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Ahmad W, Zhang K, Tong Y, Xiao D, Wu L, Liu D. Validation of the dual field-of-view polarization LIDAR technique for the retrieval of homogeneous water cloud microphysical properties: a study based on a polarimetric Monte Carlo simulation. APPLIED OPTICS 2022; 61:8936-8943. [PMID: 36607021 DOI: 10.1364/ao.468142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/19/2022] [Indexed: 06/17/2023]
Abstract
This article highlights the validation of the dual fields-of-view (FOVs) polarization lidar technique for the retrieval of cloud droplet effective radius in conjunction with cloud extinction coefficient of homogeneous water cloud via simulation approach. The simulation is based on polarimetric Monte Carlo method incorporated with semianalytic features under multiple-scattering conditions. The simulation results show that the depolarization ratio measured at dual-FOVs is a function of the cloud droplet effective radius and cloud extinction coefficient. Using the method of standard deviation on extensive simulation results and then by applying the polynomial regression, two polynomial relationships are obtained expressing the retrieval of the cloud droplet effective radius and cloud extinction coefficient from the layer integrated depolarization ratio at low optical depths close to the cloud bottom. Eventually, the results those presented by Ref.[1] are validated. The water cloud microphysical properties, liquid water content and cloud droplet number concentration are the functions of these two parameters and thus can be found numerically.
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Exploring the Potential of Optical Polarization Remote Sensing for Oil Spill Detection: A Case Study of Deepwater Horizon. REMOTE SENSING 2022. [DOI: 10.3390/rs14102398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Oil spills lead to catastrophic problems. In most oil spill cases, the spatial and temporal intractability of the detriment cannot be neglected, and problems related to economic, social and environmental factors constantly appear for a long time. Remote sensing has been widely used as a powerful means to conduct oil spill detection. Optical polarization remote sensing, thriving in recent years, shows a novel potential for oil spill detection. This paper provides a demonstration of the use of open-source POLDER/PARASOL polarization time-series data to detect oil spill. The Deepwater Horizon oil spill, one of the largest oil spill disasters, is utilized to explore the potential of optical polarization remote sensing for oil spill detection. A total of 24 feature combinations are organized to quantitatively study the positive effect of adding polarization information and the appropriate way to describe polarization characteristics. Random forest classifier models are trained with different combinations, and the results are assessed by 10-fold cross-validation. The improvement from adding polarization characteristics is remarkable ((average) accuracy: +0.51%; recall: +2.83%; precision: +3.49%; F1 score: +3.01%, (maximum) accuracy: +0.80%; recall: +5.09%; precision: +6.92%; F1 score: +4.72%), and coupling between the degree of polarization and the phase angle of polarization provides the best description of polarization information. This study confirms the potential of optical polarization remote sensing for oil spill detection, and some detailed problems related to model establishment and polarization feature characterization are discussed for the further application of polarization information.
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Abstract
Abstract
Satellite meteorology is a relatively new branch of the atmospheric sciences. The field emerged in the late 1950s during the Cold War and built on the advances in rocketry after World War II. In less than 70 years, satellite observations have transformed the way scientists observe and study Earth. This paper discusses some of the key advances in our understanding of the energy and water cycles, weather forecasting, and atmospheric composition enabled by satellite observations. While progress truly has been an international achievement, in accord with a monograph observing the centennial of the American Meteorological Society, as well as limited space, the emphasis of this chapter is on the U.S. satellite effort.
