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Abstract
This paper examines ice particle reorganization by three-dimensional horizontal kinematic flows within the comma head regions of two U.S. East Coast winter storms and the effect of reorganization on particle concentrations within snowbands in each storm. In these simplified experiments, the kinematic flows are from the initialization of the HRRR model. Ice particles falling through the comma head were started from either 9-, 8-, or 7-km altitude, spaced every 200 m, and were transported north or northwest, arriving within the north or northwest half of the primary snowband in each storm. The greatest particle concentration enhancement within each band was a factor of 2.32–3.84 for the 16–17 December 2020 storm and 1.76–2.32 for the 29–30 January 2022 storm. Trajectory analyses for particles originating at 4 km on the southeast side of the comma head beneath the dry slot showed that this region supplied particles to the south side of the band with particle enhancements of factor of 1.36–2.08 for the 16–17 December 2020 storm and 1.04–2.16 for the 29–30 January 2022 storm. Snowfall within the bands had two source regions: 1) on the north/northwestern side, from ice particles falling from the comma head, and 2) on the southeastern side, from particles forming at or below 4-km altitude and transported northwestward by low-level flow off the Atlantic. While the findings give information on the source of particles in the bands, they do not definitively determine the cause of precipitation banding since other factors, such as large-scale ascent and embedded convection, also contribute to snow growth.
Significance Statement
Wintertime storms along the east coast of North America can produce heavy snowfall, high winds, coastal flooding, and cold temperatures, resulting in major economic impacts within the northeast U.S. urban corridor. The heaviest snowfall typically occurs within snowbands, elongated narrow regions identifiable by high reflectivity on radar. This paper examines the potential sources of the ice particles contributing to the snowbands and how the flow fields throughout the storm can contribute to enhanced particle concentrations within the bands.
Abstract
This paper examines ice particle reorganization by three-dimensional horizontal kinematic flows within the comma head regions of two U.S. East Coast winter storms and the effect of reorganization on particle concentrations within snowbands in each storm. In these simplified experiments, the kinematic flows are from the initialization of the HRRR model. Ice particles falling through the comma head were started from either 9-, 8-, or 7-km altitude, spaced every 200 m, and were transported north or northwest, arriving within the north or northwest half of the primary snowband in each storm. The greatest particle concentration enhancement within each band was a factor of 2.32–3.84 for the 16–17 December 2020 storm and 1.76–2.32 for the 29–30 January 2022 storm. Trajectory analyses for particles originating at 4 km on the southeast side of the comma head beneath the dry slot showed that this region supplied particles to the south side of the band with particle enhancements of factor of 1.36–2.08 for the 16–17 December 2020 storm and 1.04–2.16 for the 29–30 January 2022 storm. Snowfall within the bands had two source regions: 1) on the north/northwestern side, from ice particles falling from the comma head, and 2) on the southeastern side, from particles forming at or below 4-km altitude and transported northwestward by low-level flow off the Atlantic. While the findings give information on the source of particles in the bands, they do not definitively determine the cause of precipitation banding since other factors, such as large-scale ascent and embedded convection, also contribute to snow growth.
Significance Statement
Wintertime storms along the east coast of North America can produce heavy snowfall, high winds, coastal flooding, and cold temperatures, resulting in major economic impacts within the northeast U.S. urban corridor. The heaviest snowfall typically occurs within snowbands, elongated narrow regions identifiable by high reflectivity on radar. This paper examines the potential sources of the ice particles contributing to the snowbands and how the flow fields throughout the storm can contribute to enhanced particle concentrations within the bands.
