C. Tinel, J. Testud, J. Pelon, R. Hogan, A. Protat, J. Delanoë, D. Bouniol
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 z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 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.
{"title":"The Retrieval of Ice-Cloud Properties from Cloud Radar and Lidar Synergy","authors":"C. Tinel, J. Testud, J. Pelon, R. Hogan, A. Protat, J. Delanoë, D. Bouniol","doi":"10.1175/JAM2229.1","DOIUrl":"https://doi.org/10.1175/JAM2229.1","url":null,"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 z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 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.","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"1 1","pages":"860-875"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89250236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Polarimetric radar data have been used to produce microphysical classifications. This kind of analysis is run in a real-time mode from several research radars, including the C-band polarimetric (C-Pol) radar in Darwin, Australia. However, these classifications have had very little systematic evaluation with independent data. Using surface data is often difficult because of sampling issues, particularly for hail. The approach taken here is to use a combination of 50- and 920-MHz wind profiler estimates of rain and hail to provide validation data for the radar pixels over the profiler. The profilers also observe signals associated with lightning, and some comparisons are made between lightning occurrence and the radar measurements of graupel. The retrievals of hail–rain mixtures are remarkably robust; there are some issues regarding other microphysical classes, however, including difficulties in detecting melting snow layers in stratiform rain. These difficulties are largely due to the resampling o...
{"title":"Evaluation of Microphysical Retrievals from Polarimetric Radar with Wind Profiler Data","authors":"P. May, T. Keenan","doi":"10.1175/JAM2230.1","DOIUrl":"https://doi.org/10.1175/JAM2230.1","url":null,"abstract":"Abstract Polarimetric radar data have been used to produce microphysical classifications. This kind of analysis is run in a real-time mode from several research radars, including the C-band polarimetric (C-Pol) radar in Darwin, Australia. However, these classifications have had very little systematic evaluation with independent data. Using surface data is often difficult because of sampling issues, particularly for hail. The approach taken here is to use a combination of 50- and 920-MHz wind profiler estimates of rain and hail to provide validation data for the radar pixels over the profiler. The profilers also observe signals associated with lightning, and some comparisons are made between lightning occurrence and the radar measurements of graupel. The retrievals of hail–rain mixtures are remarkably robust; there are some issues regarding other microphysical classes, however, including difficulties in detecting melting snow layers in stratiform rain. These difficulties are largely due to the resampling o...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"9 1","pages":"827-838"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83656584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study of the atmospheric boundary layer flow over two-dimensional low-sloped hills under a neutral atmosphere finds numerous applications in meteorology and engineering, such as the development of large-scale atmospheric models, the siting of wind turbines, and the estimation of wind loads on transmission towers and antennas. In this paper, the intermediate variable technique is applied to the momentum equations in streamline coordinates to divide the flow into regions, with each characterized by the dominance of different terms. Using a simple mixing-length turbulence closure, a simplified form of the x momentum equation is solved for the fully turbulent region, resulting in a modified logarithmic law. The solution is expressed as a power series correction to the classical logarithmic law that is valid for flat terrain. A new parameter appears: the effective radius of curvature of the hill. The modified logarithmic law is used to obtain new equations for the speedup, the relative speedup, the maximum speedup, and the height at which it occurs. A new speedup ratio is proposed to calculate the relative speedup at specific heights. The results are in very good agreement with the Askervein and Black Mountain field data.
