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- Author or Editor: Theodore W. Letcher x
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Abstract
The snow albedo feedback (SAF) is an important climate feature of mountain regions with transient snow cover. In these regions, where patterns of snow cover are largely determined by the underlying terrain, the SAF is highly variable in space and time. Under climate warming, these variations may affect the development of diurnal mountain winds either by altering the thermal contrast between high and low elevations or by increasing boundary layer mixing. In this study, high-resolution regional climate modeling experiments are used to investigate and characterize how the SAF modulates changes in diurnal wind systems in the Rocky Mountains of Colorado and Utah during the spring when SAF strength is at a maximum. Two separate 7-yr pseudo–global warming climate change experiments with differing model configurations are examined. An evaluation of the control simulations against a mesoscale network of observations reveals that the models perform reasonably well at simulating diurnal mountain winds within this region. In the experiment with a strong SAF, there is a clear increase in the strength of daytime upslope flow under climate warming, which leads to increased convergence and cloudiness near the snow margin. Additionally, there is a decrease in the strength of nighttime downslope flows. In the simulation with a weaker SAF, the results are generally similar but less pronounced. In both experiments, an altered thermal contrast, rather than increased boundary layer mixing, appears to be the primary mechanism driving changes in diurnal mountain wind systems in this region.
Abstract
The snow albedo feedback (SAF) is an important climate feature of mountain regions with transient snow cover. In these regions, where patterns of snow cover are largely determined by the underlying terrain, the SAF is highly variable in space and time. Under climate warming, these variations may affect the development of diurnal mountain winds either by altering the thermal contrast between high and low elevations or by increasing boundary layer mixing. In this study, high-resolution regional climate modeling experiments are used to investigate and characterize how the SAF modulates changes in diurnal wind systems in the Rocky Mountains of Colorado and Utah during the spring when SAF strength is at a maximum. Two separate 7-yr pseudo–global warming climate change experiments with differing model configurations are examined. An evaluation of the control simulations against a mesoscale network of observations reveals that the models perform reasonably well at simulating diurnal mountain winds within this region. In the experiment with a strong SAF, there is a clear increase in the strength of daytime upslope flow under climate warming, which leads to increased convergence and cloudiness near the snow margin. Additionally, there is a decrease in the strength of nighttime downslope flows. In the simulation with a weaker SAF, the results are generally similar but less pronounced. In both experiments, an altered thermal contrast, rather than increased boundary layer mixing, appears to be the primary mechanism driving changes in diurnal mountain wind systems in this region.
Abstract
Midlatitude mountain regions are particularly sensitive to climate change because of an active snow albedo feedback (SAF). Here, the SAF is characterized and quantified over the complex terrain of the Colorado Headwaters region using high-resolution regional climate model simulations. A pair of 7-yr control and pseudo-global warming simulations is used to study the regional climate response to a large-scale thermodynamic climate perturbation. Warming is strongly enhanced in regions of snow loss by as much as 5°C. Linear feedback analysis is used to quantify the strength of the SAF within the Headwaters region. The strength of the SAF reaches a maximum value of 4 W m−2 K−1 during April when snow loss coincides with strong incoming solar radiation. Simulations using 4- and 12-km horizontal grid spacing show good agreement in the strength and timing of the SAF, whereas a 36-km simulation shows discrepancies that are tied to differences in snow accumulation and ablation caused by smoother terrain. Energy budget analysis shows that transport by atmospheric circulations acts as a negative feedback to regional warming, damping the effects of the SAF. On the mesoscale, the SAF nonlocally enhances warming in locations with no snow, and enhances snowmelt in locations that do not experience snow cover change. The methods presented here can be used generally to quantify the role of the SAF in simulated regional climate change, illuminating the causes of differences in climate warming between models and regions.
Abstract
Midlatitude mountain regions are particularly sensitive to climate change because of an active snow albedo feedback (SAF). Here, the SAF is characterized and quantified over the complex terrain of the Colorado Headwaters region using high-resolution regional climate model simulations. A pair of 7-yr control and pseudo-global warming simulations is used to study the regional climate response to a large-scale thermodynamic climate perturbation. Warming is strongly enhanced in regions of snow loss by as much as 5°C. Linear feedback analysis is used to quantify the strength of the SAF within the Headwaters region. The strength of the SAF reaches a maximum value of 4 W m−2 K−1 during April when snow loss coincides with strong incoming solar radiation. Simulations using 4- and 12-km horizontal grid spacing show good agreement in the strength and timing of the SAF, whereas a 36-km simulation shows discrepancies that are tied to differences in snow accumulation and ablation caused by smoother terrain. Energy budget analysis shows that transport by atmospheric circulations acts as a negative feedback to regional warming, damping the effects of the SAF. On the mesoscale, the SAF nonlocally enhances warming in locations with no snow, and enhances snowmelt in locations that do not experience snow cover change. The methods presented here can be used generally to quantify the role of the SAF in simulated regional climate change, illuminating the causes of differences in climate warming between models and regions.
