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Abstract
This study evaluates the role of 1) low cloud condensation nuclei (CCN) conditions and 2) preferred radiative cooling of large cloud drops as compared to small cloud drops, on cloud droplet spectral broadening and subsequent freezing drizzle formation in stably stratified layer clouds. In addition, the sensitivity of freezing drizzle formation to ice initiation is evaluated. The evaluation is performed by simulating cloud formation over a two-dimensional idealized mountain using a detailed microphysical scheme implemented into the National Center for Atmospheric Research–Pennsylvania State University Mesoscale Model version 5. The height and width of the two-dimensional mountain were designed to produce an updraft pattern with extent and magnitude similar to documented freezing drizzle cases. The results of the model simulations were compared to observations and good agreement was found.
The key results of this study are 1) low CCN concentrations lead to rapid formation of freezing drizzle. This occurs due to the broad cloud droplet size distribution formed throughout the cloud in this situation, allowing for rapid broadening of the spectra to the point at which the collision–coalescence process is initiated. 2) Continental clouds can produce freezing drizzle given sufficient depth and time. 3) Radiative cooling of the cloud droplets near cloud top can be effective in broadening an initially continental droplet spectrum toward that of a maritime cloud droplet size distribution. 4) Any mechanism that only broadens the cloud droplet spectra near cloud top, such as radiative cooling, may not act over a sufficiently broad volume of the cloud to produce significant amounts of freezing drizzle. 5) Low ice-crystal concentrations (<0.08 L−1) in the region of freezing drizzle formation is a necessary condition for drizzle formation (from both model and observations). 6) Ice nuclei depletion is a necessary requirement for the formation of freezing drizzle. 7) The maximum cloud water mixing ratio and threshold amount for the onset of drizzle in stably stratified clouds was shown to depend strongly on the CCN concentration. 8) A key factor controlling the formation of freezing drizzle in stratified clouds is the lifetime of the mesoscale and synoptic conditions and the thickness and length of the cloud.
Abstract
This study evaluates the role of 1) low cloud condensation nuclei (CCN) conditions and 2) preferred radiative cooling of large cloud drops as compared to small cloud drops, on cloud droplet spectral broadening and subsequent freezing drizzle formation in stably stratified layer clouds. In addition, the sensitivity of freezing drizzle formation to ice initiation is evaluated. The evaluation is performed by simulating cloud formation over a two-dimensional idealized mountain using a detailed microphysical scheme implemented into the National Center for Atmospheric Research–Pennsylvania State University Mesoscale Model version 5. The height and width of the two-dimensional mountain were designed to produce an updraft pattern with extent and magnitude similar to documented freezing drizzle cases. The results of the model simulations were compared to observations and good agreement was found.
The key results of this study are 1) low CCN concentrations lead to rapid formation of freezing drizzle. This occurs due to the broad cloud droplet size distribution formed throughout the cloud in this situation, allowing for rapid broadening of the spectra to the point at which the collision–coalescence process is initiated. 2) Continental clouds can produce freezing drizzle given sufficient depth and time. 3) Radiative cooling of the cloud droplets near cloud top can be effective in broadening an initially continental droplet spectrum toward that of a maritime cloud droplet size distribution. 4) Any mechanism that only broadens the cloud droplet spectra near cloud top, such as radiative cooling, may not act over a sufficiently broad volume of the cloud to produce significant amounts of freezing drizzle. 5) Low ice-crystal concentrations (<0.08 L−1) in the region of freezing drizzle formation is a necessary condition for drizzle formation (from both model and observations). 6) Ice nuclei depletion is a necessary requirement for the formation of freezing drizzle. 7) The maximum cloud water mixing ratio and threshold amount for the onset of drizzle in stably stratified clouds was shown to depend strongly on the CCN concentration. 8) A key factor controlling the formation of freezing drizzle in stratified clouds is the lifetime of the mesoscale and synoptic conditions and the thickness and length of the cloud.
