Search Results
You are looking at 1 - 10 of 19 items for
- Author or Editor: J. Delanoë x
- Refine by Access: All Content x
Abstract
Best estimates of the bulk microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration) are derived for three case studies of tropical ice clouds sampled during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Two case studies are aged cirrus clouds produced by deep convection (the so-called 27/01 and 29/01 cases), and the third (“02/02”) is a fresh anvil produced by deep convective activity over the Tiwi Islands. Using crystal images obtained by a Cloud Particle Imager (CPI), it is observed that small ice particles (with maximum dimension D < 50–100 μm) were predominantly quasi spherical, with the degree of nonsphericity increasing rapidly in the 50 < D < 100-μm range. For D > 100 μm, the aged cirrus clouds were predominantly characterized by bullet rosettes and aggregates of bullet rosettes, plates, and columns. In contrast, the fresh anvil had more frequent occurrences of plates, columns, aggregates of plates, and occasionally capped columns. The impact of shattering of large ice crystals on probe tips and the overall quality of the TWP-ICE in situ microphysical measurements are assessed. It is suggested that shattering has a relatively small impact on the CPI and cloud droplet probe (CDP) TWP-ICE data and a large impact on the Cloud Aerosol Spectrometer data, as already documented by others. It is also shown that the CPI size distributions must be multiplied by a factor of 4 to match those of the cloud imaging probe (CIP) for maximum dimension larger than 100 μm (taken as a reference). A technique [named Best Estimate of Area and Density (BEAD)] to minimize errors associated with the density (ρ)–D and projected area (A)–D assumptions in bulk microphysics calculation is introduced and applied to the TWP-ICE data. The method makes direct use of the frequency of occurrence of each particle habit as classified from the CPI data and prescribed ρ–D and A–D relationships from the literature. This approach produces ice water content (IWC) estimates that are virtually unbiased relative to bulk measures obtained from a counterflow spectrometer and impactor (CSI) probe. In contrast, the use of ρ–D and A–D relationships for single habits does produce large biases relative to the CSI observations: from −50% for bullet rosettes to +70%–80% for aggregates. The so-called width, length, area, and perimeter (WLAP) technique, which also makes use of individual CPI images, is found to produce positively biased IWCs (by 40% or so), and has a standard deviation of the errors similar to the BEAD technique. The impact of the large variability of the size distributions measured by different probe combinations on the bulk microphysical properties is characterized. The mean fractional differences with respect to the CSI measurements are small for the CPI + CIP, CPI, and CDP + CIP combinations (2.2%, −0.8%, and −1.1%, respectively), with standard deviations of the fractional differences ranging from 7% to 9%. This result provides an independent validation of the CPI scaling factor. The fractional differences produced between the CPI + CIP, CPI, and CDP + CIP combinations for extinction, effective radius, and total concentration are 33%, 10%–20%, and 90%, respectively, with relatively small standard deviations of 5%–8%. The fractional difference on total concentration varies greatly over the concentration range though, with values being larger than a factor of 2 for total concentrations smaller than 40 L−1, but reducing to 10%–20% for concentrations larger than 100 L−1. Therefore, caution should be exercised when using total concentrations smaller than 60–80 L−1 as references for radar–lidar retrieval evaluation.
