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Abstract
On 1–2 February 1992 a major storm produced a prolonged period (6 h) of ice pellets over St. John's, Newfoundland. At least two key features contributed to the prolonged duration. First, a subsaturated region within an inversion led to a reduction in the melting rate of particles that eventually meant that they could completely refreeze in the lower subfreezing region. This subsaturated region formed within descending air aloft identified by Doppler radar observations. Second, a cold core of air between the surface and the inversion was critically important for the refreezing of partially melted particles. Results from an airmass transformation model were used to show that the ice pellet duration was extended as a result of air traveling over sea ice as opposed to over the ocean. In addition, this study showed that Doppler radar velocity information may be capable of estimating the base height of the above freezing temperature regime during freezing rain/drizzle. Furthermore, the Doppler velocity information may also be used as a warning for possible freezing rain/drizzle conditions. A conceptual model of this storm has been developed to integrate all of the observations and it was also compared to other storms producing ice pellets. Only one other storm possessed a period of sole ice pellets and it was also the only other storm that exhibited a pronounced subsaturated region within the inversion.
Abstract
On 1–2 February 1992 a major storm produced a prolonged period (6 h) of ice pellets over St. John's, Newfoundland. At least two key features contributed to the prolonged duration. First, a subsaturated region within an inversion led to a reduction in the melting rate of particles that eventually meant that they could completely refreeze in the lower subfreezing region. This subsaturated region formed within descending air aloft identified by Doppler radar observations. Second, a cold core of air between the surface and the inversion was critically important for the refreezing of partially melted particles. Results from an airmass transformation model were used to show that the ice pellet duration was extended as a result of air traveling over sea ice as opposed to over the ocean. In addition, this study showed that Doppler radar velocity information may be capable of estimating the base height of the above freezing temperature regime during freezing rain/drizzle. Furthermore, the Doppler velocity information may also be used as a warning for possible freezing rain/drizzle conditions. A conceptual model of this storm has been developed to integrate all of the observations and it was also compared to other storms producing ice pellets. Only one other storm possessed a period of sole ice pellets and it was also the only other storm that exhibited a pronounced subsaturated region within the inversion.
Abstract
High-temporal-resolution total-column precipitable water vapor (PWV) was measured using a Radiometrics Corporation WVR-1100 Atmospheric Microwave Radiometer (AMR). The AMR was deployed at the University of Manitoba in Winnipeg, Canada, during the 2003 and 2006 growing seasons (mid-May–end of August). PWV data were examined 1) to document the diurnal cycle of PWV and to provide insight into the various processes controlling this cycle and 2) to assess the accuracy of the Canadian regional Global Environmental Multiscale (GEM) model analysis and forecasts (out to 36 h) of PWV. The mean daily PWV was 22.6 mm in 2003 and 23.8 mm in 2006, with distinct diurnal amplitudes of 1.5 and 1.8 mm, respectively. It was determined that the diurnal cycle of PWV about the daily mean value was controlled by evapotranspiration (ET) and the occurrence/timing of deep convection. The PWV in both years reached its hourly maximum later in the afternoon as opposed to at solar noon. This suggested that the surface and atmosphere were well coupled, with ET primarily being controlled by the vapor pressure deficit between the vegetation/surface and atmosphere. The decrease in PWV during the evening and overnight periods of both years was likely the result of deep convection, with or without precipitation, which drew water vapor out of the atmosphere, as well as the nocturnal decline in ET. The results did not change for days on which low-level winds were light (i.e., maximum winds from the surface to 850 hPa were below 20 km h−1), which supports the notion that the diurnal PWV pattern was associated with the daily cycles of local ET and convection/precipitation and was not due to advection. Comparison of AMR PWV with the Canadian GEM model for the growing seasons of 2003 and 2006 indicated that the model error was 3 mm (13%) or more even in the first 12 h, with mean absolute errors ranging from 2 to 3.5 mm and root-mean-square errors from 3 to 4.5 mm over the full 36-h forecast period. It was also found that the 3–9-h forecast period of GEM had better error scores in 2006 than in 2003.
