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- Author or Editor: Lynn A. McMurdie x
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Abstract
The predictability of North Pacific cyclones can vary widely, from highly accurate prediction of storm intensity and location to forecast position errors of hundreds of kilometers and central pressure errors of tens of hectopascals. In this study, a Weather Research and Forecasting Model (WRF) ensemble Kalman filter is used to investigate predictability of landfalling cyclones on the west coast of North America over two winter seasons (2008/09 and 2009/10). Predictability is defined as the ensemble spread of cyclone central pressure at the final forecast time (24 h) where large spread means low predictability. Both ensemble spread and ensemble initial-condition sensitivity are examined for a wide variety of cyclones that occurred during the two seasons. Storms that are deepening and track from the southwest exhibit the largest ensemble initial-condition sensitivity and highest ensemble spread compared to decaying storms and storms that track from other directions. Storms that end south of 40°N, typically slow moving storms from the northwest, exhibit higher predictability regardless of whether or not they are deepening or decaying. Cyclones with large ensemble spread and low sensitivity are mature cyclones whose low predictability likely results from large initial-condition spread instead of large perturbation growth. These results highlight particular synoptic situations and cyclone characteristics that are associated with low predictability and can potentially be used to improve forecasts through improved observational coverage.
Abstract
The predictability of North Pacific cyclones can vary widely, from highly accurate prediction of storm intensity and location to forecast position errors of hundreds of kilometers and central pressure errors of tens of hectopascals. In this study, a Weather Research and Forecasting Model (WRF) ensemble Kalman filter is used to investigate predictability of landfalling cyclones on the west coast of North America over two winter seasons (2008/09 and 2009/10). Predictability is defined as the ensemble spread of cyclone central pressure at the final forecast time (24 h) where large spread means low predictability. Both ensemble spread and ensemble initial-condition sensitivity are examined for a wide variety of cyclones that occurred during the two seasons. Storms that are deepening and track from the southwest exhibit the largest ensemble initial-condition sensitivity and highest ensemble spread compared to decaying storms and storms that track from other directions. Storms that end south of 40°N, typically slow moving storms from the northwest, exhibit higher predictability regardless of whether or not they are deepening or decaying. Cyclones with large ensemble spread and low sensitivity are mature cyclones whose low predictability likely results from large initial-condition spread instead of large perturbation growth. These results highlight particular synoptic situations and cyclone characteristics that are associated with low predictability and can potentially be used to improve forecasts through improved observational coverage.
Abstract
Patterns in the horizontal distribution of integrated water vapor, integrated liquid water and rainfall rate derived from the Seasat Scanning Multichannel Microwave Radiometer (SMMR) during a 10–12 September 1978 North Pacific cyclone are studied. These patterns are compared with surface analyses, ship reports, radiosonde data, and GOES-West infrared satellite imagery. The SMMR data give a unique view of the large mesoscale structure of a midlatitude cyclone. The water vapor distribution is found to have characteristic patterns related to the location of the surface fronts throughout the development of the cyclone. An example is given to illustrate that SMMR data could significantly improve frontal analysis over data-sparse oceanic regions. The distribution of integrated liquid water agrees qualitatively well with corresponding cloud patterns in satellite imagery and appears to provide a means to distinguish where liquid water clouds exist under a cirrus shield. Ship reports of rainfall intensity agree qualitatively very well with SMMR-derived rainrates. Areas of mesoscale rainfall, on the order of 50 km × 50 km or greater are detected using SMMR derived rainrates.
Abstract
Patterns in the horizontal distribution of integrated water vapor, integrated liquid water and rainfall rate derived from the Seasat Scanning Multichannel Microwave Radiometer (SMMR) during a 10–12 September 1978 North Pacific cyclone are studied. These patterns are compared with surface analyses, ship reports, radiosonde data, and GOES-West infrared satellite imagery. The SMMR data give a unique view of the large mesoscale structure of a midlatitude cyclone. The water vapor distribution is found to have characteristic patterns related to the location of the surface fronts throughout the development of the cyclone. An example is given to illustrate that SMMR data could significantly improve frontal analysis over data-sparse oceanic regions. The distribution of integrated liquid water agrees qualitatively well with corresponding cloud patterns in satellite imagery and appears to provide a means to distinguish where liquid water clouds exist under a cirrus shield. Ship reports of rainfall intensity agree qualitatively very well with SMMR-derived rainrates. Areas of mesoscale rainfall, on the order of 50 km × 50 km or greater are detected using SMMR derived rainrates.
