A Modified Tracer Selection and Tracking Procedure to Derive Winds Using Water Vapor Imagers

Abstract

The remotely sensed upper-tropospheric water vapor wind information has been of increasing interest for operational meteorology. A new tracer selection based on a local image anomaly and tracking procedure, itself based on Nash-Sutcliffe model efficiency, is demonstrated here for the estimation of uppertropospheric water vapor winds both for cloudy and cloud-free regions from water vapor images. The pressure height of the selected water vapor tracers is calculated empirically using a height assignment technique based on a genetic algorithm. The new technique shows encouraging results when compared with Meteosat-5 water vapor winds over the Indian Ocean region. The water vapor winds produced by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) from Meteosat-5 and the present algorithm are compared with collocated radiosonde observations according to Coordination Group for Meteorological Satellites guidelines. The proposed algorithm shows better accuracy in terms of mean vector difference, rms vector difference, standard deviation, speed bias, number of collocations, and mean speed and mean direction differences. Also it is found that the sensitivity of the spatial consistency check in the quality indicator is not so significant for the improvement of statistics.

Estimation of Atmospheric Motion Vectors from Kalpana-1 Imagers

“…The anomaly-based tracers are generally produced by a smooth feature field in comparison with the gradient-based features. This difference can help in reducing the tracking errors (Deb et al 2008). The cross-correlation technique is used operationally for tracking the tracer between two WV images in most operational centers.…”

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

“…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.…”

“…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. The retrieval of satellite winds from Meteosat-7 follows an automatic method Schmetz et al (1993), the cloud tracking uses cross-correlation and the height assignment is based on satellite observed brightness temperature and a predicted temperature profile.…”

A comparative assessment of Kalpana-1 and MISR cloud tracked winds over the Indian Ocean region

“…It is also well established that the large source of uncertainty in restricting the optimum use of AMVs is the limitation of height assignment (Velden and Bedka 2009) techniques, which basically depends on the radiative transfer calculation of cloud radiometric signature in infrared, CO 2 , or water vapour channels and forecast temperature profiles. The AMVs from the infrared and water vapour channels of Indian Geostationary satellite Kalpana-1 are being retrieved by tracking clouds operationally at every 30-min interval at the Space Applications Centre (SAC), Indian Space Research Organisation (ISRO), Ahmedabad (Deb et al 2008;Kishtawal et al 2009), and recently, some changes have been made to the operational algorithm; especially the use of multiple images for quality control procedure (Deb et al 2013) and changes in the height assignment (Deb et al 2014a) technique (i.e. implementation of infrared window technique, H 2 O intercept method, and cloud base method, etc.).…”