Resolution sensitivity of cyclone climatology over eastern Australia using six reanalysis products.

Di Luca, A., J. Evans, A. Pepler, L. Alexander and D. Argueso
Journal of Climate, 28(24), 9530-9549, doi: 10.1175/JCLI-D-14-00645.1, 2015.

Abstract

The climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input data. Moreover, at these coarse horizontal scales, monthly, interannual, and spatial variabilities appear to be very similar across the various reanalyses with a generally stronger agreement between winter events compared with summer ones. Results also show that, when looking at cyclones using reanalysis data at their native resolution (approaching 50-km grid spacing for the most recent products), uncertainties related to the frequency, intensity, and size of lows are very large and it is not clear which reanalysis, if any, gives a better description of cyclones. Further work is needed in order to evaluate the usefulness of the finescale information in modern reanalyses and to better understand the sources of their differences.

Key Figure


Fig. 2. Annual average of the (a) event-mean 200-km MSLP gradient, (b) number of events, (c) event-mean duration, and (d) event-mean size as a function of the spatial scale. The various datasets are shown in different colors. Low-resolution reanalyses (NCEP1 and NCEP2) and the SP2009 are only available for the 300-km spatial scale.


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