Height Assignment Improvement in Kalpana-1 Atmospheric Motion Vectors |
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| Authors: | S K Deb Steve Wanzong C S Velden Inderpreet Kaur C M Kishtawal P K Pal W P Menzel |
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| Institution: | 1. Atmospheric and Oceanic Sciences Group, Space Applications Centre, Indian Space Research Organization, Ahmedabad, 380015, India
2. Cooperative Institute for Meteorological Satellite Studies, Space Science and Engineering Center, 1225, West Dayton Street, Madison, WI, 53706, USA
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| Abstract: | The real-time operational use of atmospheric motion vectors (AMVs) at numerical weather prediction (NWP) centers in India are being adversely affected due to inaccurate height assignment of cloud tracers, especially in thin semi-transparent clouds. In India, the operational derivation of AMVs from the Indian geostationary satellite Kalpana-1 began few years ago. A statistical empirical method (SEM) of height assignment, based on a genetic algorithm, is currently used to estimate the height of the retrieved vectors from Kalpana-1. This method has many limitations. In this paper, attempts have been made to implement the widely used and well tested height assignment methods such as the infrared window (WIN) technique, the H2O intercept, and the cloud base method in the Kalpana-1 AMV retrieval algorithm. The new height assignment algorithm significantly improves the statistics of the retrieved winds when compared to radiosondes, especially in high and mid levels winds. |
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