{"title":"A Modified Logarithmic Law for Neutrally Stratified Flow over Low-Sloped Hills","authors":"C. Pellegrini, G. C. R. Bodstein","doi":"10.1175/JAM2207.1","DOIUrl":"https://doi.org/10.1175/JAM2207.1","url":null,"abstract":"The study of the atmospheric boundary layer flow over two-dimensional low-sloped hills under a neutral atmosphere finds numerous applications in meteorology and engineering, such as the development of large-scale atmospheric models, the siting of wind turbines, and the estimation of wind loads on transmission towers and antennas. In this paper, the intermediate variable technique is applied to the momentum equations in streamline coordinates to divide the flow into regions, with each characterized by the dominance of different terms. Using a simple mixing-length turbulence closure, a simplified form of the x momentum equation is solved for the fully turbulent region, resulting in a modified logarithmic law. The solution is expressed as a power series correction to the classical logarithmic law that is valid for flat terrain. A new parameter appears: the effective radius of curvature of the hill. The modified logarithmic law is used to obtain new equations for the speedup, the relative speedup, the maximum speedup, and the height at which it occurs. A new speedup ratio is proposed to calculate the relative speedup at specific heights. The results are in very good agreement with the Askervein and Black Mountain field data.","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"52 1","pages":"900-916"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85932016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xing Yu, J. Dai, D. Rosenfeld, Hengchi Lei, Xiaohong Xu, Peng Fan, Zheng Chen
Abstract From 0615 to 0749 UTC 14 March 2000, an operation of cloud seeding for precipitation enhancement by aircraft was carried out in the middle part of Shaanxi Province, China. National Oceanic and Atmospheric Administration (NOAA)-14 satellite imagery was received at 0735 UTC for the study region. A vivid cloud track appeared on the satellite imagery; its length was about 350 km, and its average width and width maximum were 9 and 14 km, respectively. Through application of a three-dimensional numerical model of the transport and diffusion of the seeding material, the simulated plume shape, the turning points, and the width and length of seeding lines agree with that of the cloud pattern indicated by the satellite imagery. The track is consistent with the transport and diffusion of the seeding line. All of these factors suggest that the cloud track that is detected by satellite imaging is the direct physical evidence of cloud seeding near the cloud top, with the cloud responding to the transport and d...
{"title":"Comparison of Model-Predicted Transport and Diffusion of Seeding Material with NOAA Satellite-Observed Seeding Track in Supercooled Layer Clouds","authors":"Xing Yu, J. Dai, D. Rosenfeld, Hengchi Lei, Xiaohong Xu, Peng Fan, Zheng Chen","doi":"10.1175/JAM2224.1","DOIUrl":"https://doi.org/10.1175/JAM2224.1","url":null,"abstract":"Abstract From 0615 to 0749 UTC 14 March 2000, an operation of cloud seeding for precipitation enhancement by aircraft was carried out in the middle part of Shaanxi Province, China. National Oceanic and Atmospheric Administration (NOAA)-14 satellite imagery was received at 0735 UTC for the study region. A vivid cloud track appeared on the satellite imagery; its length was about 350 km, and its average width and width maximum were 9 and 14 km, respectively. Through application of a three-dimensional numerical model of the transport and diffusion of the seeding material, the simulated plume shape, the turning points, and the width and length of seeding lines agree with that of the cloud pattern indicated by the satellite imagery. The track is consistent with the transport and diffusion of the seeding line. All of these factors suggest that the cloud track that is detected by satellite imaging is the direct physical evidence of cloud seeding near the cloud top, with the cloud responding to the transport and d...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"103 1","pages":"749-759"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82847450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Soil erosion is a major global challenge. An increased understanding of the mechanisms driving soil erosion, especially the storms that produce it, is vital to reducing the impact on agriculture and the environment. The objective of this work was to study the spatial distribution and time trends of the soil erosion characteristics of storms, including the maximum 30-min precipitation intensity (I30), storm kinetic energy of the falling precipitation (KE), and the storm erosivity index (EI) using a long-term 15-min precipitation database. This is the first time that such an extensive climatology of soil erosion characteristics of storms has been produced. The highest mean I30, KE, and EI values occurred in all seasons in the southeastern United States, while the lowest occurred predominantly in the interior west. The lowest mean I30, KE, and EI values typically occurred in winter, and the highest occurred in summer. The exception to this was along the West Coast where winter storms exhibited the l...