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Knobelspiesse K, Tan Q, Bruegge C, Cairns B, Chowdhary J, van Diedenhoven B, Diner D, Ferrare R, van Harten G, Jovanovic V, Ottaviani M, Redemann J, Seidel F, Sinclair K. Intercomparison of airborne multi-angle polarimeter observations from the Polarimeter Definition Experiment. APPLIED OPTICS 2019; 58:650-669. [PMID: 30694252 PMCID: PMC6996873 DOI: 10.1364/ao.58.000650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 10/31/2018] [Indexed: 06/09/2023]
Abstract
In early 2013, three airborne polarimeters were flown on the high altitude NASA ER-2 aircraft in California for the Polarimeter Definition Experiment (PODEX). PODEX supported the pre-formulation NASA Aerosol-Cloud-Ecosystem (ACE) mission, which calls for an imaging polarimeter in polar orbit (among other instruments) for the remote sensing of aerosols, oceans, and clouds. Several polarimeter concepts exist as airborne prototypes, some of which were deployed during PODEX as a capabilities test. Two of those instruments to date have successfully produced Level 1 (georegistered, calibrated radiance and polarization) data from that campaign: the Airborne Multiangle Spectropolarimetric Imager (AirMSPI) and the Research Scanning Polarimeter (RSP). We compared georegistered observations of a variety of scene types by these instruments to test whether Level 1 products agreed within stated uncertainties. Initial comparisons found radiometric agreement, but polarimetric biases beyond measurement uncertainties. After subsequent updates to calibration, georegistration, and the measurement uncertainty models, observations from the instruments now largely agree within stated uncertainties. However, the 470 nm reflectance channels have a roughly +6% bias of AirMSPI relative to RSP, beyond expected measurement uncertainties. We also find that observations of dark (ocean) scenes, where polarimetric uncertainty is expected to be largest, do not agree within stated polarimetric uncertainties. Otherwise, AirMSPI and RSP observations are consistent within measurement uncertainty expectations, providing credibility for the subsequent creation of Level 2 (geophysical product) data from these instruments, and comparison thereof. The techniques used in this work can also form a methodological basis for other intercomparisons, for example, of the data gathered during the recent Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign, carried out in October and November of 2017 with four polarimeters (including AirMSPI and RSP).
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Affiliation(s)
| | - Qian Tan
- NASA Ames Research Center, Moffett Field, CA, USA
- Bay Area Environmental Research Institute, Petaluma, CA, USA
| | - Carol Bruegge
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Brian Cairns
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Jacek Chowdhary
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, New York, NY, USA
| | - Bastiaan van Diedenhoven
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, New York, NY, USA
| | - David Diner
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | - Gerard van Harten
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Veljko Jovanovic
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Matteo Ottaviani
- NASA Goddard Institute for Space Studies, New York, NY, USA
- SciSpaceLLC, Bethesda, MD, USA
| | | | - Felix Seidel
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Kenneth Sinclair
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, New York, NY, USA
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5
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Frouin RJ, Franz BA, Ibrahim A, Knobelspiesse K, Ahmad Z, Cairns B, Chowdhary J, Dierssen HM, Tan J, Dubovik O, Huang X, Davis AB, Kalashnikova O, Thompson DR, Remer LA, Boss E, Coddington O, Deschamps PY, Gao BC, Gross L, Hasekamp O, Omar A, Pelletier B, Ramon D, Steinmetz F, Zhai PW. Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era. FRONTIERS IN EARTH SCIENCE 2019; 7:10.3389/feart.2019.00145. [PMID: 32440515 PMCID: PMC7241613 DOI: 10.3389/feart.2019.00145] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the top-of-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.
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Affiliation(s)
- Robert J. Frouin
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States
- Correspondence: Robert J. Frouin,
| | - Bryan A. Franz
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States
| | - Amir Ibrahim
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States
- Science Systems and Applications Inc., Lanham, MD, United States
| | - Kirk Knobelspiesse
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States
| | - Ziauddin Ahmad
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States
- Science Application International Corporation, McLean, VA, United States
| | - Brian Cairns
- NASA Goddard Institute for Space Studies, New York, NY, United States
| | - Jacek Chowdhary
- NASA Goddard Institute for Space Studies, New York, NY, United States
- Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, United States
| | - Heidi M. Dierssen
- Department of Marine Sciences, University of Connecticut, Groton, CT, United States
| | - Jing Tan
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States