Abstract
High-temporal-resolution total-column precipitable water vapor (PWV) was measured using a Radiometrics Corporation WVR-1100 Atmospheric Microwave Radiometer (AMR). The AMR was deployed at the University of Manitoba in Winnipeg, Canada, during the 2003 and 2006 growing seasons (mid-May–end of August). PWV data were examined 1) to document the diurnal cycle of PWV and to provide insight into the various processes controlling this cycle and 2) to assess the accuracy of the Canadian regional Global Environmental Multiscale (GEM) model analysis and forecasts (out to 36 h) of PWV. The mean daily PWV was 22.6 mm in 2003 and 23.8 mm in 2006, with distinct diurnal amplitudes of 1.5 and 1.8 mm, respectively. It was determined that the diurnal cycle of PWV about the daily mean value was controlled by evapotranspiration (ET) and the occurrence/timing of deep convection. The PWV in both years reached its hourly maximum later in the afternoon as opposed to at solar noon. This suggested that the surface and atmosphere were well coupled, with ET primarily being controlled by the vapor pressure deficit between the vegetation/surface and atmosphere. The decrease in PWV during the evening and overnight periods of both years was likely the result of deep convection, with or without precipitation, which drew water vapor out of the atmosphere, as well as the nocturnal decline in ET. The results did not change for days on which low-level winds were light (i.e., maximum winds from the surface to 850 hPa were below 20 km h−1), which supports the notion that the diurnal PWV pattern was associated with the daily cycles of local ET and convection/precipitation and was not due to advection. Comparison of AMR PWV with the Canadian GEM model for the growing seasons of 2003 and 2006 indicated that the model error was 3 mm (13%) or more even in the first 12 h, with mean absolute errors ranging from 2 to 3.5 mm and root-mean-square errors from 3 to 4.5 mm over the full 36-h forecast period. It was also found that the 3–9-h forecast period of GEM had better error scores in 2006 than in 2003.
Abstract
Historical tornado events from 1982 to 2020 were documented within Canada’s forested regions using high-resolution satellite imagery. Tornado forest disturbances were identified using a three-step process: 1) detecting, 2) assessing, and 3) dating each event. A grid of 120 km × 120 km boxes was created covering Canada (excluding the extreme north). Of the 484 boxes, 367 were manually searched. Once a long, narrow region of tree damage was detected, it was first cross-referenced with known tornado databases to ensure it was a unique event. Once events were classified as either tornadic or downburst, the coordinates of the start, worst damage, and end locations were documented, as well as the direction of motion, damage indicators, degree of damage, estimated maximum wind speed, and F/EF-scale rating. In total, 231 previously unknown tornadoes were identified. In Ontario, 103 events were discovered, followed by 98 in Quebec, 9 in Manitoba, 6 in Saskatchewan, 9 in Alberta, 5 in British Columbia, and 1 in New Brunswick. The largest number of discovered tornadoes occurred in 2015, and the largest number of strong F2 tornadoes occurred in 2005. Most of the discovered tornadoes occurred in July for both F/EF1 and F/EF2 ratings. Most tornado tracks had widths between 200 and 400 m, and more than 50% of the tornadoes had a pathlength of less than 10 km. Of all the events that were discovered, 125 events could be fully dated, 19 were dated only by month, 41 were dated only by year, and 46 remained undated.
Abstract
Historical tornado events from 1982 to 2020 were documented within Canada’s forested regions using high-resolution satellite imagery. Tornado forest disturbances were identified using a three-step process: 1) detecting, 2) assessing, and 3) dating each event. A grid of 120 km × 120 km boxes was created covering Canada (excluding the extreme north). Of the 484 boxes, 367 were manually searched. Once a long, narrow region of tree damage was detected, it was first cross-referenced with known tornado databases to ensure it was a unique event. Once events were classified as either tornadic or downburst, the coordinates of the start, worst damage, and end locations were documented, as well as the direction of motion, damage indicators, degree of damage, estimated maximum wind speed, and F/EF-scale rating. In total, 231 previously unknown tornadoes were identified. In Ontario, 103 events were discovered, followed by 98 in Quebec, 9 in Manitoba, 6 in Saskatchewan, 9 in Alberta, 5 in British Columbia, and 1 in New Brunswick. The largest number of discovered tornadoes occurred in 2015, and the largest number of strong F2 tornadoes occurred in 2005. Most of the discovered tornadoes occurred in July for both F/EF1 and F/EF2 ratings. Most tornado tracks had widths between 200 and 400 m, and more than 50% of the tornadoes had a pathlength of less than 10 km. Of all the events that were discovered, 125 events could be fully dated, 19 were dated only by month, 41 were dated only by year, and 46 remained undated.
