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- Author or Editor: Thomas J. Greenwald x
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Abstract
An accurate and rapid means is presented for computing the atmospheric absorption for the infrared channel (10.2–12.7 μm) on the Defense Meteorological Satellite Program operational linescan system (OLS) for use in remote sensing studies of surface and cloud properties. The method is a new approach to correlated k-distribution theory that keeps track of spectral information at the cumulative probability (g) level and more effectively addresses overlapping absorption through a recursive procedure. It also incorporates details of the instrument’s response function. Comparisons with line-by-line (LBL) results demonstrate that calculations using only 60 g-space intervals produce total atmospheric transmittance errors of 0.24% for a tropical atmosphere and 1.2% for a midlatitude winter atmosphere. In terms of upwelling equivalent blackbody (EBB) temperatures computed at the top of the atmosphere (TOA), the errors are less than 0.5 K over a wide range of atmospheric profiles and zenith angles when compared to LBL radiative transfer calculations. Errors are smallest (<0.1 K) for tropical environments. For downwelling EBB temperatures at the surface the errors become somewhat larger, especially for the winter atmosphere (maximum error of 1.66 K). Errors also generally increase slightly with increasing zenith angle. Reducing the number of g-space intervals to 17 can still provide reasonable results with a maximum error of 0.72 K for the TOA upwelling EBB temperature in a midlatitude winter atmosphere.
Abstract
An accurate and rapid means is presented for computing the atmospheric absorption for the infrared channel (10.2–12.7 μm) on the Defense Meteorological Satellite Program operational linescan system (OLS) for use in remote sensing studies of surface and cloud properties. The method is a new approach to correlated k-distribution theory that keeps track of spectral information at the cumulative probability (g) level and more effectively addresses overlapping absorption through a recursive procedure. It also incorporates details of the instrument’s response function. Comparisons with line-by-line (LBL) results demonstrate that calculations using only 60 g-space intervals produce total atmospheric transmittance errors of 0.24% for a tropical atmosphere and 1.2% for a midlatitude winter atmosphere. In terms of upwelling equivalent blackbody (EBB) temperatures computed at the top of the atmosphere (TOA), the errors are less than 0.5 K over a wide range of atmospheric profiles and zenith angles when compared to LBL radiative transfer calculations. Errors are smallest (<0.1 K) for tropical environments. For downwelling EBB temperatures at the surface the errors become somewhat larger, especially for the winter atmosphere (maximum error of 1.66 K). Errors also generally increase slightly with increasing zenith angle. Reducing the number of g-space intervals to 17 can still provide reasonable results with a maximum error of 0.72 K for the TOA upwelling EBB temperature in a midlatitude winter atmosphere.
Abstract
In this study, the ability of different combinations of bulk cloud microphysics and planetary boundary layer (PBL) parameterization schemes implemented in the Weather Research and Forecasting Model to realistically simulate the wide variety of cloud types associated with an extratropical cyclone is examined. An ensemble of high-resolution model simulations was constructed for this case using four microphysics and two PBL schemes characterized by different levels of complexity. Simulated cloud properties, including cloud optical thickness, cloud water path, cloud-top pressure, and radiative cloud phase, were subsequently compared to cloud data from three Moderate Resolution Imaging Spectroradiometer (MODIS) overpasses across different portions of the domain. A detailed comparison of the simulated datasets revealed that the PBL and cloud microphysics schemes both exerted a strong influence on the spatial distribution and physical properties of the simulated cloud fields. In particular, the low-level cloud properties were found to be very sensitive to the PBL scheme while the upper-level clouds were sensitive to both the microphysics and PBL schemes. Overall, the simulated cloud properties were broadly similar to the MODIS observations, with the most realistic cloud fields produced by the more sophisticated parameterization schemes.