Abstract
The Front Range mountain–plain circulation (FRMC) is a large-scale diurnally driven wind system that occurs east of the Colorado Rocky Mountains in the United States and affects the weather both in the Rocky Mountains and Great Plains. As the climate warms, the snow albedo feedback will amplify the warming response in the Rocky Mountains during the spring, increasing the thermal contrast that drives the FRMC. In this study, the authors perform a 7-yr pseudo–global warming (PGW) regional climate change experiment along with an idealized PGW “fixed albedo” experiment to test the sensitivity of the FRMC to the snow albedo feedback (SAF). The authors find a mean increase in the springtime FRMC strength in the PGW experiment that is primarily driven by the snow albedo feedback. Furthermore, interannual variability of changes in FRMC strength is strongly influenced by interannual variability in the SAF. An additional case study experiment configured with a much higher resolution is performed to examine the finescale details of how the SAF and the FRMC interact. This experiment includes a passive tracer to investigate subsequent impacts on pollution transport. The case study reveals that loss of snow cover causes an increase in the strength of the FRMC. Advection by the strengthened FRMC increases the concentration of tracers emitted over the Great Plains in the boundary layer over the Front Range mountains.
Abstract
The Front Range mountain–plain circulation (FRMC) is a large-scale diurnally driven wind system that occurs east of the Colorado Rocky Mountains in the United States and affects the weather both in the Rocky Mountains and Great Plains. As the climate warms, the snow albedo feedback will amplify the warming response in the Rocky Mountains during the spring, increasing the thermal contrast that drives the FRMC. In this study, the authors perform a 7-yr pseudo–global warming (PGW) regional climate change experiment along with an idealized PGW “fixed albedo” experiment to test the sensitivity of the FRMC to the snow albedo feedback (SAF). The authors find a mean increase in the springtime FRMC strength in the PGW experiment that is primarily driven by the snow albedo feedback. Furthermore, interannual variability of changes in FRMC strength is strongly influenced by interannual variability in the SAF. An additional case study experiment configured with a much higher resolution is performed to examine the finescale details of how the SAF and the FRMC interact. This experiment includes a passive tracer to investigate subsequent impacts on pollution transport. The case study reveals that loss of snow cover causes an increase in the strength of the FRMC. Advection by the strengthened FRMC increases the concentration of tracers emitted over the Great Plains in the boundary layer over the Front Range mountains.
Abstract
The Ontario Winter Lake-Effect Systems (OWLeS) field campaign during the winter season of 2013/14 provided unprecedented data with regard to the structure and behavior of long-lake-axis-parallel (LLAP) lake-effect storms. One of the interesting characteristics of LLAP storm bands is their ability to initiate lightning. The OWLeS datasets provide an opportunity to examine more thoroughly the kinematics and microphysics of lake-effect thunder-snowstorms than ever before. The OWLeS facilities and field personnel observed six lake-effect thunderstorms during December–January 2013/14. Most of them produced very little lightning (fewer than six cloud-to-ground strokes or intracloud pulses recorded by the National Lightning Detection Network). The 7 January 2014 storm had over 50 strokes and pulses, however, which resulted in 20 flashes over a 6-h period (0630–1230 UTC), making it the most electrically active storm during the field campaign. Relative to the 18 December 2013 storm, which only had three flashes, the 7 January 2014 case had a deeper boundary layer and greater instability. Also, 45% of the lightning during the 7 January storm was likely due to flashes initiated by wind turbines or other man-made antennas, along with all of the lightning observed during 18 December. No lightning was documented over Lake Ontario, the primary source of instability for these storms.