Abstract
Limited knowledge exists about ∼100-m-scale precipitation processes within U.S. northeast coastal snowstorms because of a lack of high-resolution observations. We investigate characteristics of microscale updraft regions within the cyclone comma head and their relationships with snowbands, wind shear, frontogenesis, and vertical mass flux using high-spatiotemporal-resolution vertically pointing Ka-band radar measurements, soundings, and reanalysis data for four snowstorms observed at Stony Brook, New York. Updraft regions are defined as contiguous time–height plotted areas with upward Doppler velocity without hydrometeor sedimentation that is equal to or greater than 0.4 m s−1. Most updraft regions in the time–height data occur on a time scale of seconds (<20 s), which is equivalent to spatial scales < 500 m. These small updraft regions within cloud echo occur more than 30% of the time for three of the four cases and 18% for the other case. They are found at all altitudes and can occur with or without frontogenesis and with or without snowbands. The updraft regions with relatively large Doppler spectrum width (>0.4 m s−1) occur more frequently within midlevels of the storms, where there are strong wind shear layers and moist shear instability layers. This suggests that the dominant forcing for the updrafts appears to be turbulence associated with the vertical shear instability. The updraft regions can be responsible for upward mass flux when they are closer together in space and time. The higher values of column mean upward mass flux often occur during snowband periods.
Significance Statement
Small-scale (<500 m) upward motions within four snowstorms along the U.S. northeast coast are analyzed for the first time using high-spatiotemporal-resolution millimeter-wavelength cloud radar pointed vertically. The analysis reveals that updrafts appear in the storms regardless of whether snowbands are present or whether there is larger-scale forcing for ascent. The more turbulent and stronger updrafts frequently occur in midlevels of storms associated with instability from vertical shear and contribute to upward mass flux during snowband periods when they are closer together in space and time.
Abstract
Limited knowledge exists about ∼100-m-scale precipitation processes within U.S. northeast coastal snowstorms because of a lack of high-resolution observations. We investigate characteristics of microscale updraft regions within the cyclone comma head and their relationships with snowbands, wind shear, frontogenesis, and vertical mass flux using high-spatiotemporal-resolution vertically pointing Ka-band radar measurements, soundings, and reanalysis data for four snowstorms observed at Stony Brook, New York. Updraft regions are defined as contiguous time–height plotted areas with upward Doppler velocity without hydrometeor sedimentation that is equal to or greater than 0.4 m s−1. Most updraft regions in the time–height data occur on a time scale of seconds (<20 s), which is equivalent to spatial scales < 500 m. These small updraft regions within cloud echo occur more than 30% of the time for three of the four cases and 18% for the other case. They are found at all altitudes and can occur with or without frontogenesis and with or without snowbands. The updraft regions with relatively large Doppler spectrum width (>0.4 m s−1) occur more frequently within midlevels of the storms, where there are strong wind shear layers and moist shear instability layers. This suggests that the dominant forcing for the updrafts appears to be turbulence associated with the vertical shear instability. The updraft regions can be responsible for upward mass flux when they are closer together in space and time. The higher values of column mean upward mass flux often occur during snowband periods.
Significance Statement
Small-scale (<500 m) upward motions within four snowstorms along the U.S. northeast coast are analyzed for the first time using high-spatiotemporal-resolution millimeter-wavelength cloud radar pointed vertically. The analysis reveals that updrafts appear in the storms regardless of whether snowbands are present or whether there is larger-scale forcing for ascent. The more turbulent and stronger updrafts frequently occur in midlevels of storms associated with instability from vertical shear and contribute to upward mass flux during snowband periods when they are closer together in space and time.
Abstract
NASA’s Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign gathered data using “satellite-simulating” (albeit with higher-resolution data than satellites currently provide) and in situ aircraft to study snowstorms, with an emphasis on banding. This study used three IMPACTS microwave instruments—two passive and one active—chosen for their sensitivity to precipitation microphysics. The 10–37-GHz passive frequencies were well suited for detecting light precipitation and differentiating rain intensities over water. The 85–183-GHz frequencies were more sensitive to cloud ice, with higher cloud tops manifesting as lower brightness temperatures, but this did not necessarily correspond well to near-surface precipitation. Over land, retrieving precipitation information from radiometer data is more difficult, requiring increased reliance on radar to assess storm structure. A dual-frequency ratio (DFR) derived from the radar’s Ku- and Ka-band frequencies provided greater insight into storm microphysics than reflectivity alone. Areas likely to contain mixed-phase precipitation (often the melting layer/bright band) generally had the highest DFR, and high-altitude regions likely to contain ice usually had the lowest DFR. The DFR of rain columns increased toward the ground, and snowbands appeared as high-DFR anomalies.
