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Abstract
Wakes behind 2D fences and 3D obstacles are reviewed with special emphasis on reduced mean wind speeds and sheltering effects. Based partly on Perera's study of wakes behind 2D fences, and assuming a Gaussian spread for wakes behind 3D obstacles, a shelter model is proposed and tested. The shelter produced depends on a wake moment coefficient C̃k which appears to be significantly less for 3D obstacles than for 2D fences. The model provides a simple basis on which to “correct” anemometer data for sheltering effects associated with upstream obstacles. Such corrections are an important step in the generation of improved surface wind climatologies and wind atlases.
Abstract
Wakes behind 2D fences and 3D obstacles are reviewed with special emphasis on reduced mean wind speeds and sheltering effects. Based partly on Perera's study of wakes behind 2D fences, and assuming a Gaussian spread for wakes behind 3D obstacles, a shelter model is proposed and tested. The shelter produced depends on a wake moment coefficient C̃k which appears to be significantly less for 3D obstacles than for 2D fences. The model provides a simple basis on which to “correct” anemometer data for sheltering effects associated with upstream obstacles. Such corrections are an important step in the generation of improved surface wind climatologies and wind atlases.
Abstract
Site-specific probability density rainfall forecasts are needed to price insurance premiums, contracts, and other financial products based on precipitation. The spatiotemporal correlations in U.K. daily rainfall amounts over the Thames Valley are investigated and statistical Markov chain generalized linear models (Markov GLM) of rainfall are constructed. The authors compare point and density forecasts of total rainfall amounts, and forecasts of probability of occurrence of rain from these models and from other proposed density models, including persistence, statistical climatology, Markov chain, unconditional gamma and exponential mixture models, and density forecasts from GLM regression postprocessed NCEP numerical ensembles, at up to 45-day forecast horizons. The Markov GLMs and GLM processed ensembles produced skillful 1-day-ahead and short-term point forecasts. Diagnostic checks show all models are well calibrated, but GLMs perform best under the continuous-ranked probability score. For lead times of greater than 1 day, no models were better than the GLM processed ensembles at forecasting occurrence probability. Of all models, the ensembles are best able to account for the serial correlations in rainfall amounts. In conclusion, GLMs for future site-specific density forecasting are recommended. Investigations explain this conclusion in terms of the interaction between the autocorrelation properties of the data and the structure of the models tested.
Abstract
Site-specific probability density rainfall forecasts are needed to price insurance premiums, contracts, and other financial products based on precipitation. The spatiotemporal correlations in U.K. daily rainfall amounts over the Thames Valley are investigated and statistical Markov chain generalized linear models (Markov GLM) of rainfall are constructed. The authors compare point and density forecasts of total rainfall amounts, and forecasts of probability of occurrence of rain from these models and from other proposed density models, including persistence, statistical climatology, Markov chain, unconditional gamma and exponential mixture models, and density forecasts from GLM regression postprocessed NCEP numerical ensembles, at up to 45-day forecast horizons. The Markov GLMs and GLM processed ensembles produced skillful 1-day-ahead and short-term point forecasts. Diagnostic checks show all models are well calibrated, but GLMs perform best under the continuous-ranked probability score. For lead times of greater than 1 day, no models were better than the GLM processed ensembles at forecasting occurrence probability. Of all models, the ensembles are best able to account for the serial correlations in rainfall amounts. In conclusion, GLMs for future site-specific density forecasting are recommended. Investigations explain this conclusion in terms of the interaction between the autocorrelation properties of the data and the structure of the models tested.
Abstract
During the summer of 1959, the Green Glow program, consisting of 26 diffusion experiments during nocturnal inversions, was conducted at the Atomic Energy Commission's Hanford Site near Richland, Wash. The tracer, zinc sulfide, was released near ground level. Samplers were placed at 1.5 m above ground at 533 positions on six sampling arcs, the radii of which were 200 m, 800 m, 1.6 km, 3.2 km, 12.8 km, and 25.6 km. In addition to the ground sampling network, poles or towers were erected at 5 points, 8 deg apart, on each of the 4 inner arcs. Fifteen samplers were mounted on each pole or tower, the top level increasing from 27 m on the 200-m arc to 62 m on the 1.6-km and 3.2-km arcs.
General aspects of the experimental design and tracer technique are discussed along with terrain characteristics and meteorological conditions pertinent to these experiments. Experimental results are presented showing the increase in horizontal plume width and decrease of maximum exposure with distance from the source. An analysis of the area enclosed within a given exposure isopleth is summarized. The effect of significant wind direction shear on the vertical distributions of exposure is discussed. Results from the Green Glow experiments are compared with those from earlier diffusion experiments at O'Neil, Nebr., and later experiments at Hanford.