Abstract
In this study, the ability of different combinations of bulk cloud microphysics and planetary boundary layer (PBL) parameterization schemes implemented in the Weather Research and Forecasting Model to realistically simulate the wide variety of cloud types associated with an extratropical cyclone is examined. An ensemble of high-resolution model simulations was constructed for this case using four microphysics and two PBL schemes characterized by different levels of complexity. Simulated cloud properties, including cloud optical thickness, cloud water path, cloud-top pressure, and radiative cloud phase, were subsequently compared to cloud data from three Moderate Resolution Imaging Spectroradiometer (MODIS) overpasses across different portions of the domain. A detailed comparison of the simulated datasets revealed that the PBL and cloud microphysics schemes both exerted a strong influence on the spatial distribution and physical properties of the simulated cloud fields. In particular, the low-level cloud properties were found to be very sensitive to the PBL scheme while the upper-level clouds were sensitive to both the microphysics and PBL schemes. Overall, the simulated cloud properties were broadly similar to the MODIS observations, with the most realistic cloud fields produced by the more sophisticated parameterization schemes.
This study reviews the capability of the advanced imagers on Geostationary Operational Environmental Satellites (GOES) I–M to provide quantitative information about bulk microphysical properties of low-level stratiform clouds, namely, cloud liquid water path (LWP) and droplet effective radius (re ). Previous studies show that accurate estimates of cloud LWP from GOES imagers are possible, as evaluated from both ground-based and spaceborne passive microwave measurements, provided care is taken in vicarious calibration of the visible channel. GOES estimates of re have yet to be validated. However, the re versus LWP relationship derived from GOES and Special Sensor Microwave/Imager data shows good agreement with theory. The unique high-temporal sampling of the imager allows for detailed study of daytime characteristics of cloud microphysical properties and, possibly, indirect aerosol effect. Microphysical information for drizzling marine stratocumuli was also obtained, which was confirmed by direct comparison to ship-based C-band radar during the 1997 Tropical Eastern Pacific Process Study. From the promising results obtained thus far, GOES I–M imager data should be of great value in future field experiments involving low-level stratiform clouds.
This study reviews the capability of the advanced imagers on Geostationary Operational Environmental Satellites (GOES) I–M to provide quantitative information about bulk microphysical properties of low-level stratiform clouds, namely, cloud liquid water path (LWP) and droplet effective radius (re ). Previous studies show that accurate estimates of cloud LWP from GOES imagers are possible, as evaluated from both ground-based and spaceborne passive microwave measurements, provided care is taken in vicarious calibration of the visible channel. GOES estimates of re have yet to be validated. However, the re versus LWP relationship derived from GOES and Special Sensor Microwave/Imager data shows good agreement with theory. The unique high-temporal sampling of the imager allows for detailed study of daytime characteristics of cloud microphysical properties and, possibly, indirect aerosol effect. Microphysical information for drizzling marine stratocumuli was also obtained, which was confirmed by direct comparison to ship-based C-band radar during the 1997 Tropical Eastern Pacific Process Study. From the promising results obtained thus far, GOES I–M imager data should be of great value in future field experiments involving low-level stratiform clouds.
Abstract
A cloud-resolving model was used in conjunction with a radiative transfer (RT) modeling system to study 10.7-μm brightness temperatures computed for a simulated thunderstorm. A two-moment microphysical scheme was used that included seven hydrometeor types: pristine ice, snow, aggregates, graupel, hail, rain, and cloud water. Also, five different habits were modeled for pristine ice and snow. Hydrometeor optical properties were determined from an extended anomalous diffraction theory approach. Brightness temperatures were computed using a delta-Eddington two-stream model.