| | - Oleg Dubovik
- Laboratoire d’Optique Atmosphérique, Université de Lille, Villeneuve d’Ascq, France
| | - Xin Huang
- Laboratoire d’Optique Atmosphérique, Université de Lille, Villeneuve d’Ascq, France
| | - Anthony B. Davis
- Jet Propulsion Laboratory, California Institute of Technology Pasadena, CA, United States
| | - Olga Kalashnikova
- Jet Propulsion Laboratory, California Institute of Technology Pasadena, CA, United States
| | - David R. Thompson
- Jet Propulsion Laboratory, California Institute of Technology Pasadena, CA, United States
| | - Lorraine A. Remer
- Joint Center for Earth System Technology, University of Maryland Baltimore County, Baltimore, MD, United States
| | - Emmanuel Boss
- School of Marine Sciences, University of Maine, Orono, ME, United States
| | - Odele Coddington
- Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO, United States
| | | | - Bo-Cai Gao
- Naval Research Laboratory, Washington, DC, United States
| | | | - Otto Hasekamp
- Earth Science Group, Netherlands Institute for Space Research, Utrecht, Netherlands
| | - Ali Omar
- Atmospheric Composition Branch, NASA Langley Research Center, Hampton, VA, United States
| | - Bruno Pelletier
- Institut de Recherche Mathématique, Université de Rennes, Rennes, Franc
| | | | | | - Peng-Wang Zhai
- Department of Physics, University of Maryland Baltimore County, Baltimore, MD, United States
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6
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Grosvenor DP, Sourdeval O, Zuidema P, Ackerman A, Alexandrov MD, Bennartz R, Boers R, Cairns B, Chiu JC, Christensen M, Deneke H, Diamond M, Feingold G, Fridlind A, Hünerbein A, Knist C, Kollias P, Marshak A, McCoy D, Merk D, Painemal D, Rausch J, Rosenfeld D, Russchenberg H, Seifert P, Sinclair K, Stier P, van Diedenhoven B, Wendisch M, Werner F, Wood R, Zhang Z, Quaas J. Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives. REVIEWS OF GEOPHYSICS (WASHINGTON, D.C. : 1985) 2018; 56:409-453. [PMID: 30148283 PMCID: PMC6099364 DOI: 10.1029/2017rg000593] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 04/05/2018] [Accepted: 04/06/2018] [Indexed: 05/13/2023]
Abstract
The cloud droplet number concentration (N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol-cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel-level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high-quality ground-based observations are examined.
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Affiliation(s)
| | - Odran Sourdeval
- Leipzig Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - Paquita Zuidema
- Department of Atmospheric SciencesRosenstiel School of Marine and Atmospheric ScienceMiamiFLUSA
| | | | - Mikhail D. Alexandrov
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
- Department of Applied Physics and Applied MathematicsColumbia UniversityNew YorkNYUSA
| | - Ralf Bennartz
- Department of Earth and Environmental SciencesVanderbilt UniversityNashvilleTNUSA
- Space Science and Engineering CenterUniversity of Wisconsin‐MadisonMadisonWIUSA
| | - Reinout Boers
- Royal Netherlands Meteorological InstituteDe BiltThe Netherlands
| | - Brian Cairns
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
| | - J. Christine Chiu
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - Matthew Christensen
- Rutherford Appleton LaboratoryHarwellUK
- Department of PhysicsUniversity of OxfordOxfordUK
| | - Hartwig Deneke
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | - Michael Diamond
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | - Graham Feingold
- Chemical Sciences Division, Earth System Research LaboratoryNational Oceanic and Atmospheric AdministrationBoulderCOUSA
| | - Ann Fridlind
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
| | - Anja Hünerbein
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | | | - Pavlos Kollias
- School of Marine and Atmospheric SciencesStony Brook UniversityStony BrookNYUSA
| | | | - Daniel McCoy
- School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Daniel Merk
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | | | - John Rausch
- Department of Earth and Environmental SciencesVanderbilt UniversityNashvilleTNUSA
| | - Daniel Rosenfeld
- Institute of Earth SciencesThe Hebrew University of JerusalemJerusalemIsrael
| | - Herman Russchenberg
- Department of Geoscience and Remote SensingDelft University of TechnologyDelftThe Netherlands
| | - Patric Seifert
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | - Kenneth Sinclair
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
- Department of Earth and Environmental EngineeringColumbia UniversityNew YorkNYUSA
| | - Philip Stier
- Department of PhysicsUniversity of OxfordOxfordUK
| | - Bastiaan van Diedenhoven
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
- Center for Climate Systems ResearchColumbia UniversityNew YorkNYUSA
| | - Manfred Wendisch
- Leipzig Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - Frank Werner
- Joint Center for Earth Systems TechnologyBaltimoreMDUSA
| | - Robert Wood
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | | | - Johannes Quaas
- Leipzig Institute for MeteorologyUniversität LeipzigLeipzigGermany
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7
