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- Author or Editor: Kelly Lombardo x
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Abstract
This study documents the convective storm structures and ambient conditions associated with severe storms (wind, hail, and tornado) over the northeastern United States for two warm seasons (May–August), including 2007 and a warm season comprising randomly selected days from 2002 to 2006. The storms were classified into three main convective organizational structures (cellular, linear, and nonlinear) as well as several subcategories. The same procedure was applied to the highly populated coastal zone of the northeastern United States, including New Jersey, Connecticut, Rhode Island, and New York. The coastal analysis included six warm seasons from 2002 to 2007. Over the Northeast, severe wind events are evenly distributed among the cellular, linear, and nonlinear structures. Cellular structures are the primary hail producers, while tornadoes develop mainly from cellular and linear structures. Over the coastal zone, primarily cellular and linear systems produce severe wind and hail, while tornadoes are equally likely from all three convective structures. Composites were generated for severe weather days over the coastal region for the three main convective structures. On average, severe cellular events develop during moderate instability [most unstable CAPE (MUCAPE) ~1200 J kg−1], with low-level warm-air advection and frontogenesis at the leading edge of a thermal ridge collocated with an Appalachian lee trough. Severe linear events develop in a similar mean environment as the cellular events, except that most linear events occur with a surface trough upstream over the Ohio River valley and half of the linear events develop just ahead of progressive midlevel troughs. Nonlinear severe events develop with relatively weak mean convective instability (MUCAPE ~460 J kg−1), but they are supported by midlevel quasigeostrophic (QG) forcing for ascent.
Abstract
This study documents the convective storm structures and ambient conditions associated with severe storms (wind, hail, and tornado) over the northeastern United States for two warm seasons (May–August), including 2007 and a warm season comprising randomly selected days from 2002 to 2006. The storms were classified into three main convective organizational structures (cellular, linear, and nonlinear) as well as several subcategories. The same procedure was applied to the highly populated coastal zone of the northeastern United States, including New Jersey, Connecticut, Rhode Island, and New York. The coastal analysis included six warm seasons from 2002 to 2007. Over the Northeast, severe wind events are evenly distributed among the cellular, linear, and nonlinear structures. Cellular structures are the primary hail producers, while tornadoes develop mainly from cellular and linear structures. Over the coastal zone, primarily cellular and linear systems produce severe wind and hail, while tornadoes are equally likely from all three convective structures. Composites were generated for severe weather days over the coastal region for the three main convective structures. On average, severe cellular events develop during moderate instability [most unstable CAPE (MUCAPE) ~1200 J kg−1], with low-level warm-air advection and frontogenesis at the leading edge of a thermal ridge collocated with an Appalachian lee trough. Severe linear events develop in a similar mean environment as the cellular events, except that most linear events occur with a surface trough upstream over the Ohio River valley and half of the linear events develop just ahead of progressive midlevel troughs. Nonlinear severe events develop with relatively weak mean convective instability (MUCAPE ~460 J kg−1), but they are supported by midlevel quasigeostrophic (QG) forcing for ascent.
Abstract
This study analyzed the contribution of cyclones to projected changes in cool season (1 November–31 March) precipitation over the eastern United States and western North Atlantic Ocean. First, global climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were compared to Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) precipitation analyses for the period 1979–2004. The CMIP5 ensemble mean realistically reproduced the historical distribution of regional precipitation with no discernable effect because of model spatial resolution. Subsequently, the projected changes in precipitation on cyclone and noncyclone days under the representative concentration pathway 8.5 (RCP8.5) scenario were quantified. While precipitation on both types of days was projected to increase, the increase on noncyclone days (23%) was greater than the increase on cyclone days (12%). The increase in precipitation on cyclone days occurred despite a decrease in the number of cyclone days. This increase can be attributed primarily to a shift toward more frequent extreme precipitation events coupled with a decline in light precipitation events.
Abstract
This study analyzed the contribution of cyclones to projected changes in cool season (1 November–31 March) precipitation over the eastern United States and western North Atlantic Ocean. First, global climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were compared to Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) precipitation analyses for the period 1979–2004. The CMIP5 ensemble mean realistically reproduced the historical distribution of regional precipitation with no discernable effect because of model spatial resolution. Subsequently, the projected changes in precipitation on cyclone and noncyclone days under the representative concentration pathway 8.5 (RCP8.5) scenario were quantified. While precipitation on both types of days was projected to increase, the increase on noncyclone days (23%) was greater than the increase on cyclone days (12%). The increase in precipitation on cyclone days occurred despite a decrease in the number of cyclone days. This increase can be attributed primarily to a shift toward more frequent extreme precipitation events coupled with a decline in light precipitation events.