Results indicate that the enhanced “V,” a feature sometimes seen in satellite infrared observations, may be formed through an interaction between the overshooting dome and the upstream flanking region of high pressure. This idea is contrary to one in which the overshooting dome is viewed as an obstacle to the environmental flow. As expected, the radiative effects of pristine ice particles within the anvil largely determined the brightness temperature field. Although brightness temperatures were found to be insensitive to microphysical characteristics of moderate to thick portions of the anvil, a strong relationship did exist with column-integrated pristine ice mass for cloud optical depths below about 5. Precipitation-sized hydrometeors and surface precipitation rate, on the other hand, failed to exhibit any meaningful relationship with the cloud-top brightness temperature. The combined mesoscale model and RT modeling system used in this study may also have utility in satellite product development prior to launch of a satellite and in satellite data assimilation.
Abstract
A cloud-resolving model was used in conjunction with a radiative transfer (RT) modeling system to study 10.7-μm brightness temperatures computed for a simulated thunderstorm. A two-moment microphysical scheme was used that included seven hydrometeor types: pristine ice, snow, aggregates, graupel, hail, rain, and cloud water. Also, five different habits were modeled for pristine ice and snow. Hydrometeor optical properties were determined from an extended anomalous diffraction theory approach. Brightness temperatures were computed using a delta-Eddington two-stream model.
Results indicate that the enhanced “V,” a feature sometimes seen in satellite infrared observations, may be formed through an interaction between the overshooting dome and the upstream flanking region of high pressure. This idea is contrary to one in which the overshooting dome is viewed as an obstacle to the environmental flow. As expected, the radiative effects of pristine ice particles within the anvil largely determined the brightness temperature field. Although brightness temperatures were found to be insensitive to microphysical characteristics of moderate to thick portions of the anvil, a strong relationship did exist with column-integrated pristine ice mass for cloud optical depths below about 5. Precipitation-sized hydrometeors and surface precipitation rate, on the other hand, failed to exhibit any meaningful relationship with the cloud-top brightness temperature. The combined mesoscale model and RT modeling system used in this study may also have utility in satellite product development prior to launch of a satellite and in satellite data assimilation.
Abstract
Assimilating satellite radiance data under all weather conditions remains an outstanding problem in numerical weather prediction. This study develops an observational operator for use in radiance assimilation under both clear and cloudy conditions specifically for mesoscale models containing explicit microphysics. It is part of a larger research effort to build a 4D variational radiance assimilation system for optimal use of satellite data. The operator is suitable for radiance calculations at visible/infrared wavelengths and is adaptable to the different spectral characteristics of many types of narrowband satellite sensors. The new operator makes use of a gas extinction model and fast, multiple-scattering radiative transfer models, and relies on physical approximations for deriving cloud optical properties. One property, the asymmetry factor, is estimated through a new application of anomalous diffraction theory.
A test of the observational operator's ability to estimate cloudy radiances was performed by forecasting a continental stratus system using the Regional Atmospheric Modeling System and computing radiances at all channels of the Geostationary Operational Environmental Satellite-9 imager. The forecasted radiances were found to reproduce very well the frequency distributions of observed cloudy radiances, particularly, the subtle temporal changes in the distributions that occurred between the early and late stages of development of the cloud system. These results are very encouraging and hold promise for future application of this observational operator in a full radiance assimilation system for satellite data across a wide range of wavelengths.
Abstract
Assimilating satellite radiance data under all weather conditions remains an outstanding problem in numerical weather prediction. This study develops an observational operator for use in radiance assimilation under both clear and cloudy conditions specifically for mesoscale models containing explicit microphysics. It is part of a larger research effort to build a 4D variational radiance assimilation system for optimal use of satellite data. The operator is suitable for radiance calculations at visible/infrared wavelengths and is adaptable to the different spectral characteristics of many types of narrowband satellite sensors. The new operator makes use of a gas extinction model and fast, multiple-scattering radiative transfer models, and relies on physical approximations for deriving cloud optical properties. One property, the asymmetry factor, is estimated through a new application of anomalous diffraction theory.
