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Abstract
Landfalling lake- and sea-effect (hereafter lake-effect) systems often interact with orography, altering the distribution and intensity of precipitation, which frequently falls as snow. In this study, we examine the influence of orography on two modes of lake-effect systems: long-lake-axis-parallel (LLAP) bands and broad-coverage, open-cell convection. Specifically, we generate idealized large-eddy simulations of a LLAP band produced by an oval lake and broad-coverage, open-cell convection produced by an open lake (i.e., without flanking shorelines) with a downstream coastal plain, 500-m peak, and 2000-m ridge. Without terrain, the LLAP band intersects a coastal baroclinic zone over which ascent and hydrometeor mass growth are maximized, with transport and fallout producing an inland precipitation maximum. The 500-m peak does not significantly alter this structure, but slightly enhances precipitation due to orographic ascent, increased hydrometeor mass growth, and reduced subcloud sublimation. In contrast, a 2000-m ridge disrupts the band by blocking the continental flow that flanks the coastlines. This, combined with differential surface heating between the lake and land, leads to low-level flow reversal, shifting the coastal baroclinic zone and precipitation maximum offshore. In contrast, the flow moves over the terrain in open lake, open-cell simulations. Over the 500-m peak, this yields an increase in the frequency of weaker (<1 m s−1) updrafts and weak precipitation enhancement, although stronger updrafts decline. Over the 2000-m ridge, however, buoyancy and convective vigor increase dramatically, contributing to an eightfold increase in precipitation. Overall, these results highlight differences in the influence of orography on two common lake-effect modes.
Significance Statement
Landfalling lake- and sea-effect snowstorms frequently interact with hills, mountains, and upland regions, altering the distribution and intensity of snowfall. Using high-resolution numerical modeling with simplified lake shapes and terrain features, we illustrate how terrain features affect two common types of lake-effect storms and why long-lake-axis-parallel (LLAP) bands can feature high precipitation rates but weaker orographic enhancement than broad-coverage, open-cell convection.
Abstract
Landfalling lake- and sea-effect (hereafter lake-effect) systems often interact with orography, altering the distribution and intensity of precipitation, which frequently falls as snow. In this study, we examine the influence of orography on two modes of lake-effect systems: long-lake-axis-parallel (LLAP) bands and broad-coverage, open-cell convection. Specifically, we generate idealized large-eddy simulations of a LLAP band produced by an oval lake and broad-coverage, open-cell convection produced by an open lake (i.e., without flanking shorelines) with a downstream coastal plain, 500-m peak, and 2000-m ridge. Without terrain, the LLAP band intersects a coastal baroclinic zone over which ascent and hydrometeor mass growth are maximized, with transport and fallout producing an inland precipitation maximum. The 500-m peak does not significantly alter this structure, but slightly enhances precipitation due to orographic ascent, increased hydrometeor mass growth, and reduced subcloud sublimation. In contrast, a 2000-m ridge disrupts the band by blocking the continental flow that flanks the coastlines. This, combined with differential surface heating between the lake and land, leads to low-level flow reversal, shifting the coastal baroclinic zone and precipitation maximum offshore. In contrast, the flow moves over the terrain in open lake, open-cell simulations. Over the 500-m peak, this yields an increase in the frequency of weaker (<1 m s−1) updrafts and weak precipitation enhancement, although stronger updrafts decline. Over the 2000-m ridge, however, buoyancy and convective vigor increase dramatically, contributing to an eightfold increase in precipitation. Overall, these results highlight differences in the influence of orography on two common lake-effect modes.
Significance Statement
Landfalling lake- and sea-effect snowstorms frequently interact with hills, mountains, and upland regions, altering the distribution and intensity of snowfall. Using high-resolution numerical modeling with simplified lake shapes and terrain features, we illustrate how terrain features affect two common types of lake-effect storms and why long-lake-axis-parallel (LLAP) bands can feature high precipitation rates but weaker orographic enhancement than broad-coverage, open-cell convection.