Abstract
This study provides an assessment of changes in the occurrence frequency of four types of adverse-weather (freezing precipitation, blowing snow, fog, and low ceilings) and no-weather (i.e., no precipitation or visibility obscuration) events as observed at 15 Canadian Arctic stations of good hourly weather observations for 1953–2004. The frequency time series were subjected to a homogenization procedure prior to a logistic regression–based trend analysis.
The results show that the frequency of freezing precipitation has increased almost everywhere across the Canadian Arctic since 1953. Rising air temperature in the region has probably resulted in more times that the temperature is suitable for freezing precipitation. On the contrary, the frequency of blowing snow occurrence has decreased significantly in the Canadian Arctic. The decline is most significant in spring. Changes in fog and low ceiling (LC) occurrences have similar patterns and are most (least) significant in summer (autumn). Decreases were identified for both types of events in the eastern region in all seasons. In the southwest, however, the fog frequency has increased significantly in all seasons, while the LC frequency has decreased significantly in spring and summer. The regional mean rate of change in the frequency of the four types of adverse weather was estimated to be 7%–13% per decade.
The frequency of no-weather events has also decreased significantly at most of the 15 sites. The decrease is most significant and extensive in autumn. Comparison with the adverse-weather trends above indicates that the decline in no-weather occurrence (i.e., increase in weather occurrence) is not the result of an increase in blowing snow or fog occurrence; it is largely the result of the increasing frequency of freezing precipitation and, most likely, other types of precipitation as well. This is consistent with the reported increases in precipitation amount and more frequent cyclone activity in the lower Canadian Arctic.
Abstract
This study provides an assessment of changes in the occurrence frequency of four types of adverse-weather (freezing precipitation, blowing snow, fog, and low ceilings) and no-weather (i.e., no precipitation or visibility obscuration) events as observed at 15 Canadian Arctic stations of good hourly weather observations for 1953–2004. The frequency time series were subjected to a homogenization procedure prior to a logistic regression–based trend analysis.
The results show that the frequency of freezing precipitation has increased almost everywhere across the Canadian Arctic since 1953. Rising air temperature in the region has probably resulted in more times that the temperature is suitable for freezing precipitation. On the contrary, the frequency of blowing snow occurrence has decreased significantly in the Canadian Arctic. The decline is most significant in spring. Changes in fog and low ceiling (LC) occurrences have similar patterns and are most (least) significant in summer (autumn). Decreases were identified for both types of events in the eastern region in all seasons. In the southwest, however, the fog frequency has increased significantly in all seasons, while the LC frequency has decreased significantly in spring and summer. The regional mean rate of change in the frequency of the four types of adverse weather was estimated to be 7%–13% per decade.
The frequency of no-weather events has also decreased significantly at most of the 15 sites. The decrease is most significant and extensive in autumn. Comparison with the adverse-weather trends above indicates that the decline in no-weather occurrence (i.e., increase in weather occurrence) is not the result of an increase in blowing snow or fog occurrence; it is largely the result of the increasing frequency of freezing precipitation and, most likely, other types of precipitation as well. This is consistent with the reported increases in precipitation amount and more frequent cyclone activity in the lower Canadian Arctic.
Abstract
Blowing snow has a major impact on transportation and public safety. The goal of this study is to provide an operational technique for forecasting high-impact blowing snow on the Canadian arctic and the Prairie provinces using historical meteorological data. The focus is to provide some guidance as to the probability of reduced visibilities (e.g., less than 1 km) in blowing snow given a forecast wind speed and direction. The wind character associated with blowing snow was examined using a large database consisting of up to 40 yr of hourly observations at 15 locations in the Prairie provinces and at 17 locations in the arctic. Instances of blowing snow were divided into cases with and without concurrent falling snow. The latter group was subdivided by the time since the last snowfall in an attempt to account for aging processes of the snowpack. An empirical scheme was developed that could discriminate conditions that produce significantly reduced visibility in blowing snow using wind speed, air temperature, and time since last snowfall as predictors. This process was evaluated using actual hourly observations to compute the probability of detection, false alarm ratio, credibility, and critical success index. A critical success index as high as 66% was achieved. This technique can be used to give an objective first guess of the likelihood of high-impact blowing snow using common forecast parameters.