A test of the observational operator's ability to estimate cloudy radiances was performed by forecasting a continental stratus system using the Regional Atmospheric Modeling System and computing radiances at all channels of the Geostationary Operational Environmental Satellite-9 imager. The forecasted radiances were found to reproduce very well the frequency distributions of observed cloudy radiances, particularly, the subtle temporal changes in the distributions that occurred between the early and late stages of development of the cloud system. These results are very encouraging and hold promise for future application of this observational operator in a full radiance assimilation system for satellite data across a wide range of wavelengths.
Abstract
The characteristics of shapes and sizes of a sample of 679 hailstones, collected on 22 June 1976 during a hailstorm at Grover, Colorado, were analyzed using a three-parameter formula developed by us previously. These parameters are a, the horizontal dimension, c, the vertical dimension, and λ, the shape parameter. Once these three parameters are specified, both the shape and size of a hailstone are fixed. It is believed that this analysis produces the most complete and quantitative information about the hailstone shape and size distributions reported so far. The dataset of the three parameter also allows the relatively good reconstruction of the sizes and shapes of the original hailstones if desired. The results for this collection of hail show that the distributions of both horizontal and vertical dimensions can be described by gamma distributions, while the shape parameter can be described by an exponential distribution. Since the shape parameter basically describes the vertical asymmetry, it may provide additional information about the physics of particles in clouds and precipitation. The distributions of axial cross-sectional areas, surface areas, and volumes are also presented. They too can be described by gamma distributions. Finally, it was found that the geometrical quantities of the hailstones are best represented by a characteristic dimension rc , defined as the average of the horizontal and vertical dimension.
Abstract
The characteristics of shapes and sizes of a sample of 679 hailstones, collected on 22 June 1976 during a hailstorm at Grover, Colorado, were analyzed using a three-parameter formula developed by us previously. These parameters are a, the horizontal dimension, c, the vertical dimension, and λ, the shape parameter. Once these three parameters are specified, both the shape and size of a hailstone are fixed. It is believed that this analysis produces the most complete and quantitative information about the hailstone shape and size distributions reported so far. The dataset of the three parameter also allows the relatively good reconstruction of the sizes and shapes of the original hailstones if desired. The results for this collection of hail show that the distributions of both horizontal and vertical dimensions can be described by gamma distributions, while the shape parameter can be described by an exponential distribution. Since the shape parameter basically describes the vertical asymmetry, it may provide additional information about the physics of particles in clouds and precipitation. The distributions of axial cross-sectional areas, surface areas, and volumes are also presented. They too can be described by gamma distributions. Finally, it was found that the geometrical quantities of the hailstones are best represented by a characteristic dimension rc , defined as the average of the horizontal and vertical dimension.
Abstract
Synthetic infrared brightness temperatures (BTs) derived from a high-resolution Weather Research and Forecasting (WRF) model simulation over the contiguous United States are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) observations to assess the accuracy of the model-simulated cloud field. A sophisticated forward radiative transfer model (RTM) is used to compute the synthetic MODIS observations. A detailed comparison of synthetic and real MODIS 11-μm BTs revealed that the model simulation realistically depicts the spatial characteristics of the observed cloud features. Brightness temperature differences (BTDs) computed for 8.5–11 and 11–12 μm indicate that the combined numerical model–RTM system realistically treats the radiative properties associated with optically thin cirrus clouds. For instance, much larger 11–12-μm BTDs occurred within thin clouds surrounding optically thicker, mesoscale cloud features. Although the simulated and observed BTD probability distributions for optically thin cirrus clouds had a similar range of positive values, the synthetic 11-μm BTs were much colder than observed. Previous studies have shown that MODIS cloud optical thickness values tend to be too large for thin cirrus clouds, which contributed to the apparent cold BT bias in the simulated thin cirrus clouds. Errors are substantially reduced after accounting for the observed optical thickness bias, which indicates that the thin cirrus clouds are realistically depicted during the model simulation.
