Search Results
You are looking at 1 - 10 of 14 items for
- Author or Editor: J. Verlinde x
- Refine by Access: All Content x
Abstract
A closed form solution for the collection growth equation as used in bulk microphysical parameterizations is derived. Although the general form is mathematically complex, it can serve as a benchmark for testing a variety of approximations. Two special cases that can immediately be implemented in existing cloud models are also presented. This solution is used to evaluate two commonly used approximations. The effect of the selection of different basis functions is also investigated.
Abstract
A closed form solution for the collection growth equation as used in bulk microphysical parameterizations is derived. Although the general form is mathematically complex, it can serve as a benchmark for testing a variety of approximations. Two special cases that can immediately be implemented in existing cloud models are also presented. This solution is used to evaluate two commonly used approximations. The effect of the selection of different basis functions is also investigated.
Abstract
Controlled cloud seeding experiments were conducted near Bethlehem, South Africa during the summer of 1984–85. The experimental unit was the semi-isolated cumulus congestus cloud. Microphysical measurements were obtained by three instrumented aircraft flying in stacked formation. Radar observations were made by a 5-cm wavelength radar performing volume scans at 5-min intervals. A three-way balanced randomization scheme was used to seed the clouds near the −8°C level with either dry ice pellets, silver iodide pyrotechnics, or a placebo (no-seed) treatment. Strict cloud selection criteria, based on the measurements made during an initial inspection penetration, assured the treatment of clouds in their developing stages as their tops row up through the −10°C level. A total of 60 clouds were chosen and treated.
Using ice crystal measurements, mostly above the seeding level, it was conclusively demonstrated that some cumulus clouds were modified by the injection of either dry ice or silver iodide. High ice concentrations were produced and the evolution of the ice particle size distribution is consistent with a rain enhancement hypothesis involving an artificially induced ice embryo process. However, the liquid water contents decayed rapidly, primarily due to entrainment, and in the majority of the seeded cases precipitation particles formed due to low-density accretion onto aggregates resulting in little or no precipitation at the ground. The dry ice and silver iodide seeded clouds that echoed had significantly higher maximum 1-km average ice concentrations than the placebo clouds, as measured by the research aircraft during the clouds' developing stages.
Approximately 67% of the dry ice-treated clouds, 63% of the silver iodide–treated clouds and 45% of the placebo clouds produced radar echoes >10 dBZ. The dry ice-seeded clouds that echoed had significantly higher maximum cell heights than the placebo cells and the silver iodide-seeded cells. When the test cloud data were stratified according to cloud diameter, a positive association existed between seeding and the number of clouds that echoed. Wider clouds responded more favorably to seeding, presumably because they were affected less by entrainment.
Abstract
Controlled cloud seeding experiments were conducted near Bethlehem, South Africa during the summer of 1984–85. The experimental unit was the semi-isolated cumulus congestus cloud. Microphysical measurements were obtained by three instrumented aircraft flying in stacked formation. Radar observations were made by a 5-cm wavelength radar performing volume scans at 5-min intervals. A three-way balanced randomization scheme was used to seed the clouds near the −8°C level with either dry ice pellets, silver iodide pyrotechnics, or a placebo (no-seed) treatment. Strict cloud selection criteria, based on the measurements made during an initial inspection penetration, assured the treatment of clouds in their developing stages as their tops row up through the −10°C level. A total of 60 clouds were chosen and treated.
Using ice crystal measurements, mostly above the seeding level, it was conclusively demonstrated that some cumulus clouds were modified by the injection of either dry ice or silver iodide. High ice concentrations were produced and the evolution of the ice particle size distribution is consistent with a rain enhancement hypothesis involving an artificially induced ice embryo process. However, the liquid water contents decayed rapidly, primarily due to entrainment, and in the majority of the seeded cases precipitation particles formed due to low-density accretion onto aggregates resulting in little or no precipitation at the ground. The dry ice and silver iodide seeded clouds that echoed had significantly higher maximum 1-km average ice concentrations than the placebo clouds, as measured by the research aircraft during the clouds' developing stages.
Approximately 67% of the dry ice-treated clouds, 63% of the silver iodide–treated clouds and 45% of the placebo clouds produced radar echoes >10 dBZ. The dry ice-seeded clouds that echoed had significantly higher maximum cell heights than the placebo cells and the silver iodide-seeded cells. When the test cloud data were stratified according to cloud diameter, a positive association existed between seeding and the number of clouds that echoed. Wider clouds responded more favorably to seeding, presumably because they were affected less by entrainment.