Abstract
Best estimates of the bulk microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration) are derived for three case studies of tropical ice clouds sampled during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Two case studies are aged cirrus clouds produced by deep convection (the so-called 27/01 and 29/01 cases), and the third (“02/02”) is a fresh anvil produced by deep convective activity over the Tiwi Islands. Using crystal images obtained by a Cloud Particle Imager (CPI), it is observed that small ice particles (with maximum dimension D < 50–100 μm) were predominantly quasi spherical, with the degree of nonsphericity increasing rapidly in the 50 < D < 100-μm range. For D > 100 μm, the aged cirrus clouds were predominantly characterized by bullet rosettes and aggregates of bullet rosettes, plates, and columns. In contrast, the fresh anvil had more frequent occurrences of plates, columns, aggregates of plates, and occasionally capped columns. The impact of shattering of large ice crystals on probe tips and the overall quality of the TWP-ICE in situ microphysical measurements are assessed. It is suggested that shattering has a relatively small impact on the CPI and cloud droplet probe (CDP) TWP-ICE data and a large impact on the Cloud Aerosol Spectrometer data, as already documented by others. It is also shown that the CPI size distributions must be multiplied by a factor of 4 to match those of the cloud imaging probe (CIP) for maximum dimension larger than 100 μm (taken as a reference). A technique [named Best Estimate of Area and Density (BEAD)] to minimize errors associated with the density (ρ)–D and projected area (A)–D assumptions in bulk microphysics calculation is introduced and applied to the TWP-ICE data. The method makes direct use of the frequency of occurrence of each particle habit as classified from the CPI data and prescribed ρ–D and A–D relationships from the literature. This approach produces ice water content (IWC) estimates that are virtually unbiased relative to bulk measures obtained from a counterflow spectrometer and impactor (CSI) probe. In contrast, the use of ρ–D and A–D relationships for single habits does produce large biases relative to the CSI observations: from −50% for bullet rosettes to +70%–80% for aggregates. The so-called width, length, area, and perimeter (WLAP) technique, which also makes use of individual CPI images, is found to produce positively biased IWCs (by 40% or so), and has a standard deviation of the errors similar to the BEAD technique. The impact of the large variability of the size distributions measured by different probe combinations on the bulk microphysical properties is characterized. The mean fractional differences with respect to the CSI measurements are small for the CPI + CIP, CPI, and CDP + CIP combinations (2.2%, −0.8%, and −1.1%, respectively), with standard deviations of the fractional differences ranging from 7% to 9%. This result provides an independent validation of the CPI scaling factor. The fractional differences produced between the CPI + CIP, CPI, and CDP + CIP combinations for extinction, effective radius, and total concentration are 33%, 10%–20%, and 90%, respectively, with relatively small standard deviations of 5%–8%. The fractional difference on total concentration varies greatly over the concentration range though, with values being larger than a factor of 2 for total concentrations smaller than 40 L−1, but reducing to 10%–20% for concentrations larger than 100 L−1. Therefore, caution should be exercised when using total concentrations smaller than 60–80 L−1 as references for radar–lidar retrieval evaluation.
Abstract
The A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function.
Abstract
The A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function.
Abstract
The objective of this paper is to assess the performances of the proposed ice water content (IWC)–radar reflectivity Z and IWC–Z–temperature T relationships for accurate retrievals of IWC from radar in space or at ground-based sites, in the framework of the forthcoming CloudSat spaceborne radar, and of the European CloudNET and U.S. Atmospheric Radiation Measurement Program projects. For this purpose, a large airborne in situ microphysical database is used to perform a detailed error analysis of the IWC–Z and IWC–Z–T methods. This error analysis does not include the error resulting from the mass–dimension relationship assumed in these methods, although the expected magnitude of this error is bounded in the paper. First, this study reveals that the use of a single IWC–Z relationship to estimate IWC at global scale would be feasible up to −15 dBZ, but for larger reflectivities (and therefore larger IWCs) different sets of relationships would have to be used for midlatitude and tropical ice clouds. New IWC–Z and IWC–Z–T relationships are then developed from the large aircraft database and by splitting this database into midlatitude and tropical subsets, and an error analysis is performed. For the IWC–Z relationships, errors decrease roughly linearly from +210%/−70% for IWC = 10−4 g m−3 to +75%/−45% for IWC = 10−2 g m−3, are nearly constant (+50%/−33%) for the intermediate IWCs (0.03–1 g m−3), and then linearly increase up to +210%/−70% for the largest IWCs. The error curves have the same shape for the IWC–Z–T relationships, with a general reduction of errors with respect to the IWC–Z relationships. Comparisons with radar–lidar retrievals confirm these findings. The main improvement brought by the use of temperature as an additional constraint to the IWC retrieval is to reduce both the systematic overestimation and rms differences of the small IWCs (IWC < 0.01 g m−3). For the large IWCs, the use of temperature also results in a slight reduction of the rms differences but in a substantial reduction (by a factor of 2) of the systematic underestimation of the large IWCs, probably owing to a better account of the Mie effect when IWC–Z relationships are stratified by temperature.
