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A data assimilation method of the Ensemble Kalman Filter for use in severe dust storm forecasts over China

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Academic year: 2021

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Figure

Fig. 2. Correlations (line contours) of surface concentrations with those at di ff erent points denoted by the black dots directly estimated from ensemble perturbations at 03:00 UTC on 16 March 2002
Fig. 3. As in Fig. 2, but at 03:00 UTC on 20 March 2002.
Fig. 4. Comparison of RMS (the root mean square) error between observed daily-mean PM 10 levels and predicted dust aerosols concentrations (d<10 µm) at three independent validation sites without assimilation (line rectangle) and with EnKF assimilation a
Fig. 5. Same as Fig. 4, but for all observational sites.
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