Abstract
Storm displacement errors can arise from a number of potential sources of error within a data assimilation (DA) and forecast system. Conversely, storm displacement errors can cause issues for storm-scale, ensemble-based systems using an ensemble Kalman filter (EnKF), such as NSSL’s Warn-on-Forecast System (WoFS). A previous study developed a fully grid-based feature alignment technique (FAT) to mitigate these phase errors and their impacts. However, that study developed and tested the FAT for single-storm cases. This study advances that work by implementing an object-based merging and matching technique into the FAT and tests the updated FAT in more complex scenarios of multiple storms. Ensemble-based experiments are conducted with and without the FAT for each of the scenarios. The experiments’ analyses and forecasts of storm-related fields are then evaluated using subjective and objective methods. Results from these idealized multiple-storm experiments continue to reveal the potential benefits of correcting storm displacement errors. For example, running the FAT even once can mitigate the “spinup” period experienced by the no-FAT experiments. The new results also show that running the FAT prior to every DA cycling step generally leads to more skillful forecasts at the smaller scales, especially in earlier-initialized forecasts. However, repeatedly running the FAT prior to every DA step can eventually lead to deterioration in analyses and forecasts. Potential solutions to this problem include using longer cycling intervals and running the FAT prior to DA less often. Additional ways to improve the FAT along with other results are presented and discussed.
Significance Statement
The purpose of this work is to explore the impact of correcting storm displacements on analyses and forecasts of storms using an ensemble-based data assimilation and forecast system in an idealized framework. Storm displacement errors are a common problem in current operational and experimental storm-scale forecast systems, so understanding their impact on these systems and providing a method to help mitigate them is important. Results from this study indicate that correcting storm displacement errors with the feature alignment technique can greatly improve analyses and forecasts in multiple-storm scenarios. Future work will focus on exploring the impact of correcting storm displacement errors in a real-data, storm-scale data assimilation and forecast system.
Abstract
Storm displacement errors can arise from a number of potential sources of error within a data assimilation (DA) and forecast system. Conversely, storm displacement errors can cause issues for storm-scale, ensemble-based systems using an ensemble Kalman filter (EnKF), such as NSSL’s Warn-on-Forecast System (WoFS). A previous study developed a fully grid-based feature alignment technique (FAT) to mitigate these phase errors and their impacts. However, that study developed and tested the FAT for single-storm cases. This study advances that work by implementing an object-based merging and matching technique into the FAT and tests the updated FAT in more complex scenarios of multiple storms. Ensemble-based experiments are conducted with and without the FAT for each of the scenarios. The experiments’ analyses and forecasts of storm-related fields are then evaluated using subjective and objective methods. Results from these idealized multiple-storm experiments continue to reveal the potential benefits of correcting storm displacement errors. For example, running the FAT even once can mitigate the “spinup” period experienced by the no-FAT experiments. The new results also show that running the FAT prior to every DA cycling step generally leads to more skillful forecasts at the smaller scales, especially in earlier-initialized forecasts. However, repeatedly running the FAT prior to every DA step can eventually lead to deterioration in analyses and forecasts. Potential solutions to this problem include using longer cycling intervals and running the FAT prior to DA less often. Additional ways to improve the FAT along with other results are presented and discussed.
Significance Statement
The purpose of this work is to explore the impact of correcting storm displacements on analyses and forecasts of storms using an ensemble-based data assimilation and forecast system in an idealized framework. Storm displacement errors are a common problem in current operational and experimental storm-scale forecast systems, so understanding their impact on these systems and providing a method to help mitigate them is important. Results from this study indicate that correcting storm displacement errors with the feature alignment technique can greatly improve analyses and forecasts in multiple-storm scenarios. Future work will focus on exploring the impact of correcting storm displacement errors in a real-data, storm-scale data assimilation and forecast system.
Abstract
Research on the interaction between the Madden–Julian oscillation (MJO) and rainfall around Jakarta is limited, although the influence of the MJO on increased rainfall is acknowledged as one of the primary causes of flooding in the region. This paper investigates the local rainfall response around Jakarta to the MJO. We used C-band Doppler radar in October–April during 2009–12 to study rain-rate characteristics at much higher resolution than previous analyses. Results show that the MJO strongly modulates rain rates over the region; however, its effect varies depending on topography. During active phases, MJO induces a high rain rate over the ocean and coast, meanwhile during suppressed phases, it generates a high rain rate mainly over the mountains. In phase 2 of the MJO we find the strongest increase in mean and extreme rain rate, which is earlier in the MJO cycle than most studies reported, based on lower-resolution data. This higher rain rate is likely due to increases in convective and stratiform activities. The MJO promotes more stratiform rain once it resides over Indonesia. In phase 5, over the northwestern coast and western part of the radar domain, the MJO might bring forward the peak of the hourly rain rate that occurs in the early morning. This is likely due to a strong westerly flow arising from MJO superimposed westerly monsoonal flow, blocked by the mountains, inducing a strong wind propagating offshore resulting in convection near the coast in the morning. Our study demonstrates the benefits of using high-resolution radar for capturing local responses to the larger-scale forcing of the MJO in Indonesia.