Abstract
This paper investigates the relationships between short-term convective mode evolution, the orientations of vertical shear and mean wind vectors with respect to the initiating synoptic boundary, the motion of the boundary, and the role of forcing for ascent. The dominant mode of storms (linear, mixed mode, and discrete) was noted 3 h after convective initiation along cold fronts, drylines, or prefrontal troughs. Various shear and mean wind vector orientations relative to the boundary were calculated near the time of initiation. Results indicate a statistical correlation between storm mode at 3 h, the normal components of cloud-layer and deep-layer shear vectors, the boundary-relative mean cloud-layer wind vector, and the type of initiating boundary. Thunderstorms, most of which were initially discrete, tended to evolve more quickly into lines or mixed modes when the normal components of the shear vectors and boundary-relative mean cloud-layer wind vectors were small. There was a tendency for storms to remain discrete for larger normal shear and mean wind components. Smaller normal components of mean cloud-layer wind were associated with a greater likelihood that storms would remain within the zone of linear forcing along the boundary for longer time periods, thereby increasing the potential for upscale linear growth. The residence time of storms along the boundary is also dependent on the speed of the boundary. It was found that the boundary-relative normal component of the mean cloud-layer wind better discriminates between mode types than does simply the ground-relative normal component. The influence of mesoscale forcing for ascent and type of boundary on mode evolution was also investigated. As expected, it was found that the magnitude and nature of the forcing play a role in how storms evolve. For instance, strong linear low-level convergence often contributes to rapid upscale linear growth, especially if the boundary motion relative to the mean cloud-layer wind prevents storms from moving away from the boundary shortly after initiation. In summary, results from this study indicate that, for storms initiated along a synoptic boundary, convective mode evolution is modulated primarily by the residence time of storms within the zone of linear forcing, the nature and magnitude of linear forcing, and secondarily by the normal component of the cloud-layer shear.
Abstract
This paper investigates the relationships between short-term convective mode evolution, the orientations of vertical shear and mean wind vectors with respect to the initiating synoptic boundary, the motion of the boundary, and the role of forcing for ascent. The dominant mode of storms (linear, mixed mode, and discrete) was noted 3 h after convective initiation along cold fronts, drylines, or prefrontal troughs. Various shear and mean wind vector orientations relative to the boundary were calculated near the time of initiation. Results indicate a statistical correlation between storm mode at 3 h, the normal components of cloud-layer and deep-layer shear vectors, the boundary-relative mean cloud-layer wind vector, and the type of initiating boundary. Thunderstorms, most of which were initially discrete, tended to evolve more quickly into lines or mixed modes when the normal components of the shear vectors and boundary-relative mean cloud-layer wind vectors were small. There was a tendency for storms to remain discrete for larger normal shear and mean wind components. Smaller normal components of mean cloud-layer wind were associated with a greater likelihood that storms would remain within the zone of linear forcing along the boundary for longer time periods, thereby increasing the potential for upscale linear growth. The residence time of storms along the boundary is also dependent on the speed of the boundary. It was found that the boundary-relative normal component of the mean cloud-layer wind better discriminates between mode types than does simply the ground-relative normal component. The influence of mesoscale forcing for ascent and type of boundary on mode evolution was also investigated. As expected, it was found that the magnitude and nature of the forcing play a role in how storms evolve. For instance, strong linear low-level convergence often contributes to rapid upscale linear growth, especially if the boundary motion relative to the mean cloud-layer wind prevents storms from moving away from the boundary shortly after initiation. In summary, results from this study indicate that, for storms initiated along a synoptic boundary, convective mode evolution is modulated primarily by the residence time of storms within the zone of linear forcing, the nature and magnitude of linear forcing, and secondarily by the normal component of the cloud-layer shear.
Abstract
Recent NOAA Hazardous Weather Testbed Spring Forecasting Experiments have emphasized the sensitivity of forecast sensible weather fields to how boundary layer processes are represented in the Weather Research and Forecasting (WRF) Model. Thus, since 2010, the Center for Analysis and Prediction of Storms has configured at least three members of their WRF-based Storm-Scale Ensemble Forecast (SSEF) system specifically for examination of sensitivities to parameterizations of turbulent mixing, including the Mellor–Yamada–Janjić (MYJ); quasi-normal scale elimination (QNSE); Asymmetrical Convective Model, version 2 (ACM2); Yonsei University (YSU); and Mellor–Yamada–Nakanishi–Niino (MYNN) schemes (hereafter PBL members). In postexperiment analyses, significant differences in forecast boundary layer structure and evolution have been observed, and for preconvective environments MYNN was found to have a superior depiction of temperature and moisture profiles. This study evaluates the 24-h forecast dryline positions in the SSEF system PBL members during the period April–June 2010–12 and documents sensitivities of the vertical distribution of thermodynamic and kinematic variables in near-dryline environments. Main results include the following. Despite having superior temperature and moisture profiles, as indicated by a previous study, MYNN was one of the worst-performing PBL members, exhibiting large eastward errors in forecast dryline position. During April–June 2010–11, a dry bias in the North American Mesoscale Forecast System (NAM) initial conditions largely contributed to eastward dryline errors in all PBL members. An upgrade to the NAM and assimilation system in October 2011 apparently fixed the dry bias, reducing eastward errors. Large sensitivities of CAPE and low-level shear to the PBL schemes were found, which were largest between 1.0° and 3.0° to the east of drylines. Finally, modifications to YSU to decrease vertical mixing and mitigate its warm and dry bias greatly reduced eastward dryline errors.
