Extended Abstract (592K)P1.10
Determination of wind vectors by tracking features on sequential moisture analyses derived from hyperspectral IR satellite soundings
Christopher Velden, CIMSS/Univ. of Wisconsin, Madison, WI; and G. Dengel, R. Dengel, A. Huang, D. Stettner, H. Revercomb, R. Knudsen, and W. Smith
CIMSS is developing new approaches to passive wind tracing that will be possible from hyperspectral sounders to be flown on future geosynchronous satellites. Future measurements of atmospheric wind profiles derived from space-based platforms will involve the concept of altitude-resolved "water vapor winds". The wind observations will be taken from instruments yielding time-sequential moisture analyses derived from hyperspectral measurements. These hyperspectral measurements should provide the needed vertical resolution to derive profiles of wind velocity necessary to realize the full potential of satellite measurements. An algorithm to derive clear-sky, altitude-resolved water vapor winds is being developed and evaluated. The method utilizes the same contemporary automated cloud-tracking code used in operational practice at NOAA, however, rather than using single-channel images, the input to the algorithm is in the form of constant-level moisture analyses derived from hyperspectral sounding information. In this approach, time sequences (30-min analyses) of retrieved water vapor fields (such as constant-pressure mixing ratio analyses) become the ‘imagery’ for tracking winds. Since the moisture fields will already be analyzed to constant pressure surfaces by the retrieval, the heights of tracked moisture gradients (water-vapor wind vectors) will be pre-determined. Therefore, height assignment errors that contemporary geo-based winds suffer from should be minimized, and improved water vapor winds should result. Furthermore, the hyperspectral information allows analyses of moisture at multiple vertical levels in cloud-free areas, which can then be used to attempt to create vertical profiles of wind. These new concepts have been demonstrated by first examining simulated hyperspectral data sets, and also on one case of real data from airborne observations provided by a NASA hyperspectral instrument. The results from the real case show good agreement with a doppler wind lidar also flown on the aircraft. This new approach to retrieve winds from satellites in cloud-free areas could become a standard in regions where geosynchronous satellite hyperspectral observations are available. Our future work will concentrate on improving the target identification and tracking schemes, and transitioning the approach to operational practice when the hyperspectral data become available.
Poster Session 1, New and Future Sensors and Applications: Part 1
Monday, 20 September 2004, 9:45 AM-11:30 AM
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