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Matthew D. Shupe - One of the best experts on this subject based on the ideXlab platform.
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an intercomparison of microphysical retrieval algorithms for upper tropospheric ice clouds
Bulletin of the American Meteorological Society, 2007Co-Authors: Jennifer M. Comstock, David L. Mitchell, Patrick Minnis, Sergey Y Matrosov, Kenneth Sassen, Daniel H. Deslover, Gerald G. Mace, Sally A. Mcfarlane, Robert P Dentremont, Matthew D. ShupeAbstract:The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth's future climate. A number of passive and Active Remote Sensing retrieval algorithms exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade, however, there is room for improvement. Members of the Atmospheric Radiation measurement program (ARM) Cloud properties Working Group are involved in an intercomparison of optical depth(tau), ice water path, and characteristic particle size in clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement.
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An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds
Bulletin of the American Meteorological Society, 2007Co-Authors: Jennifer M. Comstock, David L. Mitchell, Patrick Minnis, Sergey Y Matrosov, Kenneth Sassen, Robert P. D'entremont, Daniel H. Deslover, Gerald G. Mace, Sally A. Mcfarlane, Matthew D. ShupeAbstract:The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and Active Remote Sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice ...
Patrick Minnis - One of the best experts on this subject based on the ideXlab platform.
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an intercomparison of microphysical retrieval algorithms for upper tropospheric ice clouds
Bulletin of the American Meteorological Society, 2007Co-Authors: Jennifer M. Comstock, David L. Mitchell, Patrick Minnis, Sergey Y Matrosov, Kenneth Sassen, Daniel H. Deslover, Gerald G. Mace, Sally A. Mcfarlane, Robert P Dentremont, Matthew D. ShupeAbstract:The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth's future climate. A number of passive and Active Remote Sensing retrieval algorithms exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade, however, there is room for improvement. Members of the Atmospheric Radiation measurement program (ARM) Cloud properties Working Group are involved in an intercomparison of optical depth(tau), ice water path, and characteristic particle size in clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement.
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Comparison of CALIPSO-like, LaRC, and MODIS retrievals of ice-cloud properties over SIRTA in France and Florida during CRYSTAL-FACE
Journal of Applied Meteorology and Climatology, 2007Co-Authors: Marjolaine Chiriaco, Hélène Chepfer, Pierrette Dubuisson, Darrel Baumgardner, Mark Mcgill, Martial Haeffelin, Steven Platnick, Véronique Noël, Patrick Minnis, Jacques PelonAbstract:This study compares cirrus-cloud properties and, in particular, particle effective radius retrieved by a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-like method with two similar methods using Moderate-Resolution Imaging Spectroradiometer ( MODIS), MODIS Airborne Simulator (MAS), and Geostationary Operational Environmental Satellite imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-mu m bands to infer the microphysical properties of cirrus clouds. The two other methods, using passive Remote Sensing at visible and infrared wavelengths, are the operational MODIS cloud products (using 20 spectral bands from visible to infrared, referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the Clouds and the Earth's Radiant Energy System (CERES) team at Langley Research Center (LaRC) in support of CERES algorithms (using 0.65-, 3.75-, 10.8-, and 12.05-mu m bands); the two algorithms will be referred to as the MOD06 and LaRC methods, respectively. The three techniques are compared at two different latitudes. The midlatitude ice-clouds study uses 16 days of observations at the Palaiseau ground-based site in France [Site Instrumental de Recherche par Teledetection Atmospherique (SIRTA)], including a ground-based 532-nm lidar and the MODIS overpasses on the Terra platform. The tropical ice-clouds study uses 14 different flight legs of observations collected in Florida during the intensive field experiment known as the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE), including the airborne cloud-physics lidar and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness but discrepancies in cloud detection and altitudes. The study confirms the value of an Active Remote Sensing method (CALIPSO like) for the study of subvisible ice clouds, in both the midlatitudes and Tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds, because of their particular microphysical properties.
