Articles | Volume 13, issue 9
https://doi.org/10.5194/amt-13-4947-2020
https://doi.org/10.5194/amt-13-4947-2020
Research article
 | 
18 Sep 2020
Research article |  | 18 Sep 2020

A new Orbiting Carbon Observatory 2 cloud flagging method and rapid retrieval of marine boundary layer cloud properties

Mark Richardson, Matthew D. Lebsock, James McDuffie, and Graeme L. Stephens

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Cited articles

Baum, B. A., Menzel, W. P., Frey, R. A., Tobin, D. C., Holz, R. E., Ackerman, S. A., Heidinger, A. K., and Yang, P.: MODIS Cloud-Top Property Refinements for Collection 6, J. Appl. Meteorol. Clim., 51, 1145–1163, https://doi.org/10.1175/JAMC-D-11-0203.1, 2012. 
Bennartz, R.: Global assessment of marine boundary layer cloud droplet number concentration from satellite, J. Geophys. Res., 112, D02201, https://doi.org/10.1029/2006JD007547, 2007. 
Bodas-Salcedo, A., Mulcahy, J. P., Andrews, T., Williams, K. D., Ringer, M. A., Field, P. R., and Elsaesser, G. S.: Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3, J. Adv. Model. Earth Sy., 11, 1735–1758, https://doi.org/10.1029/2019MS001688, 2019. 
Boesch, H., Brown, L., Castano, R., Christi, M., Connor, B., Crisp, D., Eldering, A., Fisher, B., Frankenberg, C., Gunson, M., Granat, R., McDuffie, J., Miller, C., Natraj, V., O'Brien, D., O'Dell, C., Osterman, G., Oyafuso, F., Payne, V., Polonsky, I., Smyth, M., Spurr, R., Thompson, D., and Toon, G.: Orbiting Carbon Observatory (OCO)-2 Level 2 Full Physics Algorithm Theoretical Basis Document, Pasadena, CA, available at: https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_ATBD.V8.pdf (last access: 7 September 2020), 2017. 
Bony, S. and Dufresne, J.-L.: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, L20806, https://doi.org/10.1029/2005GL023851, 2005. 
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Short summary
We previously combined CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data and reflected-sunlight measurements from OCO-2 (Orbiting Carbon Observatory 2) for information about low clouds over oceans. The satellites are no longer formation-flying, so this work is a step towards getting new information about these clouds using only OCO-2. We can rapidly and accurately identify liquid oceanic clouds and obtain their height better than a widely used passive sensor.
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