Prediction and Modification of Extreme Weather/Climate in Indonesia
The Houw Liong, Bayong Tj H K, R. Gernowo, P.M Siregar, F. H. widodo
From the history of natural disasters in various places in Indonesia, it can be concluded that important influences of extreme weather are floods which usually happen in December, January and February, although normally rainy season begins around the first week of November. In those months the Intertropical Convergence Zone (ITCZ) and the relative position of the sun is on the southern hemisphere. In the summer seasons of this hemisphere often emerge depression, and tropical cyclone. ITCZ and tropical cyclone cause a convergence of humid air mass which moves upward; so that water vapors will change phase becomes liquid phase through condensation process.
On the other hand in July, August, September, and October most Indonesian regions are dry season. In a long dry season these regions will lack of water and drought.
In this research it is shown mechanisms of the sun influence the weather due to relative positions and extreme weather/climate through its activities.
Early warning system of long range weather/climate can be build based on solar activity cycles that represented by time series of sunspot numbers. The time series of sunspot numbers can be predicted by using ANFIS (Adaptive Neuro Fuzzy Inference System)
For Indonesian regions beside seasonal phenomena cause by relative position of the sun, there are global and regional phenomena that influence extreme weather/climate due to solar activities such as ENSO ( El Nino Southern Oscillation), IOD ( Indian Ocean Dipole and Madden-Julian Oscillation ( MJO).
Studies of the dynamics of sun-earth interaction, dynamics of atmosphere, and dynamics of ocean and analysis of time series for predicting extreme weather in Indonesian regions are carried out. We also study the dynamics of weather modification and hydrodynamic cycle that is needed for decreasing the negative impact of extreme weather/climate such as floods and droughts that are forecast.
This study has shown that rainfalls of the middle Indonesian region are strongly correlated with sunspot numbers. ENSO mainly influences rainfalls on eastern Indonesian regions and IOD mainly influences rainfalls on western Indonesian regions.
As a case study we take the dynamics of Cilwung river as an indicator of flood forecasting in Jakarta and analysis of extreme weather using meso scale atmospheric model.
Key Words : extreme climate, extreme weather, solar activities, sunspot numbers,