Significance Statement
Winter precipitation was studied using three airborne microwave sensors. Two were passive radiometers covering a broad range of frequencies, while the other was a two-frequency radar. The radiometers did a good job of characterizing the horizontal structure of winter storms when they were over water, but struggled to provide detailed information about winter storms when they were over land. The radar was able to provide vertically resolved details of storm structure over land or water, but only provided information at nadir, so horizontal structure was less well described. The combined use of all three instruments compensated for individual deficiencies, and was very effective at characterizing overall winter storm structure.
Abstract
NASA’s Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign gathered data using “satellite-simulating” (albeit with higher-resolution data than satellites currently provide) and in situ aircraft to study snowstorms, with an emphasis on banding. This study used three IMPACTS microwave instruments—two passive and one active—chosen for their sensitivity to precipitation microphysics. The 10–37-GHz passive frequencies were well suited for detecting light precipitation and differentiating rain intensities over water. The 85–183-GHz frequencies were more sensitive to cloud ice, with higher cloud tops manifesting as lower brightness temperatures, but this did not necessarily correspond well to near-surface precipitation. Over land, retrieving precipitation information from radiometer data is more difficult, requiring increased reliance on radar to assess storm structure. A dual-frequency ratio (DFR) derived from the radar’s Ku- and Ka-band frequencies provided greater insight into storm microphysics than reflectivity alone. Areas likely to contain mixed-phase precipitation (often the melting layer/bright band) generally had the highest DFR, and high-altitude regions likely to contain ice usually had the lowest DFR. The DFR of rain columns increased toward the ground, and snowbands appeared as high-DFR anomalies.
Significance Statement
Winter precipitation was studied using three airborne microwave sensors. Two were passive radiometers covering a broad range of frequencies, while the other was a two-frequency radar. The radiometers did a good job of characterizing the horizontal structure of winter storms when they were over water, but struggled to provide detailed information about winter storms when they were over land. The radar was able to provide vertically resolved details of storm structure over land or water, but only provided information at nadir, so horizontal structure was less well described. The combined use of all three instruments compensated for individual deficiencies, and was very effective at characterizing overall winter storm structure.
Abstract
Cloud-top phase (CTP) impacts cloud albedo and pathways for ice particle nucleation, growth, and fallout within extratropical cyclones. This study uses airborne lidar, radar, and Rapid Refresh analysis data to characterize CTP within extratropical cyclones as a function of cloud-top temperature (CTT). During the 2020, 2022, and 2023 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign deployments, the Earth Resources 2 (ER-2) aircraft flew 26 research flights over the northeast and midwest United States to sample the cloud tops of a variety of extratropical cyclones. A training dataset was developed to create probabilistic phase classifications based on Cloud Physics Lidar measurements of known ice and liquid clouds. These classifications were then used to quantify dominant CTP in the top 150 m of clouds sampled by the Cloud Physics Lidar in storms during IMPACTS. Case studies are presented illustrating examples of supercooled liquid water at cloud top at different CTT ranges (−3° < CTTs < −35°C) within extratropical cyclones. During IMPACTS, 19.2% of clouds had supercooled liquid water present at cloud top. Supercooled liquid was the dominant phase in extratropical cyclone cloud tops when CTTs were >−20°C. Liquid-bearing cloud tops were found at CTTs as cold as −37°C.