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Kikuchi M, Okamoto H, Sato K, Suzuki K, Cesana G, Hagihara Y, Takahashi N, Hayasaka T, Oki R. Development of Algorithm for Discriminating Hydrometeor Particle Types with a Synergistic Use of CloudSat and CALIPSO. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2017; 122:11022-11044. [PMID: 32818127 PMCID: PMC7430508 DOI: 10.1002/2017jd027113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
We developed a method for classifying hydrometeor particle types, including cloud and precipitation phase and ice crystal habit, by a synergistic use of CloudSat/Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). We investigated how the cloud phase and ice crystal habit characterized by CALIOP globally relate with radar reflectivity and temperature. The global relationship thus identified was employed to develop an algorithm for hydrometeor type classification with CPR alone. The CPR-based type classification was then combined with CALIPSO-based type characterization to give CPR-CALIOP synergy classification. A unique aspect of this algorithm is to exploit and combine the lidar's sensitivity to thin ice clouds and the radar's ability to penetrate light precipitation to offer more complete picture of vertically resolved hydrometeor type classification than has been provided by previous studies. Given the complementary nature of radar and lidar detections of hydrometeors, our algorithm delivers thirteen hydrometeor types: warm water, supercooled water, randomly-oriented ice crystal (3D-ice), horizontally-oriented plate (2D-plate), 3D-ice+2D-plate, liquid drizzle, mixed-phase drizzle, rain, snow, mixed-phase cloud, water+liquid drizzle, water+rain and unknown. The global statistics of three-dimensional occurrence frequency of each hydrometeor type revealed that 3D-ice contributes the most to the total cloud occurrence frequency (53.8%), followed by supercooled water (14.3%), 2D-plate (9.2%), rain (5.9%), warm water (5.7%), snow (4.8%), mixed-phase drizzle (2.3%), and the remaining types (4.0%). This hydrometeor type classification provides useful observation-based information for climate model diagnostics in representation of cloud phase and their microphysical characteristics.
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Affiliation(s)
- M Kikuchi
- Earth Observation Research Center, Japan Aerospace Exploration Agency, Ibaraki, Japan
| | - H Okamoto
- Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan
| | - K Sato
- Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan
| | - K Suzuki
- Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan
| | - G Cesana
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
- Goddard Institute for Space Studies, Columbia University, New York, New York, USA
| | - Y Hagihara
- Earth Observation Research Center, Japan Aerospace Exploration Agency, Ibaraki, Japan
| | - N Takahashi
- Hydrospheric Atmospheric Research Center, Nagoya University, Aichi, Japan
| | - T Hayasaka
- Center for Atmospheric and Oceanic Studies, Tohoku University, Miyagi, Japan
| | - R Oki
- Earth Observation Research Center, Japan Aerospace Exploration Agency, Ibaraki, Japan
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8
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Korolev A, McFarquhar G, Field PR, Franklin C, Lawson P, Wang Z, Williams E, Abel SJ, Axisa D, Borrmann S, Crosier J, Fugal J, Krämer M, Lohmann U, Schlenczek O, Schnaiter M, Wendisch M. Mixed-Phase Clouds: Progress and Challenges. ACTA ACUST UNITED AC 2017. [DOI: 10.1175/amsmonographs-d-17-0001.1] [Citation(s) in RCA: 120] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Affiliation(s)
- A. Korolev
- Environment and Climate Change Canada, Toronto, Ontario, Canada
| | - G. McFarquhar
- University of Illinois at Urbana–Champaign, Urbana, Illinois
| | - P. R. Field
- Met Office, Exeter, United Kingdom
- University of Leeds, Leeds, United Kingdom
| | - C. Franklin
- Bureau of Meteorology, Melbourne, Victoria, Australia
| | - P. Lawson
- Stratton Park Engineering Corporation, Boulder, Colorado
| | - Z. Wang
- University of Wyoming, Laramie, Wyoming
| | - E. Williams
- Massachusetts Institute of Technology, Cambridge, Massachusetts
| | | | - D. Axisa
- National Center for Atmospheric Research, Boulder, Colorado
| | - S. Borrmann
- Max Planck Institute for Chemistry, Mainz, Germany
| | - J. Crosier
- School of Earth and Environment, University of Manchester, Manchester, United Kingdom
- National Centre for Atmospheric Science, University of Manchester, Manchester, United Kingdom
| | - J. Fugal
- Institute for Atmospheric Physics, University of Mainz, Mainz, Germany
| | - M. Krämer
- Forschungszentrum Jülich, Jülich, Germany
| | - U. Lohmann
- ETH Zurich, Institute for Atmospheric and Climate Science, Zurich, Switzerland
| | - O. Schlenczek
- Institute for Atmospheric Physics, University of Mainz, Mainz, Germany
| | - M. Schnaiter
- Karlsruhe Institute of Technology, Karlsruhe, Germany
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9
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Marchant B, Platnick S, Meyer K, Arnold GT, Riedi J. MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP. ATMOSPHERIC MEASUREMENT TECHNIQUES 2016; 9:1587-1599. [PMID: 32818045 PMCID: PMC7430206 DOI: 10.5194/amt-9-1587-2016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.
