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August 11, 2008 | by  | in Opinion | [ssba]

Predicting Rainfall: Modelling Weather in the Waikato

Stacey Dravitzki is studying towards a PhD in meteorology looking at predicting short and long term weather patterns in the Waikato. Her research is funded by Mighty River Power Ltd, and predicts rainfall. Her research is teamed with a second researcher, who models how rainfall affects the level of the Waikato River.

Dravitzki’s predictive model is based upon two sources; global weather modelling, and statistical information about weather in the Waikato over the past 100 years. The statistical information is used to make probabilistic predictions of what is likely to result from given indicia, but also takes account of climate phenomena such as El Niño and La Niña, and linear changes over long periods of time such as climate change.

The last week has seen three sub-tropical cyclones pass over the New Zealand, which were all predicted. The weather forecasts and photos of these recent storms can be found on More rain is predicted to occur between Salient going to print and being distributed whixch could lead to flooding in the Waikato.

Dravitzki has observed that ‘heavy events’ in the Waikato are being caused by multiple storms arriving in succession, the first saturating the area, and further storms causing flooding.

Dravitzki’s data is derived from model runs from several international institutions. Part of her research has been to determine how many days in advance the predictions of these institutions are reflecting the weather patterns that actually follow. One problem with this is that the models are global, and the data produced for New Zealand is not sufficiently sophisticated to accurately predict incoming weather. In addition, much of New Zealand’s rainfall is caused by hills, which the global models deal with poorly. High resolution modelling will be used to determine how much of the rainfall is caused by the hills. Dravitzki will be assessing this later in her research, and potentially incorporating it into her final presentation to Mighty River Power .

Another technique used, in addition to combining data from global models with historical data, is to run what is known as ‘model ensembles’. This is running essentially the same model several times, but with minor variations in each one. If the models do not produce similar results, the researcher knows that the model’s predictive power is weak for the coming storm.

Dravitzki has shown that predictions up to five days in advance are usually reliable. Five to seven days offers a good indication, and is testing the usefulness of the new 16 day forecasts that are not currently publically avaliable.

Because of the enormity of the datasets Dravitzki (and those doing similar projects in geophysical fields), is dealing with, special servers hosts these. In addition, many of these students have multiple terabyte (1000 gigabyte) personal discs for data storage. This gives an idea of the complexity of the data that is being dealt with.

Stacey Dravitzki holds a BSc in mathematics, a BSc (Hons) in geophysics and an MSc in geophysics, both from Victoria University.


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  1. John Brier says:

    This response may be well out of date, but sounds exciting for all people interested in prediction of rainfall. There seems very little work done in Agriculture like this.
    Obviously climatic expectations should be used alot more to determine ideal seed strike, lambing/calving dates, fertiliser application time and alot more strategic operations. Do you know of such data and predictive models?

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