Cloud information content analysis of multi-angular measurements in the oxygen A-band: application to 3MI and MSPI

Abstract. Information content analyses on cloud top altitude (CTOP) and geometrical thickness (CGT) from multi-angular A-band measurements in the case of monolayer homogeneous clouds are conducted. In the framework of future multi-angular radiometer development, we compared the potential performances of the 3MI (Multi-viewing, Multi-channel and Multi-polarization Imaging) instrument developed by EUMETSAT, which is an extension of POLDER/PARASOL instrument and MSPI (Multiangle SpectroPolarimetric Imager) developed by NASA's Jet Propulsion Laboratory. Quantitative information content estimates were realized for thin, moderately opaque and opaque clouds for different surface albedo and viewing geometry configurations. Analyses show that retrieval of CTOP is possible with a high accuracy in most of the cases investigated. Retrieval of CGT is also possible for optically thick clouds above a black surface, at least when CGT > 1–2 km and for thin clouds for CGT > 2–3 km. However, for intermediate optical thicknesses (COT ≃ 4), we show that the retrieval of CGT is not simultaneously possible with CTOP. A comparison between 3MI and MSPI shows a higher information content for MSPI's measurements, traceable to a thinner filter inside the oxygen A-band, yielding higher signal-to-noise ratio for absorption estimation. Cases of cloud scenes above bright surfaces are more complex but it is shown that the retrieval of CTOP remains possible in almost all situations while the information content on CGT appears to be insufficient in many cases, particularly for COT

[1]  J. Joiner,et al.  The determination of cloud pressures from rotational Raman scattering in satellite backscatter ultraviolet measurements , 1995 .

[2]  R. Marchand,et al.  A description of hydrometeor layer occurrence statistics derived from the first year of merged Cloudsat and CALIPSO data , 2009 .

[3]  Philippe Dubuisson,et al.  MERIS in-flight spectral calibration in O2 absorption using surface pressure retrieval , 2003, SPIE Asia-Pacific Remote Sensing.

[4]  Andrew K. Heidinger,et al.  Molecular Line Absorption in a Scattering Atmosphere. Part II: Application to Remote Sensing in the O2 A band , 2000 .

[5]  Piet Stammes,et al.  Deriving terrestrial cloud top pressure from photopolarimetry of reflected light , 2000 .

[6]  W. Paul Menzel,et al.  Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS) , 1992, IEEE Trans. Geosci. Remote. Sens..

[7]  Alexander Marshak,et al.  View angle dependence of cloud optical thicknesses retrieved by Moderate Resolution Imaging Spectroradiometer (MODIS) , 2007 .

[8]  Akihiro Uchiyama,et al.  Estimation of Cloud Physical Parameters from Airborne Solar Spectral Reflectance Measurements for Stratocumulus Clouds , 1995 .

[9]  A. Marshak,et al.  Solar radiation transport in the cloudy atmosphere: a 3D perspective on observations and climate impacts , 2010 .

[10]  Makoto Kuji,et al.  Retrieval of cloud geometrical parameters using remote sensing data , 2001, SPIE Asia-Pacific Remote Sensing.

[11]  Diego G. Loyola,et al.  Cloud Properties Derived From GOME/ERS-2 Backscatter Data for Trace Gas Retrieval , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Anthony J. Baran,et al.  A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study , 2015 .

[13]  Jacques Pelon,et al.  A variational approach for retrieving ice cloud properties from infrared measurements: application in the context of two IIR validation campaigns , 2013 .

[14]  Steven A. Ackerman,et al.  Vertical distributions and relationships of cloud occurrence frequency as observed by MISR, AIRS, MODIS, OMI, CALIPSO, and CloudSat , 2009 .

[15]  S. Mcclain,et al.  The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI): a new tool for aerosol and cloud remote sensing , 2013 .

[16]  Larry Di Girolamo,et al.  A global analysis on the view‐angle dependence of plane‐parallel oceanic liquid water cloud optical thickness using data synergy from MISR and MODIS , 2013 .

[17]  Bertrand Fougnie,et al.  Improvement of the PARASOL Radiometric In-Flight Calibration Based on Synergy Between Various Methods Using Natural Targets , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[18]  David P. Kratz,et al.  THE CORRELATED k-DISTRIBUTION TECHNIQUE AS APPLIED TO THE AVHRR CHANNELS , 1995 .

[19]  Norman G. Loeb,et al.  Inference of Marine Stratus Cloud Optical Depths from Satellite Measurements: Does 1D Theory Apply? , 1998 .

[20]  A. Kokhanovsky,et al.  Semianalytical cloud retrieval algorithm as applied to the cloud top altitude and the cloud geometrical thickness determination from top‐of‐atmosphere reflectance measurements in the oxygen A band , 2004 .

[21]  Steven,et al.  Objective Assessment of the Information Content of Visible and Infrared Radiance Measurements for Cloud Microphysical Property Retrievals over the Global Oceans. Part I: Liquid Clouds , 2006 .

[22]  Marie Doutriaux-Boucher,et al.  A comparison of cloud droplet radii measured from space , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[23]  D. Winker,et al.  Initial performance assessment of CALIOP , 2007 .

[24]  Rene Preusker,et al.  Remote Sensing of Cloud-Top Pressure Using Moderately Resolved Measurements within the Oxygen A Band—A Sensitivity Study , 2009 .

[25]  Jan-Peter Muller,et al.  Operational retrieval of cloud-top heights using MISR data , 2002, IEEE Trans. Geosci. Remote. Sens..

[26]  Philip Watts,et al.  Multiview Cloud-Top Height and Wind Retrieval with Photogrammetric Methods: Application to Meteosat-8 HRV Observations , 2007 .

[27]  Ab Davis,et al.  First results from a dual photoelastic-modulator-based polarimetric camera. , 2010, Applied optics.

[28]  Alexei Lyapustin,et al.  A method of retrieving cloud top height and cloud geometrical thickness with oxygen A and B bands for the Deep Space Climate Observatory (DSCOVR) mission: Radiative transfer simulations , 2013 .

[29]  G. Stephens,et al.  Molecular Line Absorption in a Scattering Atmosphere. Part III: Pathlength Characteristics and Effects of Spatially Heterogeneous Clouds , 2002 .

[30]  Maurice Herman,et al.  Analysis of the POLDER polarization measurements performed over cloud covers , 1994, IEEE Trans. Geosci. Remote. Sens..

[31]  A. Macke,et al.  Polarized light scattering by inhomogeneous hexagonal monocrystals: Validation with ADEOS-POLDER measurements , 2001 .

[32]  A. Marshak,et al.  Space-time Green functions for diffusive radiation transport, in application to active and passive cloud probing , 2009 .

[33]  John P. Burrows,et al.  The ring effect in the cloudy atmosphere , 2001 .

[34]  Paul W. Stackhouse,et al.  Impact of clouds on atmospheric heating based on the R04 CloudSat fluxes and heating rates data set , 2008 .

[35]  D. Wark,et al.  Discussion of the letter by R. A. Hanel, “Determination of cloud altitude from a satellite” , 1961 .

[36]  Frédéric Parol,et al.  Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band , 2013 .

[37]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[38]  W. Paul Menzel,et al.  The MODIS cloud products: algorithms and examples from Terra , 2003, IEEE Trans. Geosci. Remote. Sens..

[39]  Bryan A. Baum,et al.  Cloud thermodynamic phase inferred from merged POLDER and MODIS data , 2007 .

[40]  G. Vaughan,et al.  Using passive remote sensing to retrieve the vertical variation of cloud droplet size in marine stratocumulus: An assessment of information content and the potential for improved retrievals from hyperspectral measurements , 2012 .

[41]  Clive D Rodgers,et al.  Inverse Methods for Atmospheric Sounding: Theory and Practice , 2000 .

[42]  Steven Platnick,et al.  A global view of one‐dimensional solar radiative transfer through oceanic water clouds , 2010 .

[43]  G. Ohring,et al.  Some Experiments with a Zonally Averaged Climate Model , 1978 .

[44]  J. Hovenier,et al.  The adding method for multiple scattering calculations of polarized light , 1987 .

[45]  Clive D. Rodgers,et al.  Information content and optimisation of high spectral resolution remote measurements , 1998 .

[46]  Steven Platnick,et al.  Influence of ice particle model on satellite ice cloud retrieval: lessons learned from MODIS and POLDER cloud product comparison , 2009 .

[47]  D. Winker,et al.  Laminar cirrus observed near the tropical tropopause by LITE , 1998 .

[48]  T. L’Ecuyer,et al.  The vertical structure of cloud radiative heating over the Indian subcontinent during summer monsoon , 2015 .

[49]  Anthony B. Davis,et al.  Toward New Inferences about Cloud Structures from Multidirectional Measurements in the Oxygen A Band: Middle-of-Cloud Pressure and Cloud Geometrical Thickness from POLDER-3/PARASOL , 2010 .

[50]  Adrian Doicu,et al.  Information Content in the Oxygen $A$-Band for the Retrieval of Macrophysical Cloud Parameters , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[51]  W. Rossow,et al.  ISCCP Cloud Data Products , 1991 .