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A comparison of automated methods of front recognition for climate studies: A case study in southwest Western Australia


Hope, P and Keay, K and Pook, M and Catto, J and Simmonds, I and Mills, G and McIntosh, P and Risbey, J and Berry, G, A comparison of automated methods of front recognition for climate studies: A case study in southwest Western Australia, Monthly Weather Review, 142, (1) pp. 343-363. ISSN 0027-0644 (2014) [Refereed Article]


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DOI: doi:10.1175/MWR-D-12-00252.1


The identification of extratropical fronts in reanalyses and climate models is an important climate diagnostic that aids dynamical understanding and model verification. This study compares six frontal identification methods that are applied to June and July reanalysis data over the Central Wheatbelt of southwest Western Australia for 1979–2006. Much of the winter rainfall over this region originates from frontal systems. Five of the methods use automated algorithms. These make use of different approaches, based on shifts in 850-hPa winds (WND), gradients of temperature (TGR) and wet-bulb potential temperature (WPT), pattern matching (PMM), and a self-organizing map (SOM). The sixth method was a manual synoptic technique (MAN). On average, about 50% of rain days were associated with fronts in most schemes (although methods PMM and SOM exhibited a lower percentage). On a daily basis, most methods identify the same systems more than 50% of the time, and over the 28-yr period the seasonal time series correlate strongly. The association with rainfall is less clear. The WND time series of seasonal frontal counts correlate significantly with Central Wheatbelt rainfall. All automated methods identify fronts on some days that are classified as cutoff lows in the manual analysis, which will impact rainfall correlations. The front numbers identified on all days by the automated methods decline from 1979 to 2006 (but only the TGR and WPT trends were significant at the 10% level). The results here highlight that automated techniques have value in understanding frontal behavior and can be used to identify the changes in the frequency of frontal systems through time.

Item Details

Item Type:Refereed Article
Keywords:automated algorithms, automated techniques, extratropical fronts, identification method, model verification, potential temperature, seasonal time series, southwest Western Australia
Research Division:Earth Sciences
Research Group:Climate change science
Research Field:Climate change processes
Objective Division:Environmental Policy, Climate Change and Natural Hazards
Objective Group:Understanding climate change
Objective Field:Climate change models
UTAS Author:McIntosh, P (Dr Peter McIntosh)
ID Code:119495
Year Published:2014
Web of Science® Times Cited:48
Deposited By:Ecology and Biodiversity
Deposited On:2017-08-02
Last Modified:2017-10-16
Downloads:140 View Download Statistics

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