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All Journal Forum Geografi Forest and Society
Latifah, Arnida L.
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science Social Sciences

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Correlation of Climate Variability and Burned Area in Borneo using Clustering Methods Hidayati, Ishardina C.; Nalaratih, Novinda; Shabrina, Ayu; Wahyuni, Intan N.; Latifah, Arnida L.
Forest and Society Vol. 4 No. 2 (2020): NOVEMBER
Publisher : Forestry Faculty, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24259/fs.v4i2.9687

Abstract

The island of Borneo has faced seasonal forest fires for decades. This phenomenon is worsening during dry seasons, especially when droughts are concurrent with the El Niño-Southern Oscillation (ENSO) phenomenon. Climate is therefore one of the drivers of the fire phenomenon. This paper studies the relationship between climate variables, namely temperature, precipitation, relative humidity, and wind speed, and the occurrence of forest fire using two clustering methods, K-means and Fuzzy C-means (FCM) clustering methods. Borneo is clustered into four areas based on burned area data obtained from Global Fire Emission Data (GFED). It is also clustered according to the combinations of climate variables. Both methods reach the highest correlation between the climate variable and the burned area clusters in September. The K-means method gives a correlation of -0.54 while the FCM gives -0.55. In August until October, relative humidity provides the dominant correlation affecting burned area, even though an additional precipitation or wind variable slightly increases the correlation in the FCM method. In November, temperature largely contributed to the burned area by a positive correlation of 0.31 in K-means and 0.33 in FCM. The evaluation performance of the methods is conducted by an internal validation called the Silhouette index. Both methods have positive index values ranging from 0.39 to 0.69 and the maximum value is influenced by the wind cluster. This indicates that the clustering methods applied in this paper can identify one or a combination of climate variables into dense and well-separated clusters.
Investigation of the Development of Tropical Storm Nicholas based on Global and Regional Climate Data Wahyuni, Intan Nuni; Shabrina, Ayu; Lobma, Fadhil; Latifah, Arnida L.
Forum Geografi Vol 37, No 2 (2023): December 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i2.21728

Abstract

This paper studies the simulation of Cyclone Nicholas that occurred close to the coastal area of Western Australia and fell on the mainland of Southwestern Australia. The simulation was conducted via a dynamical downscaling model, Weather Research and Forecasting (WRF), to obtain a higher resolution with reference to the regional climate data. The model simulation is generated using a global reanalysis of climate data for the initial and lateral boundary conditions. We investigated the response of the tropical storm to the model regarding the track and intensity using a modified Kyklop method that appears more appropriate for a landfall cyclone. Our study suggests that the regional climate data computed by the model deviates from the storm track of the global climate data forcing field. In this study, the track of the simulated storm is parallel to the satellite data, but it is shifted slightly to the east, closer to the mainland. Nevertheless, the model simulation can implement the intensity of the storm as strongly as the observation, while the forcing data delivers substantial underestimation.
Co-Authors Ayu Shabrina Hidayati, Ishardina C. Lobma, Fadhil Nalaratih, Novinda Wahyuni, Intan N. Wahyuni, Intan Nuni