Abstract
With the atmospheric water-vapor content information available from the SEASAT and Nimbus-7 Scanning Multichannel Microwave Radiometers (SMMR), differences in water-vapor distribution between cyclonic storms in different regions of the global ocean can be examined in more detail than previously possible from radiosondes. SMMR-derived integrated water vapor is a robust and dependable variable of the same accuracy as integrated radiosonde soundings. In this study, maximum and minimum water-vapor content in the vicinity of cold fronts of 80 storms that occurred in the North Atlantic, North Pacific and Southern oceans are compared. North Atlantic storms were found to have significantly higher maximum and minimum water-vapor content near cold fronts on average than North Pacific or Southern ocean storms for both the warm and cold seasons. These differences are attributed to warmer sea surface temperatures and air temperatures in the North Atlantic, and higher baroclinity and consequently stronger upward motion in North Atlantic storms. Additionally, some of the differences may be attributed to the fact that the North Atlantic storms generally occur at lower latitudes than the storms in the other regions. Furthermore, the North Pacific storms were found to have significantly higher maximum and minimum water-vapor content near cold fronts on average than the Southern Ocean storms for both the warm and cold seasons. These differences are attributable to warmer sea surface temperatures in the North Pacific during the warm season, and to less moisture transport by Southern Ocean storms and the poleward location of the Southern Ocean storms compared to North Pacific storms during the cold season. Two examples of water-vapor content in a South Atlantic storm are given to contrast with the Southern Ocean cases. The South Atlantic storm had much higher maximum water-vapor content near the cold front than most Southern Ocean storms.
Abstract
With the atmospheric water-vapor content information available from the SEASAT and Nimbus-7 Scanning Multichannel Microwave Radiometers (SMMR), differences in water-vapor distribution between cyclonic storms in different regions of the global ocean can be examined in more detail than previously possible from radiosondes. SMMR-derived integrated water vapor is a robust and dependable variable of the same accuracy as integrated radiosonde soundings. In this study, maximum and minimum water-vapor content in the vicinity of cold fronts of 80 storms that occurred in the North Atlantic, North Pacific and Southern oceans are compared. North Atlantic storms were found to have significantly higher maximum and minimum water-vapor content near cold fronts on average than North Pacific or Southern ocean storms for both the warm and cold seasons. These differences are attributed to warmer sea surface temperatures and air temperatures in the North Atlantic, and higher baroclinity and consequently stronger upward motion in North Atlantic storms. Additionally, some of the differences may be attributed to the fact that the North Atlantic storms generally occur at lower latitudes than the storms in the other regions. Furthermore, the North Pacific storms were found to have significantly higher maximum and minimum water-vapor content near cold fronts on average than the Southern Ocean storms for both the warm and cold seasons. These differences are attributable to warmer sea surface temperatures in the North Pacific during the warm season, and to less moisture transport by Southern Ocean storms and the poleward location of the Southern Ocean storms compared to North Pacific storms during the cold season. Two examples of water-vapor content in a South Atlantic storm are given to contrast with the Southern Ocean cases. The South Atlantic storm had much higher maximum water-vapor content near the cold front than most Southern Ocean storms.
Abstract
Despite overall improvements in numerical weather prediction and data assimilation, large short-term forecast errors of sea level pressure and 2-m temperature still occur. This is especially true for the west coast of North America where short-term numerical weather forecasts of surface low pressure systems can have large position and central pressure errors. In this study, forecast errors of sea level pressure and temperature in the Pacific Northwest are related to the shape of the large-scale flow aloft. Applying a hierarchical limited-contour clustering algorithm to historical 500-hPa geopotential height data produces four distinct weather regimes. The Rockies ridge regime, which exhibits a ridge near the axis of the Rocky Mountains and nearly zonal flow across the Pacific, experiences the highest magnitude and frequency of large sea level pressure errors. On the other hand, the coastal ridge regime, which exhibits a ridge aligned with the North American west coast, experiences the highest magnitude and frequency of large 2-m minimum temperature errors.
