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Empirical Polarization Distribution Models for CLARREO-Imager Intercalibration

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Empirical Polarization Distribution Models for CLARREO-Imager Intercalibration MARCH 2016 G O L D I N A N D L U K A S H I N 439 Empirical Polarization Distribution Models for CLARREO-Imager Intercalibration D. GOLDIN Science Systems and Applications, Inc., and NASA Langley Research Center, Hampton, Virginia C. LUKASHIN NASA Langley Research Center, Hampton, Virginia (Manuscript received 12 August 2015, in final form 30 November 2015) ABSTRACT Polarization effects bias the performance of various existing passive spaceborne instruments, such as MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS), as well as geostationary imagers. It is essential to evaluate and correct for these effects in order to achieve the required accuracy of the total reflectance at the top of the atmosphere. In addition to performing highly accurate decadal climate change observations, one of the objectives of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission recommended by the Na- tional Research Council for launch by NASA is to provide the on-orbit intercalibration with the imagers over a range of parameters, including polarization. Whenever the on-orbit coincident measurements are not possible, CLARREO will provide the polarization distributions constructed using the adding–doubling ra- diative transfer model (ADRTM), which will cover the entire reflected solar spectrum. These ADRTM re- sults need to be validated using real data. To this end the empirical polarization distribution models (PDMs) based on the measurements taken by the Polarization and Anisotropy of Reflectances for Atmospheric Sci- ences Coupled with Observations from a Lidar (PARASOL) mission were developed. Examples of such PDMs for the degree of polarization and the angle of linear polarization for the cloudless ocean scenes are shown here. These PDMs are compared across the three available PARASOL polarization bands, and the effect of aerosols on them is examined. The PDM-derived dependence of the reflectance uncertainty on the degree of polarization for imagers, such as MODIS or VIIRS, after their intercalibration with the CLARREO instrument is evaluated. The influence of the aerosols on the reflectance uncertainty is examined. Finally, the PDMs for the angle of linear polarization is cross-checked against the single-scattering approximation. 1. Introduction spectral response of the optics, and sensitivity to polar- ization. In this article we focus on polarization. The Climate Absolute Radiance and Refractivity The polarization and its effect on radiance measurement Observatory (CLARREO) (Wielicki et al. 2013)isa have been considered in the past by the CLARREO team. NASA decadal survey mission recommended by the Lukashin et al. (2013) used 12 days of data collected by National Research Council. CLARREO’s objectives Polarization and Anisotropy of Reflectances for Atmo- are to conduct highly accurate climate change observa- spheric Sciences Coupled with Observations from a Lidar tions and to serve as an on-orbit intercalibration refer- (PARASOL)(Fougnie et al. 2007) to construct a global set ence for other operational instruments by measuring of the empirical polarization distribution models (PDMs). spectral reflectance and to monitor their response Using a few representative values of the sensitivity to function parameters, including gain, offset, nonlinearity, polarization, its corresponding uncertainty, and the un- certainty on the degree of polarization, the authors esti- mated the uncertainty in the reflectance measurements by Denotes Open Access content. an imager after its intercalibration with CLARREO. In this work we extend the PDM statistics from Corresponding author address: D. Goldin, NASA Langley Re- 12 days of 2006 level-1 and level-2 PARASOL data to search Center, MS 420, Hampton, VA 23681. the entire 2006 dataset using the three available polari- E-mail: [email protected] zation bands, at 490, 670, and 865 nm. We show the PDM DOI: 10.1175/JTECH-D-15-0165.1 Unauthenticated | Downloaded 10/06/21 08:33 AM UTC 440 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 33 means and standard deviations for the degree of polar- ization P and angle of polarization x. We also take a closer look at the effects the aerosols have on the PDMs and quantify the dependence of the uncertainties in P on the values of P at all aerosol optical depths (AODs) and with the AOD restriction of AOD , 0.1. We then use these dependencies to improve on the reflectance un- certainty estimates in Lukashin et al. (2013) using the polarization sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) (Xiong et al. 2013) and Visible Infrared Imaging Radiometer Suite (VIIRS) (Scalione et al. 2003). Finally, we compare the x empirical PDMs with the theoretical ones constructed using the single-scattering