Investigating Warm Marine Boundary Layer Cloud Organization By Thermodynamic and Dynamic States with NASA a-Train and MERRA Reanalysis Data

Thursday, 18 December 2014: 4:45 PM
Brian H Kahn1, Georgios Matheou2, Matthew Christensen2, Eric J Fetzer2, Matthew D Lebsock2, Joao Teixeira2 and Qing Yue3, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, Pasadena, CA, United States, (3)Jet Propulsion Laboratory, Santa Monica, CA, United States
Climatological relationships between warm marine boundary layer (MBL) cloud organization and coincident temperature, humidity, and moist static energy (MSE) budgets derived from the Atmospheric Infrared Sounder (AIRS) profiler, optical thickness and liquid water path from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS Aqua, and shallow precipitation from CloudSat, are discussed. All data are matched in time and space at the native instrument pixel resolution and MERRA gridding in order to retain the statistical variance and co-variance of geophysical data that is often lost in analyses with gridded Level-3 data. The cloud organization is defined by the mean, variance, and skewness of visible reflectance and infrared radiance from the AIRS and MODIS instruments. We show that MBL depth and lower tropospheric humidity increase in a transition from stratocumulus clouds that are characterized by Gaussian reflectances and radiances, to trade cumulus where the reflectances and radiances become highly skewed. Furthermore, shallow precipitation occurrence from CloudSat, wind speed and direction from MERRA, and lower tropospheric MSE and relative humidity are shown to relate to these cloud organizational states. We compare these satellite-derived observations against published results from the Rain in Cumulus over the Ocean (RICO) field campaign and large eddy simulation (LES) modeling experiments that provide testable relationships among cloud organization, humidity, precipitation, and wind speed and direction.