Spatio-temporal rainfall trends in southwest Western Australia — ASN Events

Spatio-temporal rainfall trends in southwest Western Australia (6606)

Richard E Chandler 1 , Bryson Bates 2 , Ken Liang 1
  1. UCL, London, NA, United Kingdom
  2. CSIRO, Perth, WA, Australia
Rainfall across southwest Western Australia (SWWA) has declined markedly over the past five decades, with noticeably drier winter conditions in the wettest months of the year (May to July). The spatial extent and intensity of the decline has accelerated rapidly since 2000. This has had serious implications for water resources and forest management, biodiversity and agricultural productivity in the north-eastern wheatbelt. It is therefore important to establish robust and reliable methods for describing rainfall variability and trends in space-time as their application can inform decision-making processes. Regression analysis is particularly useful in this context, and two approaches are considered here. First, a nonparametric representation of the trend, within the framework of generalized additive models, is used to investigate average rainfall changes in both time and space. This approach allows for inter-site dependence and therefore ensures valid statistical inference. Second, quantile regression is used to study changes in different aspects of the rainfall distribution. This approach offers more flexibility in modelling the data, and facilitates investigation of changes in the tails of the rainfall distribution. The proposed procedures are appealing to practitioners, as they do not involve the fitting of complicated spatio-temporal models, are computationally convenient to work with, and provide important information about changes in extremes as well as means. When applied to trends in SWWA winter rainfall, the broad conclusion is that declines in the tails of the distribution are consistent with those in the main body throughout the region. This in itself suggests that the underlying mechanisms are likely to be associated with an overall reduction in moisture availability rather than, for example, a shift towards different types of rainfall which would lead to differential trends at different quantiles of the distribution.