Utilisation FINN data version 2.5 for forecasting PM2.5 during forest fire 2019 in Sumatra by using WRF-Chem

被引:0
作者
Kombara, Prawira Yudha [1 ]
Pratama, Alvin [2 ]
Cahyono, Waluyo Eko [1 ]
Setyawati, Wiwiek [1 ]
Adetya, Emmanuel [1 ]
Fitriana, Hana Listi [3 ]
机构
[1] Natl Res & Innovat Agcy Indonesia, Res Ctr Climate & Atmosphere, Jalan Cisitu Sangkuriang, Bandung 40135, West Java, Indonesia
[2] Sumatera Inst Technol, Dept Atmospher & Planetary Sci, South Lampung 35365, Lampung, Indonesia
[3] Natl Res & Innovat Agcy Indonesia, Res Ctr Remote Sensing, Jalan Raya Jakarta Bogor KM 46, Bogor 16911, Indonesia
关键词
FINN; forecasting; forest fire; PM2.5; positive IOD 2019; smoke; Sumatra; WRF-Chem; MODEL; SIMULATION; CHEMISTRY; EMISSIONS;
D O I
10.1071/ES22030
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
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 mu m (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.
引用
收藏
页码:212 / 218
页数:7
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