Abstract
The calibration of the CloudSat spaceborne cloud radar has been thoroughly assessed using very accurate internal link budgets before launch, comparisons with predicted ocean surface backscatter at 94 GHz, direct comparisons with airborne cloud radars, and statistical comparisons with ground-based cloud radars at different locations of the world. It is believed that the calibration of CloudSat is accurate to within 0.5–1 dB. In the present paper it is shown that an approach similar to that used for the statistical comparisons with ground-based radars can now be adopted the other way around to calibrate other ground-based or airborne radars against CloudSat and/or to detect anomalies in long time series of ground-based radar measurements, provided that the calibration of CloudSat is followed up closely (which is the case). The power of using CloudSat as a global radar calibrator is demonstrated using the Atmospheric Radiation Measurement cloud radar data taken at Barrow, Alaska, the cloud radar data from the Cabauw site, Netherlands, and airborne Doppler cloud radar measurements taken along the CloudSat track in the Arctic by the Radar System Airborne (RASTA) cloud radar installed in the French ATR-42 aircraft for the first time. It is found that the Barrow radar data in 2008 are calibrated too high by 9.8 dB, while the Cabauw radar data in 2008 are calibrated too low by 8.0 dB. The calibration of the RASTA airborne cloud radar using direct comparisons with CloudSat agrees well with the expected gains and losses resulting from the change in configuration that required verification of the RASTA calibration.
Abstract
The calibration of the CloudSat spaceborne cloud radar has been thoroughly assessed using very accurate internal link budgets before launch, comparisons with predicted ocean surface backscatter at 94 GHz, direct comparisons with airborne cloud radars, and statistical comparisons with ground-based cloud radars at different locations of the world. It is believed that the calibration of CloudSat is accurate to within 0.5–1 dB. In the present paper it is shown that an approach similar to that used for the statistical comparisons with ground-based radars can now be adopted the other way around to calibrate other ground-based or airborne radars against CloudSat and/or to detect anomalies in long time series of ground-based radar measurements, provided that the calibration of CloudSat is followed up closely (which is the case). The power of using CloudSat as a global radar calibrator is demonstrated using the Atmospheric Radiation Measurement cloud radar data taken at Barrow, Alaska, the cloud radar data from the Cabauw site, Netherlands, and airborne Doppler cloud radar measurements taken along the CloudSat track in the Arctic by the Radar System Airborne (RASTA) cloud radar installed in the French ATR-42 aircraft for the first time. It is found that the Barrow radar data in 2008 are calibrated too high by 9.8 dB, while the Cabauw radar data in 2008 are calibrated too low by 8.0 dB. The calibration of the RASTA airborne cloud radar using direct comparisons with CloudSat agrees well with the expected gains and losses resulting from the change in configuration that required verification of the RASTA calibration.
Abstract
Snow aggregates evolve into a variety of observed shapes and densities. Despite this diversity, models and observational studies employ fractal or Euclidean geometric measures that are assumed universal for all aggregates. This work therefore seeks to improve understanding and representation of snow aggregate geometry and its evolution by characterizing distributions of both observed and Monte Carlo–generated aggregates. Two separate datasets of best-fit ellipsoid estimates derived from Multi-Angle Snowflake Camera (MASC) observations suggest the use of a bivariate beta distribution model for capturing aggregate shapes. Product moments of this model capture shape effects to within 4% of observations. This mathematical model is used along with Monte Carlo simulated aggregates to study how combinations of monomer properties affect aggregate shape evolution. Plate aggregates of any aspect ratio produce a consistent ellipsoid shape evolution whereas thin column aggregates evolve to become more spherical. Thin column aggregates yield fractal dimensions much less than the often-assumed value of 2.0. Ellipsoid densities and fractal analogs of density (lacunarity) are much more variable depending on combinations of monomer size and shape. Simple mathematical scaling relationships can explain the persistent triaxial ellipsoid shapes that appear in both observed and modeled aggregates. Overall, both simulations and observations prove aggregates are rarely oblate. Therefore, the use of the proposed bivariate ellipsoid distribution in models will allow for similar-sized aggregates to exhibit a realistic dispersion of masses and fall speeds.
