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A heavy rainfall sounding climatology over Gauteng, South Africa, using self-organising maps

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Abstract

The daily weather at a particular place is largely influenced by the synoptic circulation and thermodynamic profile of the atmosphere. Heavy rainfall occurs from a particular subset of synoptic and thermodynamic states. Baseline climatologies provide objective information on heavy rainfall-producing circulation patterns and thermodynamic variables. This is how climatologically large or extreme values associated with heavy rainfall are identified. The aim of this research is to provide a heavy rainfall sounding climatology in austral summer over Gauteng, South Africa, using self-organising maps (SOMs). The results show that the SOM captures the intra-seasonal variability of heavy rainfall soundings by clearly distinguishing between the atmospheric conditions on early summer (October–December) and late summer (January–March) heavy rainfall days. Conditions associated with heavy early summer rainfall are large vertical wind shear and conditional instability, while the atmosphere is drier and cooler than when heavy rainfall occurs in late summer. Late summer heavy rainfall conditions are higher convective instability and small vertical wind shear values. The SOM climatology shows that some heavy rainfall days occur in both early and late summer when large-scale synoptic weather systems cause strong near-surface moisture flux and large values of wind shear. On these days, both the conditional and convective instability of the atmosphere are low and heavy rainfall results from the strong synoptic forcing. In contrast, heavy rainfall also occurs on days when synoptic circulation is not very favourable and the air is relatively dry, but the atmosphere is unstable with warm surface conditions and heavy rainfall develops from local favourable conditions. The SOM climatology provides guidelines to critical values of sounding-derived parameters for all these scenarios.

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Dyson, L.L. A heavy rainfall sounding climatology over Gauteng, South Africa, using self-organising maps. Clim Dyn 45, 3051–3065 (2015). https://doi.org/10.1007/s00382-015-2523-3

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