Abstract
During the summer of 1959, the Green Glow program, consisting of 26 diffusion experiments during nocturnal inversions, was conducted at the Atomic Energy Commission's Hanford Site near Richland, Wash. The tracer, zinc sulfide, was released near ground level. Samplers were placed at 1.5 m above ground at 533 positions on six sampling arcs, the radii of which were 200 m, 800 m, 1.6 km, 3.2 km, 12.8 km, and 25.6 km. In addition to the ground sampling network, poles or towers were erected at 5 points, 8 deg apart, on each of the 4 inner arcs. Fifteen samplers were mounted on each pole or tower, the top level increasing from 27 m on the 200-m arc to 62 m on the 1.6-km and 3.2-km arcs.
General aspects of the experimental design and tracer technique are discussed along with terrain characteristics and meteorological conditions pertinent to these experiments. Experimental results are presented showing the increase in horizontal plume width and decrease of maximum exposure with distance from the source. An analysis of the area enclosed within a given exposure isopleth is summarized. The effect of significant wind direction shear on the vertical distributions of exposure is discussed. Results from the Green Glow experiments are compared with those from earlier diffusion experiments at O'Neil, Nebr., and later experiments at Hanford.
Abstract
A 34% reduction in 10-m wind speeds at Sudbury Airport in Ontario, Canada, over the period 1975–95 appears to be a result of significant changes in the surface roughness of the surrounding area that are due to land restoration and reforestation following historical environmental damage caused by high sulfur dioxide and other industrial emissions. Neither 850-hPa winds extracted from the NCEP–NCAR reanalysis database nor wind measurements at meteorological stations 200 km to the north and 120 km to the east of Sudbury show the same decrease. To assess these changes in observed wind speed quantitatively, geostrophic drag laws were employed to illustrate potential changes in near-surface wind speeds in areas surrounding the airport. A model of the internal boundary layer flow adjustment associated with changes in the surface roughness length between the surroundings and the grass or snow surface of the airport was then applied to compute expected annual average wind speeds at the airport site itself. The estimates obtained with this relatively simple procedure match the observations and confirm that reforestation is likely the major cause of the reduced wind speeds. This finding bears economic, social, and ecological importance, because it will influence wind energy potential, wind loads on structures, wind chill, and home heating costs through to the biology of small- to medium-sized lakes.
Abstract
A 34% reduction in 10-m wind speeds at Sudbury Airport in Ontario, Canada, over the period 1975–95 appears to be a result of significant changes in the surface roughness of the surrounding area that are due to land restoration and reforestation following historical environmental damage caused by high sulfur dioxide and other industrial emissions. Neither 850-hPa winds extracted from the NCEP–NCAR reanalysis database nor wind measurements at meteorological stations 200 km to the north and 120 km to the east of Sudbury show the same decrease. To assess these changes in observed wind speed quantitatively, geostrophic drag laws were employed to illustrate potential changes in near-surface wind speeds in areas surrounding the airport. A model of the internal boundary layer flow adjustment associated with changes in the surface roughness length between the surroundings and the grass or snow surface of the airport was then applied to compute expected annual average wind speeds at the airport site itself. The estimates obtained with this relatively simple procedure match the observations and confirm that reforestation is likely the major cause of the reduced wind speeds. This finding bears economic, social, and ecological importance, because it will influence wind energy potential, wind loads on structures, wind chill, and home heating costs through to the biology of small- to medium-sized lakes.
Abstract
A sensitivity analysis for horizontal localization scale is performed for a numerical weather prediction (NWP) system that uses a 30-second update to refresh a 500-m mesh with observations from a new-generation multi-parameter phased array weather radar (MP-PAWR). Testing is performed using three case studies of convective weather events that occurred during August/September 2019, with the aim to determine the most suitable scale for short-range forecasting of precipitating convective systems and better understand model behavior to a rapid update cycle. Results showed that while the model could provide useful skill at lead times up to 30-minutes, forecasts would consistently over-estimate rainfall and were unable to outperform nowcasts performed with a simple advection model. Using a larger localization scale e.g., 4-km, generated stronger convective and dynamical instability in the analyzes that made conditions more favorable for spurious and intense convection to develop in forecasts. It was demonstrated that lowering the localization scale reduced the size of analysis increments during early cycling, limiting the buildup of these conditions. Improved representation of the localized convection in the initial conditions was suggested as an important step to mitigating this issue in the model.