Significance Statement
Identifying supercooled liquid cloud tops’ frequency is crucial for understanding ice nucleation mechanisms at cloud top, cloud radiative effects, and aircraft icing. In this study, airborne lidar, radar, and model temperature data from 26 research flights during the NASA IMPACTS campaign are used to characterize extratropical cyclone cloud-top phase (CTP) as a function of cloud-top temperature (CTT). The results show that liquid was the dominant CTP present in extratropical cyclone cloud tops when CTTs were >−20°C with decreasing supercooled liquid cloud-top frequency at temperatures < −20°C. Nevertheless, liquid was present at CTTs as cold as −37°C.
Abstract
Cloud-top phase (CTP) impacts cloud albedo and pathways for ice particle nucleation, growth, and fallout within extratropical cyclones. This study uses airborne lidar, radar, and Rapid Refresh analysis data to characterize CTP within extratropical cyclones as a function of cloud-top temperature (CTT). During the 2020, 2022, and 2023 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign deployments, the Earth Resources 2 (ER-2) aircraft flew 26 research flights over the northeast and midwest United States to sample the cloud tops of a variety of extratropical cyclones. A training dataset was developed to create probabilistic phase classifications based on Cloud Physics Lidar measurements of known ice and liquid clouds. These classifications were then used to quantify dominant CTP in the top 150 m of clouds sampled by the Cloud Physics Lidar in storms during IMPACTS. Case studies are presented illustrating examples of supercooled liquid water at cloud top at different CTT ranges (−3° < CTTs < −35°C) within extratropical cyclones. During IMPACTS, 19.2% of clouds had supercooled liquid water present at cloud top. Supercooled liquid was the dominant phase in extratropical cyclone cloud tops when CTTs were >−20°C. Liquid-bearing cloud tops were found at CTTs as cold as −37°C.
Significance Statement
Identifying supercooled liquid cloud tops’ frequency is crucial for understanding ice nucleation mechanisms at cloud top, cloud radiative effects, and aircraft icing. In this study, airborne lidar, radar, and model temperature data from 26 research flights during the NASA IMPACTS campaign are used to characterize extratropical cyclone cloud-top phase (CTP) as a function of cloud-top temperature (CTT). The results show that liquid was the dominant CTP present in extratropical cyclone cloud tops when CTTs were >−20°C with decreasing supercooled liquid cloud-top frequency at temperatures < −20°C. Nevertheless, liquid was present at CTTs as cold as −37°C.
Synergistic Retrievals of Ice in High Clouds from Elastic Backscatter Lidar, Ku-Band Radar, and Submillimeter Wave Radiometer ObservationsAbstract
In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and submillimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of ice water content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments (frequencies, sensitivities, etc.) are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-means clustering algorithm. In the second step, the IWC profile is estimated using an ensemble Kalman smoother algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.
Abstract
In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and submillimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of ice water content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments (frequencies, sensitivities, etc.) are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-means clustering algorithm. In the second step, the IWC profile is estimated using an ensemble Kalman smoother algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.
Abstract
This paper explores whether particles within uniformly spaced generating cells falling at terminal velocity within observed 2D wind fields and idealized deformation flow beneath cloud top can be reorganized consistent with the presence of single and multibanded structures present on WSR-88D radars. In the first experiment, two-dimensional wind fields, calculated along cross sections normal to the long axis of snowbands observed during three northeast U.S. winter storms, were taken from the initialization of the High-Resolution Rapid Refresh model. This experiment demonstrated that the greater the residence time of the particles in each of the three storms, the greater particle reorganization occurred. For experiments with longer residence times, increases in particle concentrations were nearly or directly collocated with reflectivity bands. For experiments with shorter residence times, particle reorganization still conformed to the band features but with less concentration enhancement. This experiment demonstrates that the combination of long particle residence time and net convergent cross-sectional flow through the cloud depth is sufficient to reorganize particles into locations consistent with precipitation bands. Increased concentrations of ice particles can then contribute, along with any dynamic forcing, to the low-level reflectivity bands seen on WSR-88D radars. In a second experiment, the impact of flow deformation on the reorganization of falling ice particles was investigated using an idealized kinematic model with stretching deformation flow of different depths and magnitudes. These experiments showed that deformation flow provides for little particle reorganization given typical deformation layer depths and magnitudes within the comma head of such storms.