Abstract
Hailstorms pose a significant socioeconomic risk, necessitating detailed assessments of how the hail threat changes throughout their lifetimes. Hail production involves the favorable juxtaposition of ingredients, but how storm evolution affects these ingredients is unknown, limiting understanding of how hail production evolves. Unfortunately, neither surface hail reports nor radar-based swath estimates have adequate resolution or details needed to assess evolving hail production. Instead, we use a novel approach of coupling a detailed hail trajectory model to idealized convective storm simulations to better understand storm evolution’s influence on hail production. Hail production varies substantially throughout storms’ mature phases: maximum sizes vary by a factor of 2 and the concentration of severe hail by more than fivefold during 45–60-min periods. This variability arises from changes in updraft properties, which come from (i) changes in low-level convergence and (ii) internal storm dynamics, including anticyclonic vortex shedding/storm splitting, and the response of the updraft’s airflow and supercooled liquid water content to these events. Hodograph shape strongly affects such behaviors. Straighter hodographs lead to more prolific hail production through wider updrafts and weaker mesocyclones and a periodicity in hail size metrics associated with anticyclonic vortex shedding and/or storm splitting. In contrast, a curved hodograph (favorable for tornadoes) led to a storm with a stronger but more compact updraft, which occasionally produced giant (10-cm) hail but that was a less-prolific severe hail producer overall. Unless storms are adequately sampled throughout their life cycles, snapshots from ground reports will insufficiently resolve the true nature of hail production.
Abstract
Hailstorms pose a significant socioeconomic risk, necessitating detailed assessments of how the hail threat changes throughout their lifetimes. Hail production involves the favorable juxtaposition of ingredients, but how storm evolution affects these ingredients is unknown, limiting understanding of how hail production evolves. Unfortunately, neither surface hail reports nor radar-based swath estimates have adequate resolution or details needed to assess evolving hail production. Instead, we use a novel approach of coupling a detailed hail trajectory model to idealized convective storm simulations to better understand storm evolution’s influence on hail production. Hail production varies substantially throughout storms’ mature phases: maximum sizes vary by a factor of 2 and the concentration of severe hail by more than fivefold during 45–60-min periods. This variability arises from changes in updraft properties, which come from (i) changes in low-level convergence and (ii) internal storm dynamics, including anticyclonic vortex shedding/storm splitting, and the response of the updraft’s airflow and supercooled liquid water content to these events. Hodograph shape strongly affects such behaviors. Straighter hodographs lead to more prolific hail production through wider updrafts and weaker mesocyclones and a periodicity in hail size metrics associated with anticyclonic vortex shedding and/or storm splitting. In contrast, a curved hodograph (favorable for tornadoes) led to a storm with a stronger but more compact updraft, which occasionally produced giant (10-cm) hail but that was a less-prolific severe hail producer overall. Unless storms are adequately sampled throughout their life cycles, snapshots from ground reports will insufficiently resolve the true nature of hail production.
Abstract
Mesoscale simulations of sea breezes are sensitive to the analysis product used to initialize the simulations, primarily due to the representation of the coastline and the coastal sea surface temperatures (SSTs) in the analyses. The use of spatially coarse initial conditions, relative to the horizontal resolution of the mesoscale model grid, can introduce errors in the representation of coastal SSTs, in part due to the incorrect designation of the land surface. As a result, portions of the coastal ocean are initialized with land surface temperature values and vice versa. The diurnal variation of the sea surface is typically smaller than over land on meso- and synoptic-scale time scales. Therefore, it is common practice to retain a temporally static SST in numerical simulations, causing initial SST errors to persist through the duration of the simulation. These SST errors influence horizontal coastal temperature and humidity gradients and thereby the development of the sea-breeze circulations.