Abstract
A sensitivity analysis for horizontal localization scale is performed for a numerical weather prediction (NWP) system that uses a 30-second update to refresh a 500-m mesh with observations from a new-generation multi-parameter phased array weather radar (MP-PAWR). Testing is performed using three case studies of convective weather events that occurred during August/September 2019, with the aim to determine the most suitable scale for short-range forecasting of precipitating convective systems and better understand model behavior to a rapid update cycle. Results showed that while the model could provide useful skill at lead times up to 30-minutes, forecasts would consistently over-estimate rainfall and were unable to outperform nowcasts performed with a simple advection model. Using a larger localization scale e.g., 4-km, generated stronger convective and dynamical instability in the analyzes that made conditions more favorable for spurious and intense convection to develop in forecasts. It was demonstrated that lowering the localization scale reduced the size of analysis increments during early cycling, limiting the buildup of these conditions. Improved representation of the localized convection in the initial conditions was suggested as an important step to mitigating this issue in the model.
Abstract
A variable-resolution option has been added within the spectral element (SE) dynamical core of the U.S. Department of Energy (DOE)–NCAR Community Atmosphere Model (CAM). CAM-SE allows for static refinement via conforming quadrilateral meshes on the cubed sphere. This paper investigates the effect of mesh refinement in a climate model by running variable-resolution (var-res) simulations on an aquaplanet. The variable-resolution grid is a 2° (~222 km) grid with a refined patch of 0.25° (~28 km) resolution centered at the equator. Climatology statistics from these simulations are compared to globally uniform runs of 2° and 0.25°.
A significant resolution dependence exists when using the CAM version 4 (CAM4) subgrid physical parameterization package across scales. Global cloud fraction decreases and equatorial precipitation increases with finer horizontal resolution, resulting in drastically different climates between the uniform grid runs and a physics-induced grid imprinting in the var-res simulation. Using CAM version 5 (CAM5) physics significantly improves cloud scaling at different grid resolutions. Additional precipitation at the equator in the high-resolution mesh results in collocated zonally anomalous divergence in both var-res simulations, although this feature is much weaker in CAM5 than CAM4. The equilibrium solution at each grid spacing within the var-res simulations captures the majority of the resolution signal of the corresponding globally uniform grids. The var-res simulation exhibits good performance with respect to wave propagation, including equatorial regions where waves pass through grid transitions. In addition, the increased frequency of high-precipitation events in the refined 0.25° area within the var-res simulations matches that observed in the global 0.25° simulations.
Abstract
A variable-resolution option has been added within the spectral element (SE) dynamical core of the U.S. Department of Energy (DOE)–NCAR Community Atmosphere Model (CAM). CAM-SE allows for static refinement via conforming quadrilateral meshes on the cubed sphere. This paper investigates the effect of mesh refinement in a climate model by running variable-resolution (var-res) simulations on an aquaplanet. The variable-resolution grid is a 2° (~222 km) grid with a refined patch of 0.25° (~28 km) resolution centered at the equator. Climatology statistics from these simulations are compared to globally uniform runs of 2° and 0.25°.
A significant resolution dependence exists when using the CAM version 4 (CAM4) subgrid physical parameterization package across scales. Global cloud fraction decreases and equatorial precipitation increases with finer horizontal resolution, resulting in drastically different climates between the uniform grid runs and a physics-induced grid imprinting in the var-res simulation. Using CAM version 5 (CAM5) physics significantly improves cloud scaling at different grid resolutions. Additional precipitation at the equator in the high-resolution mesh results in collocated zonally anomalous divergence in both var-res simulations, although this feature is much weaker in CAM5 than CAM4. The equilibrium solution at each grid spacing within the var-res simulations captures the majority of the resolution signal of the corresponding globally uniform grids. The var-res simulation exhibits good performance with respect to wave propagation, including equatorial regions where waves pass through grid transitions. In addition, the increased frequency of high-precipitation events in the refined 0.25° area within the var-res simulations matches that observed in the global 0.25° simulations.
