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Evaluation of Antarctic Mesoscale Prediction System (AMPS) cyclone forecasts using infrared satellite imagery

Published online by Cambridge University Press:  17 October 2011

Melissa A. Nigro ,
John J. Cassano  and
Shelley L. Knuth
Melissa A. Nigro*
Affiliation:
Department of Atmospheric and Oceanic Sciences, Co-operative Institute for Research in Environmental Sciences, University of Colorado, 216 UCB, Boulder, CO 80309, USA
John J. Cassano
Affiliation:
Department of Atmospheric and Oceanic Sciences, Co-operative Institute for Research in Environmental Sciences, University of Colorado, 216 UCB, Boulder, CO 80309, USA
Shelley L. Knuth
Affiliation:
Department of Atmospheric and Oceanic Sciences, Co-operative Institute for Research in Environmental Sciences, University of Colorado, 216 UCB, Boulder, CO 80309, USA
*
[email protected]
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Abstract

The Antarctic coast is an area of high cyclonic activity. Specifically, the regions of Terra Nova Bay, in the western Ross Sea, and Byrd Glacier, in the western Ross Ice Shelf, are prone to cyclone development. The United States, New Zealand, and Italian Antarctic programmes conduct extensive research activities in the region of the western Ross Sea. Due to the harsh weather conditions associated with the cyclonic systems that occur in this region and the abundant research activities in the area, it is important to be able to accurately predict the timing, location and strength of cyclones in this sector of Antarctica. This study evaluates the ability of the Antarctic Mesoscale Prediction System (from 2006–09) to accurately forecast cyclones in the region of the western Ross Sea by comparing the Antarctic Mesoscale Prediction System forecasts to cyclones identified in infrared satellite imagery. The results indicate that the Antarctic Mesoscale Prediction System is able to accurately predict the presence of cyclones about 40% of the time (at a minimum) and the presence of no cyclones about 70% of the time.

Keywords

cyclone forecastingmodel evaluationremote sensingRoss Sea sectorWeather Research and Forecasting (WRF) model
Type
Physical Sciences
Information
Antarctic Science , Volume 24 , Issue 2 , 28 February 2012 , pp. 183 - 192
Copyright
Copyright © Antarctic Science Ltd 2011

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