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The OCO-2 oxygen A-band response to liquid marine cloud properties from CALIPSO...

Richardson, M., J. McDuffie, G. L. Stephens, H. Cronk, and T. E. Taylor (2017), The OCO-2 oxygen A-band response to liquid marine cloud properties from CALIPSO and MODIS, J. Geophys. Res., 122, 8255-8275, doi:10.1002/2017JD026561.

Spectra of reflected sunlight in the oxygen A-band contain information about cloud properties such as cloud top pressure, optical depth, and pressure thickness. Here we show, for the first time, that high-spectral-resolution A-band Orbiting Carbon Observatory-2 (OCO-2) spectra respond largely as simulated to the optical properties of water clouds over ocean during November 2015 (N = 184,318) using input cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and the Cloud-Aerosol Lidar with Orthogonal Polarization on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). In A-band continuum channels the standard deviation of simulated minus observed radiance is ±37%. Selecting horizontally homogeneous clouds to mitigate three-dimensional cloud effects and collocation error with the other satellites, the standard deviation of the residuals is reduced to ±18%. Using a look-up table developed from simulations, OCO-2’s estimated cloud top pressure for low clouds (Ptop > 680 hPa) has a standard deviation of ±61 hPa relative to CALIPSO retrievals, and bias is dependent on assumed cloud pressure thickness, with our smallest value being 5 hPa. Versus MODIS optical depth, the standard deviation is ±9.0 and the bias is 2.0, although these shrink for clouds of τ < 30. These values include collocation error between the different satellites, meaning that they place an upper bound on the OCO-2 retrieval uncertainty. The theoretical precision limit from OCO-2’s instrumental uncertainty is shown to be ±2.4 hPa in above-cloud path and ±0.2% in optical depth for a two-channel retrieval. Options for retrieving cloud optical depth, cloud top pressure, and pressure thickness are discussed in the context of a formal OCO-2 cloud property retrieval.

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