{"title":"Storm Precipitation in the United States. Part II: Soil Erosion Characteristics","authors":"J. Angel, M. Palecki, S. Hollinger","doi":"10.1175/JAM2242.1","DOIUrl":"https://doi.org/10.1175/JAM2242.1","url":null,"abstract":"Abstract Soil erosion is a major global challenge. An increased understanding of the mechanisms driving soil erosion, especially the storms that produce it, is vital to reducing the impact on agriculture and the environment. The objective of this work was to study the spatial distribution and time trends of the soil erosion characteristics of storms, including the maximum 30-min precipitation intensity (I30), storm kinetic energy of the falling precipitation (KE), and the storm erosivity index (EI) using a long-term 15-min precipitation database. This is the first time that such an extensive climatology of soil erosion characteristics of storms has been produced. The highest mean I30, KE, and EI values occurred in all seasons in the southeastern United States, while the lowest occurred predominantly in the interior west. The lowest mean I30, KE, and EI values typically occurred in winter, and the highest occurred in summer. The exception to this was along the West Coast where winter storms exhibited the l...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"164 1","pages":"947-959"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80375212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Q. Xiao, Y. Kuo, Juanzhen Sun, Wen-Chau Lee, E. Lim, Yong-run Guo, D. Barker
Abstract In this paper, the impact of Doppler radar radial velocity on the prediction of a heavy rainfall event is examined. The three-dimensional variational data assimilation (3DVAR) system for use with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is further developed to enable the assimilation of radial velocity observations. Doppler velocities from the Korean Jindo radar are assimilated into MM5 using the 3DVAR system for a heavy rainfall case that occurred on 10 June 2002. The results show that the assimilation of Doppler velocities has a positive impact on the short-range prediction of heavy rainfall. The dynamic balance between atmospheric wind and thermodynamic fields, based on the Richardson equation, is introduced to the 3DVAR system. Vertical velocity (w) increments are included in the 3DVAR system to enable the assimilation of the vertical velocity component of the Doppler radial velocity observation. The forecast of the hydrometeor variables of cloud water (qc...
{"title":"Assimilation of Doppler Radar Observations with a Regional 3DVAR System: Impact of Doppler Velocities on Forecasts of a Heavy Rainfall Case","authors":"Q. Xiao, Y. Kuo, Juanzhen Sun, Wen-Chau Lee, E. Lim, Yong-run Guo, D. Barker","doi":"10.1175/JAM2248.1","DOIUrl":"https://doi.org/10.1175/JAM2248.1","url":null,"abstract":"Abstract In this paper, the impact of Doppler radar radial velocity on the prediction of a heavy rainfall event is examined. The three-dimensional variational data assimilation (3DVAR) system for use with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is further developed to enable the assimilation of radial velocity observations. Doppler velocities from the Korean Jindo radar are assimilated into MM5 using the 3DVAR system for a heavy rainfall case that occurred on 10 June 2002. The results show that the assimilation of Doppler velocities has a positive impact on the short-range prediction of heavy rainfall. The dynamic balance between atmospheric wind and thermodynamic fields, based on the Richardson equation, is introduced to the 3DVAR system. Vertical velocity (w) increments are included in the 3DVAR system to enable the assimilation of the vertical velocity component of the Doppler radial velocity observation. The forecast of the hydrometeor variables of cloud water (qc...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"226 1","pages":"768-788"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78438560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. F. Evans, James R. Wang, P. Racette, G. Heymsfield, Lihua Li
Abstract Submillimeter-wave radiometry is a new technique for determining ice water path (IWP) and particle size in upper-tropospheric ice clouds. The first brightness temperatures images of ice clouds above 340 GHz were measured by the Compact Scanning Submillimeter Imaging Radiometer (CoSSIR) during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) campaign in July 2002. CoSSIR operated with 12 channels from receivers at 183, 220, 380, 487, and 640 GHz. CoSSIR and the nadir-viewing 94-GHz Cloud Radar System (CRS) flew on the NASA ER-2 airplane based out of Key West, Florida. A qualitative comparison of the CoSSIR brightness temperatures demonstrates that the submillimeter-wave frequencies are more sensitive to anvil ice cloud particles than are the lower frequencies. A Bayesian algorithm, with a priori microphysical information from in situ cloud probes, is used to retrieve the IWP and median mass equivalent sphere particle diameter (Dme). Mic...