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An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds
Bulletin of the American Meteorological Society, 2007Co-Authors: Jennifer M. Comstock, David L. Mitchell, Patrick Minnis, Sergey Y Matrosov, Kenneth Sassen, Robert P. D'entremont, Daniel H. Deslover, Gerald G. Mace, Sally A. Mcfarlane, Matthew D. ShupeAbstract:The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and Active Remote Sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice ...
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a 3 year climatology of cloud and radiative properties derived from goes 8 data over the southern great plains
11th ARM Science Team Meeting Proceedings, 2001Co-Authors: Mandana M Khaiyer, William L Smith, Patrick Minnis, Anita D Rapp, Michele L Nordeen, D R Doelling, L NguyenAbstract:While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.
Jennifer M. Comstock - One of the best experts on this subject based on the ideXlab platform.
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an intercomparison of microphysical retrieval algorithms for upper tropospheric ice clouds
Bulletin of the American Meteorological Society, 2007Co-Authors: Jennifer M. Comstock, David L. Mitchell, Patrick Minnis, Sergey Y Matrosov, Kenneth Sassen, Daniel H. Deslover, Gerald G. Mace, Sally A. Mcfarlane, Robert P Dentremont, Matthew D. ShupeAbstract:The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth's future climate. A number of passive and Active Remote Sensing retrieval algorithms exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade, however, there is room for improvement. Members of the Atmospheric Radiation measurement program (ARM) Cloud properties Working Group are involved in an intercomparison of optical depth(tau), ice water path, and characteristic particle size in clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement.
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An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds
Bulletin of the American Meteorological Society, 2007Co-Authors: Jennifer M. Comstock, David L. Mitchell, Patrick Minnis, Sergey Y Matrosov, Kenneth Sassen, Robert P. D'entremont, Daniel H. Deslover, Gerald G. Mace, Sally A. Mcfarlane, Matthew D. ShupeAbstract:The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and Active Remote Sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice ...
Scott C Doney - One of the best experts on this subject based on the ideXlab platform.
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on the ability of space based passive and Active Remote Sensing observations of co2 to detect flux perturbations to the carbon cycle
Journal of Geophysical Research, 2018Co-Authors: Sean Crowell, Randolph S Kawa, Edward V Browell, Dorit Hammerling, Berrien Moore, Kevin Schaefer, Scott C DoneyAbstract:Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT (Greenhouse Gases Observing Satellite) and OCO-2 (Orbiting Carbon Observatory 2), however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an Active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint. Plain Language Summary: Active and passive Remote sensors show the potential to provide unprecedented information on the carbon cycle. With the all-season sampling, Active Remote sensors are more capable of constraining high-latitude emissions. The reduced sensitivity to cloud and aerosol also makes Active sensors more capable of providing information in cloudy and polluted scenes with sufficient accuracy. These experiments account for errors that are fundamental to the top-down approach for constraining emissions, and even including these sources of error, we show that satellite Remote sensors are critical for understanding the carbon cycle.
Guosheng Liu - One of the best experts on this subject based on the ideXlab platform.
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dependence of the ice water content and snowfall rate on temperature globally comparison of in situ observations satellite Active Remote Sensing retrievals and global climate model simulations
Journal of Applied Meteorology and Climatology, 2017Co-Authors: Andrew J Heymsfield, Martina Kramer, Norman B Wood, Andrew Gettelman, Paul R Field, Guosheng LiuAbstract:AbstractCloud ice microphysical properties measured or estimated from in situ aircraft observations are compared with global climate models and satellite Active Remote sensor retrievals. Two large datasets, with direct measurements of the ice water content (IWC) and encompassing data from polar to tropical regions, are combined to yield a large database of in situ measurements. The intention of this study is to identify strengths and weaknesses of the various methods used to derive ice cloud microphysical properties. The in situ data are measured with total water hygrometers, condensed water probes, and particle spectrometers. Data from polar, midlatitude, and tropical locations are included. The satellite data are retrieved from CloudSat/CALIPSO [the CloudSat Ice Cloud Property Product (2C-ICE) and 2C-SNOW-PROFILE] and Global Precipitation Measurement (GPM) Level2A. Although the 2C-ICE retrieval is for IWC, a method to use the IWC to get snowfall rates S is developed. The GPM retrievals are for snowfall ...
