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Atmospheric Motion Vectors Height Assignment by IRW and Water Vapour (H2O) Intercept Methods
The atmospheric motion vectors (AMV's) derived from geostationary satellites are valuable tool in weather forecasting especially in data sparse region. This paper presents the results of an inter-comparison of AMVs assigned heights derived from Meteosat -7&Kalpana -1, geostationary satellite data for both lower and upper levels by Infrared Window (IRW) and Water Vapour (H2O or IR/WV) intercept methods. The Kalpana -1 satellite data (different sensor and resolution than Meteosat -7) is being processed by similar algorithm as Cooperative Institute of Meteorological Science (CIMSS), USA. In this short study of inter-comparison, the utility of the IR/WV intercept method in assigning the height of derived wind vectors especially at upper level winds is shown graphically. It is observed that actual wind speed direction from radiosonde data at upper levels (300-150 hPa) is higher up to the order of 8-12 m/sec and 5-8 degree for Kalpana - 1 data after applying the semi-transparency correction.
Keywords
Meteosat-7, Kalpana-1, Atmospheric Motion Vectors, IRW, H2O Intercept, Meteorological Data
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- Coakley J and Bretherton FF (1982) Cloud cover from high resolution scanner data: Detecting and allowing for partially filled of view. J. Geophys. Res. 87 (C7), 4917-4932.
- Holmlund K (1993) Operational water vapour wind vectors from Meteosat imagery data. Second International Wind Workshop, Tokyo Japan, 13-15 Dec., EUMP 14, 77-84.
- Jianmin, Xu Qisong and Zhang (1996) Calculation of cloud motion wind with GMS -5 images in China. Third International Wind Workshop, Ascona, Switzerland, 10-12 June, EUMP 18, 45-52.
- Key J and Schweiger AJ (1988) Tools for atmospheric radiative transfer: Streamer and FluxNet. Computers & Geosci. 24(5), 443-451.
- Laurent H (1990) Feasibility study on water vapour wind extraction techniques. Final report, ESA, Publ., ESTC, B.P.299, 2200.
- Menzel WP, Wanzong S, Nieman S and Schmetz J (1993) Assigning height to cloud motion winds. Proc. of 2nd International Wind Workshop (Darmstadt: EUMETSAT), Tokyo, Japan,13-15 Dec.,197-205.
- Merrill, RT, Menzel WP, Baker W, Lynch J and Legg E (1991) A report on the recent demonstration of NOAA’s upgraded capability to derive cloud motion satellite winds. Bull. Amer. Meteor. Soc. 72, 372-376.
- Nieman N, Schmetz J and Menzel WP (1993) A comparison of several techniques to assign heights to cloud tracers. J. Appl. Meteorol. 32, 1559-1568.
- Schmetz J, Holmlund K, Hoffman J. Strauss, Mason B, Gartner B, Koch VA and Berg L van de (1993) Operational cloud-motion winds from Meteosat infrared images. J. Appl. Meteor. 32, 1206–1225.
- Stamnes K, Wiscombe S, Tsay W and Jayaweera K (1988) Numerically stable algorithm for discreteordinate- method radiative transfer in multiple scattering and emitting layered media. Appl. Opt. 27, 2502-2509.
- Stewart TR, Hayden CM and Smith WL (1985) A note on water vapour wind tracking using VAS data on McIDAS. BAMS, 66,1111-1115.
- Szantai A and Desbois M (1991) Wind extraction and validation from water vapour channel of Meteosat during the International Cirrus Experiment. In: Workshop on wind extraction from operational meteorological satellite data,17-18 Sep., Washigton, DC.
- Szejwach G (1982) Determination of semi-transparent cirrus cloud temperatures from infrared radiances: application to Meteosat. J. Appl. Meteor. 21, 384.
- Tokuno M (1996) Operational system for extracting cloud motion and water vapour motion winds from GMS-5 image data. Proc. of 3rd Intl. Workshop, Ascona, Switzerland EUM. pp:18, 21-30.
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