Significance Statement
Past research with vertically pointing and scanning radars presents two different perspectives regarding snowfall organization in winter storms. Vertically pointing radars often observe cloud-top generating cells with precipitation fallstreaks descending into a broad stratiform echo at lower altitudes. In contrast, scanning radars often observe snowfall organized in quasi-linear bands. This work attempts to provide a connection between these two perspectives by examining how two-dimensional convergent and deformation flow occurring in winter storms can contribute to the reorganization of snowfall between cloud top and the ground.
Abstract
This paper explores whether particles within uniformly spaced generating cells falling at terminal velocity within observed 2D wind fields and idealized deformation flow beneath cloud top can be reorganized consistent with the presence of single and multibanded structures present on WSR-88D radars. In the first experiment, two-dimensional wind fields, calculated along cross sections normal to the long axis of snowbands observed during three northeast U.S. winter storms, were taken from the initialization of the High-Resolution Rapid Refresh model. This experiment demonstrated that the greater the residence time of the particles in each of the three storms, the greater particle reorganization occurred. For experiments with longer residence times, increases in particle concentrations were nearly or directly collocated with reflectivity bands. For experiments with shorter residence times, particle reorganization still conformed to the band features but with less concentration enhancement. This experiment demonstrates that the combination of long particle residence time and net convergent cross-sectional flow through the cloud depth is sufficient to reorganize particles into locations consistent with precipitation bands. Increased concentrations of ice particles can then contribute, along with any dynamic forcing, to the low-level reflectivity bands seen on WSR-88D radars. In a second experiment, the impact of flow deformation on the reorganization of falling ice particles was investigated using an idealized kinematic model with stretching deformation flow of different depths and magnitudes. These experiments showed that deformation flow provides for little particle reorganization given typical deformation layer depths and magnitudes within the comma head of such storms.
Significance Statement
Past research with vertically pointing and scanning radars presents two different perspectives regarding snowfall organization in winter storms. Vertically pointing radars often observe cloud-top generating cells with precipitation fallstreaks descending into a broad stratiform echo at lower altitudes. In contrast, scanning radars often observe snowfall organized in quasi-linear bands. This work attempts to provide a connection between these two perspectives by examining how two-dimensional convergent and deformation flow occurring in winter storms can contribute to the reorganization of snowfall between cloud top and the ground.
Abstract
This study investigates the evolution of temperature and lifetime of evaporating, supercooled cloud droplets considering initial droplet radius (r
0) and temperature (
Significance Statement
Cloud droplet temperature plays an important role in fundamental cloud processes like droplet growth and decay, activation of ice-nucleating particles, and determination of radiative parameters like refractive indices of water droplets. Near cloud boundaries such as cloud tops, dry air mixes with cloudy air exposing droplets to environments with low relative humidities. This study examines how the temperature of a cloud droplet that is supercooled (i.e., has an initial temperature < 0°C) evolves in these subsaturated environments. Results show that when supercooled cloud droplets evaporate near cloud boundaries, their temperatures can be several degrees Celsius lower than the surrounding drier environment. The implications of this additional cooling of droplets near cloud edges on ice particle formation are discussed.
Abstract
This study investigates the evolution of temperature and lifetime of evaporating, supercooled cloud droplets considering initial droplet radius (r
0) and temperature (
Significance Statement
Cloud droplet temperature plays an important role in fundamental cloud processes like droplet growth and decay, activation of ice-nucleating particles, and determination of radiative parameters like refractive indices of water droplets. Near cloud boundaries such as cloud tops, dry air mixes with cloudy air exposing droplets to environments with low relative humidities. This study examines how the temperature of a cloud droplet that is supercooled (i.e., has an initial temperature < 0°C) evolves in these subsaturated environments. Results show that when supercooled cloud droplets evaporate near cloud boundaries, their temperatures can be several degrees Celsius lower than the surrounding drier environment. The implications of this additional cooling of droplets near cloud edges on ice particle formation are discussed.
