A Comparison of Automated Methods of Front Recognition for Climate Studies: A Case Study in Southwest Western Australia

Abstract

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 . 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.

Seasonal and regional signature of the projected southern Australian rainfall reduction

“…Frontal systems are very important for rainfall in southern Australia (Berry et al, 2011;Simmonds et al, 2012) particularly in the southeast in autumn (Catto et al, 2012) and the southwest in winter, where they have been found to be declining in number (Hope et al, 2014). Fronts in an example GCM, ACCESS1.3, tend to be well represented in their frequency and the proportion of precipitation associated with them (Catto et al, 2013), although the intensity of that precipitation is underestimated.…”

Rainfall Changes over Southwestern Australia and Their Relationship to the Southern Annular Mode and ENSO

“…A strong inverse relationship has been found between coastal SWA rainfall and the MSLP over the region (Allan and Haylock 1993;Ansell et al 2000;Li et al 2005), indicating the role of large-scale circulation pattern in controlling the rainfall. In particular, the decline in winter rainfall has been associated with the reduced frequency of front-like low pressure systems over the region (Hope et al 2006;Alexander et al 2010) and the increases in both station MSLP over SWA and sea surface temperature (SST) over the southern Indian Ocean . For example, Risbey et al (2013) found that the reduction in coastal JJA rainfall during 1985-2009 is mostly associated with the frontal systems.…”

“…Despite a decrease in the number of low pressure systems, the mean annual frequency of fronts in the region, as deduced from several reanalyses, has increased during 1989-2009 (Berry et al 2011a). It is likely that these conflicting conclusions can be attributed to the different methods used to identify and classify rain-bearing synoptic systems such as fronts, troughs, and cutoff lows (Hope et al 2014).…”

“…Similarly Risbey et al (2013) found that the rainfall over inland SWA from cutoff lows has decreased during 1985-2009. Local changes in the land-cover type are also thought to contribute the reduced rainfall along the coast and the increased rainfall over inland area (Pitman et al 2004), although the magnitude of their contribution is difficult to quantify. It is also difficult to explain how local changes in the land-cover change the frequency of fronts and troughs as summarized in the cluster analysis of Hope et al (2006) or change the midlatitude storm tracks and position and strength of the jet stream, as reported by Frederiksen and Frederiksen (2007) and Frederiksen et al (2011).…”

“…Cluster analysis is a method commonly used to classify synoptic and surface conditions (Stone 1989;Hope et al 2006) or radiosonde profiles (Pope et al 2009) into distinct weather regimes. From the properties of these weather regimes and their trends, inferences are drawn about the physical processes responsible for the associated rainfall and its trend.…”