The authors developed a technique to modify the initial surface conditions created from a reanalysis product [North American Regional Reanalysis (NARR)] for simulations of two sea-breeze events over the New England coast to more accurately represent the finescale structure of the coastline and the spatial representation of the coastal land surface and SST. Using this technique, the coastal SST (2-m temperature) RMSE is reduced from as much as 25°–1°C (7°–1°C), contributing to a more accurate propagation of the sea-breeze front. Techniques described in this work may be important for mesoscale simulations and forecasts of other coastal phenomena.
Abstract
Mesoscale simulations of sea breezes are sensitive to the analysis product used to initialize the simulations, primarily due to the representation of the coastline and the coastal sea surface temperatures (SSTs) in the analyses. The use of spatially coarse initial conditions, relative to the horizontal resolution of the mesoscale model grid, can introduce errors in the representation of coastal SSTs, in part due to the incorrect designation of the land surface. As a result, portions of the coastal ocean are initialized with land surface temperature values and vice versa. The diurnal variation of the sea surface is typically smaller than over land on meso- and synoptic-scale time scales. Therefore, it is common practice to retain a temporally static SST in numerical simulations, causing initial SST errors to persist through the duration of the simulation. These SST errors influence horizontal coastal temperature and humidity gradients and thereby the development of the sea-breeze circulations.
The authors developed a technique to modify the initial surface conditions created from a reanalysis product [North American Regional Reanalysis (NARR)] for simulations of two sea-breeze events over the New England coast to more accurately represent the finescale structure of the coastline and the spatial representation of the coastal land surface and SST. Using this technique, the coastal SST (2-m temperature) RMSE is reduced from as much as 25°–1°C (7°–1°C), contributing to a more accurate propagation of the sea-breeze front. Techniques described in this work may be important for mesoscale simulations and forecasts of other coastal phenomena.
Abstract
The 19–21 June 2013 Alberta flood was the second costliest ($6 billion CAD) natural disaster in Canadian history, trailing only the 2016 Fort McMurray, Alberta, Canada, wildfires. One of the primary drivers was an extreme rainfall event that resulted in 75–150 mm of precipitation in the foothills west of Calgary, Canada. Here, the mesoscale dynamics and thermodynamics that contributed to the extreme rainfall event are elucidated through high-resolution numerical model simulations. In addition, terrain reduction model sensitivity experiments using Gaussian smoothing techniques quantify the importance of orography in producing the extreme rainfall event. It is suggested that the extreme rainfall event was initially characterized by the formation of a surface cyclone on the eastern side of the Canadian Rockies due to quasigeostrophic (QG) mechanisms. Orographic processes and diabatic heating feedbacks maintained the surface cyclone throughout the event, extending the duration of both easterly upslope flow and QG forcing for ascent in the flood region. The long-duration ascent and associated condensational heat release in the flood region vertically redistributed potential vorticity, anchoring and further extending the duration of the surface cyclone, upslope flow, and the rainfall. Although the magnitudes of ascent and precipitation were smaller in 10% and 25% reduced terrain simulations, only a terrain reduction of greater than 25% drastically altered the location and magnitude of the heaviest precipitation and the associated physical mechanisms.
Abstract
The 19–21 June 2013 Alberta flood was the second costliest ($6 billion CAD) natural disaster in Canadian history, trailing only the 2016 Fort McMurray, Alberta, Canada, wildfires. One of the primary drivers was an extreme rainfall event that resulted in 75–150 mm of precipitation in the foothills west of Calgary, Canada. Here, the mesoscale dynamics and thermodynamics that contributed to the extreme rainfall event are elucidated through high-resolution numerical model simulations. In addition, terrain reduction model sensitivity experiments using Gaussian smoothing techniques quantify the importance of orography in producing the extreme rainfall event. It is suggested that the extreme rainfall event was initially characterized by the formation of a surface cyclone on the eastern side of the Canadian Rockies due to quasigeostrophic (QG) mechanisms. Orographic processes and diabatic heating feedbacks maintained the surface cyclone throughout the event, extending the duration of both easterly upslope flow and QG forcing for ascent in the flood region. The long-duration ascent and associated condensational heat release in the flood region vertically redistributed potential vorticity, anchoring and further extending the duration of the surface cyclone, upslope flow, and the rainfall. Although the magnitudes of ascent and precipitation were smaller in 10% and 25% reduced terrain simulations, only a terrain reduction of greater than 25% drastically altered the location and magnitude of the heaviest precipitation and the associated physical mechanisms.