Abstract
Recent NOAA Hazardous Weather Testbed Spring Forecasting Experiments have emphasized the sensitivity of forecast sensible weather fields to how boundary layer processes are represented in the Weather Research and Forecasting (WRF) Model. Thus, since 2010, the Center for Analysis and Prediction of Storms has configured at least three members of their WRF-based Storm-Scale Ensemble Forecast (SSEF) system specifically for examination of sensitivities to parameterizations of turbulent mixing, including the Mellor–Yamada–Janjić (MYJ); quasi-normal scale elimination (QNSE); Asymmetrical Convective Model, version 2 (ACM2); Yonsei University (YSU); and Mellor–Yamada–Nakanishi–Niino (MYNN) schemes (hereafter PBL members). In postexperiment analyses, significant differences in forecast boundary layer structure and evolution have been observed, and for preconvective environments MYNN was found to have a superior depiction of temperature and moisture profiles. This study evaluates the 24-h forecast dryline positions in the SSEF system PBL members during the period April–June 2010–12 and documents sensitivities of the vertical distribution of thermodynamic and kinematic variables in near-dryline environments. Main results include the following. Despite having superior temperature and moisture profiles, as indicated by a previous study, MYNN was one of the worst-performing PBL members, exhibiting large eastward errors in forecast dryline position. During April–June 2010–11, a dry bias in the North American Mesoscale Forecast System (NAM) initial conditions largely contributed to eastward dryline errors in all PBL members. An upgrade to the NAM and assimilation system in October 2011 apparently fixed the dry bias, reducing eastward errors. Large sensitivities of CAPE and low-level shear to the PBL schemes were found, which were largest between 1.0° and 3.0° to the east of drylines. Finally, modifications to YSU to decrease vertical mixing and mitigate its warm and dry bias greatly reduced eastward dryline errors.
Abstract
This paper assesses the influence of radiative forcing and latent heating on the development and maintenance of cloud-top generating cells (GCs) in high-resolution idealized Weather Research and Forecasting Model simulations with initial conditions representative of the vertical structure of a cyclone observed during the Profiling of Winter Storms campaign. Simulated GC kinematics, structure, and ice mass are shown to compare well quantitatively with Wyoming Cloud Radar, cloud probe, and other observations. Sensitivity to radiative forcing was assessed in simulations with longwave-only (nighttime), longwave-and-shortwave (daytime), and no-radiation parameterizations. The domain-averaged longwave cooling rate exceeded 0.50 K h−1 near cloud top, with maxima greater than 2.00 K h−1 atop GCs. Shortwave warming was weaker by comparison, with domain-averaged values of 0.10–0.20 K h−1 and maxima of 0.50 K h−1 atop GCs. The stabilizing influence of cloud-top shortwave warming was evident in the daytime simulation’s vertical velocity spectrum, with 1% of the updrafts in the 6.0–8.0-km layer exceeding 1.20 m s−1, compared to 1.80 m s−1 for the nighttime simulation. GCs regenerate in simulations with radiative forcing after the initial instability is released but do not persist when radiation is not parameterized, demonstrating that radiative forcing is critical to GC maintenance under the thermodynamic and vertical wind shear conditions in this cyclone. GCs are characterized by high ice supersaturation (RHice > 150%) and latent heating rates frequently in excess of 2.00 K h−1 collocated with vertical velocity maxima. Ice precipitation mixing ratio maxima of greater than 0.15 g kg−1 were common within GCs in the daytime and nighttime simulations.
