{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:14:54Z","timestamp":1760166894075,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T00:00:00Z","timestamp":1626134400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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\u00b0.<\/jats:p>","DOI":"10.3390\/rs13142754","type":"journal-article","created":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T22:25:31Z","timestamp":1626215131000},"page":"2754","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Optical Property Model for Cirrus Clouds Based on Airborne Multi-Angle Polarization Observations"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3202-1602","authenticated-orcid":false,"given":"Yi","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2645-7298","authenticated-orcid":false,"given":"Michael D.","family":"King","sequence":"additional","affiliation":[{"name":"Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA"},{"name":"Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO 80309, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7193-2767","authenticated-orcid":false,"given":"Bryan A.","family":"Baum","sequence":"additional","affiliation":[{"name":"Science and Technology Corporation (STC), Madison, WI 53705, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"16973","DOI":"10.1029\/96JD01155","article-title":"Sensitivity of cirrus cloud albedo, bidirectional reflectance and optical thickness retrieval accuracy to ice particle shape","volume":"101","author":"Mishchenko","year":"1996","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1016\/j.jqsrt.2009.02.026","article-title":"A review of the light scattering properties of cirrus","volume":"110","author":"Baran","year":"2009","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1007\/s00376-014-0011-z","article-title":"On the radiative properties of ice clouds: Light scattering, remote sensing, and radiation parameterization","volume":"32","author":"Yang","year":"2015","journal-title":"Adv. Atmos. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1851","DOI":"10.1175\/JCLI-D-17-0426.1","article-title":"Impact of ice cloud microphysics on satellite cloud retrievals and broadband flux radiative transfer model calculations","volume":"31","author":"Loeb","year":"2018","journal-title":"J. Clim."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1109\/36.297978","article-title":"The POLDER mission: Instrument characteristics and scientific objectives","volume":"32","author":"Deschamps","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1072","DOI":"10.1109\/36.700992","article-title":"Multi-angle Imaging SpectroRadiometer (MISR) instrument description and experiment overview","volume":"36","author":"Diner","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"12126","DOI":"10.1029\/2019JD030457","article-title":"Ice cloud optical thickness, effective radius, and ice water path inferred from fused MISR and MODIS measurements based on a pixel-level optimal ice particle roughness model","volume":"124","author":"Wang","year":"2019","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1029\/1999GL010870","article-title":"Sensitivity of retrieved POLDER directional cloud optical thickness to various ice particle models","volume":"27","author":"Buriez","year":"2000","journal-title":"Geophys. Res. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"McFarlane, S.A., Marchand, R.T., and Ackerman, T.P. (2005). Retrieval of cloud phase and crystal habit from Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. J. Geophys. Res. Atmos., 110.","DOI":"10.1029\/2004JD004831"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4219","DOI":"10.1080\/01431161.2011.642323","article-title":"Determination of ice cloud models using MODIS and MISR data","volume":"33","author":"Xie","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wang, Y., Hioki, S., Yang, P., King, M.D., Di Girolamo, L., Fu, D., and Baum, B.A. (2018). Inference of an optimal ice particle model through latitudinal analysis of MISR and MODIS data. Remote Sens., 10.","DOI":"10.3390\/rs10121981"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chepfer, H., Minnis, P., Young, D., Nguyen, L., and Arduini, R.F. (2002). Estimation of cirrus cloud effective ice crystal shapes using visible reflectances from dual-satellite measurements. J. Geophys. Res. Atmos., 107.","DOI":"10.1029\/2000JD000240"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1016\/j.jqsrt.2006.02.071","article-title":"On the retrieval of ice cloud particle shapes from POLDER measurements","volume":"101","author":"Sun","year":"2006","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"key":"ref_14","first-page":"1899","article-title":"A self-consistent scattering model for cirrus. I: The solar region","volume":"133","author":"Baran","year":"2007","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2361","DOI":"10.5194\/amt-5-2361-2012","article-title":"Remote sensing of ice crystal asymmetry parameter using multi-directional polarization measurements\u2013Part 1: Methodology and evaluation with simulated measurements","volume":"5","author":"Cairns","year":"2012","journal-title":"Atmos. Meas. Tech."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3739","DOI":"10.5194\/acp-14-3739-2014","article-title":"Ice particle habit and surface roughness derived from PARASOL polarization measurements","volume":"14","author":"Cole","year":"2014","journal-title":"Atmos. Chem. Phys."