Estimation of Atmospheric Motion Vectors from Kalpana-1 Imagers

Abstract

The estimation of atmospheric motion vectors from infrared and water vapor channels on the geostationary operational Indian National Satellite System Kalpana-1 has been attempted here. An empirical height assignment technique based on a genetic algorithm is used to determine the height of cloud and water vapor tracers. The cloud-motion-vector (CMV) winds at high and midlevels and water vapor winds (WVW) derived from Kalpana-1 show a very close resemblance to the corresponding Meteosat-7 winds derived at the European Organisation for the Exploitation of Meteorological Satellites when both are compared separately with radiosonde data. The 3-month mean vector difference (MVD) of high-and midlevel CMV and WVW winds derived from Kalpana-1 is very close to that of Meteosat-7 winds, when both are compared with radiosonde. When comparing with radiosonde, the low-level CMVs from Kalpana-1 have a higher MVD value than that of Meteosat-7. This may be due to the difference in spatial resolutions of Kalpana-1 and Meteosat-7.

An inter‐comparison of Kalpana‐1 and Meteosat‐7 atmospheric motion vectors against radiosonde winds and NWP forecasts during monsoon 2011

“…Over the Northern Hemisphere, Kalpana-1 high level CMVs shows fast bias when compared to RS winds. Kishtawal et al (2009) reported similar results for Meteosat-7 and Kalpana-1 high level CMVs when both were compared independently against RS winds.…”

“…The high bias in the Kalpana-1 low and middle level CMVs with respect to NCMRWF T574L64 model first guess may be due to the empirical GA method used to retrieve the AMVs (Das Gupta and Rani, 2013). The good agreement between the Meteosat-7 AMVs and first guess may be due to its high spatial resolution (Kishtawal et al, 2009). Meteosat-7 images are taken at half hourly interval and the spatial sampling at the sub-satellite point corresponds to 5 km × 5 km in the IR and WV channels (Schmetz et al, 1993), whereas in Kalpana-1 the spatial sampling at the sub-satellite point corresponds to 8 km × 8 km in the IR and WV channels.…”

“…The comparisons of Kalpana-1 and Meteosat-7 AMVs with respect to the RS winds are reported by Deb et al (2008) and Kishtawal et al (2009). This paper describes a comparison of Kalpana-1 and Meteosat-7 AMVs to the in situ RS winds and short-term NWP forecasts during the 2011 monsoon.…”

“…EUMETSAT, NESDIS, etc.) use the H 2 O/CO 2 intercept technique for height assignment, which uses NWP models first guess as background, while an empirical method based on the genetic algorithm (GA) is used (Deb et al, 2008;Kishtawal et al, 2009) in Kaplana-1. Deb et al (2008) reported that though the GA-based approach is computationally inexpensive, and looks promising, with mean absolute error in height of approximately 27 hPa, it is an ad hoc method and tries to mimic statistically the operational height assignment method used in Meteosat-5.…”

A novel approach for the extraction of cloud motion vectors using airglow imager measurements

“…The retrieval techniques improved from a simple cross correlation analysis in the beginning (Izawa and Fujita, 1969;Leese et al, 1971;Hubert and Whitney, 1971) to those involving very advanced photogrammetry and satellite imagery analysis in recent times for obtaining CMVs with higher precision (Schmetz et al, 1993;Velden et al, 1997;Kishtawal et al, 2009;Deb et al, 2015;Kaur et al, 2014 and references therein). First level unrefined knowledge about a cloud element can be obtained from the cloud top temperatures, retrieved by Thermal infrared (IR) channel.…”