Abstract
An algorithm to consistently couple a conservative semi-Lagrangian finite-volume transport scheme with a spectral element (SE) dynamical core is presented. The semi-Lagrangian finite-volume scheme is the Conservative Semi-Lagrangian Multitracer (CSLAM), and the SE dynamical core is the National Center for Atmospheric Research (NCAR)’s Community Atmosphere Model–Spectral Elements (CAM-SE). The primary motivation for coupling CSLAM with CAM-SE is to accelerate tracer transport for multitracer applications. The coupling algorithm result is an inherently mass-conservative, shape-preserving, and consistent (for a constant mixing ratio, the CSLAM solution reduces to the SE solution for air mass) transport that is efficient and accurate. This is achieved by first deriving formulas for diagnosing SE airmass flux through the CSLAM control volume faces. Thereafter, the upstream Lagrangian CSLAM areas are iteratively perturbed to match the diagnosed SE airmass flux, resulting in an equivalent upstream Lagrangian grid that spans the sphere without gaps or overlaps (without using an expensive search algorithm). This new CSLAM algorithm is not specific to airmass fluxes provided by CAM-SE but applies to any airmass fluxes that satisfy the Lipshitz criterion and for which the Courant number is less than one.
Abstract
An algorithm to consistently couple a conservative semi-Lagrangian finite-volume transport scheme with a spectral element (SE) dynamical core is presented. The semi-Lagrangian finite-volume scheme is the Conservative Semi-Lagrangian Multitracer (CSLAM), and the SE dynamical core is the National Center for Atmospheric Research (NCAR)’s Community Atmosphere Model–Spectral Elements (CAM-SE). The primary motivation for coupling CSLAM with CAM-SE is to accelerate tracer transport for multitracer applications. The coupling algorithm result is an inherently mass-conservative, shape-preserving, and consistent (for a constant mixing ratio, the CSLAM solution reduces to the SE solution for air mass) transport that is efficient and accurate. This is achieved by first deriving formulas for diagnosing SE airmass flux through the CSLAM control volume faces. Thereafter, the upstream Lagrangian CSLAM areas are iteratively perturbed to match the diagnosed SE airmass flux, resulting in an equivalent upstream Lagrangian grid that spans the sphere without gaps or overlaps (without using an expensive search algorithm). This new CSLAM algorithm is not specific to airmass fluxes provided by CAM-SE but applies to any airmass fluxes that satisfy the Lipshitz criterion and for which the Courant number is less than one.
Abstract
The influence of anthropogenic aerosols, in the form of ship exhaust effluent, on the microphysics and radiative properties of marine stratocumulus is studied using data gathered from the U.K. Met. Office C-130 and the University of Washington C-131A aircraft during the Monterey Area Ship Track (MAST) experiment in 1994. During the period of MAST, stratocumulus clouds were studied during 11 flights and a wide range of levels of background pollution was observed. The impact of the aerosol emitted from the ships was found to be very dependent on the background cloud microphysical conditions. In clouds of continental influence, the susceptibility of the cloud to further aerosol emissions was low, with a correspondingly weak microphysics and radiation signature in the ship tracks. In clean clouds, changes in droplet concentration of a factor of 2, and reductions in droplet size of up to 50%, were measured. These changes in the microphysics had significant impacts on the cloud radiative forcing. Furthermore, as a result of the cloud droplet size being reduced, in some cases the drizzle was suppressed in the clean clouds, resulting in an increase in liquid water path in the polluted ship track environment. The impact of this combined change in liquid water path and droplet radius was to increase the cloud radiative forcing by up to a factor of 4.
Abstract
The influence of anthropogenic aerosols, in the form of ship exhaust effluent, on the microphysics and radiative properties of marine stratocumulus is studied using data gathered from the U.K. Met. Office C-130 and the University of Washington C-131A aircraft during the Monterey Area Ship Track (MAST) experiment in 1994. During the period of MAST, stratocumulus clouds were studied during 11 flights and a wide range of levels of background pollution was observed. The impact of the aerosol emitted from the ships was found to be very dependent on the background cloud microphysical conditions. In clouds of continental influence, the susceptibility of the cloud to further aerosol emissions was low, with a correspondingly weak microphysics and radiation signature in the ship tracks. In clean clouds, changes in droplet concentration of a factor of 2, and reductions in droplet size of up to 50%, were measured. These changes in the microphysics had significant impacts on the cloud radiative forcing. Furthermore, as a result of the cloud droplet size being reduced, in some cases the drizzle was suppressed in the clean clouds, resulting in an increase in liquid water path in the polluted ship track environment. The impact of this combined change in liquid water path and droplet radius was to increase the cloud radiative forcing by up to a factor of 4.