Abstract
Synthetic infrared brightness temperatures (BTs) derived from a high-resolution Weather Research and Forecasting (WRF) model simulation over the contiguous United States are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) observations to assess the accuracy of the model-simulated cloud field. A sophisticated forward radiative transfer model (RTM) is used to compute the synthetic MODIS observations. A detailed comparison of synthetic and real MODIS 11-μm BTs revealed that the model simulation realistically depicts the spatial characteristics of the observed cloud features. Brightness temperature differences (BTDs) computed for 8.5–11 and 11–12 μm indicate that the combined numerical model–RTM system realistically treats the radiative properties associated with optically thin cirrus clouds. For instance, much larger 11–12-μm BTDs occurred within thin clouds surrounding optically thicker, mesoscale cloud features. Although the simulated and observed BTD probability distributions for optically thin cirrus clouds had a similar range of positive values, the synthetic 11-μm BTs were much colder than observed. Previous studies have shown that MODIS cloud optical thickness values tend to be too large for thin cirrus clouds, which contributed to the apparent cold BT bias in the simulated thin cirrus clouds. Errors are substantially reduced after accounting for the observed optical thickness bias, which indicates that the thin cirrus clouds are realistically depicted during the model simulation.
Abstract
The large-scale spatial distribution and temporal variability of cloud liquid water path (LWP) over the world's oceans and the relationship of cloud LWP to temperature and the radiation budget are investigated using recent satellite measurements from the Special Sensor Microwave/Imager(SSM/1),the Earth Radiation Budget Experiment (ERBE), and the International Satellite Cloud Climatology Project (ISCCP). Observations of cloud liquid water on a 2.5° × 2.5° grid are used over a 53-month period beginning July 1987 and ending in December 1991.
The highest values of cloud liquid water (greater than 0.13 kg m−2) occur largely along principal routes of northern midlatitude storm and in area dominated by tropical convection. The zonally averaged structure is distinctly trimodal, where maxima appear in the midlatitudes and near the equator. The avenge marine cloud LWP over the globe is estimated to he about 0.113 kg m−2. Its highest seasonal variability is typically between 15% and 25% of the annual mean but in certain locations can exceed 30%. Comparisons of cloud LWP to temperature for low clouds during JJA and DJF of 1990 show significant positive correlations at colder temperatures and negative correlations at warmer temperatures. The correlations also exhibit strong seasonal and regional variation.
Coincident and collocated observations of cloud LWP from the SSM/I and albedo measurements from the Earth Radiation Budget Satellite (ERBS) and the NOAA-10 satellite are compared for low clouds in the North Pacific and North Atlantic. The observed albedo-LWP relationships correspond reasonably well with theory, where the average cloud effective radius (re ) is 11.1 μm and the standard deviation is 5.2 μm. The large variability in the inferred values of re suggests that other factors may be important in the albedo-LWP relationships. In terms of the effect of the LWP on the net cloud forcing, the authors find that a 0.05 kg m−2 increase in LWP (for LWP >0.2 kg m−2) results in a −25 W m−2 change in the net cloud forcing at a solar zenith angle of 75°.
Abstract
The large-scale spatial distribution and temporal variability of cloud liquid water path (LWP) over the world's oceans and the relationship of cloud LWP to temperature and the radiation budget are investigated using recent satellite measurements from the Special Sensor Microwave/Imager(SSM/1),the Earth Radiation Budget Experiment (ERBE), and the International Satellite Cloud Climatology Project (ISCCP). Observations of cloud liquid water on a 2.5° × 2.5° grid are used over a 53-month period beginning July 1987 and ending in December 1991.
The highest values of cloud liquid water (greater than 0.13 kg m−2) occur largely along principal routes of northern midlatitude storm and in area dominated by tropical convection. The zonally averaged structure is distinctly trimodal, where maxima appear in the midlatitudes and near the equator. The avenge marine cloud LWP over the globe is estimated to he about 0.113 kg m−2. Its highest seasonal variability is typically between 15% and 25% of the annual mean but in certain locations can exceed 30%. Comparisons of cloud LWP to temperature for low clouds during JJA and DJF of 1990 show significant positive correlations at colder temperatures and negative correlations at warmer temperatures. The correlations also exhibit strong seasonal and regional variation.
