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Optical Property Model for Cirrus Clouds Based on Airborne Multi-Angle Polarization Observations. REMOTE SENSING 2021. [DOI: 10.3390/rs13142754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
We present an improved remote sensing technique to infer an optimal habit/shape model for ice particles in cirrus clouds using multi-angle polarimetric measurements at 865 nm made by the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI) instrument. The common method of ice model inference is based on intensity (total reflectivity) measurements, which is generally not applicable to optically thin ice clouds (i.e., cirrus clouds) where single scattering dominates. The new approach is able to infer an ice model in clouds with optical thicknesses smaller than 5. The improvement is made by first assuming the optical thickness retrieved using total reflectivity. Subsequently, the polarized reflectivity is calculated based on look-up tables generated from simulated polarized reflectances computed for cirrus clouds in conjunction with eight ice particle models. The ice particle model that leads to the closest fit to the measurements is regarded as the optimal ice particle model. Additionally, an alternative method is applied that does not consider polarized reflectivity. These two methods are applied to a data sample as a proof-of-concept study where AirMSPI observed a single cirrus layer. In this case study, the hexagonal column aggregate model works for most pixels both with and without considering polarized reflectivities. The retrieval cost function is high when the camera pairs with large zenith angles are included in the retrievals. This result suggests that further studies will be necessary to have a better understanding of all eight selected ice particle models at scattering angles smaller than 100°.
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Bellouin N, Quaas J, Gryspeerdt E, Kinne S, Stier P, Watson‐Parris D, Boucher O, Carslaw KS, Christensen M, Daniau A, Dufresne J, Feingold G, Fiedler S, Forster P, Gettelman A, Haywood JM, Lohmann U, Malavelle F, Mauritsen T, McCoy DT, Myhre G, Mülmenstädt J, Neubauer D, Possner A, Rugenstein M, Sato Y, Schulz M, Schwartz SE, Sourdeval O, Storelvmo T, Toll V, Winker D, Stevens B. Bounding Global Aerosol Radiative Forcing of Climate Change. REVIEWS OF GEOPHYSICS (WASHINGTON, D.C. : 1985) 2020; 58:e2019RG000660. [PMID: 32734279 PMCID: PMC7384191 DOI: 10.1029/2019rg000660] [Citation(s) in RCA: 91] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 09/30/2019] [Accepted: 10/03/2019] [Indexed: 05/04/2023]
Abstract
Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol-radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of -1.6 to -0.6 W m-2, or -2.0 to -0.4 W m-2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial-era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.
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Affiliation(s)
- N. Bellouin
- Department of MeteorologyUniversity of ReadingReadingUK
| | - J. Quaas
- Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - E. Gryspeerdt
- Space and Atmospheric Physics GroupImperial College LondonLondonUK
| | - S. Kinne
- Max Planck Institute for MeteorologyHamburgGermany
| | - P. Stier
- Atmospheric, Oceanic and Planetary Physics, Department of PhysicsUniversity of OxfordOxfordUK
| | - D. Watson‐Parris
- Atmospheric, Oceanic and Planetary Physics, Department of PhysicsUniversity of OxfordOxfordUK
| | - O. Boucher
- Institut Pierre‐Simon Laplace, Sorbonne Université/CNRSParisFrance
| | - K. S. Carslaw
- School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - M. Christensen
- Atmospheric, Oceanic and Planetary Physics, Department of PhysicsUniversity of OxfordOxfordUK
| | - A.‐L. Daniau
- EPOC, UMR 5805, CNRS‐Université de BordeauxPessacFrance
| | - J.‐L. Dufresne
- Laboratoire de Météorologie Dynamique/IPSL, CNRS, Sorbonne Université, Ecole Normale Supérieure, PSL Research University, Ecole PolytechniqueParisFrance
| | - G. Feingold
- NOAA ESRL Chemical Sciences DivisionBoulderCOUSA
| | - S. Fiedler
- Max Planck Institute for MeteorologyHamburgGermany
- Now at Institut für Geophysik und MeteorologieUniversität zu KölnKölnGermany
| | - P. Forster
- Priestley International Centre for ClimateUniversity of LeedsLeedsUK
| | - A. Gettelman
- National Center for Atmospheric ResearchBoulderCOUSA
| | - J. M. Haywood
- CEMPSUniversity of ExeterExeterUK
- UK Met Office Hadley CentreExeterUK
| | - U. Lohmann
- Institute for Atmospheric and Climate ScienceETH ZürichZürichSwitzerland
| | | | - T. Mauritsen
