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Statistical modelling and variability of the subtropical front, New Zealand

Statistical modelling and variability of the subtropical front, New Zealand
Statistical modelling and variability of the subtropical front, New Zealand
Ocean fronts are narrow zones of intense dynamic activity that play an important role in global ocean-atmosphere interactions. Of particular significance is the circumglobal frontal system of the Southern Ocean where intermediate water masses are formed, heat, salt, nutrients and momentum are redistributed and carbon dioxide is absorbed. The northern limit of this frontal band is marked by the Subtropical Front, where subtropical gyre water convergences with colder subantarctic water. Owing to their highly variable nature, both in space and time, ocean fronts are notoriously difficult features to adequately sample using traditional in-situ techniques. We therefore propose a new and innovative statistical modelling approach to detecting and monitoring ocean fronts from AVHRR SST images. Weighted local likelihood is used to provide a nonparametric description of spatial variations in the position and strength of individual fronts within an image. Although we use the new algorithm on AVHRR data it is suitable for other satellite data or model output. The algorithm is used to study the spatial and temporal variability of a localized section of the Subtropical Front past New Zealand, known locally as the Southland Front. Twenty-one years (January 1985 to December 2005) of estimates of the front’s position, temperature and strength are examined using cross correlation and wavelet analysis to investigate the role that remote atmospheric and oceanic forcing relating to the El Nino-Southern Oscillation may play in interannual frontal variability. Cold (warm) anomalies are observed at the Southland Front three to four months after peak El Nino (La Nina) events. The gradient of the front changes one to two seasons in advance of extreme ENSO events suggesting that it may be used as a precursor to changes in the Southern Oscillation. There are strong seasonal dependencies to the correlation between ENSO indices and frontal characteristics. In addition, the frequency and phase relationships are inconsistent indicating that no one physical mechanism or mode of climate variability is responsible for the teleconnection.
Hopkins, Joanne E.
5de753a2-d2c3-4e9d-b305-52f22d5bd54c
Hopkins, Joanne E.
5de753a2-d2c3-4e9d-b305-52f22d5bd54c
Challenor, Peter
a7e71e56-8391-442c-b140-6e4b90c33547
Shaw, Andrew
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Hopkins, Joanne E. (2008) Statistical modelling and variability of the subtropical front, New Zealand. University of Southampton, School of Ocean and Earth Science, Doctoral Thesis, 208pp.

Record type: Thesis (Doctoral)

Abstract

Ocean fronts are narrow zones of intense dynamic activity that play an important role in global ocean-atmosphere interactions. Of particular significance is the circumglobal frontal system of the Southern Ocean where intermediate water masses are formed, heat, salt, nutrients and momentum are redistributed and carbon dioxide is absorbed. The northern limit of this frontal band is marked by the Subtropical Front, where subtropical gyre water convergences with colder subantarctic water. Owing to their highly variable nature, both in space and time, ocean fronts are notoriously difficult features to adequately sample using traditional in-situ techniques. We therefore propose a new and innovative statistical modelling approach to detecting and monitoring ocean fronts from AVHRR SST images. Weighted local likelihood is used to provide a nonparametric description of spatial variations in the position and strength of individual fronts within an image. Although we use the new algorithm on AVHRR data it is suitable for other satellite data or model output. The algorithm is used to study the spatial and temporal variability of a localized section of the Subtropical Front past New Zealand, known locally as the Southland Front. Twenty-one years (January 1985 to December 2005) of estimates of the front’s position, temperature and strength are examined using cross correlation and wavelet analysis to investigate the role that remote atmospheric and oceanic forcing relating to the El Nino-Southern Oscillation may play in interannual frontal variability. Cold (warm) anomalies are observed at the Southland Front three to four months after peak El Nino (La Nina) events. The gradient of the front changes one to two seasons in advance of extreme ENSO events suggesting that it may be used as a precursor to changes in the Southern Oscillation. There are strong seasonal dependencies to the correlation between ENSO indices and frontal characteristics. In addition, the frequency and phase relationships are inconsistent indicating that no one physical mechanism or mode of climate variability is responsible for the teleconnection.

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Published date: August 2008
Organisations: University of Southampton

Identifiers

Local EPrints ID: 63759
URI: http://eprints.soton.ac.uk/id/eprint/63759
PURE UUID: fd7b94ed-eb82-4973-b1aa-20d405e448ac

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Date deposited: 29 Oct 2008
Last modified: 13 Mar 2019 20:23

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