Abstract
Snow aggregates evolve into a variety of observed shapes and densities. Despite this diversity, models and observational studies employ fractal or Euclidean geometric measures that are assumed universal for all aggregates. This work therefore seeks to improve understanding and representation of snow aggregate geometry and its evolution by characterizing distributions of both observed and Monte Carlo–generated aggregates. Two separate datasets of best-fit ellipsoid estimates derived from Multi-Angle Snowflake Camera (MASC) observations suggest the use of a bivariate beta distribution model for capturing aggregate shapes. Product moments of this model capture shape effects to within 4% of observations. This mathematical model is used along with Monte Carlo simulated aggregates to study how combinations of monomer properties affect aggregate shape evolution. Plate aggregates of any aspect ratio produce a consistent ellipsoid shape evolution whereas thin column aggregates evolve to become more spherical. Thin column aggregates yield fractal dimensions much less than the often-assumed value of 2.0. Ellipsoid densities and fractal analogs of density (lacunarity) are much more variable depending on combinations of monomer size and shape. Simple mathematical scaling relationships can explain the persistent triaxial ellipsoid shapes that appear in both observed and modeled aggregates. Overall, both simulations and observations prove aggregates are rarely oblate. Therefore, the use of the proposed bivariate ellipsoid distribution in models will allow for similar-sized aggregates to exhibit a realistic dispersion of masses and fall speeds.
Abstract
High-resolution Doppler radar observations of mammatus clouds coupled with soundings of the preanvil and anvil environments provide a unique opportunity to examine previously reported observations of, and evaluate various hypotheses of, mammatus formation. These observations confirm the general hypothesis for mammatus formation advanced by Ludlam and Scorer, and provide detail of the cloud interior structure. Specifically, the radar observations indicate that mammatus elements are reminiscent of eddy circulations with a weak downdraft core flanked by horizontal convergence and divergence at the top and base of the cloud, respectively. Doppler spectral width measurements, however, yielded values of only 2–3 m s−1, indicating only weak turbulent motions within individual mammatus elements. Reflectivity analyses of mammatus elements indicate a firm link to the parent anvil. A dual-Doppler analysis of the parent anvil indicates that the larger-scale environment where the mammatus exist is characterized by the existence of gravity waves or shear overturning. It is hypothesized that these circulations might play a role in the initiation of this particular outbreak of mammatus.
Abstract
High-resolution Doppler radar observations of mammatus clouds coupled with soundings of the preanvil and anvil environments provide a unique opportunity to examine previously reported observations of, and evaluate various hypotheses of, mammatus formation. These observations confirm the general hypothesis for mammatus formation advanced by Ludlam and Scorer, and provide detail of the cloud interior structure. Specifically, the radar observations indicate that mammatus elements are reminiscent of eddy circulations with a weak downdraft core flanked by horizontal convergence and divergence at the top and base of the cloud, respectively. Doppler spectral width measurements, however, yielded values of only 2–3 m s−1, indicating only weak turbulent motions within individual mammatus elements. Reflectivity analyses of mammatus elements indicate a firm link to the parent anvil. A dual-Doppler analysis of the parent anvil indicates that the larger-scale environment where the mammatus exist is characterized by the existence of gravity waves or shear overturning. It is hypothesized that these circulations might play a role in the initiation of this particular outbreak of mammatus.
Abstract
Theoretical calculations and experiments verify that the National Weather Service WSR-88D radars have the sensitivity to detect nonprecipitating clouds, but show that significant obstacles impair the generality of this cloud sensing technique. Bragg scatter from refractive index inhomogeneities can be of the same magnitude as cloud echoes under many conditions, whereupon interpretation of WSR-88D echoes can be either complicated or impossible. Moreover, problems with echoes from ground clutter and from insects, birds, and other floating debris hinder WSR-88D cloud detection capabilities, particularly at low elevation angles. To illustrate these problems WSR-88D reflectivities collected using volume coverage pattern (VCP) 21 from the months of March and October 1996 were compared with collocated reflectivities obtained from a zenith-pointing 94-GHz cloud radar located in central Pennsylvania. Coincident echo detection occurred 82% and 39% of the time, while the WSR-88D had significant detections 7% and 44% more of the time, during the March and October periods, respectively. For the coincident detections, there were a number of discrepancies in the reflectivity values that were a function of season, height, and time of day. In a separate analysis the WSR-88D located in Upton, Long Island, New York, was used to validate the theoretical minimum detectable signal of the radar in VCP 31 and show that ground clutter contamination may remain despite the use of clutter suppression techniques.
