HR: 1400h
AN: OS33A-05    [Abstracts]
TI: Radiative Transfer Modeling of AVHRR Brightness Temperatures for Improved Sea Surface Temperature Retrievals: Initial Results
AU: * Ignatov, A
EM: Alex.Ignatov@noaa.gov
AF: NOAA/NESDIS, Center for Satellite Applications and Research (STAR), 5200 Auth Road, WWB/601, Camp Springs, MD 20746, United States
AU: Dash, P
EM: Prasanjit.Dash@noaa.gov
AF: NOAA/NESDIS, Center for Satellite Applications and Research (STAR), 5200 Auth Road, WWB/601, Camp Springs, MD 20746, United States
AU: Dash, P
EM: Prasanjit.Dash@noaa.gov
AF: Cooperative Institute for Research in the Atmospheres (CIRA), Colorado State University, Foothills Campus, Fort Collins, CO 80523, United States
AB: Operational Sea Surface Temperature (SST) products at NOAA/NESDIS have been derived from the Advanced Very High Resolution Radiometers (AVHRR) onboard NOAA satellites since the early 1980s. The two major SST algorithms, the multi-channel and non-linear SST (MC/NLSST), were initially introduced for the AVHRR in the mid- 1980s and mid-1990s, respectively. Both algorithms are based on solid physical principles but also include some empirical elements (such as for instance treatment of the view angle dependence in the SST equations and tuning their coefficients against in-situ SST), to account for approximations and assumptions in their derivation. The simple MC/NLSST formulations proved to be accurate and robust, and are still in use with the newer sensors, such as the Moderate Resolution Imaging Spectro-Radiometer (MODIS). They are also considered for the future sensors such as the Visible Infrared Imager and Radiometer Suite (VIIRS) onboard NPOESS, and the Advanced Baseline Imager (ABI) onboard GOES-R. Despite the apparent success and good accuracies, improved SST formulations should be explored based on improved and accurate Radiative Transfer Models (RTM). In order to be useful for inverse problem simulation (i.e., SST retrieval), the RTM should be able to adequately reproduce the top-of-the-atmosphere brightness temperatures. In this study, we use MODTRAN 4.2 model, coupled with two surface reflection models (black body and Fresnel), to simulate TOA brightness temperatures in the three thermal infrared AVHRR bands. Atmospheric profiles and SST come from the National Centers for Environmental Prediction (NCEP) Global Data Analysis System (GDAS) data as input, assuming aerosol- and cloud-free conditions. The simulation results are then convoluted with the respective relative spectral response functions of the individual sensors, and compared with collocated TOA brightness temperatures measured from NOAA-16, -17, and -18 satellites during nighttime. Initial results suggest, model brightness temperatures are biased high with respect to measured, in all bands. Bias is smallest in AVHRR channel 4 (11 μm; a few tenths of Kelvin), largest in channel 5 (12 μm; more than 1K), with channel 3B (3.7 μm) falling in between. In all bands, RTM slightly underestimates angular dependence. Including surface reflectance improves agreement between RTM and measurements, in all bands, but still measurable differences exist. Agreement also improves in areas which are more densely populated with satellite data, suggesting that AVHRR SSTs may be subject to residual cloud. Possible causes of the differences between RTM simulations and AVHRR measurements, and ways to reconcile them are discussed.
DE: 0550 Model verification and validation
DE: 4260 Ocean data assimilation and reanalysis (3225)
DE: 4275 Remote sensing and electromagnetic processes (0689, 2487, 3285, 4455, 6934)
SC: Ocean Sciences [OS]
MN: 2007 Joint Assembly