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- Author or Editor: Roland Stull x
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Abstract
Three of the atmospheric datasets that were originally used to verity statistical dispersion theory are reevaluated. These datasets are described as well by transilient turbulence theory as by statistical theory over the range of time periods of interest for practical dispersion problems. The limitations of transilient turbulence theory, particularly its inability to duplicate the linear growth of plume-width standard deviation at infinitesimally short times, are also investigated.
Abstract
Three of the atmospheric datasets that were originally used to verity statistical dispersion theory are reevaluated. These datasets are described as well by transilient turbulence theory as by statistical theory over the range of time periods of interest for practical dispersion problems. The limitations of transilient turbulence theory, particularly its inability to duplicate the linear growth of plume-width standard deviation at infinitesimally short times, are also investigated.
Abstract
An equation is presented for wet-bulb temperature as a function of air temperature and relative humidity at standard sea level pressure. It was found as an empirical fit using gene-expression programming. This equation is valid for relative humidities between 5% and 99% and for air temperatures between −20° and 50°C, except for situations having both low humidity and cold temperature. Over the valid range, errors in wet-bulb temperature range from −1° to +0.65°C, with mean absolute error of less than 0.3°C.
Abstract
An equation is presented for wet-bulb temperature as a function of air temperature and relative humidity at standard sea level pressure. It was found as an empirical fit using gene-expression programming. This equation is valid for relative humidities between 5% and 99% and for air temperatures between −20° and 50°C, except for situations having both low humidity and cold temperature. Over the valid range, errors in wet-bulb temperature range from −1° to +0.65°C, with mean absolute error of less than 0.3°C.
To document the inner workings of graduate degree programs, the authors surveyed the 67 American and Canadian universities that grant Doctor of Philosophy (Ph.D.) and/or Master of Science (M.S.) degrees in the atmospheric sciences and related fields. Topics included (a) admission standards such as graduate record exam scores and grade point averages; (b) start-up issues such as course requirements and computer programming skills; (c) M.S. attributes such as thesis length, years until graduation, and thesis versus nonthesis options; (d) Ph.D. procedures such as exam sequences and timing, thesis page length, workplace ethics and teamwork, and development of teaching skills; and (e) employment after graduation. This information could aid university departments in their future program planning.
To document the inner workings of graduate degree programs, the authors surveyed the 67 American and Canadian universities that grant Doctor of Philosophy (Ph.D.) and/or Master of Science (M.S.) degrees in the atmospheric sciences and related fields. Topics included (a) admission standards such as graduate record exam scores and grade point averages; (b) start-up issues such as course requirements and computer programming skills; (c) M.S. attributes such as thesis length, years until graduation, and thesis versus nonthesis options; (d) Ph.D. procedures such as exam sequences and timing, thesis page length, workplace ethics and teamwork, and development of teaching skills; and (e) employment after graduation. This information could aid university departments in their future program planning.
Abstract
An anisotropic surface analysis method based on the mother–daughter (MD) approach has been developed to spread valley station observations to grid points in circuitous steep valleys. In this paper, the MD approach is further refined to allow spreading the mountain-top observations to grid points near neighboring high ridges across valleys. Starting with a 3D first guess from a high-resolution mesoscale model forecast, surface weather observations are assimilated into the boundary layer, and pseudo-upper-air data (interpolated from the coarser-resolution analyses from major operational centers) are assimilated into the free atmosphere. Incremental analysis updating is then used to incorporate the final analysis increments (the difference between the final analysis and the first guess) into a high-resolution numerical weather prediction model. The MD approaches (including one with shoreline refinement) are compared with other objective analysis methods using case examples and daily mesoscale real-time forecast runs during November and December 2004. This study further confirms that the MD approaches outperform the other methods, and that the shoreline refinement achieves better analysis quality than the basic MD approach. The improvement of mountain-top refinement over the basic MD approach increases with the percentage of mountain-top stations, which is usually low. Higher skill in predicting near-surface potential temperature is found when surface information is spread upward throughout the boundary layer instead of at only the bottom model level. The results show improved near-surface forecasts of temperature and humidity that are directly assimilated into the model, but poorer forecasts of near-surface winds and precipitation, which are not assimilated into the model.