Abstract
Blowing snow has a major impact on transportation and public safety. The goal of this study is to provide an operational technique for forecasting high-impact blowing snow on the Canadian arctic and the Prairie provinces using historical meteorological data. The focus is to provide some guidance as to the probability of reduced visibilities (e.g., less than 1 km) in blowing snow given a forecast wind speed and direction. The wind character associated with blowing snow was examined using a large database consisting of up to 40 yr of hourly observations at 15 locations in the Prairie provinces and at 17 locations in the arctic. Instances of blowing snow were divided into cases with and without concurrent falling snow. The latter group was subdivided by the time since the last snowfall in an attempt to account for aging processes of the snowpack. An empirical scheme was developed that could discriminate conditions that produce significantly reduced visibility in blowing snow using wind speed, air temperature, and time since last snowfall as predictors. This process was evaluated using actual hourly observations to compute the probability of detection, false alarm ratio, credibility, and critical success index. A critical success index as high as 66% was achieved. This technique can be used to give an objective first guess of the likelihood of high-impact blowing snow using common forecast parameters.
Abstract
The time series of daily averaged cloud fractions (CFs) collected from different platforms—two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on Terra and Aqua satellites, the National Centers for Environmental Prediction (NCEP) model, a Vaisala 25K laser ceilometer, and ground-based manual observations (manobs)—above the winter camp of the Canadian Arctic Shelf Exchange Study (CASES) field experiment are analyzed in this study. Taking the manobs as standard, the authors conclude that 1) the NCEP products considerably underestimated CFs in spring (e.g., from April to May) and 2) the performance of two MODIS products depends on the variation of solar zenith angle (SZA). Aqua MODIS misrepresents the snow-covered surface as clouds with almost randomly distributed CFs during the dark winter [cos(SZA) < 0], leading to the overestimation of CFs in winter while Terra MODIS has good agreement with manobs. When 0.1 < cos(SZA) < 0.4, both MODIS products regularly misrepresent the snow-covered background as clouds, leading to the significant overestimation of CFs in late winter (February) and early spring (March). When cos(SZA) > 0.4, both MODIS products have good performance in detecting cloud masks over snow backgrounds. If the sky is slightly cloudy, surface-based meteorological observers tend to underestimate cloud amounts when there is a lack of light. Comparing the CFs from Terra and manobs, the authors conclude that this bias can be over 10%. Power spectral analysis and wavelet analysis show three results: 1) High clouds more frequently appear in winter than in spring with periods between 8 and 16 days, indicating their close connection with synoptic events. Current NCEP products can predict this periodicity but have a phase lag. 2) Middle and low clouds are more local and are common in mid- and late spring (April and May) with periods between 2 and 4 days. At the CASES winter and spring field site, the periodicity of high clouds is dominant. 3) The time-scale-dependent correlation coefficients (CCs) between both MODIS products, NCEP and manobs, show that with high frequent CF sampling per day, the CCs are stable when the time scale varies between 1 and 4 days: with Terra MODIS and NCEP, the value is about 0.6; with Aqua MODIS, between 0.4 and 0.5. All CCs get smaller when the time scale increases beyond 8 days: with respect to both MODIS products, the CCs get closer with values between 0.3 and 0.4; with respect to NCEP, the CC dramatically decreases from positive values to negative values, indicating the lack of accuracy in current NCEP cloud schemes.
Abstract
The time series of daily averaged cloud fractions (CFs) collected from different platforms—two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on Terra and Aqua satellites, the National Centers for Environmental Prediction (NCEP) model, a Vaisala 25K laser ceilometer, and ground-based manual observations (manobs)—above the winter camp of the Canadian Arctic Shelf Exchange Study (CASES) field experiment are analyzed in this study. Taking the manobs as standard, the authors conclude that 1) the NCEP products considerably underestimated CFs in spring (e.g., from April to May) and 2) the performance of two MODIS products depends on the variation of solar zenith angle (SZA). Aqua MODIS misrepresents the snow-covered surface as clouds with almost randomly distributed CFs during the dark winter [cos(SZA) < 0], leading to the overestimation of CFs in winter while Terra MODIS has good agreement with manobs. When 0.1 < cos(SZA) < 0.4, both MODIS products regularly misrepresent the snow-covered background as clouds, leading to the significant overestimation of CFs in late winter (February) and early spring (March). When cos(SZA) > 0.4, both MODIS products have good performance in detecting cloud masks over snow backgrounds. If the sky is slightly cloudy, surface-based meteorological observers tend to underestimate cloud amounts when there is a lack of light. Comparing the CFs from Terra and manobs, the authors conclude that this bias can be over 10%. Power spectral analysis and wavelet analysis show three results: 1) High clouds more frequently appear in winter than in spring with periods between 8 and 16 days, indicating their close connection with synoptic events. Current NCEP products can predict this periodicity but have a phase lag. 2) Middle and low clouds are more local and are common in mid- and late spring (April and May) with periods between 2 and 4 days. At the CASES winter and spring field site, the periodicity of high clouds is dominant. 3) The time-scale-dependent correlation coefficients (CCs) between both MODIS products, NCEP and manobs, show that with high frequent CF sampling per day, the CCs are stable when the time scale varies between 1 and 4 days: with Terra MODIS and NCEP, the value is about 0.6; with Aqua MODIS, between 0.4 and 0.5. All CCs get smaller when the time scale increases beyond 8 days: with respect to both MODIS products, the CCs get closer with values between 0.3 and 0.4; with respect to NCEP, the CC dramatically decreases from positive values to negative values, indicating the lack of accuracy in current NCEP cloud schemes.