Abstract
The objective of this paper is to assess the performances of the proposed ice water content (IWC)–radar reflectivity Z and IWC–Z–temperature T relationships for accurate retrievals of IWC from radar in space or at ground-based sites, in the framework of the forthcoming CloudSat spaceborne radar, and of the European CloudNET and U.S. Atmospheric Radiation Measurement Program projects. For this purpose, a large airborne in situ microphysical database is used to perform a detailed error analysis of the IWC–Z and IWC–Z–T methods. This error analysis does not include the error resulting from the mass–dimension relationship assumed in these methods, although the expected magnitude of this error is bounded in the paper. First, this study reveals that the use of a single IWC–Z relationship to estimate IWC at global scale would be feasible up to −15 dBZ, but for larger reflectivities (and therefore larger IWCs) different sets of relationships would have to be used for midlatitude and tropical ice clouds. New IWC–Z and IWC–Z–T relationships are then developed from the large aircraft database and by splitting this database into midlatitude and tropical subsets, and an error analysis is performed. For the IWC–Z relationships, errors decrease roughly linearly from +210%/−70% for IWC = 10−4 g m−3 to +75%/−45% for IWC = 10−2 g m−3, are nearly constant (+50%/−33%) for the intermediate IWCs (0.03–1 g m−3), and then linearly increase up to +210%/−70% for the largest IWCs. The error curves have the same shape for the IWC–Z–T relationships, with a general reduction of errors with respect to the IWC–Z relationships. Comparisons with radar–lidar retrievals confirm these findings. The main improvement brought by the use of temperature as an additional constraint to the IWC retrieval is to reduce both the systematic overestimation and rms differences of the small IWCs (IWC < 0.01 g m−3). For the large IWCs, the use of temperature also results in a slight reduction of the rms differences but in a substantial reduction (by a factor of 2) of the systematic underestimation of the large IWCs, probably owing to a better account of the Mie effect when IWC–Z relationships are stratified by temperature.
Abstract
In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.
Abstract
In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.
Abstract
Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z 0 must be known. Because the algorithms are stable for inversion performed from range z 0 toward the emitter, z 0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.
Abstract
Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z 0 must be known. Because the algorithms are stable for inversion performed from range z 0 toward the emitter, z 0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.
Abstract
A quantitative assessment of Cloudsat reflectivities and basic ice cloud properties (cloud base, top, and thickness) is conducted in the present study from both airborne and ground-based observations. Airborne observations allow direct comparisons on a limited number of ocean backscatter and cloud samples, whereas the ground-based observations allow statistical comparisons on much longer time series but with some additional assumptions. Direct comparisons of the ocean backscatter and ice cloud reflectivities measured by an airborne cloud radar and Cloudsat during two field experiments indicate that, on average, Cloudsat measures ocean backscatter 0.4 dB higher and ice cloud reflectivities 1 dB higher than the airborne cloud radar. Five ground-based sites have also been used for a statistical evaluation of the Cloudsat reflectivities and basic cloud properties. From these comparisons, it is found that the weighted-mean difference Z Cloudsat − Z Ground ranges from −0.4 to +0.3 dB when a ±1-h time lag around the Cloudsat overpass is considered. Given the fact that the airborne and ground-based radar calibration accuracy is about 1 dB, it is concluded that the reflectivities of the spaceborne, airborne, and ground-based radars agree within the expected calibration uncertainties of the airborne and ground-based radars. This result shows that the Cloudsat radar does achieve the claimed sensitivity of around −29 dBZ. Finally, an evaluation of the tropical “convective ice” profiles measured by Cloudsat has been carried out over the tropical site in Darwin, Australia. It is shown that these profiles can be used statistically down to approximately 9-km height (or 4 km above the melting layer) without attenuation and multiple scattering corrections over Darwin. It is difficult to estimate if this result is applicable to all types of deep convective storms in the tropics. However, this first study suggests that the Cloudsat profiles in convective ice need to be corrected for attenuation by supercooled liquid water and ice aggregates/graupel particles and multiple scattering prior to their quantitative use.
