ESRL Contributes to Transition of Improved GOES Sounder Products into Ops
In 2012, ESRL's Global Systems Division/Forecast Applications Branch (GSD/FAB) developed a Web-based software application that was used by the University of Wisconsin's Space Science Engineering Center (SSEC) to evaluate the reliability of proposed improvements to future Geostationary Operational Environmental Satellite (GOES) sounder products. This evaluation was successful, and the new data processing software is scheduled to transition into NOAA operations on February 21, 2013.
For more than a decade, NESDIS has used the Ma Algorithm (Ma et al. 1999) to retrieve vertical temperature and moisture profiles, total (column integrated) precipitable water vapor (TPW), and derived atmospheric stability indices from its operational GOES spacecraft in geostationary orbit above the eastern and western U.S. The decision to transition from the Ma algorithm to an improved algorithm (Li et al. 2008) was motivated by several factors including: 1) the availability of advanced radiative transfer codes not available in the 1990s; 2) improved radiance bias correction techniques; 3) the ability to use true error covariance matrices in place of approximations; 4) a surface emissivity regression scheme in place of a fixed model; and 5) single (10 km) field-of-view estimates versus 30 km (3x3 pixel averages) used in the Ma algorithm, to improve horizontal resolution and enhance cloud detection/elimination.
In early FY2012, FAB was asked by NESDIS to collaborate with SSEC and verify the benefits of the Li algorithm. Using the techniques developed by Birkenheuer and Gutman (2005), FAB developed an application (http://gpsmet.noaa.gov/goesssec) that allows SSEC scientists and engineers to compare legacy and improved GOES products with ground-based GPS water vapor observations at more than 300 locations over the continental U.S.
This application provided SSEC with a convenient way to objectively compare the relative benefits of the Li and Ma algorithms, reliably assess the impact of changes in the Li algorithm on TPW accuracy and precision, and gather sufficient justification for NESDIS managers to support the decision to transition the research software into operations.
- Birkenheuer, D. and S. I. Gutman, 2005: A comparison of GOES moisture-derived product and GPS-IPW data during IHOP 2002. J. Atmos. Ocean. Technol., 22, No. 11, pp. 1840–1847.
- Li, Z., J. Li, W. P. Menzel, T. J. Schmit, J. P. Nelson III, J. Daniels, and S. A. Ackerman, 2008: GOES sounding improvement and applications to severe storm nowcasting. Geophys. Res. Lett., 35, L03806.
- Ma, Xia L., T. J. Schmit, and W. L. Smith, 1999: A nonlinear physical retrieval algorithm - Its application to the GOES-8/9 sounder. J. Appl. Meteor., 38, 501-513.
Name: Seth Gutman