Abstract
In the determination of atmospheric motion vectors (AMVs) from sequential images obtained from geostationary satellites, registration of the images play a primary and important role. Image registration is an essential and fundamental component in the retrieval of AMVs from triplet consecutive images of Kalpana -1 satellite is done by suitable matching of valid tracers in back and forth from middle image. If the triplet is not properly registered than it may lead to errors in wind speed and direction. The inaccuracy of registration (N-S or E –W shift) in one set of triplet images will generate the errors in wind speed and direction this will affect in other images if available in sequence also. Image registration maintains the spatial relationship between the pixels within images and between images. Improper registration results due to the deviation in orbital parameters, spacecraft attitude, thermal distortions and earth sensor biases. If we need continuous train of images like, sometimes we need morphing in images to get continuous AMVs which can be a potential source of errors for the input of Numerical Weather Prediction (NWP). But in this framework the other issues will also need further investigation like cloud evolution, height assignment and thickness biases, etc. in AMVs. In this paper, authors will deal only the registration issue. It has been shown from daily registration shift in Kalpana -1 satellite images during the year 2008 between 0000UTC to 0200 UTC in Northern Hemisphere that, the errors introduced in wind speed varies from 10 m/sec to 45 m/sec at nadir due to registration only. Few cases have been shown appreciable improvement after applying the interactive correction of registration errors. Keywords: AMV, Image registration, NWP, Weather
Highlights
The Atmospheric Motion Vectors (AMVs) winds are derived by passive tracers in triplet image sequence of half an hour difference
In AMVs retrieval, all N images are in sequence and optimized matching is applied to subsequent N-1 images and the suitable candidate is saved along with its score
Type of simulation (Bremen et al, 2009) by using the high resolution European Centre for Medium Range Weather Forecast (ECMWF) forecast fields over a 6 hour period is tried and AMVs is derived at Cooperative Institute of Meteorological Satellite Studies (CIMSS)
Summary
The Atmospheric Motion Vectors (AMVs) winds are derived by passive tracers in triplet image sequence of half an hour difference. Image registration accuracy in AMV computation should be of the order of one pixel, if it is more than it will introduce an error in the wind speed. The winds production process is much more The procedure used, in the present paper is based on sensitive to changes in registration than to errors in Christopher et al (2001) in which the random shift ( x, y) absolute earth location (i.e., navigation). Due midnight navigation are worsened during the periods just to the dynamical nature of the meteorological before and just after satellite eclipse, which occur near phenomena, an image time sequence analysis is more the time of solar equinox and registration quality were appropriate, which can be used for AMVs detection. Apparent in early experimental GOES-8/9 winds Because the response of the every pixel is important, as it processing, prompting NESDIS to perform manual is the representative of the average temperature of the registration corrections (Nieman et al, 1997)
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