated by comparing results at CZD and KDAX. A shoulder structure located about 2.5 km above the bright band was also evident in the KDAX profiles, suggesting that this feature is related to large-scale dynamic, thermodynamic, and microphysical processes rather than orographic effects. The relationship between surface rainfall rate and low-level radar reflectivity near KDAX closely followed a trend expected for a Marshall–Palmer drop size distribution, implying the presence of relatively larger raindrops than observed at CZD and indicating that NBB rainfall occurs less frequently near KDAX.
Abstract
A multiscale analysis is presented of extreme precipitation events (EPEs) in Northern California during winter 2016–17, which caused flooding and contributed substantially to highly anomalous seasonal precipitation totals. The EPEs were characterized by long durations (≥7 days) and involved persistent large-scale flow patterns. The three largest EPEs involved blocking over the Bering Sea–Alaska region. A detailed investigation of the largest EPE, occurring on 2–10 February 2017, reveals that extreme precipitation was produced as four discrete cyclones moved across the eastern North Pacific equatorward of a high-amplitude blocking ridge and impacted the U.S. West Coast in rapid succession. The latter three cyclones developed and moved in conjunction with elongated negatively tilted troughs or PV streamers resulting from repeated episodes of baroclinic development and cyclonic Rossby wave breaking on the upstream flank of the block. Each of the four cyclones interacted with a PV streamer and an associated baroclinic zone established by anticyclonic wave breaking on the downstream flank of the block and, thereby, tracked into the U.S. West Coast. The serial clustering of the cyclones during the 9-day event resulted in persistent water vapor flux and lifting that supported extreme precipitation totals in Northern California. A climatological analysis for 1979–2017 reveals a significant statistical relationship between blocking over the Bering Sea–Alaska region and EPEs in Northern California, indicating that this type of blocking pattern represents a favorable large-scale scenario for extreme precipitation in Northern California.
Abstract
A multiscale analysis is presented of extreme precipitation events (EPEs) in Northern California during winter 2016–17, which caused flooding and contributed substantially to highly anomalous seasonal precipitation totals. The EPEs were characterized by long durations (≥7 days) and involved persistent large-scale flow patterns. The three largest EPEs involved blocking over the Bering Sea–Alaska region. A detailed investigation of the largest EPE, occurring on 2–10 February 2017, reveals that extreme precipitation was produced as four discrete cyclones moved across the eastern North Pacific equatorward of a high-amplitude blocking ridge and impacted the U.S. West Coast in rapid succession. The latter three cyclones developed and moved in conjunction with elongated negatively tilted troughs or PV streamers resulting from repeated episodes of baroclinic development and cyclonic Rossby wave breaking on the upstream flank of the block. Each of the four cyclones interacted with a PV streamer and an associated baroclinic zone established by anticyclonic wave breaking on the downstream flank of the block and, thereby, tracked into the U.S. West Coast. The serial clustering of the cyclones during the 9-day event resulted in persistent water vapor flux and lifting that supported extreme precipitation totals in Northern California. A climatological analysis for 1979–2017 reveals a significant statistical relationship between blocking over the Bering Sea–Alaska region and EPEs in Northern California, indicating that this type of blocking pattern represents a favorable large-scale scenario for extreme precipitation in Northern California.