Abstract
The Ontario Winter Lake-Effect Systems (OWLeS) field campaign during the winter season of 2013/14 provided unprecedented data with regard to the structure and behavior of long-lake-axis-parallel (LLAP) lake-effect storms. One of the interesting characteristics of LLAP storm bands is their ability to initiate lightning. The OWLeS datasets provide an opportunity to examine more thoroughly the kinematics and microphysics of lake-effect thunder-snowstorms than ever before. The OWLeS facilities and field personnel observed six lake-effect thunderstorms during December–January 2013/14. Most of them produced very little lightning (fewer than six cloud-to-ground strokes or intracloud pulses recorded by the National Lightning Detection Network). The 7 January 2014 storm had over 50 strokes and pulses, however, which resulted in 20 flashes over a 6-h period (0630–1230 UTC), making it the most electrically active storm during the field campaign. Relative to the 18 December 2013 storm, which only had three flashes, the 7 January 2014 case had a deeper boundary layer and greater instability. Also, 45% of the lightning during the 7 January storm was likely due to flashes initiated by wind turbines or other man-made antennas, along with all of the lightning observed during 18 December. No lightning was documented over Lake Ontario, the primary source of instability for these storms.
Abstract
The character and causes of elevation-dependent warming (EDW) of surface temperatures are examined in a suite of high-resolution (
Abstract
The character and causes of elevation-dependent warming (EDW) of surface temperatures are examined in a suite of high-resolution (
Abstract
Blowing snow presents substantial risk to human activities by causing severe visibility degradation and snow drifting. Furthermore, blowing snow presents a weather forecast challenge since it is not generally simulated in operational weather forecast models. In this study, we apply a physically based blowing snow model as a diagnostic overlay to output from a reforecast WRF simulation of a significant blowing snow event that occurred over the northern Great Plains of the United States during the winter of 2019. The blowing snow model is coupled to an optics parameterization that estimates the visibility reduction by blowing snow. This overlay is qualitatively evaluated against false color satellite imagery from the GOES-16 operational weather satellite and available surface visibility observations. The WRF-simulated visibility is substantially improved when incorporating blowing snow hydrometeors. Furthermore, the model-simulated plume of blowing snow roughly corresponds to the blowing snow plumes visible in the satellite imagery. Overall, this study illustrates how a blowing snow diagnostic model can aid weather forecasters in making blowing snow visibility forecasts, and demonstrates how the model can be evaluated against satellite imagery.
Abstract
Blowing snow presents substantial risk to human activities by causing severe visibility degradation and snow drifting. Furthermore, blowing snow presents a weather forecast challenge since it is not generally simulated in operational weather forecast models. In this study, we apply a physically based blowing snow model as a diagnostic overlay to output from a reforecast WRF simulation of a significant blowing snow event that occurred over the northern Great Plains of the United States during the winter of 2019. The blowing snow model is coupled to an optics parameterization that estimates the visibility reduction by blowing snow. This overlay is qualitatively evaluated against false color satellite imagery from the GOES-16 operational weather satellite and available surface visibility observations. The WRF-simulated visibility is substantially improved when incorporating blowing snow hydrometeors. Furthermore, the model-simulated plume of blowing snow roughly corresponds to the blowing snow plumes visible in the satellite imagery. Overall, this study illustrates how a blowing snow diagnostic model can aid weather forecasters in making blowing snow visibility forecasts, and demonstrates how the model can be evaluated against satellite imagery.
Abstract
Improved understanding of the influence of orography on lake-effect storms is crucial for weather forecasting in many lake-effect regions. The Tug Hill Plateau of northern New York (hereafter Tug Hill), rising 500 m above eastern Lake Ontario, experiences some of the most intense snowstorms in the world. Herein the authors investigate the enhancement of lake-effect snowfall over Tug Hill during IOP2b of the Ontario Winter Lake-effect Systems (OWLeS) field campaign. During the 24-h study period, total liquid precipitation equivalent along the axis of maximum precipitation increased from 33.5 mm at a lowland (145 m MSL) site to 62.5 mm at an upland (385 m MSL) site, the latter yielding 101.5 cm of snow. However, the ratio of upland to lowland precipitation, or orographic ratio, varied with the mode of lake-effect precipitation. Strongly organized long-lake-axis parallel bands, some of which formed in association with the approach or passage of upper-level short-wave troughs, produced the highest precipitation rates but the smallest orographic ratios. Within these bands, radar echoes were deepest and strongest over Lake Ontario and the coastal lowlands and decreased in depth and median intensity over Tug Hill. In contrast, nonbanded broad-coverage periods exhibited the smallest precipitation rates and the largest orographic ratios, the latter reflecting an increase in the coverage and frequency of radar echoes over Tug Hill. These findings should aid operational forecasts and, given the predominance of broad-coverage lake-effect periods during the cool season, help explain the climatological snowfall maximum found over the Tug Hill Plateau.