Abstract
Despite overall improvements in numerical weather prediction and data assimilation, large short-term forecast errors of sea level pressure and 2-m temperature still occur. This is especially true for the west coast of North America where short-term numerical weather forecasts of surface low pressure systems can have large position and central pressure errors. In this study, forecast errors of sea level pressure and temperature in the Pacific Northwest are related to the shape of the large-scale flow aloft. Applying a hierarchical limited-contour clustering algorithm to historical 500-hPa geopotential height data produces four distinct weather regimes. The Rockies ridge regime, which exhibits a ridge near the axis of the Rocky Mountains and nearly zonal flow across the Pacific, experiences the highest magnitude and frequency of large sea level pressure errors. On the other hand, the coastal ridge regime, which exhibits a ridge aligned with the North American west coast, experiences the highest magnitude and frequency of large 2-m minimum temperature errors.
Abstract
Rapidly deepening cyclones in midlatitudes are characterized by large cloud shields and abundant condensation qualitatively evident in infrared and visible satellite images. With the availability of passive microwave measurements from polar-orbiting satellites, it is now possible to characterize rapidly deepening cyclones quantitatively in terms of integrated water vapor and precipitation intensity. In this study, fields of integrated water vapor, integrated water vapor anomaly (defined as the observed water vapor content minus the monthly mean water vapor content at the particular location), and rainfall intensity index derived from the Special Sensor Microwave Imager (SSM/I) on the F-8 satellite of the Defense Meteorological Satellite Program are examined for 12 North Atlantic rapidly deepening and 11 North Atlantic non-rapidly deepening storms that occurred during the 1988 and 1989 winter months. By correlating concurrent 6-h deepening rates with the satellite-derived parameters for a region within 550 km of the surface low pressure center, signatures of rapid cyclogenesis are identified in the SSM/I fields. Maximum water vapor anomaly and average precipitation index have correlations with concurrent 6-h deepening rates of 0.56 and 0.55, respectively. The correlations improve dramatically when two outliers are removed, becoming 0.68 and 0.70, respectively. These results indicate that, although most rapidly deepening cyclones have high water vapor anomaly and stronger precipitation index than non-rapidly deepening cyclones, there are storms that deepen rapidly in the absence of high water vapor anomaly or heavy precipitation. In addition, occasionally there are storms that have exceptionally high water vapor anomalies yet do not deepen rapidly. In these unusual cases, it is suggested that atmospheric water vapor and condensation play a secondary role and that dynamical processes are dominant.
Abstract
Rapidly deepening cyclones in midlatitudes are characterized by large cloud shields and abundant condensation qualitatively evident in infrared and visible satellite images. With the availability of passive microwave measurements from polar-orbiting satellites, it is now possible to characterize rapidly deepening cyclones quantitatively in terms of integrated water vapor and precipitation intensity. In this study, fields of integrated water vapor, integrated water vapor anomaly (defined as the observed water vapor content minus the monthly mean water vapor content at the particular location), and rainfall intensity index derived from the Special Sensor Microwave Imager (SSM/I) on the F-8 satellite of the Defense Meteorological Satellite Program are examined for 12 North Atlantic rapidly deepening and 11 North Atlantic non-rapidly deepening storms that occurred during the 1988 and 1989 winter months. By correlating concurrent 6-h deepening rates with the satellite-derived parameters for a region within 550 km of the surface low pressure center, signatures of rapid cyclogenesis are identified in the SSM/I fields. Maximum water vapor anomaly and average precipitation index have correlations with concurrent 6-h deepening rates of 0.56 and 0.55, respectively. The correlations improve dramatically when two outliers are removed, becoming 0.68 and 0.70, respectively. These results indicate that, although most rapidly deepening cyclones have high water vapor anomaly and stronger precipitation index than non-rapidly deepening cyclones, there are storms that deepen rapidly in the absence of high water vapor anomaly or heavy precipitation. In addition, occasionally there are storms that have exceptionally high water vapor anomalies yet do not deepen rapidly. In these unusual cases, it is suggested that atmospheric water vapor and condensation play a secondary role and that dynamical processes are dominant.