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"7545","DOI":"10.5194\/acp-16-7545-2016","article-title":"Degree of ice particle surface roughness inferred from polarimetric observations","volume":"16","author":"Hioki","year":"2016","journal-title":"Atmos. Chem. Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/0034-4257(92)90139-B","article-title":"Feasibility study of derivation of cirrus information using polarimetric measurements from satellite","volume":"39","author":"Masuda","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2007","DOI":"10.5194\/amt-6-2007-2013","article-title":"The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI): A new tool for aerosol and cloud remote sensing","volume":"6","author":"Diner","year":"2013","journal-title":"Atmos. Meas. Tech."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"McFarlane, S.A., and Marchand, R.T. (2008). Analysis of ice crystal habits derived from MISR and MODIS observations over the ARM Southern Great Plains site. J. Geophys. Res. Atmos., 113.","DOI":"10.1029\/2007JD009191"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7115","DOI":"10.5194\/acp-9-7115-2009","article-title":"Influence of ice particle model on satellite ice cloud retrieval: Lessons learned from MODIS and POLDER cloud product comparison","volume":"9","author":"Zhang","year":"2009","journal-title":"Atmos. Chem. Phys."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1175\/JAS-D-12-039.1","article-title":"Spectrally consistent scattering, absorption, and polarization properties of atmospheric ice crystals at wavelengths from 0.2 to 100 \u03bcm","volume":"70","author":"Yang","year":"2013","journal-title":"J. Atmos. Sci."},{"key":"ref_23","first-page":"223","article-title":"Single-scattering properties of complex ice crystals in terrestrial atmosphere","volume":"71","author":"Yang","year":"1998","journal-title":"Beitr. Phys. Atmosphare-Contrib. Atmos. Phys."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1109\/TGRS.2016.2610522","article-title":"The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua","volume":"55","author":"Platnick","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Yang, P., Hioki, S., Saito, M., Kuo, C.P., Baum, B.A., and Liou, K.-N. (2018). A review of ice cloud optical property models for passive satellite remote sensing. Atmosphere, 9.","DOI":"10.3390\/atmos9120499"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1878","DOI":"10.1175\/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2","article-title":"Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: Theory","volume":"47","author":"Nakajima","year":"1990","journal-title":"J. Atmos. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.jqsrt.2014.09.014","article-title":"Effect of mineral dust aerosol aspect ratio on polarized reflectance","volume":"151","author":"Huang","year":"2015","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1364\/JOSA.44.000838","article-title":"Measurement of the roughness of the sea surface from photographs of the sun\u2019s glitter","volume":"44","author":"Cox","year":"1954","journal-title":"J. Opt. Soc. Am."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2389","DOI":"10.1029\/2012JD018201","article-title":"A global analysis on the view-angle dependence of plane-parallel oceanic liquid water cloud optical thickness using data synergy from MISR and MODIS","volume":"118","author":"Liang","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Mitchell, D.L., Mejia, J., Garnier, A., Tomii, Y., Kr\u00e4mer, M., and Hosseinpour, F. (2020). An estimate of global, regional and seasonal cirrus cloud radiative effects contributed by homogeneous ice nucleation. Atmos. Chem. Phys. Discuss.","DOI":"10.5194\/acp-2020-846"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"17325","DOI":"10.5194\/acp-18-17325-2018","article-title":"CALIPSO (IIR\u2013CALIOP) retrievals of cirrus cloud ice-particle concentrations","volume":"18","author":"Mitchell","year":"2018","journal-title":"Atmos. Chem. Phys."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"14327","DOI":"10.5194\/acp-18-14327-2018","article-title":"Ice crystal number concentration estimates from lidar\u2013radar satellite remote sensing\u2013Part 1: Method and evaluation","volume":"18","author":"Sourdeval","year":"2018","journal-title":"Atmos. Chem. Phys."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"14351","DOI":"10.5194\/acp-18-14351-2018","article-title":"Ice crystal number concentration estimates from lidar\u2013radar satellite remote sensing\u2013Part 2: Controls on the ice crystal number concentration","volume":"18","author":"Gryspeerdt","year":"2018","journal-title":"Atmos. Chem. Phys."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2635","DOI":"10.1175\/JAS-D-19-0031.1","article-title":"Oriented ice crystals: A single-scattering property database for applications to lidar and optical phenomenon simulations","volume":"76","author":"Saito","year":"2019","journal-title":"J. Atmos. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2754\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:29:57Z","timestamp":1760164197000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,13]]},"references-count":34,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["rs13142754"],"URL":"https:\/\/doi.org\/10.3390\/rs13142754","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,7,13]]}}}