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- Author or Editor: Benjamin A. Toms x
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Abstract
A road ice prediction model was developed on the basis of existing data networks with an objective of providing a computationally efficient method of road ice forecasting. Icing risk was separated into three distinct road ice formation mechanisms: hoarfrost, freezing fog, and frozen precipitation. Hoarfrost parameterizations were mostly gathered as presented in previous literature, with modifications incorporated to account for diffusional ice crystal growth-rate complexity. Freezing-fog parameterizations were based on previous fog typological analyses under the assumption that fog formation mechanisms are similar in above- and subfreezing temperatures. Frozen-precipitation parameterizations were primarily unique to the developed model but were also partially based on previous research. Diagnostic analyses use a synthesis of Automated Surface Observing System (ASOS), Automated Weather Observing System (AWOS), and Oklahoma Mesonet data. Prognostic analyses utilize the National Digital Forecast Database (NDFD), a 2.5-km gridded database of forecast meteorological variables output from National Weather Service Weather Forecast Offices. A frequency analysis was performed using the diagnostic parameterizations to determine general road icing risk across the state of Oklahoma. The frequency analyses aligned well with expected temporal maxima and confirmed the viability of the developed parameterizations. Further, a fog typological analysis showed the implemented freezing-fog-formation parameterizations to capture 89% of fog events. These results suggest that the developed model, identified as the Road-Ice Model (RIM), may be implemented as a robust option for analyzing the potential for road ice development based on the background meteorological environment.
Abstract
A road ice prediction model was developed on the basis of existing data networks with an objective of providing a computationally efficient method of road ice forecasting. Icing risk was separated into three distinct road ice formation mechanisms: hoarfrost, freezing fog, and frozen precipitation. Hoarfrost parameterizations were mostly gathered as presented in previous literature, with modifications incorporated to account for diffusional ice crystal growth-rate complexity. Freezing-fog parameterizations were based on previous fog typological analyses under the assumption that fog formation mechanisms are similar in above- and subfreezing temperatures. Frozen-precipitation parameterizations were primarily unique to the developed model but were also partially based on previous research. Diagnostic analyses use a synthesis of Automated Surface Observing System (ASOS), Automated Weather Observing System (AWOS), and Oklahoma Mesonet data. Prognostic analyses utilize the National Digital Forecast Database (NDFD), a 2.5-km gridded database of forecast meteorological variables output from National Weather Service Weather Forecast Offices. A frequency analysis was performed using the diagnostic parameterizations to determine general road icing risk across the state of Oklahoma. The frequency analyses aligned well with expected temporal maxima and confirmed the viability of the developed parameterizations. Further, a fog typological analysis showed the implemented freezing-fog-formation parameterizations to capture 89% of fog events. These results suggest that the developed model, identified as the Road-Ice Model (RIM), may be implemented as a robust option for analyzing the potential for road ice development based on the background meteorological environment.
Abstract
On 10 August 2014, a gravity wave complex generated by convective outflow propagated across much of Oklahoma. The four-dimensional evolution of the wave complex was analyzed using a synthesis of near-surface and vertical observations from the Oklahoma Mesonet and Atmospheric Radiation Measurement (ARM) Southern Great Plains networks. Two Atmospheric Emitted Radiance Interferometers (AERI)—one located at the ARM SGP central facility in Lamont, Oklahoma, and the other in Norman, Oklahoma—were used in concert with a Doppler wind lidar (DWL) in Norman to determine the vertical characteristics of the wave complex. Hydraulic theory was applied to the AERI-derived observations to corroborate the observationally derived wave characteristics.
It was determined that a bore-soliton wave packet initially formed when a density current interacted with a nocturnal surface-based inversion and eventually propagated independently as the density current became diffuse. The soliton propagated within an elevated inversion, which was likely induced by ascending air at the leading edge of the bore head. Bore and density current characteristics derived from the observations agreed with hydraulic theory estimates to within a relative difference of 15%. While the AERI did not accurately resolve the postbore elevated inversion, an error propagation analysis suggested that uncertainties in the AERI and DWL observations had a negligible influence on the findings of this study.
Abstract
On 10 August 2014, a gravity wave complex generated by convective outflow propagated across much of Oklahoma. The four-dimensional evolution of the wave complex was analyzed using a synthesis of near-surface and vertical observations from the Oklahoma Mesonet and Atmospheric Radiation Measurement (ARM) Southern Great Plains networks. Two Atmospheric Emitted Radiance Interferometers (AERI)—one located at the ARM SGP central facility in Lamont, Oklahoma, and the other in Norman, Oklahoma—were used in concert with a Doppler wind lidar (DWL) in Norman to determine the vertical characteristics of the wave complex. Hydraulic theory was applied to the AERI-derived observations to corroborate the observationally derived wave characteristics.
It was determined that a bore-soliton wave packet initially formed when a density current interacted with a nocturnal surface-based inversion and eventually propagated independently as the density current became diffuse. The soliton propagated within an elevated inversion, which was likely induced by ascending air at the leading edge of the bore head. Bore and density current characteristics derived from the observations agreed with hydraulic theory estimates to within a relative difference of 15%. While the AERI did not accurately resolve the postbore elevated inversion, an error propagation analysis suggested that uncertainties in the AERI and DWL observations had a negligible influence on the findings of this study.