Abstract
Multifrequency airborne radars have become instrumental in evaluating the performance of satellite retrievals and furthering our understanding of ice microphysical properties. The dual-frequency ratio (DFR) is influenced by the size, density, and shape of ice particles, with higher values associated with the presence of larger ice particles that may have implications regarding snowfall at the surface. The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign involves the coordination of remote sensing measurements above winter midlatitude cyclones from an ER-2 aircraft to document the fine-scale precipitation structure spanning four radar (X-, Ku-, Ka-, and W-band) frequencies and in situ microphysical measurements from a P-3 aircraft that provide additional insight into the particle size distribution (PSD) behavior and habits of the hydrometeors related to the DFR. A novel approach to identify regions of prominently higher Ku- and Ka-band DFR at the P-3 location for five coordinated flights is presented. The solid-phase mass-weighted mean diameter (Dm ) was 58% larger, the effective density (ρe ) 37% smaller, and the liquid-equivalent normalized intercept parameter (Nw ) 74% lower in regions of prominently higher DFR. Microphysical properties within a triple-frequency framework suggest signatures consistent with aggregation and riming as in previous studies. Last, a pretrained neural network radar retrieval is used to investigate the vertical structure of microphysical properties associated with the larger DFR signatures and provides the spatial context for inferring certain microphysical processes.
Significance Statement
The purpose of this study is to better understand what radar measurements from multiple frequencies can tell us about the sizes, shapes, and concentrations of ice particles within winter snowstorms, and how these observations are related to banded precipitation structures since they can have implications for snowfall at the surface. Our results show that ice particles are on average larger and less dense when the reflectivity difference between two radars operating at different wavelengths is larger and supports the process by which crystals aggregate to form larger particles. These findings aim to improve how satellites and forecasting models represent precipitation in the cloud and at the surface.
Abstract
Multifrequency airborne radars have become instrumental in evaluating the performance of satellite retrievals and furthering our understanding of ice microphysical properties. The dual-frequency ratio (DFR) is influenced by the size, density, and shape of ice particles, with higher values associated with the presence of larger ice particles that may have implications regarding snowfall at the surface. The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign involves the coordination of remote sensing measurements above winter midlatitude cyclones from an ER-2 aircraft to document the fine-scale precipitation structure spanning four radar (X-, Ku-, Ka-, and W-band) frequencies and in situ microphysical measurements from a P-3 aircraft that provide additional insight into the particle size distribution (PSD) behavior and habits of the hydrometeors related to the DFR. A novel approach to identify regions of prominently higher Ku- and Ka-band DFR at the P-3 location for five coordinated flights is presented. The solid-phase mass-weighted mean diameter (Dm ) was 58% larger, the effective density (ρe ) 37% smaller, and the liquid-equivalent normalized intercept parameter (Nw ) 74% lower in regions of prominently higher DFR. Microphysical properties within a triple-frequency framework suggest signatures consistent with aggregation and riming as in previous studies. Last, a pretrained neural network radar retrieval is used to investigate the vertical structure of microphysical properties associated with the larger DFR signatures and provides the spatial context for inferring certain microphysical processes.
Significance Statement
The purpose of this study is to better understand what radar measurements from multiple frequencies can tell us about the sizes, shapes, and concentrations of ice particles within winter snowstorms, and how these observations are related to banded precipitation structures since they can have implications for snowfall at the surface. Our results show that ice particles are on average larger and less dense when the reflectivity difference between two radars operating at different wavelengths is larger and supports the process by which crystals aggregate to form larger particles. These findings aim to improve how satellites and forecasting models represent precipitation in the cloud and at the surface.
Abstract
The Olympic Mountains Experiment (OLYMPEX) documented precipitation and drop size distributions (DSDs) in landfalling midlatitude cyclones with gauges and disdrometers located at various distances from the coast and at different elevations on the windward side of the mountain range. Statistics of the drop size and gauge data for the season and case study analysis of a high-rainfall-producing storm of the atmospheric river type show that DSDs during stratiform raining periods exhibit considerable variability in regions of complex terrain. Seasonal statistics show that different relative proportions of drop sizes are present, depending on synoptic and mesoscale conditions, which vary within a single storm. The most frequent DSD regime contains modest concentrations of both small and large drops with synoptic factors near their climatological norms and moderate precipitation enhancement on the lower windward slopes. The heaviest rains are the most strongly enhanced on the lower slope and have DSDs marked by large concentrations of small to medium drops and varying concentrations of large drops. During the heavy-rain period of the case examined here, the low-level flow was onshore and entirely up terrain, the melting level was ~2.5 km, and stability moist neutral so that large amounts of small raindrops were produced. At the same time, melting ice particles produced at upper levels contributed varying amounts of large drops to the DSD, depending on the subsynoptic variability of the storm structure. When the low-level flow is directed downslope and offshore, small-drop production at low altitudes is reduced or eliminated.