Abstract
Two high-impact convective snowband events (“snow bursts”) that affected Calgary, Alberta, Canada, are examined to better understand the dynamics and thermodynamics of heavy snowbands not associated with lake effects or the cold conveyor belt of synoptic-scale cyclones. Such events are typically characterized by brief, but heavy, periods of snow; low visibilities; and substantial hazards to automobile and aviation interests. Previous literature on these events has been limited to a few case studies across North America, including near the leeside foothills of the U.S. Rockies. The large-scale dynamics and thermodynamics are investigated using the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR). Previously, high-resolution convection-explicit Weather Research and Forecasting Model (WRF) simulations have shown some ability to successfully reproduce the dynamics, thermodynamics, and appearance of convective snowbands, with small errors in location and timing. Therefore, WRF simulations are performed for both events, and are evaluated along with the NCEP North American Mesoscale (NAM) model forecasts. Both the NARR and WRF simulations show that while the two snow bursts are similar in appearance, they form as a result of different dynamic and thermodynamic mechanisms. The first event occurs downstream of an upper-tropospheric jet streak in a region of little synoptic-scale ascent, where ageostrophic frontogenesis helps to release conditional, dry symmetric, and inertial instability in an unsaturated environment. The inertial instability is determined to be related to fast flow over upstream high terrain. The second event occurs in a saturated environment in a region of Q-vector convergence (primarily geostrophic frontogenesis), which acts to release conditional, convective, and conditional symmetric instability (CSI).
Abstract
Two high-impact convective snowband events (“snow bursts”) that affected Calgary, Alberta, Canada, are examined to better understand the dynamics and thermodynamics of heavy snowbands not associated with lake effects or the cold conveyor belt of synoptic-scale cyclones. Such events are typically characterized by brief, but heavy, periods of snow; low visibilities; and substantial hazards to automobile and aviation interests. Previous literature on these events has been limited to a few case studies across North America, including near the leeside foothills of the U.S. Rockies. The large-scale dynamics and thermodynamics are investigated using the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR). Previously, high-resolution convection-explicit Weather Research and Forecasting Model (WRF) simulations have shown some ability to successfully reproduce the dynamics, thermodynamics, and appearance of convective snowbands, with small errors in location and timing. Therefore, WRF simulations are performed for both events, and are evaluated along with the NCEP North American Mesoscale (NAM) model forecasts. Both the NARR and WRF simulations show that while the two snow bursts are similar in appearance, they form as a result of different dynamic and thermodynamic mechanisms. The first event occurs downstream of an upper-tropospheric jet streak in a region of little synoptic-scale ascent, where ageostrophic frontogenesis helps to release conditional, dry symmetric, and inertial instability in an unsaturated environment. The inertial instability is determined to be related to fast flow over upstream high terrain. The second event occurs in a saturated environment in a region of Q-vector convergence (primarily geostrophic frontogenesis), which acts to release conditional, convective, and conditional symmetric instability (CSI).
Abstract
Extratropical cyclone track density, genesis frequency, deepening rate, and maximum intensity distributions over eastern North America and the western North Atlantic were analyzed for 15 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical period (1979–2004) and three future periods (2009–38, 2039–68, and 2069–98). The cyclones were identified using an automated tracking algorithm applied to sea level pressure every 6 h. The CMIP5 results for the historical period were evaluated using the Climate Forecast System Reanalysis (CFSR). The CMIP5 models were ranked given their track density, intensity, and overall performance for the historical period. It was found that six of the top seven CMIP5 models with the highest spatial resolution were ranked the best overall. These models had less underprediction of cyclone track density, more realistic distribution of intense cyclones along the U.S. East Coast, and more realistic cyclogenesis and deepening rates. The best seven models were used to determine projected future changes in cyclones, which included a 10%–30% decrease in cyclone track density and weakening of cyclones over the western Atlantic storm track, while in contrast there is a 10%–20% increase in cyclone track density over the eastern United States, including 10%–40% more intense (<980 hPa) cyclones and 20%–40% more rapid deepening rates just inland of the U.S. East Coast. Some of the reasons for these CMIP5 model differences were explored for the selected models based on model generated Eady growth rate, upper-level jet, surface baroclinicity, and precipitation.