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Affiliation(s)
- Benjamin Marchant
- 1) USRA Universities Space Research Association, Columbia, Maryland, USA
- 2) NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Steven Platnick
- 2) NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Kerry Meyer
- 1) USRA Universities Space Research Association, Columbia, Maryland, USA
- 2) NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - G. Thomas Arnold
- 2) NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- 3) SSAI (Science Systems and Application Inc)
| | - Jérôme Riedi
- 4) LOA (Laboratoire d’Optique Atmospherique), Université Lille 1, France
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10
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Pust NJ, Shaw JA. Digital all-sky polarization imaging of partly cloudy skies. APPLIED OPTICS 2008; 47:H190-8. [PMID: 19037342 DOI: 10.1364/ao.47.00h190] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Clouds reduce the degree of linear polarization (DOLP) of skylight relative to that of a clear sky. Even thin subvisual clouds in the "twilight zone" between clouds and aerosols produce a drop in skylight DOLP long before clouds become visible in the sky. In contrast, the angle of polarization (AOP) of light scattered by a cloud in a partly cloudy sky remains the same as in the clear sky for most cases. In unique instances, though, select clouds display AOP signatures that are oriented 90 degrees from the clear-sky AOP. For these clouds, scattered light oriented parallel to the scattering plane dominates the perpendicularly polarized Rayleigh-scattered light between the instrument and the cloud. For liquid clouds, this effect may assist cloud particle size identification because it occurs only over a relatively limited range of particle radii that will scatter parallel polarized light. Images are shown from a digital all-sky-polarization imager to illustrate these effects. Images are also shown that provide validation of previously published theories for weak (approximately 2%) polarization parallel to the scattering plane for a 22 degrees halo.
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Affiliation(s)
- Nathan J Pust
- Department of Electrical and Computer Engineering, 610 Cobleigh Hall,Montana State University, Bozeman, Montana 59717, USA
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11
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Loisel H, Duforet L, Dessailly D, Chami M, Dubuisson P. Investigation of the variations in the water leaving polarized reflectance from the POLDER satellite data over two biogeochemical contrasted oceanic areas. OPTICS EXPRESS 2008; 16:12905-12918. [PMID: 18711530 DOI: 10.1364/oe.16.012905] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
The biogeochemical characterization of marine particles suspended in sea water, is of fundamental importance in many areas of ocean science. Previous studies based on theoretical calculations and field measurements have demonstrated the importance of the use of the polarized light field in the retrieval of the suspended marine particles properties. However, because of the weakness of the water leaving polarized signal and of the limited number of appropriate spatial sensors, such measurements have never been exploited from space. Here we show that the marine polarized remote sensing reflectance, as detected from the POLarization and Directionality of the Earth's Reflectances (POLDER) sensor, can be measured from space over bright waters and in absence of aerosols. This feasibility study is carried out over two oceanic areas characterized by different nature of the bulk particulate assemblage: the Barents sea during an intense coccolithophore bloom, and the Rio de la Plata estuary waters dominated by suspended sediments. The retrieved absolute values of the degree of polarization, P, its angular pattern, and its behavior with the scattering level are consistent with theory and field measurements. Radiative transfer simulations confirm the sensitivity of the POLDER-2 P values to the nature of the particulate assemblage. These preliminary results are very promising for the assessment of the bulk particle composition from remote sensing of the polarized signal, at least over highly scattering waters.