Abstract
On 14 July 2014 during the Deep Propagating Gravity Wave Experiment (DEEPWAVE), aircraft remote sensing instruments detected large-amplitude gravity wave oscillations within mesospheric airglow and sodium layers at altitudes z ~ 78–83 km downstream of the Auckland Islands, located ~1000 km south of Christchurch, New Zealand. A high-altitude reanalysis and a three-dimensional Fourier gravity wave model are used to investigate the dynamics of this event. At 0700 UTC when the first observations were made, surface flow across the islands’ terrain generated linear three-dimensional wave fields that propagated rapidly to z ~ 78 km, where intense breaking occurred in a narrow layer beneath a zero-wind region at z ~ 83 km. In the following hours, the altitude of weak winds descended under the influence of a large-amplitude migrating semidiurnal tide, leading to intense breaking of these wave fields in subsequent observations starting at 1000 UTC. The linear Fourier model constrained by upstream reanalysis reproduces the salient aspects of observed wave fields, including horizontal wavelengths, phase orientations, temperature and vertical displacement amplitudes, heights and locations of incipient wave breaking, and momentum fluxes. Wave breaking has huge effects on local circulations, with inferred layer-averaged westward flow accelerations of ~350 m s−1 h−1 and dynamical heating rates of ~8 K h−1, supporting recent speculation of important impacts of orographic gravity waves from subantarctic islands on the mean circulation and climate of the middle atmosphere during austral winter.
Abstract
On 14 July 2014 during the Deep Propagating Gravity Wave Experiment (DEEPWAVE), aircraft remote sensing instruments detected large-amplitude gravity wave oscillations within mesospheric airglow and sodium layers at altitudes z ~ 78–83 km downstream of the Auckland Islands, located ~1000 km south of Christchurch, New Zealand. A high-altitude reanalysis and a three-dimensional Fourier gravity wave model are used to investigate the dynamics of this event. At 0700 UTC when the first observations were made, surface flow across the islands’ terrain generated linear three-dimensional wave fields that propagated rapidly to z ~ 78 km, where intense breaking occurred in a narrow layer beneath a zero-wind region at z ~ 83 km. In the following hours, the altitude of weak winds descended under the influence of a large-amplitude migrating semidiurnal tide, leading to intense breaking of these wave fields in subsequent observations starting at 1000 UTC. The linear Fourier model constrained by upstream reanalysis reproduces the salient aspects of observed wave fields, including horizontal wavelengths, phase orientations, temperature and vertical displacement amplitudes, heights and locations of incipient wave breaking, and momentum fluxes. Wave breaking has huge effects on local circulations, with inferred layer-averaged westward flow accelerations of ~350 m s−1 h−1 and dynamical heating rates of ~8 K h−1, supporting recent speculation of important impacts of orographic gravity waves from subantarctic islands on the mean circulation and climate of the middle atmosphere during austral winter.
Abstract
The boundary layer plays a critical role in regulating energy and moisture exchange between the surface and the free atmosphere. However, the boundary layer and lower atmosphere (including shallow flow features and horizontal gradients that influence local weather) are not sampled at time and space scales needed to improve mesoscale analyses that are used to drive short-term model predictions of impactful weather. These data gaps are exasperated in remote and less developed parts of the world where relatively cheap observational capabilities could help immensely. The continued development of small, weather-sensing uncrewed aircraft systems (UAS), coupled with the emergence of an entirely new commercial sector focused on UAS applications, has created novel opportunities for partially filling this observational gap. This article provides an overview of the current level of readiness of small UAS for routinely sensing the lower atmosphere in support of national meteorological and hydrological services (NMHS) around the world. The potential benefits of UAS observations in operational weather forecasting and numerical weather prediction are discussed, as are key considerations that will need to be addressed before their widespread adoption. Finally, potential pathways for implementation of weather-sensing UAS into operations, which hinge on their successful demonstration within collaborative, multi-agency-sponsored testbeds, are suggested.
Abstract
The boundary layer plays a critical role in regulating energy and moisture exchange between the surface and the free atmosphere. However, the boundary layer and lower atmosphere (including shallow flow features and horizontal gradients that influence local weather) are not sampled at time and space scales needed to improve mesoscale analyses that are used to drive short-term model predictions of impactful weather. These data gaps are exasperated in remote and less developed parts of the world where relatively cheap observational capabilities could help immensely. The continued development of small, weather-sensing uncrewed aircraft systems (UAS), coupled with the emergence of an entirely new commercial sector focused on UAS applications, has created novel opportunities for partially filling this observational gap. This article provides an overview of the current level of readiness of small UAS for routinely sensing the lower atmosphere in support of national meteorological and hydrological services (NMHS) around the world. The potential benefits of UAS observations in operational weather forecasting and numerical weather prediction are discussed, as are key considerations that will need to be addressed before their widespread adoption. Finally, potential pathways for implementation of weather-sensing UAS into operations, which hinge on their successful demonstration within collaborative, multi-agency-sponsored testbeds, are suggested.