Abstract
On 7 February 2020 a relatively deep cyclone (∼980 hPa) with midlevel frontogenesis produced heavy snow (20–30 mm liquid equivalent) over western and central New York State. Despite these characteristics, the precipitation was not organized into a narrow band of intensive snowfall. This event occurred during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Using coordinated flight legs across New York State, a remote sensing aircraft (ER-2) sampled above the cloud, while a P-3 aircraft collected in-cloud data. These data are used to validate several Weather Research and Forecasting (WRF) Model simulations at 2- and 0.67-km grid spacing using different initial and boundary conditions (RAP, GFS, and ERA5 analyses) and microphysics schemes (Thompson and P3). The differences between the WRF runs are used to explore sensitivity to initial conditions and microphysics schemes. All 18–24-h runs realistically produced a broad sloping region of frontogenesis at midlevels typically; however, there were relatively large (20%–30%) uncertainties in the magnitude of this forcing using different analyses and initialization times. The differences in surface precipitation distribution are small (<10%) among the microphysics schemes, likely because there was little riming in the region of heaviest precipitation. Those runs with frontogenesis closest to the RAP analysis and a surface precipitation underprediction of 20%–30% have too little ice aloft and at low levels, suggesting deficiencies in ice generation and snow growth aloft in those runs. The 0.67-km grid produced more realistic convective cells aloft, but only 5%–10% more precipitation than the 2-km grid.
Significance Statement
Heavy snowfall from U.S. East Coast winter storms can cause major societal problems, yet few studies have investigated these storms using field observations and model data. This study focuses on the 7 February 2020 event, where 20–40 cm of snow fell over west-central New York. Our analysis shows a broad region of ascent, rather than a concentrated region favoring a well-defined snowband was the primary process contributing to snowfall. Last, model microphysics were validated within this storm using the in situ aircraft data. Errors in the snow generation aloft and snow growth at low levels likely contributed to the simulated surface precipitation underprediction, but most of the forecast uncertainty is from initial conditions for this short-term (∼24-h lead time) forecast.
Abstract
On 7 February 2020 a relatively deep cyclone (∼980 hPa) with midlevel frontogenesis produced heavy snow (20–30 mm liquid equivalent) over western and central New York State. Despite these characteristics, the precipitation was not organized into a narrow band of intensive snowfall. This event occurred during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Using coordinated flight legs across New York State, a remote sensing aircraft (ER-2) sampled above the cloud, while a P-3 aircraft collected in-cloud data. These data are used to validate several Weather Research and Forecasting (WRF) Model simulations at 2- and 0.67-km grid spacing using different initial and boundary conditions (RAP, GFS, and ERA5 analyses) and microphysics schemes (Thompson and P3). The differences between the WRF runs are used to explore sensitivity to initial conditions and microphysics schemes. All 18–24-h runs realistically produced a broad sloping region of frontogenesis at midlevels typically; however, there were relatively large (20%–30%) uncertainties in the magnitude of this forcing using different analyses and initialization times. The differences in surface precipitation distribution are small (<10%) among the microphysics schemes, likely because there was little riming in the region of heaviest precipitation. Those runs with frontogenesis closest to the RAP analysis and a surface precipitation underprediction of 20%–30% have too little ice aloft and at low levels, suggesting deficiencies in ice generation and snow growth aloft in those runs. The 0.67-km grid produced more realistic convective cells aloft, but only 5%–10% more precipitation than the 2-km grid.