Abstract
A quantitative assessment of Cloudsat reflectivities and basic ice cloud properties (cloud base, top, and thickness) is conducted in the present study from both airborne and ground-based observations. Airborne observations allow direct comparisons on a limited number of ocean backscatter and cloud samples, whereas the ground-based observations allow statistical comparisons on much longer time series but with some additional assumptions. Direct comparisons of the ocean backscatter and ice cloud reflectivities measured by an airborne cloud radar and Cloudsat during two field experiments indicate that, on average, Cloudsat measures ocean backscatter 0.4 dB higher and ice cloud reflectivities 1 dB higher than the airborne cloud radar. Five ground-based sites have also been used for a statistical evaluation of the Cloudsat reflectivities and basic cloud properties. From these comparisons, it is found that the weighted-mean difference Z Cloudsat − Z Ground ranges from −0.4 to +0.3 dB when a ±1-h time lag around the Cloudsat overpass is considered. Given the fact that the airborne and ground-based radar calibration accuracy is about 1 dB, it is concluded that the reflectivities of the spaceborne, airborne, and ground-based radars agree within the expected calibration uncertainties of the airborne and ground-based radars. This result shows that the Cloudsat radar does achieve the claimed sensitivity of around −29 dBZ. Finally, an evaluation of the tropical “convective ice” profiles measured by Cloudsat has been carried out over the tropical site in Darwin, Australia. It is shown that these profiles can be used statistically down to approximately 9-km height (or 4 km above the melting layer) without attenuation and multiple scattering corrections over Darwin. It is difficult to estimate if this result is applicable to all types of deep convective storms in the tropics. However, this first study suggests that the Cloudsat profiles in convective ice need to be corrected for attenuation by supercooled liquid water and ice aggregates/graupel particles and multiple scattering prior to their quantitative use.
Abstract
The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well-instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar–lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (because of limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar–Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2-km height because of instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of-atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar–lidar instruments and radiative transfer calculations are also found above 10 km (up to 0.35 K day−1 for the shortwave and 0.8 K day−1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud–radiation interactions in large-scale models, and limitations of each set of instrumentation should be considered when interpreting model–observation differences.
Abstract
The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well-instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar–lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (because of limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar–Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2-km height because of instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of-atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar–lidar instruments and radiative transfer calculations are also found above 10 km (up to 0.35 K day−1 for the shortwave and 0.8 K day−1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud–radiation interactions in large-scale models, and limitations of each set of instrumentation should be considered when interpreting model–observation differences.
