Utilisation FINN data version 2.5 for forecasting PM2.5 during forest fire 2019 in Sumatra by using WRF–Chem
Prawira Yudha Kombara
A * , Alvin Pratama B , Waluyo Eko Cahyono A , Wiwiek Setyawati A , Emmanuel Adetya A and Hana Listi Fitriana C
A Research Centre for Climate and Atmosphere, National Research and Innovation Agency of Indonesia, Jalan Cisitu Sangkuriang, Bandung, 40135, West Java, Indonesia.
B Department of Atmospheric and Planetary Science, Sumatera Institute of Technology, South Lampung, 35365, Lampung Province, Indonesia.
C Research Centre for Remote Sensing, National Research and Innovation Agency of Indonesia, Jalan Raya Jakarta-Bogor KM 46, Cibinong, 16911, Bogor, Indonesia.
Journal of Southern Hemisphere Earth Systems Science 73(2) 212-218 https://doi.org/10.1071/ES22030
Submitted: 26 September 2022 Accepted: 2 August 2023 Published: 17 August 2023
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of the Bureau of Meteorology. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
In 2019 there were forest fires in Sumatra, Indonesia, which co-occurred with a strong positive IOD. The forest fire disaster caused the thick smoke containing dusts such as particulate matter with a size of 2.5 μm (PM2.5). In this study, a model simulation was conducted to predict the distribution of PM2.5 using the WRF–Chem model when forest fires in 2019 occurred. The prediction was produced by adding the latest version of fire inventory from NCAR (FINN) input data, version 2.5. The prediction result was verified and compared with ground station data from the Ministry of Environment and Forestry (KLHK) station and NASA’s EOSDIS satellite imagery. There are three ground stations that were used for verification: the Jambi, Palembang and Pekanbaru stations. Of the three stations, the prediction results at the Palembang station are the best in correlation and RMSE value. Spatially, the distribution of PM2.5 from the model result is similar and can follow the pattern of smoke distribution from satellite imagery observations. Even though, generally the WRF–Chem model equipped with the latest FINN data still cannot produce an accurate prediction for the 2019 forest fires event yet in Sumatra region.
Keywords: FINN, forecasting, forest fire, PM2.5, positive IOD 2019, smoke, Sumatra, WRF–Chem.
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