Abstract
This paper assesses the influence of radiative forcing and latent heating on the development and maintenance of cloud-top generating cells (GCs) in high-resolution idealized Weather Research and Forecasting Model simulations with initial conditions representative of the vertical structure of a cyclone observed during the Profiling of Winter Storms campaign. Simulated GC kinematics, structure, and ice mass are shown to compare well quantitatively with Wyoming Cloud Radar, cloud probe, and other observations. Sensitivity to radiative forcing was assessed in simulations with longwave-only (nighttime), longwave-and-shortwave (daytime), and no-radiation parameterizations. The domain-averaged longwave cooling rate exceeded 0.50 K h−1 near cloud top, with maxima greater than 2.00 K h−1 atop GCs. Shortwave warming was weaker by comparison, with domain-averaged values of 0.10–0.20 K h−1 and maxima of 0.50 K h−1 atop GCs. The stabilizing influence of cloud-top shortwave warming was evident in the daytime simulation’s vertical velocity spectrum, with 1% of the updrafts in the 6.0–8.0-km layer exceeding 1.20 m s−1, compared to 1.80 m s−1 for the nighttime simulation. GCs regenerate in simulations with radiative forcing after the initial instability is released but do not persist when radiation is not parameterized, demonstrating that radiative forcing is critical to GC maintenance under the thermodynamic and vertical wind shear conditions in this cyclone. GCs are characterized by high ice supersaturation (RHice > 150%) and latent heating rates frequently in excess of 2.00 K h−1 collocated with vertical velocity maxima. Ice precipitation mixing ratio maxima of greater than 0.15 g kg−1 were common within GCs in the daytime and nighttime simulations.
Abstract
Recent field observations suggest that cloud-top precipitation generating cells (GCs) are ubiquitous in the warm-frontal and comma-head regions of midlatitude winter cyclones. The presence of fallstreaks emanating from the GCs and their persistence either to the surface or until merging into precipitation bands suggests that GCs are a critical component of the precipitation process in these cyclones. This paper is the second part of a three-part series that investigates the dynamics of GCs through very-high-resolution idealized Weather Research and Forecasting (WRF) Model simulations. This paper assesses the role of cloud-top instability paired with nighttime, daytime, or no radiative forcing on the development and maintenance (or lack) of GCs. Under initially unstable conditions at cloud top, GCs develop regardless of radiative forcing but only persist clearly with radiative forcing. Cloud-top destabilization due to longwave cooling leads to development of GCs even under initially neutral and stable conditions, providing a physical explanation for the observed ubiquity of GCs atop winter cyclones. GCs do not develop in initially stable simulations with no radiation. Decreased range in vertical velocity spectra under daytime radiative forcing is consistent with offset of the destabilizing influence of longwave cooling by shortwave heating.
Abstract
Recent field observations suggest that cloud-top precipitation generating cells (GCs) are ubiquitous in the warm-frontal and comma-head regions of midlatitude winter cyclones. The presence of fallstreaks emanating from the GCs and their persistence either to the surface or until merging into precipitation bands suggests that GCs are a critical component of the precipitation process in these cyclones. This paper is the second part of a three-part series that investigates the dynamics of GCs through very-high-resolution idealized Weather Research and Forecasting (WRF) Model simulations. This paper assesses the role of cloud-top instability paired with nighttime, daytime, or no radiative forcing on the development and maintenance (or lack) of GCs. Under initially unstable conditions at cloud top, GCs develop regardless of radiative forcing but only persist clearly with radiative forcing. Cloud-top destabilization due to longwave cooling leads to development of GCs even under initially neutral and stable conditions, providing a physical explanation for the observed ubiquity of GCs atop winter cyclones. GCs do not develop in initially stable simulations with no radiation. Decreased range in vertical velocity spectra under daytime radiative forcing is consistent with offset of the destabilizing influence of longwave cooling by shortwave heating.
Abstract
Cloud-top generating cells (GCs) are a common feature atop stratiform clouds within the comma head of winter cyclones. The dynamics of cloud-top GCs are investigated using very high-resolution idealized WRF Model simulations to examine the role of shear in modulating the structure and intensity of GCs. Simulations were run for the same combinations of radiative forcing and instability as in of this series, but with six different shear profiles ranging from 0 to 10 m s−1 km−1 within the layer encompassing the GCs.
The primary role of shear was to modulate the organization of GCs, which organized as closed convective cells in simulations with radiative forcing and no shear. In simulations with shear and radiative forcing, GCs organized in linear streets parallel to the wind. No GCs developed in the initially stable simulations with no radiative forcing. In the initially unstable and neutral simulations with no radiative forcing or shear, GCs were exceptionally weak, with no clear organization. In moderate-shear (Δu/Δz = 2, 4 m s−1 km−1) simulations with no radiative forcing, linear organization of the weak cells was apparent, but this organization was less coherent in simulations with high shear (Δu/Δz = 6, 8, 10 m s−1 km−1). The intensity of the updrafts was primarily related to the mode of radiative forcing but was modulated by shear. The more intense GCs in nighttime simulations were either associated with no shear (closed convective cells) or strong shear (linear streets). Updrafts within GCs under conditions with radiative forcing were typically ~1–2 m s−1 with maximum values < 4 m s−1.
