Observing and modelling the high water level from satellite radar altimetry during tropical cyclones

Deng, Xiaoli and Gharineiat, Zahra and Andersen, Ole B. and Stewart, Mark G. (2016) Observing and modelling the high water level from satellite radar altimetry during tropical cyclones. In: Proceedings of the 2013 IAG Scientific Assembly, Postdam, Germany, 1–6 September, 2013, 1–6 September, 2013, Postdam, Germany.

Abstract

This paper investigates the capability of
observing tropical cyclones using satellite radar
altimetry. Two representative cyclones Yasi
(February 2011) and Larry (March 2006) in the
northeast Australian coastal area are selected based
also on available tide gauge sea level measurements.
It is shown that altimetry data can capture high water
levels induced by Larry and Yasi through a careful
re-processing and re-editing of the data. About 18
years of data from multi-satellite altimetry missions
including TOPEX/Poseidon, Jason-1 and Jason-2,
and seven tide gauges around the northern
Australian coast are integrated using a multivariate
regression approach. The results reveal that the
multi-regression model can, in general, explain
>60% of sea level variances in the study area. The
model is then validated using independent data from
tide gauge in Townsville. The comparison results
indicate that the high sea levels predicted by the
model taken into account of both altimetry and tide gauge
data agree well with those observed at
Townsville during cyclone Larry.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version, in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 03 Nov 2016 06:41
Last Modified: 05 Jul 2017 05:09
Uncontrolled Keywords: satellite radar altimetry, tropical cyclone, coastal sea level, multivariate regression
Fields of Research : 05 Environmental Sciences > 0599 Other Environmental Sciences > 059999 Environmental Sciences not elsewhere classified
04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040604 Natural Hazards
04 Earth Sciences > 0405 Oceanography > 040599 Oceanography not elsewhere classified
04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040699 Physical Geography and Environmental Geoscience not elsewhere classified
Socio-Economic Objective: D Environment > 96 Environment > 9603 Climate and Climate Change > 960307 Effects of Climate Change and Variability on Australia (excl. Social Impacts)
Identification Number or DOI: 10.1007/1345_2015_108
URI: http://eprints.usq.edu.au/id/eprint/29874

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