RESEARCH ARTICLE Height Assignment Improvement in Kalpana-1 Atmospheric Motion Vectors S. K. Deb & Steve Wanzong & C. S. Velden & Inderpreet Kaur & C. M. Kishtawal & P.K. Pal & W. P. Menzel Received: 11 September 2012 / Accepted: 15 April 2013 # Indian Society of Remote Sensing 2014 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 assign- ment methods such as the infrared window (WIN) tech- nique, the H 2 O intercept, and the cloud base method in the Kalpana-1 AMV retrieval algorithm. The new height as- signment algorithm significantly improves the statistics of the retrieved winds when compared to radiosondes, espe- cially in high and mid levels winds. Keywords Height assignment . AMV . Kalpana-1 Introduction The generation of atmospheric motion vectors (AMVs) from infrared and water vapor channel images of geosta- tionary satellites began operationally in the early 1970s (Hubert and Whitney 1971). The winds from the satellite images are derived using the movement of cloud and water vapor features in the atmosphere. The use of water vapor images from geostationary platform has allowed the use of winds from clear-sky regions, targeting upper-level mois- ture content as well. The AMVs are used for assimilation in both regional and global-scale models that result in positive impacts on weather forecasts (Kelly 2004; Bedka and Mecikalski 2005; Deb et al. 2010), especially in the tropics. However, optimal use of these winds at operational centers across the globe is hindered by the improper height estima- tion of the retrieved vectors, especially in thin semitrans- parent clouds. The AMVs are currently available from many operational centers across the globe on real-time (Velden et al. 2005; Nieman et al. 1993; Velden et al. 1997; Schmetz et al. 1993; Tokuno 1996). Minimal work has been done for AMV retrieval from the meteorological geostationary Indian National Satellite System (INSAT) series (e.g., INSAT-3A, Kalpana-1) of satellites. With the availability of IR-window (10.5 μm) and WV (6.3 μm) channels on the Kalpana-1 Very High Resolution Radiometer (VHRR), initial operational derivation of AMVs consisted of cloud-tracked winds (950–100 hPa) and WV winds (500–100 hPa) from INSAT (Kishtawal et al. 2009). The algorithm is running operational at the Space Applications Centre (SAC), Indian Space Research Organization (ISRO) Ahmedabad, India (here after called the Kalpana-1 operational algorithm). One of the major constraints of optimum use of AMVs from the Kalpana-1 operational algorithm at NWP centres in India is due to J Indian Soc Remote Sens DOI 10.1007/s12524-013-0278-z S. K. Deb (*) : I. Kaur : C. M. Kishtawal : P. K. Pal Atmospheric and Oceanic Sciences Group, Space Applications Centre, Indian Space Research Organization, Ahmedabad 380015, India e-mail: sanjib_deb@sac.isro.gov.in S. K. Deb e-mail: sanjib_deb@rediffmail.com S. Wanzong : C. S. Velden : W. P. Menzel Cooperative Institute for Meteorological Satellite Studies, Space Science and Engineering Center, 1225, West Dayton Street, Madison, WI 53706, USA