Abstract
Improved understanding of the influence of orography on lake-effect storms is crucial for weather forecasting in many lake-effect regions. The Tug Hill Plateau of northern New York (hereafter Tug Hill), rising 500 m above eastern Lake Ontario, experiences some of the most intense snowstorms in the world. Herein the authors investigate the enhancement of lake-effect snowfall over Tug Hill during IOP2b of the Ontario Winter Lake-effect Systems (OWLeS) field campaign. During the 24-h study period, total liquid precipitation equivalent along the axis of maximum precipitation increased from 33.5 mm at a lowland (145 m MSL) site to 62.5 mm at an upland (385 m MSL) site, the latter yielding 101.5 cm of snow. However, the ratio of upland to lowland precipitation, or orographic ratio, varied with the mode of lake-effect precipitation. Strongly organized long-lake-axis parallel bands, some of which formed in association with the approach or passage of upper-level short-wave troughs, produced the highest precipitation rates but the smallest orographic ratios. Within these bands, radar echoes were deepest and strongest over Lake Ontario and the coastal lowlands and decreased in depth and median intensity over Tug Hill. In contrast, nonbanded broad-coverage periods exhibited the smallest precipitation rates and the largest orographic ratios, the latter reflecting an increase in the coverage and frequency of radar echoes over Tug Hill. These findings should aid operational forecasts and, given the predominance of broad-coverage lake-effect periods during the cool season, help explain the climatological snowfall maximum found over the Tug Hill Plateau.
Abstract
A pronounced snowfall maximum occurs about 30 km downwind of Lake Ontario over the 600-m-high Tug Hill Plateau (hereafter Tug Hill), a region where lake-effect convection is affected by mesoscale forcing associated with landfall and orographic uplift. Profiling radar data from the Ontario Winter Lake-effect Systems field campaign are used to characterize the inland evolution of lake-effect convection that produces the Tug Hill snowfall maximum. Four K-band profiling Micro Rain Radars (MRRs) were aligned in a transect from the Ontario coast onto Tug Hill. Additional observations were provided by an X-band profiling radar (XPR). Analysis is presented of a major lake-effect storm that produced 6.4-cm liquid precipitation equivalent (LPE) snowfall over Tug Hill. This event exhibited strong inland enhancement, with LPE increasing by a factor of 1.9 over 15-km horizontal distance. MRR profiles reveal that this enhancement was not due to increases in the depth or intensity of lake-effect convection. With increasing inland distance, echoes transitioned from a convective toward a stratiform morphology, becoming less intense, more uniform, more frequent, and less turbulent. An inland increase in echo frequency (possibly orographically forced) contributes somewhat to snowfall enhancement. The XPR observations reproduce the basic vertical structure seen by the MRRs while also revealing a suppression of snowfall below 600 m AGL upwind of Tug Hill, possibly associated with subcloud sublimation or hydrometeor advection. Statistics from 29 events demonstrate that the above-described inland evolution of convection is common for lake-effect storms east of Lake Ontario.
Abstract
A pronounced snowfall maximum occurs about 30 km downwind of Lake Ontario over the 600-m-high Tug Hill Plateau (hereafter Tug Hill), a region where lake-effect convection is affected by mesoscale forcing associated with landfall and orographic uplift. Profiling radar data from the Ontario Winter Lake-effect Systems field campaign are used to characterize the inland evolution of lake-effect convection that produces the Tug Hill snowfall maximum. Four K-band profiling Micro Rain Radars (MRRs) were aligned in a transect from the Ontario coast onto Tug Hill. Additional observations were provided by an X-band profiling radar (XPR). Analysis is presented of a major lake-effect storm that produced 6.4-cm liquid precipitation equivalent (LPE) snowfall over Tug Hill. This event exhibited strong inland enhancement, with LPE increasing by a factor of 1.9 over 15-km horizontal distance. MRR profiles reveal that this enhancement was not due to increases in the depth or intensity of lake-effect convection. With increasing inland distance, echoes transitioned from a convective toward a stratiform morphology, becoming less intense, more uniform, more frequent, and less turbulent. An inland increase in echo frequency (possibly orographically forced) contributes somewhat to snowfall enhancement. The XPR observations reproduce the basic vertical structure seen by the MRRs while also revealing a suppression of snowfall below 600 m AGL upwind of Tug Hill, possibly associated with subcloud sublimation or hydrometeor advection. Statistics from 29 events demonstrate that the above-described inland evolution of convection is common for lake-effect storms east of Lake Ontario.