Abstract
Cloud-top generating cells (GCs) are a common feature atop stratiform clouds within the comma head of winter cyclones. The dynamics of cloud-top GCs are investigated using very high-resolution idealized WRF Model simulations to examine the role of shear in modulating the structure and intensity of GCs. Simulations were run for the same combinations of radiative forcing and instability as in of this series, but with six different shear profiles ranging from 0 to 10 m s−1 km−1 within the layer encompassing the GCs.
The primary role of shear was to modulate the organization of GCs, which organized as closed convective cells in simulations with radiative forcing and no shear. In simulations with shear and radiative forcing, GCs organized in linear streets parallel to the wind. No GCs developed in the initially stable simulations with no radiative forcing. In the initially unstable and neutral simulations with no radiative forcing or shear, GCs were exceptionally weak, with no clear organization. In moderate-shear (Δu/Δz = 2, 4 m s−1 km−1) simulations with no radiative forcing, linear organization of the weak cells was apparent, but this organization was less coherent in simulations with high shear (Δu/Δz = 6, 8, 10 m s−1 km−1). The intensity of the updrafts was primarily related to the mode of radiative forcing but was modulated by shear. The more intense GCs in nighttime simulations were either associated with no shear (closed convective cells) or strong shear (linear streets). Updrafts within GCs under conditions with radiative forcing were typically ~1–2 m s−1 with maximum values < 4 m s−1.
Abstract
Climate change is expected to accelerate the hydrologic cycle, increase the fraction of precipitation that is rain, and enhance snowpack melting. The enhanced hydrological cycle is also expected to increase snowfall amounts due to increased moisture availability. These processes are examined in this paper in the Colorado Headwaters region through the use of a coupled high-resolution climate–runoff model. Four high-resolution simulations of annual snowfall over Colorado are conducted. The simulations are verified using Snowpack Telemetry (SNOTEL) data. Results are then presented regarding the grid spacing needed for appropriate simulation of snowfall. Finally, climate sensitivity is explored using a pseudo–global warming approach. The results show that the proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing and parameterizations. The pseudo–global warming simulations indicate enhanced snowfall on the order of 10%–25% over the Colorado Headwaters region, with the enhancement being less in the core headwaters region due to the topographic reduction of precipitation upstream of the region (rain-shadow effect). The main climate change impacts are in the enhanced melting at the lower-elevation bound of the snowpack and the increased snowfall at higher elevations. The changes in peak snow mass are generally near zero due to these two compensating effects, and simulated wintertime total runoff is above current levels. The 1 April snow water equivalent (SWE) is reduced by 25% in the warmer climate, and the date of maximum SWE occurs 2–17 days prior to current climate results, consistent with previous studies.
Abstract
Climate change is expected to accelerate the hydrologic cycle, increase the fraction of precipitation that is rain, and enhance snowpack melting. The enhanced hydrological cycle is also expected to increase snowfall amounts due to increased moisture availability. These processes are examined in this paper in the Colorado Headwaters region through the use of a coupled high-resolution climate–runoff model. Four high-resolution simulations of annual snowfall over Colorado are conducted. The simulations are verified using Snowpack Telemetry (SNOTEL) data. Results are then presented regarding the grid spacing needed for appropriate simulation of snowfall. Finally, climate sensitivity is explored using a pseudo–global warming approach. The results show that the proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing and parameterizations. The pseudo–global warming simulations indicate enhanced snowfall on the order of 10%–25% over the Colorado Headwaters region, with the enhancement being less in the core headwaters region due to the topographic reduction of precipitation upstream of the region (rain-shadow effect). The main climate change impacts are in the enhanced melting at the lower-elevation bound of the snowpack and the increased snowfall at higher elevations. The changes in peak snow mass are generally near zero due to these two compensating effects, and simulated wintertime total runoff is above current levels. The 1 April snow water equivalent (SWE) is reduced by 25% in the warmer climate, and the date of maximum SWE occurs 2–17 days prior to current climate results, consistent with previous studies.
Abstract
This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.
Abstract
This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.
