New Cirrus Retrieval Algorithms and Results from eMAS during SEAC4RS

Monday, 15 December 2014: 10:35 AM
Robert Holz1, Steven E Platnick2, Kerry Meyer3, Chenxi Wang4, Galina Wind5, Thomas Arnold5, Michael D King6, John E Yorks7 and Matthew J McGill2, (1)UW SSEC, Madison, WI, United States, (2)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (3)Universities Space Research Association Greenbelt, Greenbelt, MD, United States, (4)University of Maryland College Park, College Park, MD, United States, (5)Science Systems and Applications, Inc., Lanham, MD, United States, (6)University of Colorado at Boulder, Boulder, CO, United States, (7)SSAI/NASA GSFC, Greenbelt, MD, United States
The enhanced MODIS Airborne Simulator (eMAS) scanning imager was flown on the ER-2 during the SEAC4RS field campaign. The imager provides measurements in 38 spectral channels from the visible into the 13µm CO2 absorption bands at approximately 25 m nadir spatial resolution at cirrus altitudes, and with a swath width of about 18 km, provided substantial context and synergy for other ER-2 cirrus observations. The eMAS is an update to the original MAS scanner, having new midwave and IR spectrometers coupled with the previous VNIR/SWIR spectrometers.

In addition to the standard MODIS-like cloud retrieval algorithm (MOD06/MYD06 for MODIS Terra/Aqua, respectively) that provides cirrus optical thickness (COT) and effective particle radius (CER) from several channel combinations, three new algorithms were developed to take advantage of unique aspects of eMAS and/or other ER-2 observations. The first uses a combination of two solar reflectance channels within the 1.88 µm water vapor absorption band, each with significantly different single scattering albedo, allowing for simultaneous COT and CER retrievals. The advantage of this algorithm is that the strong water vapor absorption can significantly reduce the sensitivity to lower level clouds and ocean/land surface properties thus better isolating cirrus properties. A second algorithm uses a suite of infrared channels in an optimal estimation algorithm to simultaneously retrieve COT, CER, and cloud-top pressure/temperature. Finally, a window IR algorithm is used to retrieve COT in synergy with the ER-2 Cloud Physics Lidar (CPL) cloud top/base boundary measurements. Using a variety of quantifiable error sources, uncertainties for all eMAS retrievals will be shown along with comparisons with CPL COT retrievals.