Abstract
Extratropical cyclone track density, genesis frequency, deepening rate, and maximum intensity distributions over eastern North America and the western North Atlantic were analyzed for 15 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical period (1979–2004) and three future periods (2009–38, 2039–68, and 2069–98). The cyclones were identified using an automated tracking algorithm applied to sea level pressure every 6 h. The CMIP5 results for the historical period were evaluated using the Climate Forecast System Reanalysis (CFSR). The CMIP5 models were ranked given their track density, intensity, and overall performance for the historical period. It was found that six of the top seven CMIP5 models with the highest spatial resolution were ranked the best overall. These models had less underprediction of cyclone track density, more realistic distribution of intense cyclones along the U.S. East Coast, and more realistic cyclogenesis and deepening rates. The best seven models were used to determine projected future changes in cyclones, which included a 10%–30% decrease in cyclone track density and weakening of cyclones over the western Atlantic storm track, while in contrast there is a 10%–20% increase in cyclone track density over the eastern United States, including 10%–40% more intense (<980 hPa) cyclones and 20%–40% more rapid deepening rates just inland of the U.S. East Coast. Some of the reasons for these CMIP5 model differences were explored for the selected models based on model generated Eady growth rate, upper-level jet, surface baroclinicity, and precipitation.
Abstract
This paper describes the climatology of tornadoes around New York City (NYC) and Long Island (LI), New York, and the structural evolution of two tornadic events that affected NYC on 8 August 2007 and 16 September 2010. Nearly half (18 of 34 events from 1950 to 2010) of NYC–LI tornadoes developed between 0500 and 1300 EDT, and August is the peak tornado month as compared to July for most of the northeast United States. A spatial composite highlights the approaching midlevel trough, moderate most unstable convective available potential energy (MUCAPE), and frontogenesis along a low-level baroclinic zone. Shortly before the early morning tornadoes on 8 August 2007, a mesoscale convective system intensified in the lee of the Appalachians in a region of low-level frontogenesis and moderate MUCAPE (~1500 J kg−1). Warm advection at low levels and evaporative cooling within an elevated mixed layer (EML) ahead of the mesoscale convective system (MCS) helped steepen the low-level lapse rates. Meanwhile, a surface mesolow along a quasi-stationary frontal zone enhanced the warm advection and low-level shear. The late afternoon event on 16 September 2010 was characterized by a quasi-linear convective system (QLCS) that also featured an EML aloft, a surface mesolow just west of NYC, low-level frontogenesis, and a southerly low-level jet ahead of an approaching midlevel trough. The QLCS intensified approaching NYC and generated mesovortices as the QLCS bowed outward. These cases illustrate the benefit of high-density surface observations, terminal Doppler radars, and sounding profiles from commercial aircraft for nowcasting these events.
Abstract
This paper describes the climatology of tornadoes around New York City (NYC) and Long Island (LI), New York, and the structural evolution of two tornadic events that affected NYC on 8 August 2007 and 16 September 2010. Nearly half (18 of 34 events from 1950 to 2010) of NYC–LI tornadoes developed between 0500 and 1300 EDT, and August is the peak tornado month as compared to July for most of the northeast United States. A spatial composite highlights the approaching midlevel trough, moderate most unstable convective available potential energy (MUCAPE), and frontogenesis along a low-level baroclinic zone. Shortly before the early morning tornadoes on 8 August 2007, a mesoscale convective system intensified in the lee of the Appalachians in a region of low-level frontogenesis and moderate MUCAPE (~1500 J kg−1). Warm advection at low levels and evaporative cooling within an elevated mixed layer (EML) ahead of the mesoscale convective system (MCS) helped steepen the low-level lapse rates. Meanwhile, a surface mesolow along a quasi-stationary frontal zone enhanced the warm advection and low-level shear. The late afternoon event on 16 September 2010 was characterized by a quasi-linear convective system (QLCS) that also featured an EML aloft, a surface mesolow just west of NYC, low-level frontogenesis, and a southerly low-level jet ahead of an approaching midlevel trough. The QLCS intensified approaching NYC and generated mesovortices as the QLCS bowed outward. These cases illustrate the benefit of high-density surface observations, terminal Doppler radars, and sounding profiles from commercial aircraft for nowcasting these events.
