Numerical Analysis using Empirical Orthogonal Function Based on Multivariate Singular Value Decomposition on Indonesian Forest Fire Signal

International Conference On Tropical Meteorology And Atmospheric Sciences

生态环境科学;原子能学

Septiawan, P.^1 ; Nurdiati, S.^1 ; Sopaheluwakan, A.^2

Mathematics Department, Faculty of Mathematics and Natural Science, Bogor Agricultural University, Bogor

16680, Indonesia^1

Research and Development Center, Meteorology, Climatology and Geophysics Agency, Jakarta

10720, Indonesia^2

关键词: Burned areas;    Carbon emissions;    Climate hazards;    Empirical Orthogonal Function;    Empirical orthogonal function analysis;    Forest fires;    GFEDs;    Station data;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/303/1/012053/pdf
DOI  :  10.1088/1755-1315/303/1/012053

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Over the past years, fires have burn Indonesian forest annually. The strength of the fire and many of fire points is vary each year. In 1997 there was 9.75 million ha forest burned in one year with 206,6 million ton of carbon emissions. In 2015 there was 2.089 million ha forest and 805 million tons carbon emissions. Both years involved the biggest incidences of burned forest in Indonesia. The purpose of this research is to analyze the pattern of burned forest in Indonesia and to analyze linkages of variables that affect it. Datasets that used in this research is monthly data from 1997 until 2016 Global Fires Emissions Database (GFED) with variable burned area, GFEDs with variable carbon emissions, and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Using Singular Value Decomposition and Empirical Orthogonal Function analysis, for the overlapping period detected that there is annual signal that dominate the incidences of fires in Indonesia, especially in Riau, Palembang, South Kalimantan and Central Kalimantan. There was 4 annual signal that can explain 72% of fires incidences in Indonesia in 1997-2016. In Riau there is another signal that have 6 months period caused by 6 months rainfall period.