Significance Statement
Rainfall in Jakarta and its surroundings is highly variable and often heavy resulting in devastating floods. In this region, in the wet season, rainfall is influenced by large-scale climate variability including the Madden–Julian oscillation (MJO) characterized by eastward propagation of clouds near the equatorial regions on intraseasonal time scales. The MJO has been known to increase the probability of rainfall occurrence and its magnitude, but we show that the impact differs in varying topography. The frequency and intensity of rainfall increase over land areas including mountains even when MJO has not arrived in Indonesia. Meanwhile, once MJO moves through Indonesia, the frequency and magnitude of the rainfall increases over the northern coast and ocean as well as in the west of the radar domain.
Abstract
Research on the interaction between the Madden–Julian oscillation (MJO) and rainfall around Jakarta is limited, although the influence of the MJO on increased rainfall is acknowledged as one of the primary causes of flooding in the region. This paper investigates the local rainfall response around Jakarta to the MJO. We used C-band Doppler radar in October–April during 2009–12 to study rain-rate characteristics at much higher resolution than previous analyses. Results show that the MJO strongly modulates rain rates over the region; however, its effect varies depending on topography. During active phases, MJO induces a high rain rate over the ocean and coast, meanwhile during suppressed phases, it generates a high rain rate mainly over the mountains. In phase 2 of the MJO we find the strongest increase in mean and extreme rain rate, which is earlier in the MJO cycle than most studies reported, based on lower-resolution data. This higher rain rate is likely due to increases in convective and stratiform activities. The MJO promotes more stratiform rain once it resides over Indonesia. In phase 5, over the northwestern coast and western part of the radar domain, the MJO might bring forward the peak of the hourly rain rate that occurs in the early morning. This is likely due to a strong westerly flow arising from MJO superimposed westerly monsoonal flow, blocked by the mountains, inducing a strong wind propagating offshore resulting in convection near the coast in the morning. Our study demonstrates the benefits of using high-resolution radar for capturing local responses to the larger-scale forcing of the MJO in Indonesia.
Significance Statement
Rainfall in Jakarta and its surroundings is highly variable and often heavy resulting in devastating floods. In this region, in the wet season, rainfall is influenced by large-scale climate variability including the Madden–Julian oscillation (MJO) characterized by eastward propagation of clouds near the equatorial regions on intraseasonal time scales. The MJO has been known to increase the probability of rainfall occurrence and its magnitude, but we show that the impact differs in varying topography. The frequency and intensity of rainfall increase over land areas including mountains even when MJO has not arrived in Indonesia. Meanwhile, once MJO moves through Indonesia, the frequency and magnitude of the rainfall increases over the northern coast and ocean as well as in the west of the radar domain.
Abstract
This study builds upon recent rapid-scan radar observations of mesocyclonic tornadogenesis in supercells by investigating the formation of seven tornadoes (four from a single cyclic supercell), most of which include samples at heights < 100 m above radar level. The spatiotemporal evolution of the tornadic vortex signatures (TVSs), maximum velocity differentials across the vortex couplet, and pseudovorticity are analyzed. In general, the tornadoes formed following a non-descending pattern of evolution, although one case was descending over time scales O(<60) s and the evolution of another case was dependent upon the criteria used to define a tornado, and may have been associated with a rapidly occurring top-down process. Thus, it was determined that the vertical sense of evolution of a tornado can be sensitive to the criteria employed to define a TVS. Furthermore, multiple instances were found in which TVSs terminated at heights below 1.5 km, although vertical sampling above this height was often limited.
Significance Statement
It is generally well understood that tornadoes form over short time scales [i.e., O(∼60) s]. Despite this fact, detailed scientific measurements of tornado evolution during and just prior to genesis remains limited, particularly very near the ground and on time and space scales sufficient to observe tornado processes. Multiple recent studies have supported a non-descending evolution of rotation in supercell tornadoes, but the small number of analyzed cases is still insufficient for generalization. This study investigates seven new cases of tornadogenesis using high spatiotemporal resolution radar data that include near-ground level observations to examine the evolution of rotation with time and height. For the time scales observable by the radar platform [i.e., O(∼30) s], genesis occurred predominately following a non-descending manner in five out of the seven tornadoes studied, while the vertical evolution of two tornadoes were sensitive to the criterion used to define a “tornadic” vortex signature.
