What do satellite backscatter ultraviolet and visible spectrometers see over snow and ice? A study of clouds and ozone using the A-train

Abstract. In this paper, we examine how clouds over snow and ice affect ozone absorption and how these effects may be accounted for in satellite retrieval algorithms. Over snow and ice, the Aura Ozone Monitoring Instrument (OMI) Raman cloud pressure algorithm derives an effective scene pressure. When this scene pressure differs appreciably from the surface pressure, the difference is assumed to be caused by a cloud that is shielding atmospheric absorption and scattering below cloud-top from satellite view. A pressure difference of 100 hPa is used as a crude threshold for the detection of clouds that significantly shield tropospheric ozone absorption. Combining the OMI effective scene pressure and the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) cloud top pressure, we can distinguish between shielding and non-shielding clouds. To evaluate this approach, we performed radiative transfer simulations under various observing conditions. Using cloud vertical extinction profiles from the CloudSat Cloud Profiling Radar (CPR), we find that clouds over a bright surface can produce significant shielding (i.e., a reduction in the sensitivity of the top-of-the-atmosphere radiance to ozone absorption below the clouds). The amount of shielding provided by clouds depends upon the geometry (solar and satellite zenith angles) and the surface albedo as well as cloud optical thickness. We also use CloudSat observations to qualitatively evaluate our approach. The CloudSat, Aqua, and Aura satellites fly in an afternoon polar orbit constellation with ground overpass times within 15 min of each other. The current Total Ozone Mapping Spectrometer (TOMS) total column ozone algorithm (that has also been applied to the OMI) assumes no clouds over snow and ice. This assumption leads to errors in the retrieved ozone column. We show that the use of OMI effective scene pressures over snow and ice reduces these errors and leads to a more homogeneous spatial distribution of the retrieved total ozone.

[1]  Mark R. Schoeberl,et al.  Accurate satellite-derived estimates of the tropospheric ozone impact on the global radiation budget , 2009 .

[2]  M. Buchwitz,et al.  SCIAMACHY: Mission Objectives and Measurement Modes , 1999 .

[3]  R. B. A. Koelemeijer,et al.  Effects of clouds on ozone column retrieval from GOME UV measurements , 1999 .

[4]  J. Hovenier,et al.  A fast method for retrieval of cloud parameters using oxygen A band measurements from the Global Ozone Monitoring Experiment , 2001 .

[5]  James F. Gleason,et al.  Impact of tropospheric nitrogen dioxide on the regional radiation budget , 2009 .

[6]  E. O'connor,et al.  The CloudSat mission and the A-train: a new dimension of space-based observations of clouds and precipitation , 2002 .

[7]  Xuanji Wang,et al.  Recent Trends in Arctic Surface, Cloud, and Radiation Properties from Space , 2003, Science.

[8]  A. Trishchenko,et al.  SPARC: New Cloud, Snow, and Cloud Shadow Detection Scheme for Historical 1-km AVHHR Data over Canada , 2007 .

[9]  M. Allen,et al.  Enhancement of atmospheric radiation by an aerosol layer. , 1992, Journal of geophysical research.

[10]  K. Stamnes,et al.  Bidirectional reflectance distribution function of snow: corrections for the Lambertian assumption in remote sensing applications , 2007 .

[11]  Simone Tanelli,et al.  CloudSat mission: Performance and early science after the first year of operation , 2008 .

[12]  Heikki Saari,et al.  The ozone monitoring instrument , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Robert J. D. Spurr,et al.  Evaluation of the OMI cloud pressures derived from rotational Raman scattering by comparisons with other satellite data and radiative transfer simulations , 2008 .

[14]  J. D. Haan,et al.  Discrete-ordinate radiative transfer in a stratified medium with first-order rotational Raman scattering , 2008 .

[15]  Bo-Cai Gao,et al.  Cloud Detection over the Arctic Region Using Airborne Imaging Spectrometer Data during the Daytime , 1998 .

[16]  Steven Platnick,et al.  Detection of multi-layer and vertically-extended clouds using A-train sensors , 2009 .

[17]  Michael Buchwitz,et al.  Total ozone retrieval from GOME UV spectral data using the weighting function DOAS approach , 2004 .

[18]  Piet Stammes,et al.  Click Here for Full Article , 1989 .

[19]  P. Bhartia,et al.  Accurate determination of total ozone using SBUV continuous spectral scan measurements , 1997 .

[20]  Rachel T. Pinker,et al.  Toward improved satellite estimates of short‐wave radiative fluxes—Focus on cloud detection over snow: 1. Methodology , 2007 .

[21]  James F. Gleason,et al.  Retrieval of cloud pressure and oceanic chlorophyll content using Raman scattering in GOME ultraviolet spectra , 2004 .

[22]  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 .

[23]  Michael Buchwitz,et al.  The Global Ozone Monitoring Experiment (Gome) : Mission, instrument concept, and first scientific results , 1997 .

[24]  Ilse Aben,et al.  Distinction between clouds and ice/snow covered surfaces in the identification of cloud-free observations using SCIAMACHY PMDs , 2005 .

[25]  J. Key,et al.  Estimating the cloudy-sky albedo of sea ice and snow from space , 2001 .

[26]  P. Levelt,et al.  Ozone mixing ratios inside tropical deep convective clouds from OMI satellite measurements , 2008 .

[27]  Michael D. King,et al.  A solar reflectance method for retrieving the optical thickness and droplet size of liquid water clouds over snow and ice surfaces , 2001 .

[28]  Vladimir V. Rozanov,et al.  The determination of cloud altitudes using GOME reflectance spectra: multilayered cloud systems , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[29]  P. Bhartia,et al.  Observations over hurricanes from the ozone monitoring instrument , 2006 .

[30]  W. Menzel,et al.  Discriminating clear sky from clouds with MODIS , 1998 .

[31]  M. King,et al.  Bulk Scattering Properties for the Remote Sensing of Ice Clouds. Part II: Narrowband Models , 2005 .

[32]  D. Deirmendjian.  Electromagnetic scattering on spherical polydispersions , 1969 .

[33]  Zhibo Zhang,et al.  Improvements in Shortwave Bulk Scattering and Absorption Models for the Remote Sensing of Ice Clouds , 2011 .

[34]  John P. Burrows,et al.  The semianalytical cloud retrieval algorithm for SCIAMACHY I. The validation , 2005 .

[35]  Joanna Joiner,et al.  First results from the OMI rotational Raman scattering cloud pressure algorithm , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[36]  Pieter Valks,et al.  Ten years of GOME/ERS-2 total ozone data—The new GOME data processor (GDP) version 4: 1. Algorithm description , 2006 .

[37]  Kai Yang,et al.  Improving total column ozone retrievals by using cloud pressures derived from Raman scattering in the UV , 2004 .

[38]  J. Burrows,et al.  Cloud and surface classification using SCIAMACHY polarization measurement devices , 2008 .

[39]  Judith A. Curry,et al.  Overview of Arctic Cloud and Radiation Characteristics , 1996 .