The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission

Abstract. This paper provides the theoretical basis and simulated retrievals for the Cloud Height Retrieval from O2 Molecular Absorption (CHROMA) algorithm. Simulations are performed for the Ocean Color Instrument (OCI), which is the primary payload on the forthcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, and the Ocean Land Colour Instrument (OLCI) currently flying on the Sentinel 3 satellites. CHROMA is a Bayesian approach which simultaneously retrieves cloud optical thickness (COT), cloud-top pressure and height (CTP and CTH respectively), and (with a significant prior constraint) surface albedo. Simulated retrievals suggest that the sensor and algorithm should be able to meet the PACE mission goal for CTP error, which is ±60 mb for 65 % of opaque (COT ≥3) single-layer clouds on global average. CHROMA will provide pixel-level uncertainty estimates, which are demonstrated to have skill at telling low-error situations from high-error ones. CTP uncertainty estimates are well-calibrated in magnitude, although COT uncertainty is overestimated relative to observed errors. OLCI performance is found to be slightly better than OCI overall, demonstrating that it is a suitable proxy for the latter in advance of PACE's launch. CTP error is only weakly sensitive to correct cloud phase identification or assumed ice crystal habit/roughness. As with other similar algorithms, for simulated retrievals of multi-layer systems consisting of optically thin cirrus clouds above liquid clouds, retrieved height tends to be underestimated because the satellite signal is dominated by the optically thicker lower layer. Total (liquid plus ice) COT also becomes underestimated in these situations. However, retrieved CTP becomes closer to that of the upper ice layer for ice COT ≈3 or higher.

[1]  A. Marshak,et al.  EPIC/DSCOVR as a Pathfinder in Cloud Remote Sensing Using Differential Oxygen Absorption Spectroscopy , 2022, Frontiers in Remote Sensing.

[2]  Yongxiang Hu,et al.  An improved pseudo spherical shell algorithm for vector radiative transfer , 2022, Journal of Quantitative Spectroscopy and Radiative Transfer.

[3]  E. O'connor,et al.  Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O2–O2, MODIS, and Suomi-NPP VIIRS , 2021, Atmospheric Measurement Techniques.

[4]  P. Pilewskie,et al.  The TSIS‐1 Hybrid Solar Reference Spectrum , 2021, Geophysical research letters.

[5]  Robert E. Holz,et al.  The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products , 2020, Remote. Sens..

[6]  Stefan Adriaensen,et al.  Use of Moon Observations for Characterization of Sentinel-3B Ocean and Land Color Instrument , 2020, Remote. Sens..

[7]  S. Platnick,et al.  Evaluation of the MODIS Collection 6 multilayer cloud detection algorithm through comparisons with CloudSat Cloud Profiling Radar and CALIPSO CALIOP products , 2020, Atmospheric Measurement Techniques.

[8]  P. Francis,et al.  Evaluating nonlinear maximum likelihood optimal estimation uncertainty in cloud and aerosol remote sensing , 2020, Atmospheric Science Letters.

[9]  B. Cairns,et al.  Global Statistics of Ice Microphysical and Optical Properties at Tops of Optically Thick Ice Clouds , 2020, Journal of Geophysical Research: Atmospheres.

[10]  Alexei Lyapustin,et al.  Merging regional and global aerosol optical depth records from major available satellite products , 2020 .

[11]  D. Fahey,et al.  A microphysics guide to cirrus – Part 2: Climatologies of clouds and humidity from observations , 2020, Atmospheric Chemistry and Physics.

[12]  M. Witek,et al.  A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing , 2019, Atmospheric Measurement Techniques.

[13]  E. Boss,et al.  The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission: Status, Science, Advances , 2019, Bulletin of the American Meteorological Society.

[14]  Simon J. Hook,et al.  The ECOSTRESS spectral library version 1.0 , 2019, Remote Sensing of Environment.

[15]  Aaldert van Amerongen,et al.  SPEXone: a compact multi-angle polarimeter , 2019, International Conference on Space Optics.

[16]  Jun Wang,et al.  Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep space , 2019, Atmospheric Measurement Techniques.

[17]  L. G. Tilstra,et al.  FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2 , 2019, Atmospheric Measurement Techniques.

[18]  James McDuffie,et al.  Marine liquid cloud geometric thickness retrieved from OCO-2's oxygen A-band spectrometer , 2019, Atmospheric Measurement Techniques.

[19]  Henrique M. J. Barbosa,et al.  The Harp Hype Ran Gular Imaging Polarimeter and the Need for Small Satellite Payloads with High Science Payoff for Earth Science Remote Sensing , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[20]  Michael J. Garay,et al.  New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water , 2017 .

