||Federation and Meteorology
Table of Contents
Developments in Climatology in Australia
Australian Climatology Before 1946
The Current State and Future of Climatology
Climate Prediction (continued)
Since the 1982/83 El Niņo, the influence of this phenomenon on Australian climate has become well-recognised. So much so, that a computer package, 'Australian RAINMAN', has been developed by several organisations, notably the Queensland Department of Primary Industries and the Bureau of Meteorology, to provide information to individual users. This package allows users to investigate the likely consequences of particular phases or trends of the SOI on rainfall at thousands of locations. This information, with readily available real-time SOI values, can allow users to prepare their own seasonal climate forecasts.
Dynamical methods, using coupled ocean-atmosphere models, can also provide predictions of the likely future behaviour of the El NiņoSouthern Oscillation. The Bureau uses a dynamical model of the coupled ocean-atmosphere system in the tropical Pacific to predict the behaviour of sea-surface temperatures related to the El Niņo (Kleeman 1996). Forecasts of east equatorial Pacific sea-surface temperatures from this model have been included in the Seasonal Climate Outlooks since 1996. This coupled model does not include all the complex mechanisms involved in the atmosphere and ocean, but retains the larger-scale mechanisms believed responsible for the El NiņoSouthern Oscillation. Similar models were first used to predict the 1986/87 El Niņo and have been used operationally ever since, although with continual improvements. They have demonstrated some skill in prediction, forecasting the 1991 and (some models) the 1994 El Niņo events. They do, however, only forecast ocean conditions, i.e., sea-surface temperatures. These are then interpreted in terms of the El Niņo and its statistical implications for rainfall over the areas generally affected by the phenomenon. The Kleeman model, unlike some other models of this type, uses sub-surface ocean temperature data (Smith 1995). The inclusion of these data has led to improved model predictions and the model can provide forecasts of El Niņo several seasons ahead.
A new statistical forecast system, which uses global and regional patterns of sea-surface temperature as predictors, has been developed to replace the current operational technique based largely on the SOI. It is expected that the less chaotic nature of the sea-surface temperature fields should allow for improved predictions, partly because less smoothing will be necessary, and also because effects separate from the El NiņoSouthern Oscillation may provide skill in areas where the El NiņoSouthern Oscillation is of little help. Nicholls (1989) and Drosdowsky (1993a, b) suggest that the sea-surface temperature fields in the Indian Ocean and Indonesian area may provide predictions for some of the areas where the El NiņoSouthern Oscillation is not dominant.
More refined statistical techniques are being used to develop systems for operational prediction. A major problem with the development of statistical forecast systems is the short period of data available for development. Typically, only about 50 years of data are available. The shortness of this period means care is needed if 'artificial skill' is not to degrade the accuracy of the forecasts. Such artificial skill arises from attempting to use many predictors to improve the apparent skill on the data used to derive the statistical forecast system. The 'increased' skill then usually disappears when the system is used operationally. In fact, inclusion of extra predictors can actually lead to a degradation of the forecasts. The new systems under development take great care to avoid this problem.
People in Bright Sparcs - Nicholls, Neville
© Online Edition Australian Science and Technology Heritage Centre and Bureau of Meteorology 2001
Published by Australian Science and Technology Heritage Centre, using the Web Academic Resource Publisher