Abstract
The purpose of this study was to focus on how anomalies in the normalized difference vegetation index (NDVI; a proxy for soil moisture) over the Canadian Prairies can condition the convective boundary layer (CBL) so as to inhibit or facilitate thunderstorm activity while also considering the role of synoptic-scale forcing. This study focused on a census agricultural region (CAR) over central Alberta for which we had observed lightning data (proxy for thunderstorms), remotely sensed NDVI data, and in situ rawinsonde data (to quantify impacts of vegetation vigor on the CBL characteristics) for 11 summers from 1999 to 2009. The authors’ data suggest that the occurrence of lightning over the study area is more likely (and is of longer duration) when storms develop in an environment in which the surface and upper-air synoptic-scale forcing are synchronized. On days when surface forcing and midtropospheric ascent are present, storms are more likely to be triggered when NDVI is much above average, compared to when NDVI is much below average. Additionally, the authors found the response of thunderstorm duration to NDVI anomalies to be asymmetric. That is, the response of lightning duration to anomalies in NDVI is marked when NDVI is below average but is not necessarily discernible when NDVI is above average. The authors propose a conceptual model, based largely on observations, that integrates all of the above findings to describe how a reduction in vegetation vigor—in response to soil moisture deficits—modulates the partitioning of available energy into sensible and latent heat fluxes at the surface, thereby modulating lifting condensation level heights, which in turn affect lightning activity.
Abstract
The purpose of this study was to focus on how anomalies in the normalized difference vegetation index (NDVI; a proxy for soil moisture) over the Canadian Prairies can condition the convective boundary layer (CBL) so as to inhibit or facilitate thunderstorm activity while also considering the role of synoptic-scale forcing. This study focused on a census agricultural region (CAR) over central Alberta for which we had observed lightning data (proxy for thunderstorms), remotely sensed NDVI data, and in situ rawinsonde data (to quantify impacts of vegetation vigor on the CBL characteristics) for 11 summers from 1999 to 2009. The authors’ data suggest that the occurrence of lightning over the study area is more likely (and is of longer duration) when storms develop in an environment in which the surface and upper-air synoptic-scale forcing are synchronized. On days when surface forcing and midtropospheric ascent are present, storms are more likely to be triggered when NDVI is much above average, compared to when NDVI is much below average. Additionally, the authors found the response of thunderstorm duration to NDVI anomalies to be asymmetric. That is, the response of lightning duration to anomalies in NDVI is marked when NDVI is below average but is not necessarily discernible when NDVI is above average. The authors propose a conceptual model, based largely on observations, that integrates all of the above findings to describe how a reduction in vegetation vigor—in response to soil moisture deficits—modulates the partitioning of available energy into sensible and latent heat fluxes at the surface, thereby modulating lifting condensation level heights, which in turn affect lightning activity.
Abstract
Linkages between the terrestrial ecosystem and precipitation play a critical role in regulating regional weather and climate. These linkages can manifest themselves as positive or negative feedback loops, which may either favor or inhibit the triggering and intensity of thunderstorms. Although the Canadian Prairies terrestrial system has been identified as having the potential to exert a detectable influence on convective precipitation during the warm season, little work has been done in this area using in situ observations.
