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1、Prototyping SST Retrievals from GOES-R ABI with MSG SEVIRI Data Nikolay V. Shabanov1,2, Nikolay.Shabanovnoaa.gov, (301)763-8102 154 Alexander Ignatov1, Boris Petrenko1,2, Yuri Kihai1,3, XingMing Liang1,4, Wei Guo1,2, Feng Xu1,4, Prasanjit Dash1,4, Michael Goldberg1 , John Sapper5 1NOAA/NESDIS/STAR;
2、2IMSG Inc; 3Perot Systems Government Services; 4Colorado State University- CIRA; 5NOAA/NESDIS/OSDPD Geostationary Operational Environmental Satellite-R Series (GOES-R) will carry Advanced Baseline Imager (ABI) onboard. Sea Surface Temperature (SST) algorithm for ABI is being developed by the SST Tea
3、m which is a part of the GOES-R Algorithm Working Group (AWG). ABI SST production is prototyped with the Meteosat Second Generation (MSG) Spinning Enhanced Visible and IR Imager (SEVIRI) data (Schmetz et al., 2002). The Advanced Clear-Sky Processor for Oceans (ACSPO) developed at NOAA/NESDIS and cur
4、rently operational with AVHRR data onboard NOAA-18 and MetOp-A has been adopted to SEVIRI. ACSPO-SEVIRI system processes 15-minute full-disk (FD) SEVIRI Level 1 data in near-real time (NRT) and generates Level 2 clear-sky products over ocean, including top-of-atmosphere (TOA) clear-sky brightness te
5、mperatures (BTs), SST and aerosols. This poster evaluates initial BT and SST retrievals from Meteosat-9 SEVIRI for one full month of data in June 2008. The views, opinions and findings contained in this report are those of the authors and should not be construed as an official NOAA or U.S. Governmen
6、t position, policy, or decision. This poster does not reflect the views or policies of the GOES-R Program Office or Algorithm Working Group. ACSPO-SEVIRI System CRTM simulations for SEVIRI longwave bands 9 (11 m) and 10 (12 m) are consistent with similar results for the AVHRR. More analyses are need
7、ed to better quantify these preliminary observations. M-O bias in Ch4 (3.7 m) is inconsistent with AVHRR and requires further analyses. Comparison with Global Reference SSTs The SST Quality Monitor (SQUAM) currently routinely generates consistency statistics between the retrieved AVHRR SST and multi
8、ple reference SST fields (Dash et al., 2009). SQUAM was applied to quickly evaluate SEVIRI SST retrievals. The following reference SST were used: Daily Reynolds: OISST (AVHRR-based) and OISST-A (AVHRR+AMSR-E), OSTIA, RTG HR (High Resolution) and Low Resolution (LR), and Pathfinder SST climatology. S
9、ST Diurnal Cycle Introduction CRTM and BT Simulations Fig. 2. Example of MSG-2 SEVIRI 15-min FD data for June 14, 2008, 2:00pm UMT, processed by the ACSPO-SEVIRI system. (a) Visible true-color image constructed from albedo. Black strip expanding from SE corresponds to night-time; (b) Cloud Mask; (c)
10、 SST; (d) AOD retrieved from Ch01 using single-channel algorithm (De Paepe et al., 2008). Dash et al., (2009). The SST Quality Monitor (SQUAM), submitted, RSE. De Paepe et al., (2008). Aerosol retrieval over Ocean from SEVIRI for the use in GERB Earths radiation budget analysis, RSE, 112, 2455-2468.
11、 Liang et al., (2009). Implementation of CRTM in ACSPO and validation against nighttime AVHRR radiances, submitted, JGR. Merchant et al., (2008). Optimal estimation of sea surface temperature from split-window observations, in press, RSE. Schmetz et al., (2002). An Introduction to Meteosat Second Ge
12、neration, BAMS, 83, 977-992. Walton et al. (1998). The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites. JGR, vol. 103(C12), 27999- 28012. Disclaimer Literature (a) (b) (d) (c) Input
13、to ACSPO-SEVIRI system is 15-min SEVIRI FD channel data (optical Ch1-3 and thermal Ch4, 9-10). 1-resolution weekly Reynolds SST and 6-hour National Centers for Environmental Prediction Global Forecast System (NCEP/GFS) data are used as input to the fast Community Radiative Transfer Model (CRTM) to s
14、imulate clear-sky BT in Ch4, 9-10 (Liang et al., 2009). Two SST algorithms are implemented. The Regression (split-window, NLSST) algorithm is based on Walton et al. 1985 equation: Currently used regression coefficients a0a3 were derived by EUMETSAT for Meteosat-8. The Physical algorithm uses CRTM to
15、 invert BT9 and BT10 for SST and water-vapor optical depth scaling factor (Merchant et al., 2008). The regression and physical algorithms will be cross-evaluated, to generate a superior quality hybrid SST algorithm. For this study, a simplified cloud-mask was implemented which currently uses only tw
16、o tests: SST test (comparison of retrieved and Reynolds SST) and BT test (comparison of CRTM simulated and measured BTs). The end-to-end NRT processing system has been set up for data stream processing: (1) downloading SEVIRI data from NOAA operational servers (in collaboration with AWG Land Team), (2) data processing at SST Team servers, (3) data analysis with web-based QC tools. SEVIRI data for 2008 are online, 2006-2007 are on external disks. The product file contains up