Abstract
An anisotropic surface analysis method based on the mother–daughter (MD) approach has been developed to spread valley station observations to grid points in circuitous steep valleys. In this paper, the MD approach is further refined to allow spreading the mountain-top observations to grid points near neighboring high ridges across valleys. Starting with a 3D first guess from a high-resolution mesoscale model forecast, surface weather observations are assimilated into the boundary layer, and pseudo-upper-air data (interpolated from the coarser-resolution analyses from major operational centers) are assimilated into the free atmosphere. Incremental analysis updating is then used to incorporate the final analysis increments (the difference between the final analysis and the first guess) into a high-resolution numerical weather prediction model. The MD approaches (including one with shoreline refinement) are compared with other objective analysis methods using case examples and daily mesoscale real-time forecast runs during November and December 2004. This study further confirms that the MD approaches outperform the other methods, and that the shoreline refinement achieves better analysis quality than the basic MD approach. The improvement of mountain-top refinement over the basic MD approach increases with the percentage of mountain-top stations, which is usually low. Higher skill in predicting near-surface potential temperature is found when surface information is spread upward throughout the boundary layer instead of at only the bottom model level. The results show improved near-surface forecasts of temperature and humidity that are directly assimilated into the model, but poorer forecasts of near-surface winds and precipitation, which are not assimilated into the model.
Abstract
The surface radiation budget of a groomed ski run is important to ski racing. Variables such as snow-surface temperature and liquid water content depend upon the surface radiation budget and are crucial to preparing fast skis. This case study focuses on downwelling longwave radiation, measurements of which were made at a point on a ski run on Whistler Mountain, British Columbia, Canada, throughout a 5-day clear-sky intensive observation period. Tall trees often dominate the horizon of a point on a ski run, and so contributions to total downwelling longwave radiation from trees and sky were treated separately. The “LWRAD” longwave radiative flux model estimated the total downwelling longwave radiation by first calculating thermal contributions from the trees, incorporating regressions for tree temperature that use routine meteorological measurements. Contributions from each azimuth direction were determined with horizon-elevation angles from a theodolite survey. Thermal emissions were weighted accordingly and summed. Sky contributions were estimated using the “libRadtran” radiative transfer model with input of local atmospheric profiles of temperature and humidity and were added to tree emissions. Two clear-sky emissivity parameterizations using screen-height measurements were tested for comparison. LWRAD total downwelling longwave radiation varies between 235 and 265 W m−2 and compares well to measurements, with correlation coefficient squared (r 2) of 0.96. These results can be used to improve estimates of downwelling longwave radiation for a groomed ski run.
Abstract
The surface radiation budget of a groomed ski run is important to ski racing. Variables such as snow-surface temperature and liquid water content depend upon the surface radiation budget and are crucial to preparing fast skis. This case study focuses on downwelling longwave radiation, measurements of which were made at a point on a ski run on Whistler Mountain, British Columbia, Canada, throughout a 5-day clear-sky intensive observation period. Tall trees often dominate the horizon of a point on a ski run, and so contributions to total downwelling longwave radiation from trees and sky were treated separately. The “LWRAD” longwave radiative flux model estimated the total downwelling longwave radiation by first calculating thermal contributions from the trees, incorporating regressions for tree temperature that use routine meteorological measurements. Contributions from each azimuth direction were determined with horizon-elevation angles from a theodolite survey. Thermal emissions were weighted accordingly and summed. Sky contributions were estimated using the “libRadtran” radiative transfer model with input of local atmospheric profiles of temperature and humidity and were added to tree emissions. Two clear-sky emissivity parameterizations using screen-height measurements were tested for comparison. LWRAD total downwelling longwave radiation varies between 235 and 265 W m−2 and compares well to measurements, with correlation coefficient squared (r 2) of 0.96. These results can be used to improve estimates of downwelling longwave radiation for a groomed ski run.