Abstract
This study builds upon recent rapid-scan radar observations of mesocyclonic tornadogenesis in supercells by investigating the formation of seven tornadoes (four from a single cyclic supercell), most of which include samples at heights < 100 m above radar level. The spatiotemporal evolution of the tornadic vortex signatures (TVSs), maximum velocity differentials across the vortex couplet, and pseudovorticity are analyzed. In general, the tornadoes formed following a non-descending pattern of evolution, although one case was descending over time scales O(<60) s and the evolution of another case was dependent upon the criteria used to define a tornado, and may have been associated with a rapidly occurring top-down process. Thus, it was determined that the vertical sense of evolution of a tornado can be sensitive to the criteria employed to define a TVS. Furthermore, multiple instances were found in which TVSs terminated at heights below 1.5 km, although vertical sampling above this height was often limited.
Significance Statement
It is generally well understood that tornadoes form over short time scales [i.e., O(∼60) s]. Despite this fact, detailed scientific measurements of tornado evolution during and just prior to genesis remains limited, particularly very near the ground and on time and space scales sufficient to observe tornado processes. Multiple recent studies have supported a non-descending evolution of rotation in supercell tornadoes, but the small number of analyzed cases is still insufficient for generalization. This study investigates seven new cases of tornadogenesis using high spatiotemporal resolution radar data that include near-ground level observations to examine the evolution of rotation with time and height. For the time scales observable by the radar platform [i.e., O(∼30) s], genesis occurred predominately following a non-descending manner in five out of the seven tornadoes studied, while the vertical evolution of two tornadoes were sensitive to the criterion used to define a “tornadic” vortex signature.
Abstract
Snow squalls are sudden snow events that last less than 1 h, are characterized by low visibility and gusty winds, and can result in notable societal impacts. This analysis develops a climatology of non-lake-effect snow squall events in southern New England for 1994–2018 and investigates the synoptic environment and mesoscale factors conducive to their formation. National Weather Service surface observations were used to identify events; sea level pressure maps, composite radar charts, and a cell-tracking algorithm were used to determine their organization and movement; and ERA5 hourly reanalysis data were used to analyze the associated synoptic and infer mesoscale features, as well as convective and symmetric instability. A total of 100 events were identified and categorized into four distinct types on the basis of the direction of movement of the associated radar echoes, which is closely linked to characteristic synoptic structures and mesoscale factors. The four types are Classic (squall movement from the northwest; 72 events), Atlantic (from the southwest; 15 events), Northern (from the north; 9 events), and Special (varying; 4 events). All types have a 500-hPa trough over the Northeast but differ in the structure of the trough and its relation to lower-level flow, which accounts for the differences in movement of the squalls. The snow events occur in shallow, convective squall lines, and the ingredients for convection were present in all cases. Both upright and symmetric instability are typically present, all cases had at least one lower-tropospheric layer with cyclonic differential vorticity advection, and many cases were also associated with frontogenesis.
Abstract
Snow squalls are sudden snow events that last less than 1 h, are characterized by low visibility and gusty winds, and can result in notable societal impacts. This analysis develops a climatology of non-lake-effect snow squall events in southern New England for 1994–2018 and investigates the synoptic environment and mesoscale factors conducive to their formation. National Weather Service surface observations were used to identify events; sea level pressure maps, composite radar charts, and a cell-tracking algorithm were used to determine their organization and movement; and ERA5 hourly reanalysis data were used to analyze the associated synoptic and infer mesoscale features, as well as convective and symmetric instability. A total of 100 events were identified and categorized into four distinct types on the basis of the direction of movement of the associated radar echoes, which is closely linked to characteristic synoptic structures and mesoscale factors. The four types are Classic (squall movement from the northwest; 72 events), Atlantic (from the southwest; 15 events), Northern (from the north; 9 events), and Special (varying; 4 events). All types have a 500-hPa trough over the Northeast but differ in the structure of the trough and its relation to lower-level flow, which accounts for the differences in movement of the squalls. The snow events occur in shallow, convective squall lines, and the ingredients for convection were present in all cases. Both upright and symmetric instability are typically present, all cases had at least one lower-tropospheric layer with cyclonic differential vorticity advection, and many cases were also associated with frontogenesis.