Abstract
Cloud-resolving simulations are used to evaluate the importance of topography to the diurnal cycle (DC) of precipitation (DCP) over Luzon, Philippines, and surrounding ocean during the July–August 2016 boreal summer intraseasonal oscillation (BSISO) event. Composites of surface precipitation for each 30-min time increment during the day are made to determine the mean DCP. The mean DCP is computed separately for suppressed and active BSISO conditions and compared across three simulations with varying topography—flat, true, and doubled topographic height. The magnitude of the topographic height helps to dictate the timing, intensity, and location of diurnal precipitation over and near Luzon. For example, the mean DCP in the true topography run peaks 1.5 h later, is broader by 1 h, and has a 9% larger amplitude during active conditions relative to suppressed conditions. By contrast, the flat run mean DCP is earlier and narrower by 0.5 h with a 5% smaller amplitude during active conditions versus suppressed conditions. Within the suppressed or active BSISO conditions, the mean DCP peak and amplitude increase as the topographic height increases. The presence of elevated topography focuses precipitation over the coastal mountains during suppressed conditions, while dictating which side of the domain (i.e., east Luzon and the Philippine Sea vs west Luzon and the South China Sea) more precipitation occurs in during active conditions. These topographic-induced changes are discussed in terms of mechanical and thermodynamic forcing differences between the two large-scale BSISO regimes for the three runs.
Abstract
Cloud-resolving simulations are used to evaluate the importance of topography to the diurnal cycle (DC) of precipitation (DCP) over Luzon, Philippines, and surrounding ocean during the July–August 2016 boreal summer intraseasonal oscillation (BSISO) event. Composites of surface precipitation for each 30-min time increment during the day are made to determine the mean DCP. The mean DCP is computed separately for suppressed and active BSISO conditions and compared across three simulations with varying topography—flat, true, and doubled topographic height. The magnitude of the topographic height helps to dictate the timing, intensity, and location of diurnal precipitation over and near Luzon. For example, the mean DCP in the true topography run peaks 1.5 h later, is broader by 1 h, and has a 9% larger amplitude during active conditions relative to suppressed conditions. By contrast, the flat run mean DCP is earlier and narrower by 0.5 h with a 5% smaller amplitude during active conditions versus suppressed conditions. Within the suppressed or active BSISO conditions, the mean DCP peak and amplitude increase as the topographic height increases. The presence of elevated topography focuses precipitation over the coastal mountains during suppressed conditions, while dictating which side of the domain (i.e., east Luzon and the Philippine Sea vs west Luzon and the South China Sea) more precipitation occurs in during active conditions. These topographic-induced changes are discussed in terms of mechanical and thermodynamic forcing differences between the two large-scale BSISO regimes for the three runs.
Abstract
While the boreal summer Madden–Julian oscillation (MJO) is commonly defined as a planetary-scale disturbance, the convective elements that constitute its cloud dipole exhibit pronounced variability in their morphology. We therefore investigate the relationship between the intraseasonal cloud anomaly of the MJO and the convective elements that populate its interior by simulating a boreal summer MJO event over the Maritime Continent using a cloud-resolving model. A progressive relationship between convective cell morphology and the MJO within the convectively enhanced region of the MJO was identified and characterized as follows: anomalously long-lasting cells in the initial phases, followed by an increased number of cells in the intermediate phases, progressing into more expansive cells in the terminal phases. A progressive relationship does not seem to exist within the convectively suppressed region of the MJO within the simulated domain, however. Within the convectively enhanced region of the MJO, the progressive relationship is partially explained by the evolution of bulk atmospheric characteristics, such as instability and wind shear. Positive midlevel moisture anomalies coincide with anomalously long-lasting convective cells, which is hypothesized to further cascade into an increase in convective cell volume, although variability in the number of convective cells seems to be related to an unidentified variable. This intraseasonal relationship between convective cell morphology and the boreal summer MJO within the Maritime Continent may have broader implications for the large-scale structure and evolution of the MJO, related to both convective moistening and cloud-radiative feedbacks.
Abstract
While the boreal summer Madden–Julian oscillation (MJO) is commonly defined as a planetary-scale disturbance, the convective elements that constitute its cloud dipole exhibit pronounced variability in their morphology. We therefore investigate the relationship between the intraseasonal cloud anomaly of the MJO and the convective elements that populate its interior by simulating a boreal summer MJO event over the Maritime Continent using a cloud-resolving model. A progressive relationship between convective cell morphology and the MJO within the convectively enhanced region of the MJO was identified and characterized as follows: anomalously long-lasting cells in the initial phases, followed by an increased number of cells in the intermediate phases, progressing into more expansive cells in the terminal phases. A progressive relationship does not seem to exist within the convectively suppressed region of the MJO within the simulated domain, however. Within the convectively enhanced region of the MJO, the progressive relationship is partially explained by the evolution of bulk atmospheric characteristics, such as instability and wind shear. Positive midlevel moisture anomalies coincide with anomalously long-lasting convective cells, which is hypothesized to further cascade into an increase in convective cell volume, although variability in the number of convective cells seems to be related to an unidentified variable. This intraseasonal relationship between convective cell morphology and the boreal summer MJO within the Maritime Continent may have broader implications for the large-scale structure and evolution of the MJO, related to both convective moistening and cloud-radiative feedbacks.
Abstract
The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C3LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.
Abstract
The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C3LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.
