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GOES-R/ABI Legacy Profile Algorithm Evaluation Using MSG/SEVIRI

GOES-R/ABI Legacy Profile Algorithm Evaluation Using MSG/SEVIRI. Xin Jin 1 , Jun Li 1 , Timothy J. Schmit 2 , Jinlong Li 1 , Elisabeth Weisz 1 , Zhenglong Li 1 , and Mitchell D. Goldberg 2

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GOES-R/ABI Legacy Profile Algorithm Evaluation Using MSG/SEVIRI

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  1. GOES-R/ABI Legacy Profile Algorithm Evaluation Using MSG/SEVIRI Xin Jin1, Jun Li1, Timothy J. Schmit2 , Jinlong Li1, Elisabeth Weisz1, Zhenglong Li1, and Mitchell D. Goldberg2 1 Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin - Madison, 2 NOAA/NESDIS/STAR Xin.Jin@ssec.wisc.edu 2.Algorithm Evaluation Using SEVIRI, RAOB and Analysis Abstract SEVIRI (Spinning Enhanced Visible and InfraRed Imager ) onboard the Meteosat Second Generation (MSG-1) satellite is used as proxy to test the algorithm to retrieve the legacy atmospheric profiles from the Advanced Baseline Imager (ABI) onboard the next generation GOES Satellite (GOES-R) . The ECMWF 12H forecasts are used as first guess. The ECMWF analysis data and the radiosonde data are used for validation. The SEVIRI data for August 2006 is processed. Results show that the improvement is significant between 300 and 700 hPa for moisture profiles. Since there is only one temperature-sensitive spectral band on SEVIRI, the temperature profile does not show noticeable improvement. SEVIRI spectral bands 5 (6.2 µm), 6 (7.3 µm), 9 (10.8 µm), 10 (12 µm), 11 (13.4 µm) are used in physical retrieval. Band 7 (8.7 µm) can also be included in physical retrieval over ocean. One month (August 2006) spatially and temporally collocated SEVIRI/RAOB/Analysis data over radiosonde observation sites are used. Operational SEVIRI cloud mask product from EUMETSAT is used for clear pixel identification. Test results show that physical retrieval does improve the regression which is used as the first guess, and the regression improves the forecast. Solid lines: ABI Dash lines: SEVIRI Radiosonde Observations (RAOBs) in August 2006 (see the sites in left panel) are used for SEVIRI legacy profile evaluation over land. ECMWF forecasts are used as the background. WV1: SFC – 900 hPa WV2: 900 – 700 hPa WV3: 700 – 300 hPa 1. Algorithm for Legacy Profiles Using ABI The algorithm has been reviewed by GOES-R Algorithm Working Group (AWG) in June 2007. The recommendation has been made on the selection of physical algorithm for ABI legacy profile related products. The algorithm is built upon the current improved GOES legacy sounding method (Ma et al. 1999; Li et al. 2000; Li et al. 2008). Some important components of the algorithm include: (1) 1DVAR approach - Maximum likelihood approach; (2) Regularization with discrepancy principal (Li and Huang 1999); (3) Observation error covariances; (4) Reliable fast and accurate radiative transfer model (RTM) for inverse and the linear tangent model of RTM for Jacobian. Currently PFAAST is used for algorithm testing; (5) Short-range forecast as background; (6) Background error covariance matrix; (7) EOF representation for profile; (8) Regression as first guess; (9) Predetermined surface IR emissivities for inverse; (10) Radiance bias adjustment 3.Algorithm Evaluation Using SEVIRI and AMSR-E over Ocean Δ time < 15 minutes Δ dist < 10 km. References Li, J., W. Wolf, W. P. Menzel, W. Zhang, H.-L. Huang, and T. H. Achtor, 2000: Global soundings of the atmosphere from ATOVS measurements: The algorithm and validation, J. Appl. Meteorol., 39: 1248 - 1268. Li, J., and H.-L. Huang, 1999: Retrieval of atmospheric profiles from satellite sounder measurements by use of the discrepancy principle, J. Appl. Optics,38, 916-923. Li, Zhenglong,Jun Li, W. P. Menzel, T. J. Schmit, J. P. Nelson, J. Daniels, and S. A. Ackerman, 2007: GOES sounding improvement and applications to severe storm nowcasting, Geophysical Research Letters (in press). Ma, X. L., T. Schmit, and W. L. Smith, 1999: A non-linear physical retrieval algorithm - its application to the GOES-8/9 sounder. J. Appl. Meteor., 38, 501-513. Validation of TPW from SEVIRI physical retrievals compared with TPW from AMSR-E over ocean in August 2006 (2,822,939 samples). Mean bias (SEVIRI – AMSR-E) (middle) and RMSE (right) for all pixels collected for August 2006: pixels are grouped into each 1 by 1 deg. boxes, only boxes with more than 20 samples are considered. 4. Summary As imaging instruments, SEVIRI/ABI has two/three broadband water vapor absorbing bands for moisture retrieval, but temperature information is limited. The legacy type profile related products can be developed by combining short range forecast and ABI/SEVIRI IR radiances. The legacy algorithm has been evaluated with SEVIRI. Retrieved TPW is comparable with AMSR-E and better than the forecast. The high spatial/temporal resolution and wide coverage makes SEVIRI/ABI a unique instrument to monitor continuous moisture variation. ACKNOWLEDGEMENT: This study was partly funded by GOES-R Risk Reduction (GOES-R3) and GOES-R Algorithm Working Group (AWG) projects at CIMSS. Thanks to Mat Gunshor for the help on this study. The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration or U.S. Government position, policy, or decision.

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