Abstract
The Olympic Mountains Experiment (OLYMPEX) documented precipitation and drop size distributions (DSDs) in landfalling midlatitude cyclones with gauges and disdrometers located at various distances from the coast and at different elevations on the windward side of the mountain range. Statistics of the drop size and gauge data for the season and case study analysis of a high-rainfall-producing storm of the atmospheric river type show that DSDs during stratiform raining periods exhibit considerable variability in regions of complex terrain. Seasonal statistics show that different relative proportions of drop sizes are present, depending on synoptic and mesoscale conditions, which vary within a single storm. The most frequent DSD regime contains modest concentrations of both small and large drops with synoptic factors near their climatological norms and moderate precipitation enhancement on the lower windward slopes. The heaviest rains are the most strongly enhanced on the lower slope and have DSDs marked by large concentrations of small to medium drops and varying concentrations of large drops. During the heavy-rain period of the case examined here, the low-level flow was onshore and entirely up terrain, the melting level was ~2.5 km, and stability moist neutral so that large amounts of small raindrops were produced. At the same time, melting ice particles produced at upper levels contributed varying amounts of large drops to the DSD, depending on the subsynoptic variability of the storm structure. When the low-level flow is directed downslope and offshore, small-drop production at low altitudes is reduced or eliminated.
Abstract
Fields of divergence calculated from the Seasat-A Satellite Scatterometer winds and fields of integrated water vapor and rainrate from the Scanning Multichannel Microwave Radiometer on Seasat are constructed for three different midlatitude cyclones. These storms include an explosively deepening cyclone that occurred in the North Atlantic (also known as the Queen Elizabeth II cyclone), a storm that occurred in the North Pacific, and a Southern Ocean storm. In all three cases, the regions of convergence and atmospheric water (vapor and rain) are consistent with each other and help to define features of each storm. The vertical distribution of moisture is inferred for one case using both the convergence pattern and the integrated water vapor field. In another, interpretation of the convergence field in a data gap region is aided by the water vapor field. In all three cases, surface low pressure centers, fronts, and even frontal waves are clearly evident as areas of convergence, and increased water vapor and rainrate.
Abstract
Fields of divergence calculated from the Seasat-A Satellite Scatterometer winds and fields of integrated water vapor and rainrate from the Scanning Multichannel Microwave Radiometer on Seasat are constructed for three different midlatitude cyclones. These storms include an explosively deepening cyclone that occurred in the North Atlantic (also known as the Queen Elizabeth II cyclone), a storm that occurred in the North Pacific, and a Southern Ocean storm. In all three cases, the regions of convergence and atmospheric water (vapor and rain) are consistent with each other and help to define features of each storm. The vertical distribution of moisture is inferred for one case using both the convergence pattern and the integrated water vapor field. In another, interpretation of the convergence field in a data gap region is aided by the water vapor field. In all three cases, surface low pressure centers, fronts, and even frontal waves are clearly evident as areas of convergence, and increased water vapor and rainrate.
Abstract
Despite recent advances in numerical weather prediction, major errors in short-range forecasts still occur. To gain insight into the origin and nature of model forecast errors, error frequencies and magnitudes need to be documented for different models and different regions. This study examines errors in sea level pressure for four operational forecast models at observation sites along the east and west coasts of the United States for three 5-month cold seasons. Considering several metrics of forecast accuracy, the European Centre for Medium-Range Weather Forecasts (ECMWF) model outperformed the other models, while the North American Mesoscale (NAM) model was least skillful. Sea level pressure errors on the West Coast are greater than those on the East Coast. The operational switch from the Eta to the Weather Research and Forecasting Nonhydrostatic Mesoscale Model (WRF-NMM) at the National Centers for Environmental Prediction (NCEP) did not improve forecasts of sea level pressure. The results also suggest that the accuracy of the Canadian Meteorological Centre’s Global Environmental Mesoscale model (CMC-GEM) improved between the first and second cold seasons, that the ECMWF experienced improvement on both coasts during the 3-yr period, and that the NCEP Global Forecast System (GFS) improved during the third cold season on the West Coast.