Significance Statement
Heavy snowfall from U.S. East Coast winter storms can cause major societal problems, yet few studies have investigated these storms using field observations and model data. This study focuses on the 7 February 2020 event, where 20–40 cm of snow fell over west-central New York. Our analysis shows a broad region of ascent, rather than a concentrated region favoring a well-defined snowband was the primary process contributing to snowfall. Last, model microphysics were validated within this storm using the in situ aircraft data. Errors in the snow generation aloft and snow growth at low levels likely contributed to the simulated surface precipitation underprediction, but most of the forecast uncertainty is from initial conditions for this short-term (∼24-h lead time) forecast.
Abstract
Coincident radar data with Doppler radar measurements at X, Ku, Ka, and W bands on the NASA ER-2 aircraft overflying the NASA P-3 aircraft acquiring in situ microphysical measurements are used to characterize the relationship between radar measurements and ice microphysical properties. The data were obtained from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS). Direct measurements of the condensed water content and coincident Doppler radar measurements were acquired, facilitating improved estimates of ice particle mass, a variable that is an underlying factor for calculating and therefore retrieving the radar reflectivity Ze , median mass diameter Dm , particle terminal velocity, and snowfall rate S. The relationship between the measured ice water content (IWC) and that calculated from the particle size distributions (PSDs) using relationships developed in earlier studies, and between the calculated and measured radar reflectivity at the four radar wavelengths, are quantified. Relationships are derived between the measured IWC and properties of the PSD, Dm , Ze at the four radar wavelengths, and the dual-wavelength ratio. Because IWC and Ze are measured directly, the coefficients in the mass–dimensional relationship that best match both the IWC and Ze are derived. The relationships developed here, and the mass–dimensional relationship that uses both the measured IWC and Ze to find a best match for both variables, can be used in studies that characterize the properties of wintertime snow clouds.
Significance Statement
The goal of this study is to provide reliable microphysical measurements and algorithms to facilitate improvements in cloud model microphysical parameterizations and in retrieval of snow precipitation properties from spaceborne active remote sensors and to characterize ice and snow precipitation development within clouds. This work draws upon a unique set of in situ measurements of the ice and total water content coupled with overflying aircraft radar measurements at four radar wavelengths. Better estimates of the contributions of the ice phase to the total global precipitation using spaceborne radar data pave the way for assessing and advancing global climate modeling, thereby strengthening predictions of global climate change.
Abstract
Coincident radar data with Doppler radar measurements at X, Ku, Ka, and W bands on the NASA ER-2 aircraft overflying the NASA P-3 aircraft acquiring in situ microphysical measurements are used to characterize the relationship between radar measurements and ice microphysical properties. The data were obtained from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS). Direct measurements of the condensed water content and coincident Doppler radar measurements were acquired, facilitating improved estimates of ice particle mass, a variable that is an underlying factor for calculating and therefore retrieving the radar reflectivity Ze , median mass diameter Dm , particle terminal velocity, and snowfall rate S. The relationship between the measured ice water content (IWC) and that calculated from the particle size distributions (PSDs) using relationships developed in earlier studies, and between the calculated and measured radar reflectivity at the four radar wavelengths, are quantified. Relationships are derived between the measured IWC and properties of the PSD, Dm , Ze at the four radar wavelengths, and the dual-wavelength ratio. Because IWC and Ze are measured directly, the coefficients in the mass–dimensional relationship that best match both the IWC and Ze are derived. The relationships developed here, and the mass–dimensional relationship that uses both the measured IWC and Ze to find a best match for both variables, can be used in studies that characterize the properties of wintertime snow clouds.
Significance Statement
The goal of this study is to provide reliable microphysical measurements and algorithms to facilitate improvements in cloud model microphysical parameterizations and in retrieval of snow precipitation properties from spaceborne active remote sensors and to characterize ice and snow precipitation development within clouds. This work draws upon a unique set of in situ measurements of the ice and total water content coupled with overflying aircraft radar measurements at four radar wavelengths. Better estimates of the contributions of the ice phase to the total global precipitation using spaceborne radar data pave the way for assessing and advancing global climate modeling, thereby strengthening predictions of global climate change.