- Department of MeteorologyStockholm UniversityStockholmSweden
| | - D. T. McCoy
- School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - G. Myhre
- Center for International Climate and Environmental Research‐Oslo (CICERO)OsloNorway
| | - J. Mülmenstädt
- Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - D. Neubauer
- Institute for Atmospheric and Climate ScienceETH ZürichZürichSwitzerland
| | - A. Possner
- Department of Global EcologyCarnegie Institution for ScienceStanfordCAUSA
- Now at Institute for Atmospheric and Environmental SciencesGoethe UniversityFrankfurtGermany
| | | | - Y. Sato
- Department of Applied Energy, Graduate School of Engineering, Nagoya UniversityNagoyaJapan
- Now at Faculty of Science, Department of Earth and Planetary SciencesHokkaido UniversitySapporoJapan
| | - M. Schulz
- Climate Modelling and Air Pollution Section, Research and Development DepartmentNorwegian Meteorological InstituteOsloNorway
| | - S. E. Schwartz
- Brookhaven National Laboratory Environmental and Climate Sciences DepartmentUptonNYUSA
| | - O. Sourdeval
- Institute for MeteorologyUniversität LeipzigLeipzigGermany
- Laboratoire d'Optique AtmosphériqueUniversité de LilleVilleneuve d'AscqFrance
| | - T. Storelvmo
- Department of GeosciencesUniversity of OsloOsloNorway
| | - V. Toll
- Department of MeteorologyUniversity of ReadingReadingUK
- Now at Institute of PhysicsUniversity of TartuTartuEstonia
| | - D. Winker
- NASA Langley Research CenterHamptonVAUSA
| | - B. Stevens
- Max Planck Institute for MeteorologyHamburgGermany
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Gryspeerdt E, Mülmenstädt J, Gettelman A, Malavelle FF, Morrison H, Neubauer D, Partridge DG, Stier P, Takemura T, Wang H, Wang M, Zhang K. Surprising similarities in model and observational aerosol radiative forcing estimates. ATMOSPHERIC CHEMISTRY AND PHYSICS 2020; 20:613-623. [PMID: 33204244 PMCID: PMC7668122 DOI: 10.5194/acp-20-613-2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The radiative forcing from aerosols (particularly through their interaction with clouds) remains one of the most uncertain components of the human forcing of the climate. Observation-based studies have typically found a smaller aerosol effective radiative forcing than in model simulations and were given preferential weighting in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). With their own sources of uncertainty, it is not clear that observation-based estimates are more reliable. Understanding the source of the model and observational differences is thus vital to reduce uncertainty in the impact of aerosols on the climate. These reported discrepancies arise from the different methods of separating the components of aerosol forcing used in model and observational studies. Applying the observational decomposition to global climate model (GCM) output, the two different lines of evidence are surprisingly similar, with a much better agreement on the magnitude of aerosol impacts on cloud properties. Cloud adjustments remain a significant source of uncertainty, particularly for ice clouds. However, they are consistent with the uncertainty from observation-based methods, with the liquid water path adjustment usually enhancing the Twomey effect by less than 50%. Depending on different sets of assumptions, this work suggests that model and observation-based estimates could be more equally weighted in future synthesis studies.
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Affiliation(s)
- Edward Gryspeerdt
- Space and Atmospheric Physics Group, Imperial College London, London, UK
| | | | | | - Florent F. Malavelle
- College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, UK
- Met Office, Fitzroy Road, Exeter, UK
| | - Hugh Morrison
- National Center for Atmospheric Research, Boulder, USA
| | - David Neubauer
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
| | - Daniel G. Partridge
- College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, UK
| | - Philip Stier
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
| | - Toshihiko Takemura
- Research Institute for Applied Mathematics, Kyushu University, Fukuoka, Japan
| | - Hailong Wang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, USA
| | - Minghuai Wang
- Institute for Climate and Global Change Research, Nanjing University, Nanjing, China
- School of Atmospheric Sciences, Nanjing University, Nanjing, China
- Collaborative Innovation Center of Climate Change, Nanjing, China
| | - Kai Zhang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, USA
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