Abstract
Despite recent advances in numerical weather prediction, major errors in short-range forecasts still occur. To gain insight into the origin and nature of model forecast errors, error frequencies and magnitudes need to be documented for different models and different regions. This study examines errors in sea level pressure for four operational forecast models at observation sites along the east and west coasts of the United States for three 5-month cold seasons. Considering several metrics of forecast accuracy, the European Centre for Medium-Range Weather Forecasts (ECMWF) model outperformed the other models, while the North American Mesoscale (NAM) model was least skillful. Sea level pressure errors on the West Coast are greater than those on the East Coast. The operational switch from the Eta to the Weather Research and Forecasting Nonhydrostatic Mesoscale Model (WRF-NMM) at the National Centers for Environmental Prediction (NCEP) did not improve forecasts of sea level pressure. The results also suggest that the accuracy of the Canadian Meteorological Centre’s Global Environmental Mesoscale model (CMC-GEM) improved between the first and second cold seasons, that the ECMWF experienced improvement on both coasts during the 3-yr period, and that the NCEP Global Forecast System (GFS) improved during the third cold season on the West Coast.
Abstract
Midlatitude cyclones approaching coastal mountain ranges experience flow modifications on a variety of scales including orographic lift, blocking, mountain waves, and valley flows. During the 2015/16 Olympic Mountain Experiment (OLYMPEX), a pair of scanning ground radars observed precipitating clouds as they were modified by these orographically induced flows. The DOW radar, positioned to scan up the windward Quinault Valley, conducted RHI scans during 285 h of precipitation, 80% of which contained reversed, down-valley flow at lower levels. The existence of down-valley flow in the Quinault Valley was found to be well correlated with upstream flow blocking and the large-scale sea level pressure gradient orientated down the valley. Deep down-valley flow occurred in environments with high moist static stability and southerly winds, conditions that are common in prefrontal sectors of midlatitude cyclones in the coastal Pacific Northwest. Finally, a case study of prolonged down-valley flow in a prefrontal storm sector was simulated to investigate whether latent heat absorption (cooling) contributed to the event. Three experiments were conducted: a Control simulation and two simulations where the temperature tendencies from melting and evaporation were separately turned off. Results indicated that evaporative cooling had a stronger impact on the event’s down-valley flow than melting, likely because evaporation occurred within the low-level down-valley flow layer. Through these experiments, we show that evaporation helped prolong down-valley flow for several hours past the time of the event’s warm frontal passage.
Significance Statement
This paper analyzes the characteristics of down-valley flow over the windward Quinault Valley on the Olympic Peninsula of Washington State using data from OLYMPEX, with an emphasis on regional pressure differences and blocking metrics. Results demonstrate that the location of precipitation over the Olympic Peninsula is shifted upstream during events with deep down-valley flow, consistent with blocked upstream airflow. A case study of down-valley flow highlights the role of evaporative cooling to prolong the flow reversal.
Abstract
Midlatitude cyclones approaching coastal mountain ranges experience flow modifications on a variety of scales including orographic lift, blocking, mountain waves, and valley flows. During the 2015/16 Olympic Mountain Experiment (OLYMPEX), a pair of scanning ground radars observed precipitating clouds as they were modified by these orographically induced flows. The DOW radar, positioned to scan up the windward Quinault Valley, conducted RHI scans during 285 h of precipitation, 80% of which contained reversed, down-valley flow at lower levels. The existence of down-valley flow in the Quinault Valley was found to be well correlated with upstream flow blocking and the large-scale sea level pressure gradient orientated down the valley. Deep down-valley flow occurred in environments with high moist static stability and southerly winds, conditions that are common in prefrontal sectors of midlatitude cyclones in the coastal Pacific Northwest. Finally, a case study of prolonged down-valley flow in a prefrontal storm sector was simulated to investigate whether latent heat absorption (cooling) contributed to the event. Three experiments were conducted: a Control simulation and two simulations where the temperature tendencies from melting and evaporation were separately turned off. Results indicated that evaporative cooling had a stronger impact on the event’s down-valley flow than melting, likely because evaporation occurred within the low-level down-valley flow layer. Through these experiments, we show that evaporation helped prolong down-valley flow for several hours past the time of the event’s warm frontal passage.
Significance Statement
This paper analyzes the characteristics of down-valley flow over the windward Quinault Valley on the Olympic Peninsula of Washington State using data from OLYMPEX, with an emphasis on regional pressure differences and blocking metrics. Results demonstrate that the location of precipitation over the Olympic Peninsula is shifted upstream during events with deep down-valley flow, consistent with blocked upstream airflow. A case study of down-valley flow highlights the role of evaporative cooling to prolong the flow reversal.