The authors present findings from a novel study designed to explore linkages between the normalized difference vegetation index (NDVI) and lightning duration (DUR) from the Canadian Lightning Detection Network for 38 census agricultural regions (CARs) on the Canadian Prairies. Statistics Canada divides the prairie agricultural zone into CARs (polygons of varying size and shape) for the purpose of calculating agricultural statistics. Here, DUR is used as a proxy for thunderstorm activity. Statistical analyses were undertaken for 38 CARs for summers [June–August (JJA)] between 1999 and 2008. Specifically, coefficients of determination were calculated between pairs of standardized anomalies of DUR and NDVI by season and by month. Correlations were also calculated for CARs grouped by size and/or magnitude of the NDVI anomalies.
The main findings are as follows: 1) JJA lightning activity is overwhelmingly below average within larger dry areas (i.e., areas with below-average NDVI); that is, the linkages between NDVI and DUR increased significantly as both the area and magnitude of the dry anomaly increased. 2) In contrast, CARs with above-average NDVI did not consistently experience above-average lightning activity, regardless of the CAR size. 3) The lower threshold for the length scale of the dry anomalies required to affect the boundary layer sufficiently to reduce lightning activity was found to be approximately 150 km (~18 000 km2). 4) The authors’ analysis suggests that the surface-convection feedback appears to be a real phenomenon, in which drought tends to perpetuate drought with respect to convective storms and associated rainfall, within the limits found in 1) and 3).
Abstract
Linkages between the terrestrial ecosystem and precipitation play a critical role in regulating regional weather and climate. These linkages can manifest themselves as positive or negative feedback loops, which may either favor or inhibit the triggering and intensity of thunderstorms. Although the Canadian Prairies terrestrial system has been identified as having the potential to exert a detectable influence on convective precipitation during the warm season, little work has been done in this area using in situ observations.
The authors present findings from a novel study designed to explore linkages between the normalized difference vegetation index (NDVI) and lightning duration (DUR) from the Canadian Lightning Detection Network for 38 census agricultural regions (CARs) on the Canadian Prairies. Statistics Canada divides the prairie agricultural zone into CARs (polygons of varying size and shape) for the purpose of calculating agricultural statistics. Here, DUR is used as a proxy for thunderstorm activity. Statistical analyses were undertaken for 38 CARs for summers [June–August (JJA)] between 1999 and 2008. Specifically, coefficients of determination were calculated between pairs of standardized anomalies of DUR and NDVI by season and by month. Correlations were also calculated for CARs grouped by size and/or magnitude of the NDVI anomalies.
The main findings are as follows: 1) JJA lightning activity is overwhelmingly below average within larger dry areas (i.e., areas with below-average NDVI); that is, the linkages between NDVI and DUR increased significantly as both the area and magnitude of the dry anomaly increased. 2) In contrast, CARs with above-average NDVI did not consistently experience above-average lightning activity, regardless of the CAR size. 3) The lower threshold for the length scale of the dry anomalies required to affect the boundary layer sufficiently to reduce lightning activity was found to be approximately 150 km (~18 000 km2). 4) The authors’ analysis suggests that the surface-convection feedback appears to be a real phenomenon, in which drought tends to perpetuate drought with respect to convective storms and associated rainfall, within the limits found in 1) and 3).
Abstract
The environment of elevated nocturnal deep convection initiation (CI) on 24 June 2015 is investigated using radiosonde data from the Plains Elevated Convection at Night (PECAN) field experiment and a convection-allowing simulation. Elevated CI occurs around midnight in ascending westerly flow above the northeastern terminus of the nocturnal low-level jet (LLJ) several hundred kilometers poleward of the leading edge of a surface warm front. This CI originates from within preexisting banded altocumulus clouds that are supported by persistent large-scale ascent within the entrance region of a midtropospheric jet streak. Model trajectories calculated backward from convective updraft cores during CI indicate abrupt lifting at the leading edge of the surface front during the late afternoon to altitudes above that of the subsequent southerly LLJ. This air remains significantly subsaturated during northward movement until after several hours of weaker but persistent ascent within the highly elevated westerly airstream during the evening. Unlike in many previous studies of frontal overrunning by the LLJ, strong local drying occurs within the LLJ core. Nevertheless, vertical displacements from persistent mesoscale ascent were sufficient for trajectory air parcels to reach their LFC and sustain deep convection. The mesoscale upward displacement along trajectories is well explained by isentropic upglide associated with frontal overrunning at horizontal distances greater than 100 km from the CI and subsequent mature convection. However, the significant additional mesoscale vertical displacements needed for deep CI to occur in the westerlies above the horizontally convergent ~100-km-wide LLJ terminus region, were associated with local cooling and are not accounted for by steady isentropic upglide.