approximation. At 490, 670, and 865 nm, the three polarized bands from the PARASOL sample the blue, yellow, and near-infrared part of the reflected solar spectrum. The PDMs derived from these channels will be used to validate the polariza- tion modeling over the entire reflected solar spectrum using the adding–doubling radiative transfer model (ADRTM) (Sun and Lukashin 2013). We note that such PDMs would provide the complete set of polarization parameters to the low-Earth-orbiting (LEO) imagers, such as MODIS and VIIRS, and geosynchronous (GEO) in- struments, such as GOES, which can subsequently be used to correct for the polarization biases (see, e.g., Lyapustin et al. 2014; Kulkarny et al. 2010). In this work we considered the cloudless-sky over ocean scene. This choice was motivated by several fac- tors. First, as is well known, the ocean alone, the biggest water body on the planet, covers approximately two- thirds of the earth’s surface. Second, we wish to consider FIG. 1. Illustrations showing the coordinate variables used in the u u the worst-case scenario, where polarization affects the text. Terms s and are the solar and viewing zenith angles, re- f f radiance measurements the most. The unpolarized spectively. Terms s and y are the solar and viewing azimuth angles, f [ f 2 f sunlight becomes polarized through atmospheric scat- respectively. Relative azimuth, defined as s y,isshownin (bottom) Poincaré sphere. Also shown in the bottom drawing are the tering and surface reflection, with the water surface two polarization angles: x, the angle relative to the principal plane, being the best polarizer among the surface types iden- and c, the angle relative to the scattering plane. tified by the International Geosphere–Biosphere Pro- x gramme (IGBP) (Bartholomé and Belward 2005). we show examples of PDMs with and without aerosols x This article is structured in the following way. In and, as a cross-check, compare the PDM with the section 2 we define the viewing geometry and polariza- single-scattering approximation. Finally, in the appen- tion parameters. In section 3 we briefly describe the dix we discuss the correction that needs to be applied to x PARASOL instrument and discuss the PARASOL data PDMs in order to obtain well-defined means and format, which is used in forming our datasets (discussed standard deviations across the entire PDM. in section 4), which, in turn, are used to construct 2. Viewing geometry, polarization, and PDM the PDMs. In section 5, first, for the three available definitions PARASOL polarization bands, we examine the empir- ical P PDMs for the cloudless-sky over ocean scene In this section we define the geometrical and polari- and the effect of the aerosols on them. The P PDMs can zation variables used throughout this article. By con- then be used to derive the uncertainty dependence vention, we use polar coordinates with the z axis of the imagers, such as MODIS and VIIRS, on the de- coinciding with the local zenith (Fig. 1). The position of gree of polarization after their intercalibration with the PARASOL instrument is described in terms of the CLARREO; this is illustrated in section 6.Insection 7 viewing zenith angle and viewing azimuth as (u, fy). The Unauthenticated | Downloaded 10/06/21 08:33 AM UTC MARCH 2016 G O L D I N A N D L U K A S H I N 441 current position of the sun in terms of the solar zenith constraints on the scene type, such as surface type and u f angle and solar azimuth is denoted as ( s, s), while the wind speed, as well as the solar zenith angle. In this ar- f [ f 2 f relative azimuth is defined as s y. ticle the PDMs are represented by the two-dimensional The polarization of light (Kattawar et al. 2016) may be histograms with f on the x axis, u on the y axis, and the described by the following four Stokes parameters: I, Q, degree of polarization P or angle of polarization U, and V, where I is the total intensity, Q and U contain x indicated by the color bar. Each P or x bin is averaged information about the linear polarization, and V de- over the data-taking period. For this work we have scribes circular polarization. The reflected solar radia- considered the entire year of 2006 PARASOL data1 tion polarization is linear to a high degree and V can be with the global coverage, save for the polar regions, neglected (Coulson 1988). The remaining Stokes com- which were not sampled. ponents may be expressed as (Hansen and Travis 1974) 5 1 3. PARASOL description and data format I I08 I908 , 5 2 Q I08 I908 , The PARASOL mission was active between 2004 and 5 2 2 U I458 I1358 , 2013 and consisted of the microsatellite flying as a part of A-Train formation at 705-km altitude. The mission’s where the quantities on the right-hand side are the ra- primary aim was to study aerosols and clouds. The diation intensities along the measurement directions measurements were carried out by the wide-field imag- indicated by the indices.
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