Coincident and collocated observations of cloud LWP from the SSM/I and albedo measurements from the Earth Radiation Budget Satellite (ERBS) and the NOAA-10 satellite are compared for low clouds in the North Pacific and North Atlantic. The observed albedo-LWP relationships correspond reasonably well with theory, where the average cloud effective radius (re ) is 11.1 μm and the standard deviation is 5.2 μm. The large variability in the inferred values of re suggests that other factors may be important in the albedo-LWP relationships. In terms of the effect of the LWP on the net cloud forcing, the authors find that a 0.05 kg m−2 increase in LWP (for LWP >0.2 kg m−2) results in a −25 W m−2 change in the net cloud forcing at a solar zenith angle of 75°.
Abstract
In this study, the accuracy of a simulated infrared brightness temperature dataset derived from a unique large-scale, high-resolution Weather Research and Forecasting (WRF) Model simulation is evaluated through a comparison with Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations. Overall, the analysis revealed that the simulated brightness temperatures realistically depict many of the observed features, although several large discrepancies were also identified. The similar shapes of the simulated and observed probability distributions calculated for each infrared band indicate that the model simulation realistically depicted the cloud morphology and relative proportion of clear and cloudy pixels. A traditional error analysis showed that the largest model errors occurred over central Africa because of a general mismatch in the locations of deep tropical convection and intervening regions of clear skies and low-level cloud cover. A detailed inspection of instantaneous brightness temperature difference (BTD) imagery showed that the modeling system realistically depicted the radiative properties associated with various cloud types. For instance, thin cirrus clouds along the edges of deep tropical convection and within midlatitude cloud shields were characterized by much larger 10.8 − 12.0-μm BTD than optically thicker clouds. Simulated ice clouds were effectively discriminated from liquid clouds and clear pixels by the close relationship between positive 8.7 − 10.8-μm BTD and the coldest 10.8-μm brightness temperatures. Comparison of the simulated and observed BTD probability distributions revealed that the liquid and mixed-phase cloud-top properties were consistent with the observations, whereas the narrower BTD distributions for the colder 10.8-μm brightness temperatures indicated that the microphysics scheme was unable to simulate the full dynamic range of ice clouds.
Abstract
In this study, the accuracy of a simulated infrared brightness temperature dataset derived from a unique large-scale, high-resolution Weather Research and Forecasting (WRF) Model simulation is evaluated through a comparison with Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations. Overall, the analysis revealed that the simulated brightness temperatures realistically depict many of the observed features, although several large discrepancies were also identified. The similar shapes of the simulated and observed probability distributions calculated for each infrared band indicate that the model simulation realistically depicted the cloud morphology and relative proportion of clear and cloudy pixels. A traditional error analysis showed that the largest model errors occurred over central Africa because of a general mismatch in the locations of deep tropical convection and intervening regions of clear skies and low-level cloud cover. A detailed inspection of instantaneous brightness temperature difference (BTD) imagery showed that the modeling system realistically depicted the radiative properties associated with various cloud types. For instance, thin cirrus clouds along the edges of deep tropical convection and within midlatitude cloud shields were characterized by much larger 10.8 − 12.0-μm BTD than optically thicker clouds. Simulated ice clouds were effectively discriminated from liquid clouds and clear pixels by the close relationship between positive 8.7 − 10.8-μm BTD and the coldest 10.8-μm brightness temperatures. Comparison of the simulated and observed BTD probability distributions revealed that the liquid and mixed-phase cloud-top properties were consistent with the observations, whereas the narrower BTD distributions for the colder 10.8-μm brightness temperatures indicated that the microphysics scheme was unable to simulate the full dynamic range of ice clouds.