Abstract
The environment of elevated nocturnal deep convection initiation (CI) on 24 June 2015 is investigated using radiosonde data from the Plains Elevated Convection at Night (PECAN) field experiment and a convection-allowing simulation. Elevated CI occurs around midnight in ascending westerly flow above the northeastern terminus of the nocturnal low-level jet (LLJ) several hundred kilometers poleward of the leading edge of a surface warm front. This CI originates from within preexisting banded altocumulus clouds that are supported by persistent large-scale ascent within the entrance region of a midtropospheric jet streak. Model trajectories calculated backward from convective updraft cores during CI indicate abrupt lifting at the leading edge of the surface front during the late afternoon to altitudes above that of the subsequent southerly LLJ. This air remains significantly subsaturated during northward movement until after several hours of weaker but persistent ascent within the highly elevated westerly airstream during the evening. Unlike in many previous studies of frontal overrunning by the LLJ, strong local drying occurs within the LLJ core. Nevertheless, vertical displacements from persistent mesoscale ascent were sufficient for trajectory air parcels to reach their LFC and sustain deep convection. The mesoscale upward displacement along trajectories is well explained by isentropic upglide associated with frontal overrunning at horizontal distances greater than 100 km from the CI and subsequent mature convection. However, the significant additional mesoscale vertical displacements needed for deep CI to occur in the westerlies above the horizontally convergent ~100-km-wide LLJ terminus region, were associated with local cooling and are not accounted for by steady isentropic upglide.
Abstract
A field study on visibility during Arctic blowing snow events over sea ice in Franklin Bay, Northwest Territories, Canada, was carried out from mid-January to early April 2004 during the Canadian Arctic Shelf Exchange Study (CASES) 2003–04 expedition. Visibilities at two heights, wind and temperature profiles, plus blowing and drifting snow particle flux at several heights were monitored continually during the study period. Good relations between visibility and wind speed were found in individual events of ground blowing snow with coefficients of determination >0.9. Regression equations relating 1.5-m height visibility to 10-m wind speed can be used for predicting visibility with a mean relative error in the range of 19%–32%. Similar regression functions obtained from the data for observed visibility of less than 1 km could predict visibilities more accurately for more extreme visibility reductions and wind speeds (>9.5 m s−1) with mean relative error ranging from 15% to 26%. For the event of ground blowing snow, a simple power law relationship between wind speed and visibility is sufficient for operational purposes. A poorer relationship was observed in the event of blowing snow with concurrent precipitating snow. A theoretical visibility model developed by Pomeroy and Male fit well with observed visibilities if using a mean radius of 50 μm and an alpha value of 10. The predicted visibility had a mean relative error of 30.5% and root-mean-square error of 1.3 km. The observed visibility at 1.5 m had a strong relation with particle counter readings, with an R 2 of 0.92, and was consistent among all events.
Abstract
A field study on visibility during Arctic blowing snow events over sea ice in Franklin Bay, Northwest Territories, Canada, was carried out from mid-January to early April 2004 during the Canadian Arctic Shelf Exchange Study (CASES) 2003–04 expedition. Visibilities at two heights, wind and temperature profiles, plus blowing and drifting snow particle flux at several heights were monitored continually during the study period. Good relations between visibility and wind speed were found in individual events of ground blowing snow with coefficients of determination >0.9. Regression equations relating 1.5-m height visibility to 10-m wind speed can be used for predicting visibility with a mean relative error in the range of 19%–32%. Similar regression functions obtained from the data for observed visibility of less than 1 km could predict visibilities more accurately for more extreme visibility reductions and wind speeds (>9.5 m s−1) with mean relative error ranging from 15% to 26%. For the event of ground blowing snow, a simple power law relationship between wind speed and visibility is sufficient for operational purposes. A poorer relationship was observed in the event of blowing snow with concurrent precipitating snow. A theoretical visibility model developed by Pomeroy and Male fit well with observed visibilities if using a mean radius of 50 μm and an alpha value of 10. The predicted visibility had a mean relative error of 30.5% and root-mean-square error of 1.3 km. The observed visibility at 1.5 m had a strong relation with particle counter readings, with an R 2 of 0.92, and was consistent among all events.