Abstract
A tornado outbreak occurred across the Southeast United States on 13–14 April 2019, during the Verification of the Origins of Rotation in Tornadoes Experiment–Southeast (VORTEX-SE) Meso18-19 experiment. Among the most noteworthy events was a pair of large tornadoes in Monroe County, Mississippi, near the Columbus Air Force Base (GWX) Weather Surveillance Radar–1988 Doppler (WSR-88D). The second tornado, near the Greenwood Springs community, formed within the “no data” region near the radar and passed about 900 m to its east, rapidly strengthening into an intense tornado. This tornado produced forest devastation and electrical infrastructure damage up to at least EF4 intensity. The maximum radial velocity from GWX was 81.5 m s−1 (182 mph) in a resolution volume centered at 56 m (183 ft) above radar level. This paper presents a damage survey of the Greenwood Springs tornado and compares this assessment to the GWX data. A displacement of the maximum forest damage from the maximum radial velocity, despite the radar beam sampling <100 m ARL, is documented, as well as other likely effects of debris loading by the tornado on the observed radar signatures. The radar observations are placed into context with past mobile radar studies to illustrate the unique nature of this dataset. The relationship between radar data and damage observations, the implications for tornado structure in rough terrain and land cover, and the use of forest damage and radar data in tornado intensity estimation are discussed.
Significance Statement
This study showcases radar and damage observations of an intense tornado in a forested region of Mississippi. The formation of the tornado within 1 km of a WSR-88D allowed for near-surface radar observations to be collected as significant tree destruction was occurring. Doppler velocities below 60 m above radar level (ARL), near tree canopy top, exceeded 80 m s−1. Tree damage patterns were complicated while the tornado was near maximum intensity. The most severe tree damage was notably displaced from the highest radar-observed velocities, despite the radar sampling as low as 45 m ARL. These findings highlight challenges in utilizing radar data to estimate tornado intensity and structure, particularly in a region of relatively high surface and terrain roughness.
Abstract
A tornado outbreak occurred across the Southeast United States on 13–14 April 2019, during the Verification of the Origins of Rotation in Tornadoes Experiment–Southeast (VORTEX-SE) Meso18-19 experiment. Among the most noteworthy events was a pair of large tornadoes in Monroe County, Mississippi, near the Columbus Air Force Base (GWX) Weather Surveillance Radar–1988 Doppler (WSR-88D). The second tornado, near the Greenwood Springs community, formed within the “no data” region near the radar and passed about 900 m to its east, rapidly strengthening into an intense tornado. This tornado produced forest devastation and electrical infrastructure damage up to at least EF4 intensity. The maximum radial velocity from GWX was 81.5 m s−1 (182 mph) in a resolution volume centered at 56 m (183 ft) above radar level. This paper presents a damage survey of the Greenwood Springs tornado and compares this assessment to the GWX data. A displacement of the maximum forest damage from the maximum radial velocity, despite the radar beam sampling <100 m ARL, is documented, as well as other likely effects of debris loading by the tornado on the observed radar signatures. The radar observations are placed into context with past mobile radar studies to illustrate the unique nature of this dataset. The relationship between radar data and damage observations, the implications for tornado structure in rough terrain and land cover, and the use of forest damage and radar data in tornado intensity estimation are discussed.
Significance Statement
This study showcases radar and damage observations of an intense tornado in a forested region of Mississippi. The formation of the tornado within 1 km of a WSR-88D allowed for near-surface radar observations to be collected as significant tree destruction was occurring. Doppler velocities below 60 m above radar level (ARL), near tree canopy top, exceeded 80 m s−1. Tree damage patterns were complicated while the tornado was near maximum intensity. The most severe tree damage was notably displaced from the highest radar-observed velocities, despite the radar sampling as low as 45 m ARL. These findings highlight challenges in utilizing radar data to estimate tornado intensity and structure, particularly in a region of relatively high surface and terrain roughness.