{"title":"Ice Cloud Retrievals and Analysis with the Compact Scanning Submillimeter Imaging Radiometer and the Cloud Radar System during CRYSTAL FACE","authors":"K. F. Evans, James R. Wang, P. Racette, G. Heymsfield, Lihua Li","doi":"10.1175/JAM2250.1","DOIUrl":"https://doi.org/10.1175/JAM2250.1","url":null,"abstract":"Abstract Submillimeter-wave radiometry is a new technique for determining ice water path (IWP) and particle size in upper-tropospheric ice clouds. The first brightness temperatures images of ice clouds above 340 GHz were measured by the Compact Scanning Submillimeter Imaging Radiometer (CoSSIR) during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) campaign in July 2002. CoSSIR operated with 12 channels from receivers at 183, 220, 380, 487, and 640 GHz. CoSSIR and the nadir-viewing 94-GHz Cloud Radar System (CRS) flew on the NASA ER-2 airplane based out of Key West, Florida. A qualitative comparison of the CoSSIR brightness temperatures demonstrates that the submillimeter-wave frequencies are more sensitive to anvil ice cloud particles than are the lower frequencies. A Bayesian algorithm, with a priori microphysical information from in situ cloud probes, is used to retrieve the IWP and median mass equivalent sphere particle diameter (Dme). Mic...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"5 1","pages":"839-859"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88820556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Climate studies of precipitation have generally focused on daily or longer time scales of precipitation accumulation. The main objective of this work was to identify the precipitation characteristics of storms based on 15-min precipitation data, including storm total precipitation, storm duration, mean storm intensity, and maximum 15-min intensity. A group of precipitation characteristics was subjected to a cluster analysis that identified nine regions of the conterminous United States with homogeneous seasonal cycles of mean storm precipitation characteristics. Both mean and extreme statistics were derived for each characteristic and season for each zone. Continuous probability density functions were generated that appropriately fit the empirical distributions of storm total precipitation and maximum 15-min intensity. The storm characteristics, in turn, were a function of seasonal water availability from source regions, atmospheric water vapor capacity, and storm precipitation mechanism. This is...
{"title":"Storm Precipitation in the United States. Part I: Meteorological Characteristics.","authors":"M. Palecki, J. Angel, S. Hollinger","doi":"10.1175/JAM2243.1","DOIUrl":"https://doi.org/10.1175/JAM2243.1","url":null,"abstract":"Abstract Climate studies of precipitation have generally focused on daily or longer time scales of precipitation accumulation. The main objective of this work was to identify the precipitation characteristics of storms based on 15-min precipitation data, including storm total precipitation, storm duration, mean storm intensity, and maximum 15-min intensity. A group of precipitation characteristics was subjected to a cluster analysis that identified nine regions of the conterminous United States with homogeneous seasonal cycles of mean storm precipitation characteristics. Both mean and extreme statistics were derived for each characteristic and season for each zone. Continuous probability density functions were generated that appropriately fit the empirical distributions of storm total precipitation and maximum 15-min intensity. The storm characteristics, in turn, were a function of seasonal water availability from source regions, atmospheric water vapor capacity, and storm precipitation mechanism. This is...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"84 1","pages":"933-946"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90937781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract A simple semianalytical model of dispersion of nanoparticle aerosols from a busy road in the presence of intensive particle fragmentation is developed. In particular, it is predicted that the total number concentration may be characterized by a significant maximum at an optimal distance from the road. Simple analytical existence conditions of such a maximum are derived. Applicability conditions for the model and the effect of turbulent diffusion and dry deposition of nanoparticles on the theoretical predictions are also discussed. As a result of the comparison of the theoretical predictions with the experimental results on the total number concentration as a function of distance from the road, the typical fragmentation rate coefficient has been determined as ≈0.086 s−1, with an estimated error of ∼30%.