Abstract
A technique is developed to anisotropically spread surface observations in steep valleys. The goal is to create an improved objective analysis for the lowest, terrain-following numerical weather prediction (NWP) model level in mountainous terrain.
The method is a mother–daughter (MD) approach, where the amount of information transferred from one grid point (the mother) to all neighboring grid points (the daughters) depends on elevation differences. The daughters become mothers and further share information with their neighboring grid points. This iterative method allows information to follow valleys around ridges, while reducing spread over the ridge top. The method is further refined to account for land–sea anisotropy.
This approach is tested in the objective analyses of surface potential temperatures over the steep mountainous and coastal terrain of southwestern British Columbia, Canada. Analysis results are compared with other existing schemes using the Advanced Regional Prediction System Data Assimilation System (ADAS). It is found that the MD approach outperforms the other schemes over mountainous and coastal terrain.
Abstract
A technique is developed to anisotropically spread surface observations in steep valleys. The goal is to create an improved objective analysis for the lowest, terrain-following numerical weather prediction (NWP) model level in mountainous terrain.
The method is a mother–daughter (MD) approach, where the amount of information transferred from one grid point (the mother) to all neighboring grid points (the daughters) depends on elevation differences. The daughters become mothers and further share information with their neighboring grid points. This iterative method allows information to follow valleys around ridges, while reducing spread over the ridge top. The method is further refined to account for land–sea anisotropy.
This approach is tested in the objective analyses of surface potential temperatures over the steep mountainous and coastal terrain of southwestern British Columbia, Canada. Analysis results are compared with other existing schemes using the Advanced Regional Prediction System Data Assimilation System (ADAS). It is found that the MD approach outperforms the other schemes over mountainous and coastal terrain.
Abstract
For a boundary layer in free convection where turbulent thermal structures communicate information between the surface and the interior of the mixed layer, it is hypothesized that the surface momentum flux can be parameterized by u
*
2 = bDwBM
ML, the heat flux by
Using data from the BLX83 field experiment in Oklahoma (roughness length: 0.05 m, latitude: 35.03°N, vegetation: mixed pasture and crops, season: spring), the convective transport coefficients are empirically found to be bH = 5.0×10−4 for heat and moisture, and bD =1.83 × 10−3 for momentum. These parameters worked well when tested against independent data from the Australian Koorin field experiment (roughness length: 0.4 m, latitude: 16.27°S, vegetation: uniform sparse trees, season: winter). If these parameterizations and coefficient values are validated for other sites, then convective transport theory could be considered as a candidate to replace the resistance law similarity theory based on profile matching, for conditions of free convection.
The theory is extended to include near-free convective conditions in which mechanical transport associated with. mean wind shear contributes to the still dominant buoyant transport. Scaling variables such as Obukhov length are rewritten using the convective transport relationships, which could potentially be used in similarity theories to compute other surface-layer and mixed-layer quantities.
Abstract
For a boundary layer in free convection where turbulent thermal structures communicate information between the surface and the interior of the mixed layer, it is hypothesized that the surface momentum flux can be parameterized by u
*
2 = bDwBM
ML, the heat flux by
Using data from the BLX83 field experiment in Oklahoma (roughness length: 0.05 m, latitude: 35.03°N, vegetation: mixed pasture and crops, season: spring), the convective transport coefficients are empirically found to be bH = 5.0×10−4 for heat and moisture, and bD =1.83 × 10−3 for momentum. These parameters worked well when tested against independent data from the Australian Koorin field experiment (roughness length: 0.4 m, latitude: 16.27°S, vegetation: uniform sparse trees, season: winter). If these parameterizations and coefficient values are validated for other sites, then convective transport theory could be considered as a candidate to replace the resistance law similarity theory based on profile matching, for conditions of free convection.
The theory is extended to include near-free convective conditions in which mechanical transport associated with. mean wind shear contributes to the still dominant buoyant transport. Scaling variables such as Obukhov length are rewritten using the convective transport relationships, which could potentially be used in similarity theories to compute other surface-layer and mixed-layer quantities.