Abstract
The predictability of precipitation type in a January 2017 winter storm over the northeastern United States and southeastern Canada is examined using a convective-scale initial-condition ensemble with the Weather Research and Forecasting (WRF) Model. Real-time forecasts of the event by Environment and Climate Change Canada predicted 15–25 cm of snow accumulation in Montreal, Quebec, Canada. However, the initial 4 h of the event had 5–8 mm of freezing rain instead, followed by 7 cm of snow. While the total liquid-equivalent precipitation was consistent with the forecast, the unexpected freezing rain caused significant disruption in the Montreal region. The fraction of freezing precipitation (freezing rain and/or ice pellets) over the initial 4 h in Montreal varied greatly across the ensemble, with some members producing nearly all snow and others producing nearly all freezing precipitation. In members with larger fractions of freezing precipitation (as opposed to snow), the cyclone’s midlevel trough was displaced slightly to the northwest, and its downstream (eastern) edge was narrower, the latter of which was traced back to model initialization. These differences increased the midlevel southerly flow into southern Quebec, which both enhanced the horizontal warm advection and decreased the vertical cold advection leading up to the event. The consequent midlevel warming over Montreal in these members produced an above-zero layer that melted falling precipitation, leading to freezing upon contact with the ground. This case study highlights the value of convective-scale ensembles for identifying mechanisms by which initial synoptic-scale uncertainties lead to high-impact localized errors in precipitation type.
Abstract
The predictability of precipitation type in a January 2017 winter storm over the northeastern United States and southeastern Canada is examined using a convective-scale initial-condition ensemble with the Weather Research and Forecasting (WRF) Model. Real-time forecasts of the event by Environment and Climate Change Canada predicted 15–25 cm of snow accumulation in Montreal, Quebec, Canada. However, the initial 4 h of the event had 5–8 mm of freezing rain instead, followed by 7 cm of snow. While the total liquid-equivalent precipitation was consistent with the forecast, the unexpected freezing rain caused significant disruption in the Montreal region. The fraction of freezing precipitation (freezing rain and/or ice pellets) over the initial 4 h in Montreal varied greatly across the ensemble, with some members producing nearly all snow and others producing nearly all freezing precipitation. In members with larger fractions of freezing precipitation (as opposed to snow), the cyclone’s midlevel trough was displaced slightly to the northwest, and its downstream (eastern) edge was narrower, the latter of which was traced back to model initialization. These differences increased the midlevel southerly flow into southern Quebec, which both enhanced the horizontal warm advection and decreased the vertical cold advection leading up to the event. The consequent midlevel warming over Montreal in these members produced an above-zero layer that melted falling precipitation, leading to freezing upon contact with the ground. This case study highlights the value of convective-scale ensembles for identifying mechanisms by which initial synoptic-scale uncertainties lead to high-impact localized errors in precipitation type.
Abstract
We define extreme precipitation regimes (EPRs) during the eastern North American winter based on widespread and persistent heavy precipitation, using ERA5 precipitation data from 1979 to 2020. We find 62 EPRs and analyze their synoptic-scale and thermodynamic environments. EPRs impact most of eastern North America with heavy precipitation, especially from Louisiana to Quebec, and generally last for 5–8 days. They are associated with an anomalously strong 500-hPa trough–ridge over western–eastern North America that travels slowly eastward, favoring intrusions of moist, tropical air into eastern North America, and a strong baroclinic zone from the central United States to Atlantic Canada. They are also characterized by high frequencies of cyclones in the midwestern United States, anticyclones over eastern Canada and the subtropical Atlantic, and atmospheric rivers (ARs) in eastern North America. Precipitation is maintained by large moisture influxes, primarily from the Gulf of Mexico and Caribbean Sea, from the EPR start to the time midway through the EPR period. The influxes are often associated with ARs feeding into cyclones, where the moisture falls as precipitation. We also categorize EPRs based on the spatial anomaly correlation (AC) of synoptic-scale weather patterns between individual EPRs and the EPR composite. High AC EPRs have similar but stronger 500-hPa features over North America, greater moisture flux from the Gulf of Mexico and inland precipitation over eastern North America, farther inland cyclone track, higher frequency of subtropical Atlantic anticyclones, and lower EPR-to-EPR variability than low AC EPRs.
Significance Statement
Cool-season extreme precipitation regimes (EPRs) often lead to flooding and other impacts and represent a significant forecast challenge. We define and analyze EPRs during the eastern North American winter to obtain a better understanding of their associated meteorological conditions. We also categorize EPRs into two distinct categories to capture the variability among EPRs. EPRs generally last 5–8 days and are associated with slowly moving large-scale weather patterns favoring intrusions of moist, tropical air into eastern North America, a strong temperature contrast, and frequent cyclones in the midwestern United States with anticyclones to the north and south. The intrusions of moist, tropical air are often associated with atmospheric rivers (ARs) that deposit their moisture in cyclones as precipitation.
