5th GOES Users' Conference


GOES-R wind retrieval algorithm development

Iliana Genkova, CIMSS/Univ. of Wisconsin, Madison, WI; and S. Wanzong, C. S. Velden, D. A. Santek, J. Li, E. R. Olson, and J. A. Otkin

The Cooperative Institute for Meteorological Satellite Studies (CIMSS) is conducting research on satellite-derived atmospheric motion vectors (AMVs) in preparation for the GOES-R instrument series. It integrates the use of proxy and simulated data sets, such as MSG/SEVIRI imagery, WRF model derived Top of Atmosphere (TOA) radiances, simulated hyperspectral moisture analysis fields, and current GOES Sounder data. Such a framework allows for better characterization of the expected properties of GOES-R AMVs, processing error diagnostics (risk reduction), and algorithm readiness for Day1 processing.

Two distinct approaches using automated software are explored for the most efficient AMV derivation from the expected Advanced Baseline Imager (ABI) observations. The first uses the current version of the automated CIMSS/NESDIS AMV retrieval code, and is tested with a simulated ABI dataset from the WRF model. A 2km horizontal, 5-minute time step simulation was run for an hour over the east coast of the United States and into the western Atlantic Ocean. TOA radiances for ABI channels 8 through 16 were used to create images for the AMV retrieval algorithm. AMVs are then computed from heritage channels (3.90Ám, 6.19Ám, 11.2Ám, and 13.3Ám) and non-heritage channels (7.0 m, 7.3 m and 8.5 m). The software is being modified with a new ABI calibration module allowing AMV production from non-heritage channels, but the height assignment routines are retained. The second approach uses navigated and calibrated radiances and cloud top heights output from the GEOstationary Cloud Algorithm Testbed (GEOCAT). Adaptive changes are being made to the existing AMV derivation software to accommodate this new data type, in particular the height assignment under cloudy conditions. Validation efforts will use GOES and SEVIRI data. AMVs produced using both methods will be presented.

Another novel AMV effort involves the creation of height-resolved AMV profiles using constant pressure level moisture analyses derived from geostationary satellite retrievals in clear sky. This approach employs the existing automated AMV-tracking algorithm. The sources for retrieval moisture fields are: 1) real data from the current GOES sounder, and 2) simulated data from the proposed hyper-spectral sounder on GOES-R. For 2), simulated hyper-spectral retrievals from the Geostationary Imaging Fourier Transform Spectrometer (GIFTS), and the Hyper-spectral Environmental Suite (HES) are analyzed at 101 pressure levels. Levels that exhibit a strong water vapor signal and exhibit gradients are analyzed and converted to images for feature tracking. AMVs can be derived by tracking the advecting moisture features in an image triplet created from 3 successive analyses. As a result, a 3-dimensional wind field can be produced. This method is also being tested with data from the GOES11/12 sounders. Near real-time height resolved AMVs are retrieved from successive moisture analyses. The quality of the AMVs is currently being monitored and assessed. Examples will be shown.

Supplementary URL: http://cimss.ssec.wisc.edu/~ilianag/

Poster Session 1, Fifth GOES Users' Confererence Poster Session
Wednesday, 23 January 2008, 2:30 PM-4:00 PM, Exhibit Hall B

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