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PM2.5 forecast system by using machine learning and WRF model, A case study: Ho Chi Minh City, Vietnam

Vo Thi Tam Minh1,2, Tran Trung Tin3,2 , To Thi Hien1,2

1 Faculty of Environment, University of Science, Ho Chi Minh City, Vietnam

2 Vietnam National University, Ho Chi Minh City, Vietnam 3 Faculty of Applied Science, University of Technology, Ho Chi Minh City, Vietnam

Corresponding author. Tel: (+84) 387-353-440 E-mail address: vttminh@hcmus.edu.vn

The evaluation results of WRF forecast

The evaluation results of meteorological data simulated by WRF compared with observed meteorology. The results of these two datasets have a good correlation. Simulated meteorological data can be used as input to a machine learning model. The objective of this study was to evaluate a machine learning model using meteorological data simulated by WRF. The forecast results show similarities with observations; see Figs. S1-S4 and the following assessments.

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Fig. S1. Temperature observed and predicted by WRF model (a) in September, 2020 and (b) January 2021

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The WRF model has very good predictive performance for meteorological data ranging from temperature and humidity to wind direction and wind speed. Fig. S1 is a comparison between forecast and observed temperature data for September 2020 (Fig. S1a) and January 2021 (Fig. S1b). The trends of the two temperature data sets are highly correlated. The temperature variation with time in both graphs roughly coincides. The trend is similar for relative humidity variation (Fig. S2). For two months, the forecast results by WRF are similar to the observed data.

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Fig. S2. Relative humidity observed and predicted by WRF model (a) in September, 2020 and (b) January 2021

The wind roses in Fig. S3 is the result of wind parameter prediction with two components of wind direction and wind speed. The WRF model does a pretty good job of predicting seasonal wind trends. September 2020 belongs to the rainy season, the dominant wind direction is the southwest monsoon. Comparing the forecast and observation results for this month in Figs. S3 (a), (b), the WRF model correctly predicted the dominant wind direction. The trend of wind speed (Fig. S4 a) also gives quite similar results, although not as good as the forecast for the two temperature and humidity ranges. Similar to the dry season, in January 2021, the main wind season is the northeast monsoon, the results of the WRF model give a very good forecast (Fig. S3 c,d and Fig. S4b).

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(a) observed September, 2020 (b) predicted September, 2020

(c) observed January, 2021 (d) predicted January, 2021

Fig. S3. Wind rose observed and predicted by WRF model (a) (b) in September, 2020 and (c) (d) January 2021

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Fig. S4. Wind speed observed and predicted by WRF model (a) in September, 2020 and (b) January 2021