Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

Abstract

El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can affect the increase in rainfall intensity and the number of dry days, also known as dry spells that can cause drought and increase the potential for forest fires. This study examines the effect of ENSO and IOD conditions on the joint distribution of the number of dry days and total precipitation in a fire-prone area in southern Sumatra, Indonesia. The joint distribution is constructed using rotated copulas from several families, including Gaussian, student's t, Clayton, Gumbel, Frank, Joe, Galambos, BB1, BB6, BB7, and BB8. Fire-prone areas are defined using k-mean clustering, while the copula parameters are estimated using the inference of function for margins (IFM) method. Based on the peak of joint probability density functions (PDFs), ENSO and IOD conditions had a significant effect in the dry season but had no significant effect in the rainy season. The peak of joint PDFs is getting to the dry-dry conditions when the ENSO and IOD indexes increase in the dry season. However, based on coincidence probability, ENSO conditions still influence the joint distribution between the number of dry days and total precipitation during the rainy season but not with IOD conditions. The lower the ENSO index, the higher the probability of wet conditions co-occurring in the number of dry days and total precipitation. Meanwhile, ENSO and IOD conditions significantly affect the coincidence probability between the number of dry days and total precipitation. Moderate-Strong El Niño has the most considerable coincidence probability of 68.5%, followed by Positive IOD with 62.6%. The two conditions had similar effects on the joint distribution of the number of dry days and total precipitation. Moreover, the association between the number of dry days and the total precipitation was stronger in the dry season than in the rainy season.

Analisis Pembentukan Sebaran Bivariat Berbasis Copula Antara Luas Area Terbakar dan Curah Hujan di Sumatra Bagian Selatan

“…Oleh karena itu, penelitian ini menganalisis sebaran bersama antara luas area terbakar dan curah hujan di Sumatra bagian selatan menggunakan copula. Data yang digunakan pada penelitian ini yaitu data area terbakar Global Fire Emissions Database with small fires (GFED4s) sebagai indikator kebakaran, data European Centre for Medium-Range Weather Forecasts (ECMWF) sebagai dara curah hujan, serta indeks Oceanic Nio Index SST 3.4 (ONI) dan Dipole Mode Index (DMI) masing-masing sebagai indeks dari indikator iklim global ENSO dan IOD yang telah diekstraksi pada penelitian sebelumnya [23]. Analisis dilakukan menggunakan copula berdasarkan Inference of Function for Margins (IFM).…”

“…Data yang digunakan dalam penelitian ini adalah data presipitasi dan luas area terbakar yang masing-masing diekstraksi dari ECMWF Reanalysis v5 (ERA5) dan Global Fire Emissions Database (GFED4s). Data diekstraksi pada area rawan terbakar di Sumatra bagian selatan yang telah didefinisikan oleh Nurdiati et al [23]. Sementara itu, data indeks Nio 3.4 atau ONI adalah data deret waktu yang direproduksi dari psl.noaa.gov/gcos wgsp/Timeseries/Nino34/.…”