Abstract
Abstract. The Orbiting Carbon Observatory 2 (OCO-2) carries a hyperspectral A-band sensor that can obtain information about cloud geometric thickness (H). The OCO2CLD-LIDAR-AUX product retrieved H with the aid of collocated CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data to identify suitable clouds and provide a priori cloud top pressure (Ptop). This collocation is no longer possible, since CALIPSO's coordination flying with OCO-2 has ended, so here we introduce a new cloud flagging and a priori assignment using only OCO-2 data, restricted to ocean footprints where solar zenith angle <45∘. Firstly, a multi-layer perceptron network was trained to identify liquid clouds over the ocean with sufficient optical depth (τ>1) for a valid retrieval, and agreement with MODIS–CALIPSO (Moderate Resolution Imaging Spectroradiometer) is 90.0 %. Secondly, we developed a lookup table to simultaneously retrieve cloud τ, effective radius (re) and Ptop from A-band and CO2 band radiances, with the intention that these will act as the a priori state estimate in a future retrieval. Median Ptop difference vs. CALIPSO is 12 hPa with an inter-decile range of [-11,87]hPa, substantially better than the MODIS–CALIPSO range of [-83,81]hPa. The MODIS–OCO-2 τ difference is 0.8[-3.8,6.9], and re is -0.3[-2.8,2.1]µm. The τ difference is due to optically thick and horizontally heterogeneous cloud scenes. As well as an improved passive Ptop retrieval, this a priori information will allow for a purely OCO-2-based Bayesian retrieval of cloud droplet number concentration (Nd). Finally, our cloud flagging procedure may also be useful for future partial-column above-cloud CO2 abundance retrievals.
Highlights
Hyperspectral O2 A-band measurements near λ = 0.78 μm, such as those taken by the Orbiting Carbon Observatory-2 (OCO-2), may provide unique new information about boundary layer clouds by retrieving their geometric thickness (H ) or droplet number concentration (Nd), provided coincident information about effective radius from other channels
The OCO-2 measurement approach and instrumentation are detailed in Bösch et al (2017); the Level 2 Full Physics (L2FP) radiative transfer (RT)’s application to clouds is detailed in Richardson et al (2017); and the Moderate Resolution Imaging Spectroradiometer (MODIS)–CloudAerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)–OCO-2 matchup data are as used in Taylor et al (2016)
We use the following terms: i. true positive (TP), classifier = 1, truth = 1; ii. false positive (FP), classifier = 1, truth = 0; iii. false negative (FN), classifier = 0, truth = 1; and iv. true negative (TN), classifier = 0, truth = 0. These are normalised such that TP+FP+FN+TN = 100 %
Summary
Hyperspectral O2 A-band measurements near λ = 0.78 μm, such as those taken by the Orbiting Carbon Observatory-2 (OCO-2), may provide unique new information about boundary layer clouds by retrieving their geometric thickness (H ) or droplet number concentration (Nd), provided coincident information about effective radius (re) from other channels. They are able to do this because the spectrum responds to the photon path length between the Sun, Earth and the sensor. Others rely on multi-angle (Ferlay et al, 2010) or combined A- and B-band information (Yang et al, 2013), these tend to contain little information on low-altitude
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