Abstract
We define extreme precipitation regimes (EPRs) during the eastern North American winter based on widespread and persistent heavy precipitation, using ERA5 precipitation data from 1979 to 2020. We find 62 EPRs and analyze their synoptic-scale and thermodynamic environments. EPRs impact most of eastern North America with heavy precipitation, especially from Louisiana to Quebec, and generally last for 5–8 days. They are associated with an anomalously strong 500-hPa trough–ridge over western–eastern North America that travels slowly eastward, favoring intrusions of moist, tropical air into eastern North America, and a strong baroclinic zone from the central United States to Atlantic Canada. They are also characterized by high frequencies of cyclones in the midwestern United States, anticyclones over eastern Canada and the subtropical Atlantic, and atmospheric rivers (ARs) in eastern North America. Precipitation is maintained by large moisture influxes, primarily from the Gulf of Mexico and Caribbean Sea, from the EPR start to the time midway through the EPR period. The influxes are often associated with ARs feeding into cyclones, where the moisture falls as precipitation. We also categorize EPRs based on the spatial anomaly correlation (AC) of synoptic-scale weather patterns between individual EPRs and the EPR composite. High AC EPRs have similar but stronger 500-hPa features over North America, greater moisture flux from the Gulf of Mexico and inland precipitation over eastern North America, farther inland cyclone track, higher frequency of subtropical Atlantic anticyclones, and lower EPR-to-EPR variability than low AC EPRs.
Significance Statement
Cool-season extreme precipitation regimes (EPRs) often lead to flooding and other impacts and represent a significant forecast challenge. We define and analyze EPRs during the eastern North American winter to obtain a better understanding of their associated meteorological conditions. We also categorize EPRs into two distinct categories to capture the variability among EPRs. EPRs generally last 5–8 days and are associated with slowly moving large-scale weather patterns favoring intrusions of moist, tropical air into eastern North America, a strong temperature contrast, and frequent cyclones in the midwestern United States with anticyclones to the north and south. The intrusions of moist, tropical air are often associated with atmospheric rivers (ARs) that deposit their moisture in cyclones as precipitation.
Abstract
Generating accurate weather forecasts of planetary boundary layer (PBL) properties is challenging in many geographical regions, oftentimes due to complex topography or horizontal variability in, for example, land characteristics. While recent advances in high-performance computing platforms have led to an increase in the spatial resolution of numerical weather prediction (NWP) models, the horizontal gridcell spacing (Δx) of many regional-scale NWP models currently fall within or are beginning to approach the gray zone (i.e., Δx ≈ 100–1000 m). At these gridcell spacings, three-dimensional (3D) effects are important, as the most energetic turbulent eddies are neither fully parameterized (as in traditional mesoscale simulations) nor fully resolved [as in traditional large-eddy simulations (LES)]. In light of this modeling challenge, we have implemented a 3D PBL parameterization for high-resolution mesoscale simulations using the Weather Research and Forecasting Model. The PBL scheme, which is based on the algebraic model developed by Mellor and Yamada, accounts for the 3D effects of turbulence by calculating explicitly the momentum, heat, and moisture flux divergences in addition to the turbulent kinetic energy. In this study, we present results from idealized simulations in the gray zone that illustrate the benefit of using a fully consistent turbulence closure framework under convective conditions. While the 3D PBL scheme reproduces the evolution of convective features more appropriately than the traditional 1D PBL scheme, we highlight the need to improve the turbulent length scale formulation.
Significance Statement
The spatial resolution of weather models continues to increase at a rapid rate in accordance with the enhancement of computing power. As a result, smaller-scale atmospheric features become more explicitly resolved. However, most numerical models still ignore the impact of horizontal weather variations on boundary layer flows, which becomes more important at these smaller spatial scales. To address this issue, we have implemented a new modeling approach, using fundamental principles, which accounts for horizontal variability. Our results show that including three-dimensional effects of turbulence is necessary to achieve realistic boundary layer characteristics. This novel technique may be useful for many applications including complex terrain flows, pollutant dispersion, and surface–atmosphere interaction studies.
