PERFORMENCE OF FORECASTING MODEL FOR AVERAGE SURFACE AIR TEMPERATURE PREDICTION OVER SOUTHEAST ASIA

Purinchaya Sornmee, Dusadee Sukawat

Abstract


In this study, the problem of prediction of a given time series has
been investigated. The monthly experimental data sets of average surface
air temperature over Southeast Asia are analyzed using Educational
Global Climate Model (EdGCM). An attempt is being made to examine
the performance of a forecasting model based on concept of error
growing rate measurement namely Lyapunov exponent (LE). Here, LE
and Supremum Lyapunov exponent (SLE) have been evaluated for average
surface air temperature under climate change condition. From the
LE and SLE behavior, it showed a clear decrease in error growing rate
of average surface air temperature after 90-years forecast. This results
suggest general good performance for surface air temperature prediction
method.

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