Abstract
On 7 February 2020, precipitation within the comma-head region of an extratropical cyclone was sampled remotely and in situ by two research aircraft, providing a vertical cross section of microphysical observations and fine-scale radar measurements. The sampled region was stratified vertically by distinct temperature layers and horizontally into a stratiform region on the west side, and a region of elevated convection on the east side. In the stratiform region, precipitation formed near cloud top as side-plane, polycrystalline, and platelike particles. These habits occurred through cloud depth, implying that the cloud-top region was the primary source of particles. Almost no supercooled water was present. The ice water content within the stratiform region showed an overall increase with depth between the aircraft flight levels, while the total number concentration slightly decreased, consistent with growth by vapor deposition and aggregation. In the convective region, new particle habits were observed within each temperature-defined layer along with detectable amounts of supercooled water, implying that ice particle formation occurred in several layers. Total number concentration decreased from cloud top to the −8°C level, consistent with particle aggregation. At temperatures > −8°C, ice particle concentrations in some regions increased to >100 L−1, suggesting secondary ice production occurred at lower altitudes. WSR-88D reflectivity composites during the sampling period showed a weak, loosely organized banded feature. The band, evident on earlier flight legs, was consistent with enhanced vertical motion associated with frontogenesis, and at least partial melting of ice particles near the surface. A conceptual model of precipitation growth processes within the comma head is presented.
Significance Statement
Snowstorms over the northeast United States have major impacts on travel, power availability, and commerce. The processes by which snow forms in winter storms over this region are complex and their snowfall totals are hard to forecast accurately because of a poor understanding of the microphysical processes within the clouds composing the storms. This paper presents a case study from the NASA IMPACTS field campaign that involved two aircraft sampling the storm simultaneously with radars, and probes that measure the microphysical properties within the storm. The paper examines how variations in stability and frontal structure influence the microphysical evolution of ice particles as they fall from cloud top to the surface within the storm.
Abstract
On 7 February 2020, precipitation within the comma-head region of an extratropical cyclone was sampled remotely and in situ by two research aircraft, providing a vertical cross section of microphysical observations and fine-scale radar measurements. The sampled region was stratified vertically by distinct temperature layers and horizontally into a stratiform region on the west side, and a region of elevated convection on the east side. In the stratiform region, precipitation formed near cloud top as side-plane, polycrystalline, and platelike particles. These habits occurred through cloud depth, implying that the cloud-top region was the primary source of particles. Almost no supercooled water was present. The ice water content within the stratiform region showed an overall increase with depth between the aircraft flight levels, while the total number concentration slightly decreased, consistent with growth by vapor deposition and aggregation. In the convective region, new particle habits were observed within each temperature-defined layer along with detectable amounts of supercooled water, implying that ice particle formation occurred in several layers. Total number concentration decreased from cloud top to the −8°C level, consistent with particle aggregation. At temperatures > −8°C, ice particle concentrations in some regions increased to >100 L−1, suggesting secondary ice production occurred at lower altitudes. WSR-88D reflectivity composites during the sampling period showed a weak, loosely organized banded feature. The band, evident on earlier flight legs, was consistent with enhanced vertical motion associated with frontogenesis, and at least partial melting of ice particles near the surface. A conceptual model of precipitation growth processes within the comma head is presented.
Significance Statement
Snowstorms over the northeast United States have major impacts on travel, power availability, and commerce. The processes by which snow forms in winter storms over this region are complex and their snowfall totals are hard to forecast accurately because of a poor understanding of the microphysical processes within the clouds composing the storms. This paper presents a case study from the NASA IMPACTS field campaign that involved two aircraft sampling the storm simultaneously with radars, and probes that measure the microphysical properties within the storm. The paper examines how variations in stability and frontal structure influence the microphysical evolution of ice particles as they fall from cloud top to the surface within the storm.
