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Methods for Initial Ensembles

Methods for Initial Ensembles. Assimilated observation. Sea fog case. Observed sea fog (brown shades) evolution detected from MTSAT data from 6 to 7 March 2006. The light-blue areas indicate high clouds overcast. Model configuration. Experiments design.

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Methods for Initial Ensembles

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  1. Methods for Initial Ensembles

  2. Assimilated observation

  3. Sea fog case Observed sea fog (brown shades) evolution detected from MTSAT data from 6 to 7 March 2006. The light-blue areas indicate high clouds overcast.

  4. Model configuration

  5. Experiments design There are 40 members in each ensemble experiment.

  6. SST perturbation Each ensemble member has the fixed perturbations throughout the experimental period, in order to avoid abrupt changes in the SST fields at every 6 h.

  7. Evaluation method Statistical scores POD, FAR, bias, ETS Flowchart of the Yellow Sea fog detection by using MTSAT data. (Wang et al. 2014)

  8. Results -- fog area statistical scores The probability threshold should be selected around 30%-50%,with bias around 1.0. YS and MS are better than others, especially than 2 single forecasts.

  9. BSS(Brier skill score) A good probabilistic forecast should have a positive and larger BSS. YSU and MYNN mean the five ensembles use the Y-D and M-D single forecasts as the references (BSr), respectively BSS results show that SST perturbation is important for sea fog ensembles.

  10. Fog visibility forecasts 200 m 500 m SST perturbation improves the visibility forecast, and YSU scheme is more skillful than MYNN scheme for that in this case.

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