In summary, the results of this study suggest that WSR-88D reflectivity data may contain useful information about cloud structure when cloud droplets are the dominant scatterers. To determine if they are dominant requires information about the turbulent structure of the measurement volume and a method to discriminate undesirable targets such as ground clutter, insects, and birds. These requirements suggest that remotely sensing nonprecipitating and lightly precipitating clouds with the WSR-88D would be a difficult process to automate. Extrapolation of the results of this study imply that the best time to remotely sense low clouds with the WSR-88D may be winter nights and mornings when 1) clouds and wind prevent the development of a strong surface-based inversion that can produce beam ducting that enhances ground clutter, 2) insects and birds are not present, and 3) moisture gradients in the lower troposphere are relatively weak, which may reduce the likelihood that Bragg scatter from turbulent eddies would dominate Rayleigh scatter from cloud droplets.
Abstract
Theoretical calculations and experiments verify that the National Weather Service WSR-88D radars have the sensitivity to detect nonprecipitating clouds, but show that significant obstacles impair the generality of this cloud sensing technique. Bragg scatter from refractive index inhomogeneities can be of the same magnitude as cloud echoes under many conditions, whereupon interpretation of WSR-88D echoes can be either complicated or impossible. Moreover, problems with echoes from ground clutter and from insects, birds, and other floating debris hinder WSR-88D cloud detection capabilities, particularly at low elevation angles. To illustrate these problems WSR-88D reflectivities collected using volume coverage pattern (VCP) 21 from the months of March and October 1996 were compared with collocated reflectivities obtained from a zenith-pointing 94-GHz cloud radar located in central Pennsylvania. Coincident echo detection occurred 82% and 39% of the time, while the WSR-88D had significant detections 7% and 44% more of the time, during the March and October periods, respectively. For the coincident detections, there were a number of discrepancies in the reflectivity values that were a function of season, height, and time of day. In a separate analysis the WSR-88D located in Upton, Long Island, New York, was used to validate the theoretical minimum detectable signal of the radar in VCP 31 and show that ground clutter contamination may remain despite the use of clutter suppression techniques.
In summary, the results of this study suggest that WSR-88D reflectivity data may contain useful information about cloud structure when cloud droplets are the dominant scatterers. To determine if they are dominant requires information about the turbulent structure of the measurement volume and a method to discriminate undesirable targets such as ground clutter, insects, and birds. These requirements suggest that remotely sensing nonprecipitating and lightly precipitating clouds with the WSR-88D would be a difficult process to automate. Extrapolation of the results of this study imply that the best time to remotely sense low clouds with the WSR-88D may be winter nights and mornings when 1) clouds and wind prevent the development of a strong surface-based inversion that can produce beam ducting that enhances ground clutter, 2) insects and birds are not present, and 3) moisture gradients in the lower troposphere are relatively weak, which may reduce the likelihood that Bragg scatter from turbulent eddies would dominate Rayleigh scatter from cloud droplets.
Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate and regional models have generally proven unsuccessful at simulating Arctic cloudiness, particularly during the colder months. Specifically, models tend to underpredict the amount of liquid water in mixed-phase clouds. The Mixed-Phase Arctic Cloud Experiments (M-PACE), conducted from late September through October 2004 in the vicinity of the Department of Energy's Atmospheric Radiation Measurement (ARM) North Slope of Alaska field site, focused on characterizing low-level Arctic stratus clouds. Ice nuclei (IN) measurements were made using a continuous-flow ice thermal diffusion chamber aboard the University of North Dakota's Citation II aircraft. These measurements indicated IN concentrations that were significantly lower than those used in many models. Using the Regional Atmospheric Modeling System (RAMS), we show that these low IN concentrations, as well as inadequate parameterizations of the depletion of IN through nucleation scavenging, may be partially responsible for the poor model predictions. Moreover, we show that this can lead to errors in the modeled surface radiative energy budget of 10–100 Wm−2. Finally, using the measured IN concentrations as input to RAMS and comparing to a mixed-phase cloud observed during M-PACE, we show excellent agreement between modeled and observed liquid water content and net infrared surface flux.
Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate and regional models have generally proven unsuccessful at simulating Arctic cloudiness, particularly during the colder months. Specifically, models tend to underpredict the amount of liquid water in mixed-phase clouds. The Mixed-Phase Arctic Cloud Experiments (M-PACE), conducted from late September through October 2004 in the vicinity of the Department of Energy's Atmospheric Radiation Measurement (ARM) North Slope of Alaska field site, focused on characterizing low-level Arctic stratus clouds. Ice nuclei (IN) measurements were made using a continuous-flow ice thermal diffusion chamber aboard the University of North Dakota's Citation II aircraft. These measurements indicated IN concentrations that were significantly lower than those used in many models. Using the Regional Atmospheric Modeling System (RAMS), we show that these low IN concentrations, as well as inadequate parameterizations of the depletion of IN through nucleation scavenging, may be partially responsible for the poor model predictions. Moreover, we show that this can lead to errors in the modeled surface radiative energy budget of 10–100 Wm−2. Finally, using the measured IN concentrations as input to RAMS and comparing to a mixed-phase cloud observed during M-PACE, we show excellent agreement between modeled and observed liquid water content and net infrared surface flux.
Abstract
The performance of a 94-GHz radar is evaluated for a variety of cloud conditions. Descriptions of the radar hardware, signal processing, and calibration provide an overview of the radar's capabilities. An important component of the signal processing is the application of two cloud-mask schemes to the data to provide objective estimates of cloud boundaries and to detect significant returns that would otherwise be discarded if a simple threshold method for delectability was applied to the return power. Realistic profiles of atmospheric pressure, temperature, and water vapor are used in a radiative transfer model to address clear-sky attenuation. A physically relevant study of beam extinction and backscattering by clouds is attempted by modeling cloud drop size distributions with a gamma distribution over a range of number concentrations, particle mean diameters, and distribution shape factors; cloud liquid water contents and mean drop size diameters reported in the literature are analyzed in this context. Results of observations of a number of cloud structures, including marine strato- cumulus, cirrus, and stratus and cirrus associated with a midlatitude cyclone are described.
Abstract
The performance of a 94-GHz radar is evaluated for a variety of cloud conditions. Descriptions of the radar hardware, signal processing, and calibration provide an overview of the radar's capabilities. An important component of the signal processing is the application of two cloud-mask schemes to the data to provide objective estimates of cloud boundaries and to detect significant returns that would otherwise be discarded if a simple threshold method for delectability was applied to the return power. Realistic profiles of atmospheric pressure, temperature, and water vapor are used in a radiative transfer model to address clear-sky attenuation. A physically relevant study of beam extinction and backscattering by clouds is attempted by modeling cloud drop size distributions with a gamma distribution over a range of number concentrations, particle mean diameters, and distribution shape factors; cloud liquid water contents and mean drop size diameters reported in the literature are analyzed in this context. Results of observations of a number of cloud structures, including marine strato- cumulus, cirrus, and stratus and cirrus associated with a midlatitude cyclone are described.
Abstract
The surface downwelling longwave radiation component (LW↓) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW↓ signal measured at the surface. In this study, we examine the LW↓ model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 model relative to observations from the ARM West Antarctic Radiation Experiment (AWARE) campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud-layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW↓ during clear-sky conditions, high error variability (standard deviations > 20 W m−2) during any type of cloud occurrence, and negative LW↓ biases when LBCLs are observed (bias magnitudes >15 W m−2 in tenuous LBCL cases and >43 W m−2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW↓ biases in both models is the result of excessive ice formation and growth, which could stem from the model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.
Abstract
The surface downwelling longwave radiation component (LW↓) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW↓ signal measured at the surface. In this study, we examine the LW↓ model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 model relative to observations from the ARM West Antarctic Radiation Experiment (AWARE) campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud-layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW↓ during clear-sky conditions, high error variability (standard deviations > 20 W m−2) during any type of cloud occurrence, and negative LW↓ biases when LBCLs are observed (bias magnitudes >15 W m−2 in tenuous LBCL cases and >43 W m−2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW↓ biases in both models is the result of excessive ice formation and growth, which could stem from the model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.
