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Ann. Geophys., 23, 3229-3235, 2005
www.ann-geophys.net/23/3229/2005/
© European Geosciences Union 2005
A complex autoregressive model and application to monthly temperature forecasts
X. Gu1 and J. Jiang2
1State Key Laboratory of Sever Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
2Training Center of China Meteorological Administration, Beijing, 100081, China
Abstract. A complex autoregressive model was established based on
the mathematic derivation of the least squares for the complex number
domain which is referred to as the complex least squares. The model is
different from the conventional way that the real number and the imaginary
number are separately calculated. An application of this new model shows a
better forecast than forecasts from other conventional statistical models, in
predicting monthly temperature anomalies in July at 160 meteorological
stations in mainland China. The conventional statistical models include an
autoregressive model, where the real number and the imaginary number are
separately disposed, an autoregressive model in the real number domain, and
a persistence-forecast model.
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