{"title":"Modeling of Aerosol Dispersion from a Busy Road in the Presence of Nanoparticle Fragmentation","authors":"D. Gramotnev, G. Gramotnev","doi":"10.1175/JAM2238.1","DOIUrl":"https://doi.org/10.1175/JAM2238.1","url":null,"abstract":"Abstract A simple semianalytical model of dispersion of nanoparticle aerosols from a busy road in the presence of intensive particle fragmentation is developed. In particular, it is predicted that the total number concentration may be characterized by a significant maximum at an optimal distance from the road. Simple analytical existence conditions of such a maximum are derived. Applicability conditions for the model and the effect of turbulent diffusion and dry deposition of nanoparticles on the theoretical predictions are also discussed. As a result of the comparison of the theoretical predictions with the experimental results on the total number concentration as a function of distance from the road, the typical fragmentation rate coefficient has been determined as ≈0.086 s−1, with an estimated error of ∼30%.","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"54 1","pages":"888-899"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74045979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Naud, J. Muller, E. Slack, C. Wrench, E. Clothiaux
Abstract The Chilbolton 3-GHz Advanced Meteorological Radar (CAMRa), which is mounted on a fully steerable 25-m dish, can provide three-dimensional information on the presence of hydrometeors. The potential for this radar to make useful measurements of low-altitude liquid water cloud structure is investigated. To assess the cloud-height assignment capabilities of the 3-GHz radar, low-level cloud-top heights were retrieved from CAMRa measurements made between May and July 2003 and were compared with cloud-top heights retrieved from a vertically pointing 94-GHz radar that operates alongside CAMRa. The average difference between the 94- and 3-GHz radar-derived cloud-top heights is shown to be −0.1 ± 0.4 km. To assess the capability of 3-GHz radar scans to be used for satellite-derived cloud-top-height validation, multiangle imaging spectroradiometer (MISR) cloud-top heights were compared with both 94- and 3-GHz radar retrievals. The average difference between 94-GHz radar and MISR cloud-top heights is shown ...
{"title":"Assessment of the Performance of the Chilbolton 3-GHz Advanced Meteorological Radar for Cloud-Top-Height Retrieval","authors":"C. Naud, J. Muller, E. Slack, C. Wrench, E. Clothiaux","doi":"10.1175/JAM2244.1","DOIUrl":"https://doi.org/10.1175/JAM2244.1","url":null,"abstract":"Abstract The Chilbolton 3-GHz Advanced Meteorological Radar (CAMRa), which is mounted on a fully steerable 25-m dish, can provide three-dimensional information on the presence of hydrometeors. The potential for this radar to make useful measurements of low-altitude liquid water cloud structure is investigated. To assess the cloud-height assignment capabilities of the 3-GHz radar, low-level cloud-top heights were retrieved from CAMRa measurements made between May and July 2003 and were compared with cloud-top heights retrieved from a vertically pointing 94-GHz radar that operates alongside CAMRa. The average difference between the 94- and 3-GHz radar-derived cloud-top heights is shown to be −0.1 ± 0.4 km. To assess the capability of 3-GHz radar scans to be used for satellite-derived cloud-top-height validation, multiangle imaging spectroradiometer (MISR) cloud-top heights were compared with both 94- and 3-GHz radar retrievals. The average difference between 94-GHz radar and MISR cloud-top heights is shown ...","PeriodicalId":15026,"journal":{"name":"Journal of Applied Meteorology","volume":"1 1","pages":"876-887"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84805076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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