Abstract
In this paper, unprecedented bulk measurements of ice water content (IWC) up to approximately 5 g m−3 and 95-GHz radar reflectivities Z 95 are used to analyze the statistical relationship between these two quantities and its variability. The unique aspect of this study is that these IWC–Z 95 relationships do not use assumptions on cloud microphysics or backscattering calculations. IWCs greater than 2 g m−3 are also included for the first time in such an analysis, owing to improved bulk IWC probe technology and a flight program targeting high ice water content. Using a single IW–Z 95 relationship allows for the retrieval of IWC from radar reflectivities with less than 30% bias and 40%–70% rms difference. These errors can be reduced further, down to 10%–20% bias over the whole IWC range, using the temperature variability of this relationship. IWC errors largely increase for Z 95 > 16 dBZ, as a result of the distortion of the IWC–Z 95 relationship by non-Rayleigh scattering effects. A nonlinear relationship is proposed to reduce these errors down to 20% bias and 20%–35% rms differences. This nonlinear relationship also outperforms the temperature-dependent IWC–Z 95 relationship for convective profiles. The joint frequency distribution of IWC and temperature within and around deep tropical convective cores shows that at the −50° ± 5°C level, the cruise altitude of many commercial jet aircraft, IWCs greater than 1.5 g m−3 were found exclusively in convective profiles.
Abstract
In this paper, unprecedented bulk measurements of ice water content (IWC) up to approximately 5 g m−3 and 95-GHz radar reflectivities Z 95 are used to analyze the statistical relationship between these two quantities and its variability. The unique aspect of this study is that these IWC–Z 95 relationships do not use assumptions on cloud microphysics or backscattering calculations. IWCs greater than 2 g m−3 are also included for the first time in such an analysis, owing to improved bulk IWC probe technology and a flight program targeting high ice water content. Using a single IW–Z 95 relationship allows for the retrieval of IWC from radar reflectivities with less than 30% bias and 40%–70% rms difference. These errors can be reduced further, down to 10%–20% bias over the whole IWC range, using the temperature variability of this relationship. IWC errors largely increase for Z 95 > 16 dBZ, as a result of the distortion of the IWC–Z 95 relationship by non-Rayleigh scattering effects. A nonlinear relationship is proposed to reduce these errors down to 20% bias and 20%–35% rms differences. This nonlinear relationship also outperforms the temperature-dependent IWC–Z 95 relationship for convective profiles. The joint frequency distribution of IWC and temperature within and around deep tropical convective cores shows that at the −50° ± 5°C level, the cruise altitude of many commercial jet aircraft, IWCs greater than 1.5 g m−3 were found exclusively in convective profiles.
Abstract
This study addresses clouds with significant ice water content (IWC) in the stratiform regions downwind of the convective cores of African squall lines in the framework of the French–Indian satellite Megha-Tropiques project, observed in August 2010 next to Niamey (13.5°N, 2°E) in the southwestern part of Niger. The objectives included comparing the IWC–Z reflectivity relationship for precipitation radars in deep stratiform anvils, collocating reflectivity observed from ground radar with the calculated reflectivity from in situ microphysics for all aircraft locations inside the radar range, and interpreting the role of large ice crystals in the reflectivity of centimeter radars through analysis of their microphysical characteristics as ice crystals larger than 5 mm frequently occurred. It was found that, in the range of 20–30 dBZ, IWC and C-band reflectivity are not really correlated. Cloud regions with high IWC caused by important crystal number concentrations can lead to the same reflectivity factor as cloud regions with low IWC formed by a few millimeter-sized ice crystals.
Abstract
This study addresses clouds with significant ice water content (IWC) in the stratiform regions downwind of the convective cores of African squall lines in the framework of the French–Indian satellite Megha-Tropiques project, observed in August 2010 next to Niamey (13.5°N, 2°E) in the southwestern part of Niger. The objectives included comparing the IWC–Z reflectivity relationship for precipitation radars in deep stratiform anvils, collocating reflectivity observed from ground radar with the calculated reflectivity from in situ microphysics for all aircraft locations inside the radar range, and interpreting the role of large ice crystals in the reflectivity of centimeter radars through analysis of their microphysical characteristics as ice crystals larger than 5 mm frequently occurred. It was found that, in the range of 20–30 dBZ, IWC and C-band reflectivity are not really correlated. Cloud regions with high IWC caused by important crystal number concentrations can lead to the same reflectivity factor as cloud regions with low IWC formed by a few millimeter-sized ice crystals.
