Weather/Climate Regional Model in Indonesia and Terrestrial Effects of Solar Activity

Weather/Climate Regional Model in Indonesia
and Terrestrial Effects of Solar Activity

Plato M. Siregar 1) Deni Septiadi 2) The Houw Liong 3)

1) Science Atmosphere Division, Faculty of Earth Science and Mineral Technology, ITB
2) Climatology Station of Siantan Pontianak, Meteorologycal and Geophysical Agency, BMG
3) Physics of Complex System Division, Faculty of Mathematics and Natural Sciences, ITB



ABSTRACT

Weather/Climate in Indonesia is influenced by four main quasi periodic cycles: Solar Activity Cycle (Sunspot Numbers Cycle), Galactic Cosmic Ray Cycle, El Nino Southern Oscillation (ENSO) Cycle, and Indian Ocean Dipole Mode (IOD) Cycle. It can be shown that solar activity cycle can be considered as primary cycle that influence other cycles. In practice eastern Indonesian region is dominantly influenced by ENSO. When the heat pools moves to eastern Indonesian region, then rainfall in this region will be above normal. On the other hand when the heat pool leaves eastern Indonesian region and moves to Pacific Ocean then the rainfall in this region will be below normal.
During a typical Indian Ocean Dipole Mode (IOD) event the weakening and reversal of winds in the central equatorial Indian Ocean lead to the development of unusually warm sea surface temperatures in the western Indian Ocean. IOD negative means wet condition or the rainfall will be above normal along the western Indonesian region.
Precipitation in Pontianak region which represent middle Indonesian region correlated strongly with sunspot numbers cycle (solar activity cycle).
Using ANFIS (Adaptive Neuro Fuzzy Inference System) we are able to predict sunspot numbers cycles so that extreme weather in Indonesian regions can be predicted.
Fuzzy c-means is used to classify regions that are influenced strongly by sunspot numbers (solar activity), IOD, and ENSO cycles. This method is based on fuzzy set as fuzzy c-partition of three cycles above and as cluster center. Fuzzy c-partition matrix for grouping a collection of n data set into c classes.
This study explores the physical of climate predictions and classifications of Indonesian regions and its physical interpretations.
This research using monthly rainfall data (mm) collected by 5 raingauges in West Kalimantan (BMKG) with 46 years length of data (1961-2006). Additionally data are monthly sunspot and cosmic rays data (1961-2006) of Royal Observatory of Belgium and Sunspot Index Data Center at http://www.astro.oma.be/SIDC.


Keywords : ANFIS, fuzzy clustering, climate, solar activity