Abstract
Generating accurate weather forecasts of planetary boundary layer (PBL) properties is challenging in many geographical regions, oftentimes due to complex topography or horizontal variability in, for example, land characteristics. While recent advances in high-performance computing platforms have led to an increase in the spatial resolution of numerical weather prediction (NWP) models, the horizontal gridcell spacing (Δx) of many regional-scale NWP models currently fall within or are beginning to approach the gray zone (i.e., Δx ≈ 100–1000 m). At these gridcell spacings, three-dimensional (3D) effects are important, as the most energetic turbulent eddies are neither fully parameterized (as in traditional mesoscale simulations) nor fully resolved [as in traditional large-eddy simulations (LES)]. In light of this modeling challenge, we have implemented a 3D PBL parameterization for high-resolution mesoscale simulations using the Weather Research and Forecasting Model. The PBL scheme, which is based on the algebraic model developed by Mellor and Yamada, accounts for the 3D effects of turbulence by calculating explicitly the momentum, heat, and moisture flux divergences in addition to the turbulent kinetic energy. In this study, we present results from idealized simulations in the gray zone that illustrate the benefit of using a fully consistent turbulence closure framework under convective conditions. While the 3D PBL scheme reproduces the evolution of convective features more appropriately than the traditional 1D PBL scheme, we highlight the need to improve the turbulent length scale formulation.
Significance Statement
The spatial resolution of weather models continues to increase at a rapid rate in accordance with the enhancement of computing power. As a result, smaller-scale atmospheric features become more explicitly resolved. However, most numerical models still ignore the impact of horizontal weather variations on boundary layer flows, which becomes more important at these smaller spatial scales. To address this issue, we have implemented a new modeling approach, using fundamental principles, which accounts for horizontal variability. Our results show that including three-dimensional effects of turbulence is necessary to achieve realistic boundary layer characteristics. This novel technique may be useful for many applications including complex terrain flows, pollutant dispersion, and surface–atmosphere interaction studies.
Abstract
The phenomenon that rapid contraction (RC) of the radius of maximum wind (RMW) could precede rapid intensification (RI) in tropical cyclones (TCs) has been found in several previous studies, but it is still unclear how frequently and to what extent RC precedes RI in rapidly intensifying and contracting TCs in observations. In this study, the statistical relationship between RMW RC and TC RI is examined based on the extended best track dataset for the North Atlantic and eastern North Pacific during 1999–2019. Results show that for more than ∼65% of available TCs, the time of the peak contraction rate precedes the time of the peak intensification rate, on average, by ∼10–15 h. With the quantitatively defined RC and RI, results show that ∼50% TCs with RC experience RI, and TCs with larger intensity and smaller RMW and embedded in more favorable environmental conditions tend to experience RI more readily following an RC. Among those TCs with RC and RI, more than ∼65% involve the onset of RC preceding the onset of RI, on average, by ∼15–25 h. The preceding time tends to be longer with lower TC intensity and larger RMW and shows weak correlations with environmental conditions. The qualitative results are insensitive to the time interval for the calculation of intensification/contraction rates and the definition of RI. The results from this study can improve our understanding of TC structure and intensity changes.
Abstract
The phenomenon that rapid contraction (RC) of the radius of maximum wind (RMW) could precede rapid intensification (RI) in tropical cyclones (TCs) has been found in several previous studies, but it is still unclear how frequently and to what extent RC precedes RI in rapidly intensifying and contracting TCs in observations. In this study, the statistical relationship between RMW RC and TC RI is examined based on the extended best track dataset for the North Atlantic and eastern North Pacific during 1999–2019. Results show that for more than ∼65% of available TCs, the time of the peak contraction rate precedes the time of the peak intensification rate, on average, by ∼10–15 h. With the quantitatively defined RC and RI, results show that ∼50% TCs with RC experience RI, and TCs with larger intensity and smaller RMW and embedded in more favorable environmental conditions tend to experience RI more readily following an RC. Among those TCs with RC and RI, more than ∼65% involve the onset of RC preceding the onset of RI, on average, by ∼15–25 h. The preceding time tends to be longer with lower TC intensity and larger RMW and shows weak correlations with environmental conditions. The qualitative results are insensitive to the time interval for the calculation of intensification/contraction rates and the definition of RI. The results from this study can improve our understanding of TC structure and intensity changes.
