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  • Author or Editor: Christoph C. Raible x
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Oliver Sievers
,
Klaus Fraedrich
, and
Christoph C. Raible

Abstract

An analog model is used to predict the tropical cyclone tracks in the Atlantic and east Pacific basins. The model is self-adapting in its search of ensembles of optimal historic analogs by creating a norm that minimizes the forecast error depending on the model parameters and the kind of prediction. Comparison with the Climatology Persistence (CLIPER) reference model shows different results in the Atlantic and east Pacific basins using the best track data as an independent verification dataset. In the Atlantic, the self-adapting analog model achieves a great circle error of same order as the reference but improves the forecasts by 15%–20% in the east Pacific. In another trial, based on simulated operational data, the performance of both models measured by absolute errors deteriorates compared to the best track data forecasts. However, the self-adapting analog scheme, which is less sensitive to noise, shows positive skill against CLIPER for all lead times in both basins.

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Klaus Fraedrich
,
Christoph C. Raible
, and
Frank Sielmann

Abstract

Tropical cyclone tracks in the Australian basin are predicted by an analog ensemble forecast model. It is self-adapting in its search of optimal ensemble members from historic cyclone tracks by creating a metric that minimizes the error of the ensemble mean forecast. When compared with the climatology–persistence reference model, the adapted analog forecasts achieve great-circle errors that improve the reference model by 15%–20%. Ensemble mean forecast errors grow almost linearly with ensemble spread.

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Christoph C. Raible
,
Georg Bischof
,
Klaus Fraedrich
, and
Edilbert Kirk

Abstract

Two statistical single-station short-term forecast schemes are introduced and applied to real-time weather prediction. A multiple regression model (R model) predicting the temperature anomaly and a multiple regression Markov model (M model) forecasting the probability of precipitation are shown. The following forecast experiments conducted for central European weather stations are analyzed: (a) The single-station performance of the statistical models, (b) a linear error minimizing combination of independent forecasts of numerical weather prediction and statistical models, and (c) the forecast representation for a region deduced by applying a suitable interpolation technique. This leads to an operational weather forecasting system for the temperature anomaly and the probability of precipitation; the statistical techniques demonstrated provide a potential for future applications in operational weather forecasts.

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Christoph C. Raible
,
Georg Bischof
,
Klaus Fraedrich
, and
Edilbert Kirk
Full access