[21]  T. Vukicevic,et al.  Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements , 2017, Journal of geophysical research. Atmospheres : JGR.

[22]  Steven Platnick,et al.  The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[23]  K. Subrahmanyam,et al.  CloudSat observations of multi layered clouds across the globe , 2017, Climate Dynamics.

[24]  E. Clothiaux,et al.  Development and Applications of ARM Millimeter-Wavelength Cloud Radars , 2016 .

[25]  B. Cairns,et al.  Vertical variation of ice particle size in convective cloud tops , 2016, Geophysical research letters.

[26]  Arve Kylling,et al.  The libRadtran software package for radiative transfer calculations (version 2.0.1) , 2015 .

[27]  Piet Stammes,et al.  Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O 2 A band observations from GOME-2A , 2015 .

[28]  J. Delanoë,et al.  Ice water content vertical profiles of high-level clouds: classification and impact on radiative fluxes , 2015 .

[29]  Q. Min,et al.  Estimating the vertical profiles of cloud water content in warm rain clouds , 2015 .

[30]  Roy G. Grainger,et al.  Known and unknown unknowns: Uncertainty estimation in satellite remote sensing data , 2015 .

[31]  Josef Gasteiger,et al.  Representative wavelengths absorption parameterization applied to satellite channels and spectral bands , 2014 .

[32]  Bryan A. Baum,et al.  Ice cloud single-scattering property models with the full phase matrix at wavelengths from 0.2 to 100 µm , 2014 .

[33]  B. Cairns,et al.  A Flexible Parameterization for Shortwave Optical Properties of Ice Crystals , 2014 .

[34]  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 .

[35]  J. Fischer,et al.  FAME-C: Retrieval of cloud top pressure with vertically inhomogeneous cloud profiles , 2013 .

[36]  Yunyan Zhang,et al.  Factors Controlling the Vertical Extent of Fair-Weather Shallow Cumulus Clouds over Land: Investigation of Diurnal-Cycle Observations Collected at the ARM Southern Great Plains Site , 2013 .

[37]  W. Paul Menzel,et al.  Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[38]  Bryan A. Baum,et al.  Spectrally Consistent Scattering, Absorption, and Polarization Properties of Atmospheric Ice Crystals at Wavelengths from 0.2 to 100 um , 2013 .

[39]  E. R. Polovtseva,et al.  The HITRAN2012 molecular spectroscopic database , 2013 .

[40]  Brian Cairns,et al.  Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter , 2012 .

[41]  Lorraine A. Remer,et al.  Retrieving aerosol in a cloudy environment: aerosol product availability as a function of spatial resolution , 2012 .

[42]  Jean-Luc Moncet,et al.  Development and recent evaluation of the MT_CKD model of continuum absorption , 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[43]  C. Donlon,et al.  The Global Monitoring for Environment and Security (GMES) Sentinel-3 mission , 2012 .

[44]  Qiang Fu,et al.  Comparison of the CALIPSO satellite and ground‐based observations of cirrus clouds at the ARM TWP sites , 2011 .

[45]  John P. Burrows,et al.  Seven years of global retrieval of cloud properties using space-borne data of GOME , 2011 .

[46]  Claudia Emde,et al.  New secondary-scattering correction in DISORT with increased efficiency for forward scattering , 2011 .

[47]  Brian Harvey,et al.  Russian Space Probes: Scientific Discoveries and Future Missions , 2011 .

[48]  Richard Siddans,et al.  Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR , 2011 .

[49]  P. Bhartia,et al.  Fast simulators for satellite cloud optical centroid pressure retrievals; evaluation of OMI cloud retrievals , 2011 .

[50]  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 .

[51]  Philip Watts,et al.  Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment , 2010 .

[52]  Dominik Brunner,et al.  MERIS albedo climatology for FRESCO+ O2 A-band cloud retrieval , 2010 .

[53]  Odele Coddington,et al.  Characterizing the retrieval of cloud properties from optical remote sensing , 2010 .

[54]  Michael J. Pavolonis,et al.  Gazing at Cirrus Clouds for 25 Years through a Split Window. Part I: Methodology , 2009 .

[55]  S. Hook,et al.  The ASTER spectral library version 2.0 , 2009 .

[56]  M. V. Roozendael,et al.  FRESCO+: an improved O 2 A-band cloud retrieval algorithm for tropospheric trace gas retrievals , 2008 .

[57]  W. Paul Menzel,et al.  MODIS Global Cloud-Top Pressure and Amount Estimation: Algorithm Description and Results , 2008 .

[58]  H. Barker,et al.  In situ measurements of liquid water content profiles in midlatitude stratiform clouds , 2007 .