Abstract
Ensemble temperature forecasts from the North American Ensemble Forecast System were assessed for quality against observations for 10 cities in western North America, for a 7-month period beginning in February 2007. Medium-range probabilistic temperature forecasts can provide information for those economic sectors exposed to temperature-related business risk, such as agriculture, energy, transportation, and retail sales.
The raw ensemble forecasts were postprocessed, incorporating a 14-day moving-average forecast–observation difference, for each ensemble member. This postprocessing reduced the mean error in the sample to 0.6°C or less. It is important to note that the North American Ensemble Forecast System available to the public provides bias-corrected maximum and minimum temperature forecasts.
Root-mean-square-error and Pearson correlation skill scores, applied to the ensemble average forecast, indicate positive, but diminishing, forecast skill (compared to climatology) from 1 to 9 days into the future. The probabilistic forecasts were evaluated using the continuous ranked probability skill score, the relative operating characteristics skill score, and a value assessment incorporating cost–loss determination. The full suite of ensemble members provided skillful forecasts 10–12 days into the future.
A rank histogram analysis was performed to test ensemble spread relative to the observations. Forecasts are underdispersive early in the forecast period, for forecast days 1 and 2. Dispersion improves rapidly but remains somewhat underdispersive through forecast day 6. The forecasts show little or no dispersion beyond forecast day 6. A new skill versus spread diagram is presented that shows the trade-off between higher skill but low spread early in the forecast period and lower skill but better spread later in the forecast period.
Abstract
Ensemble temperature forecasts from the North American Ensemble Forecast System were assessed for quality against observations for 10 cities in western North America, for a 7-month period beginning in February 2007. Medium-range probabilistic temperature forecasts can provide information for those economic sectors exposed to temperature-related business risk, such as agriculture, energy, transportation, and retail sales.
The raw ensemble forecasts were postprocessed, incorporating a 14-day moving-average forecast–observation difference, for each ensemble member. This postprocessing reduced the mean error in the sample to 0.6°C or less. It is important to note that the North American Ensemble Forecast System available to the public provides bias-corrected maximum and minimum temperature forecasts.
Root-mean-square-error and Pearson correlation skill scores, applied to the ensemble average forecast, indicate positive, but diminishing, forecast skill (compared to climatology) from 1 to 9 days into the future. The probabilistic forecasts were evaluated using the continuous ranked probability skill score, the relative operating characteristics skill score, and a value assessment incorporating cost–loss determination. The full suite of ensemble members provided skillful forecasts 10–12 days into the future.
A rank histogram analysis was performed to test ensemble spread relative to the observations. Forecasts are underdispersive early in the forecast period, for forecast days 1 and 2. Dispersion improves rapidly but remains somewhat underdispersive through forecast day 6. The forecasts show little or no dispersion beyond forecast day 6. A new skill versus spread diagram is presented that shows the trade-off between higher skill but low spread early in the forecast period and lower skill but better spread later in the forecast period.
Abstract
A mathematical model to describe the height changes and other characteristics of an inversion base under the influence of surface convection and general subsidence is developed. Inversion interface dynamics and entrainment rates are formulated based on an unstable boundary layer environment of well-organized, plume-like, penetrative convection. The use of unstable boundary layer scaling velocities in describing the convection leads to a natural inclusion of the relevant parameters associated with inversions into this model. It is found that the model does accurately predict realistic rates of inversion rise and of temperature changes for conditions where organized free convection is prevalent.
Abstract
A mathematical model to describe the height changes and other characteristics of an inversion base under the influence of surface convection and general subsidence is developed. Inversion interface dynamics and entrainment rates are formulated based on an unstable boundary layer environment of well-organized, plume-like, penetrative convection. The use of unstable boundary layer scaling velocities in describing the convection leads to a natural inclusion of the relevant parameters associated with inversions into this model. It is found that the model does accurately predict realistic rates of inversion rise and of temperature changes for conditions where organized free convection is prevalent.