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Affiliation(s)
- Hubert Loisel
- Université du Littoral Côte d'Opale, Laboratoire d'Océanologie et de Géosciences, 62930 Wimereux, France
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Weidle F, Wernli H. Comparison of ERA40 cloud top phase with POLDER-1 observations. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd009234] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Florian Weidle
- Institute for Atmospheric Physics; University of Mainz; Mainz Germany
| | - Heini Wernli
- Institute for Atmospheric Physics; University of Mainz; Mainz Germany
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Abstract
Current proposals for the characterization of extrasolar terrestrial planets rest primarily on the use of spectroscopic techniques. While spectroscopy is effective in detecting the gaseous components of a planet's atmosphere, it provides no way of detecting the presence of liquid water, the defining characteristic of a habitable planet. In this paper, I investigate the potential of an alternative technique for characterizing the atmosphere of a planet using polarization. By looking for a polarization peak at the "primary rainbow" scattering angle, it is possible to detect the presence of liquid droplets in a planet's atmosphere and constrain the nature of the liquid through its refractive index. Single scattering calculations are presented to show that a well-defined rainbow scattering peak is present over the full range of likely cloud droplet sizes and clearly distinguishes the presence of liquid droplets from solid particles such as ice or dust. Rainbow scattering has been used in the past to determine the nature of the cloud droplets in the Venus atmosphere and by the POLarization and Directionality of Earth Reflectances (POLDER) instrument to distinguish between liquid and ice clouds in the Earth atmosphere. While the presence of liquid water clouds does not guarantee the presence of water at the surface, this technique could complement spectroscopic techniques for characterizing the atmospheres of potential habitable planets. The disk-integrated rainbow peak for Earth is estimated to be at a degree of polarization of 12.7% or 15.5% for two different cloud cover scenarios. The observation of this rainbow peak is shown to be feasible with the proposed Terrestrial Planet Finder Coronograph mission in similar total integration times to those required for spectroscopic characterization.
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Affiliation(s)
- Jeremy Bailey
- Australian Centre for Astrobiology, Macquarie University, Sydney, New South Wales, Australia.
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Knap WH, Labonnote LC, Brogniez G, Stammes P. Modeling total and polarized reflectances of ice clouds: evaluation by means of POLDER and ATSR-2 measurements. APPLIED OPTICS 2005; 44:4060-73. [PMID: 16004054 DOI: 10.1364/ao.44.004060] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Four ice-crystal models are tested by use of ice-cloud reflectances derived from Along Track Scanning Radiometer-2 (ATSR-2) and Polarization and Directionality of Earth's Reflectances (POLDER) radiance measurements. The analysis is based on dual-view ATSR-2 total reflectances of tropical cirrus and POLDER global-scale total and polarized reflectances of ice clouds at as many as 14 viewing directions. Adequate simulations of ATSR-2 total reflectances at 0.865 microm are obtained with model clouds consisting of moderately distorted imperfect hexagonal monocrystals (IMPs). The optically thickest clouds (tau > approximately 16) in the selected case tend to be better simulated by use of pure hexagonal monocrystals (PHMs). POLDER total reflectances at 0.670 microm are best simulated with columnar or platelike IMPs or columnar inhomogeneous hexagonal monocrystals (IHMs). Less-favorable simulations are obtained for platelike IHMs and polycrystals (POLYs). Inadequate simulations of POLDER total and polarized reflectances are obtained for model clouds consisting of PHMs. Better simulations of the POLDER polarized reflectances at 0.865 microm are obtained with IMPs, IHMs, or POLYs, although POLYs produce polarized reflectances that are systematically lower than most of the measurements. The best simulations of the polarized reflectance for the ice-crystal models assumed in this study are obtained for model clouds consisting of columnar IMPs or IHMs.
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Affiliation(s)
- Wouter H Knap
- Royal Netherlands Meteorological Institute, PO Box 201, 3730 AE De Bilt, The Netherlands.
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15
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Kokhanovsky AA. A semianalytical cloud retrieval algorithm using backscattered radiation in 0.4–2.4 μm spectral region. ACTA ACUST UNITED AC 2003. [DOI: 10.1029/2001jd001543] [Citation(s) in RCA: 79] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Chepfer H, Goloub P, Riedi J, De Haan JF, Hovenier JW, Flamant PH. Ice crystal shapes in cirrus clouds derived from POLDER/ADEOS-1. ACTA ACUST UNITED AC 2001. [DOI: 10.1029/2000jd900285] [Citation(s) in RCA: 56] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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