[59]  J. M. Krijger,et al.  Technical Note: The effect of sensor resolution on the number of cloud-free observations from space , 2007 .

[60]  Bryan A. Baum,et al.  Comparison of MISR and MODIS cloud-top heights in the presence of cloud overlap , 2007 .

[61]  Birgit Heese,et al.  Validation of MERIS Cloud-Top Pressure Using Airborne Lidar Measurements , 2006 .

[62]  John L. Gras,et al.  Satellite monitoring of the first indirect aerosol effect: Retrieval of the droplet concentration of water clouds , 2006 .

[63]  R. Wood,et al.  Drizzle in Stratiform Boundary Layer Clouds. Part I: Vertical and Horizontal Structure , 2005 .

[64]  Ilse Aben,et al.  Surface pressure retrieval from SCIAMACHY measurements in the O 2 A Band: validation of the measurements and sensitivity on aerosols , 2005 .

[65]  R. Wood,et al.  Drizzle in Stratiform Boundary Layer Clouds , 2005 .

[66]  Diego G. Loyola,et al.  Automatic cloud analysis from polar-orbiting satellites using neural network and data fusion techniques , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[67]  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 .

[68]  Piet Stammes,et al.  Cloud pressure retrieval using the O2‐O2 absorption band at 477 nm , 2004 .

[69]  A. Kokhanovsky,et al.  The physical parameterization of the top-of-atmosphere reflection function for a cloudy atmosphere—underlying surface system: the oxygen A-band case study , 2004 .

[70]  Johannes Orphal,et al.  Measurements of molecular absorption spectra with the SCIAMACHY pre-flight model: instrument characterization and reference data for atmospheric remote-sensing in the 230–2380 nm region , 2003 .

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

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

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

[74]  Andrew K. Heidinger,et al.  Molecular Line Absorption in a Scattering Atmosphere. Part I: Theory , 2000 .

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

[76]  L. Schüller,et al.  Radiative Properties of Boundary Layer Clouds: Droplet Effective Radius versus Number Concentration , 2000 .

[77]  J. Slusser,et al.  On Rayleigh Optical Depth Calculations , 1999 .

[78]  M. Rast,et al.  The ESA Medium Resolution Imaging Spectrometer MERIS a review of the instrument and its mission , 1999 .

[79]  Geneviève Sèze,et al.  Apparent pressure derived from ADEOS‐POLDER observations in the oxygen A‐band over ocean , 1998 .

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

[81]  Akihiko Kuze,et al.  Analysis of cloud top height and cloud coverage from satellites using the O2 A and B bands , 1994 .

[82]  R. M. Mitchell,et al.  Error Estimates for Retrieval of Cloud-Top Pressure Using Absorption in the A Band of Oxygen , 1992 .

[83]  John P. Burrows,et al.  SCIAMACHY—scanning imaging absorption spectrometer for atmospheric chartography , 1992 .

[84]  J. Fischer,et al.  Detection of Cloud-Top Height from Backscattered Radiances within the Oxygen A Band. Part 1: Theoretical Study. , 1991 .

[85]  W. Renger,et al.  Detection of Cloud-Top Height from Backscattered Radiances within the Oxygen A Band. Part 2: Measurements , 1991 .

[86]  E. Shettle Models of aerosols, clouds, and precipitation for atmospheric propagation studies , 1990 .

[87]  F. X. Kneizys,et al.  Line shape and the water vapor continuum , 1989 .

[88]  M. S. Malkevich,et al.  Methodological principles and the results of the earth survey from “cosmos” and “intercosmos” satellites , 1988 .

[89]  Man-li C. Wu,et al.  Remote Sensing of Cloud-Top Pressure Using Reflected Solar Radiation in the Oxygen A-Band , 1985 .

[90]  J. Smith,et al.  Multichannel scanning radiometer for remote sensing cloud physical parameters , 1981 .

[91]  Liu Xinwu This is How the Discussion Started , 1981 .

[92]  G. M. Hale,et al.  Optical Constants of Water in the 200-nm to 200-microm Wavelength Region. , 1973, Applied optics.

[93]  R. A. McClatchey,et al.  AFCRL atmospheric absorption line parameters compilation , 1973 .

[94]  D. Wark,et al.  On Cloud-Top Determination from Gemini-5. , 1967 .

[95]  D. Wark,et al.  Absorption in the Atmosphere by the Oxygen “A” Band , 1965 .

[96]  F. Saiedy,et al.  Cloud-Top Altitude Measurements from Satellites , 1965 .

[97]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[98]  R. M. Chapman Cloud distributions and altitude profiles from a satellite , 1962 .

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

[100]  Rudolf A. Hanel,et al.  Determination of Cloud Altitude from a Satellite , 1961 .

[101]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .