Abstract

Abstract. The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of ≃ 20–25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April–May) for OCO-2 nadir-land, glint-land and glint-water observations.No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

Highlights

  • National Aeronautics and Space Administration (NASA)’s Orbiting Carbon Observatory-2 (OCO-2) satellite was launched on 2 July 2014 into a sun-synchronous orbit

  • These results suggest that the A-Band Preprocessor (ABP), which relies on photon path-length (PPL) modification to detect cloud, is unable to discern cloud near the surface, even when the optical thickness is large

  • We have shown that the OCO-2 cloud screening preprocessors perform well in comparison to the MODISAqua cloud mask on a large, global data set consisting of four 16-day orbit track repeat cycles in both nadir and glint viewing modes

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Summary

Introduction

NASA’s OCO-2 satellite was launched on 2 July 2014 into a sun-synchronous orbit. After an initial on-orbit satellite bus checkout period, it was inserted into the 705 km Afternoon Constellation, known as the A-Train (L’Ecuyer and Jiang, 2010). Observations in glint viewing mode, with the bore sight oriented towards the point of specular reflection, maximizes the SNR but yields larger footprint sizes and longer atmospheric optical paths. This increases the likelihood of cloud contamination within the FOV. This study presents the first comparisons between OCO-2, MODIS-Aqua and CALIOP cloud screening results for a series of measurements collected during the first year of OCO2 operations Because these sensors are all in the A-Train, Atmos. The collocation data set for the MODIS comparison is comprised of four 16-day repeat cycles, two in nadir and two in glint viewing, over both a winter (December) and spring (April– May) time range (approximately 50 million soundings in total).

OCO-2 aerosol and cloud screening algorithms
The ABP
The IDP
Combing ABP and IDP on simulated data
Collocation methodology
MODIS cloud mask
CALIOP layered data
Contingency table analysis
Validation of OCO-2 cloud screening algorithms against MODIS
Validation of OCO-2 cloud screening algorithms against CALIPSO
Findings
Conclusions
Full Text
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