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SEASONAL sensitivity study on COBEL-ISBA LOCAL FORECAST SYSTEM for fog and low clouds

SEASONAL sensitivity study on COBEL-ISBA LOCAL FORECAST SYSTEM for fog and low clouds at Paris CDG airport. ROQUELAURE Stevie and BERGOT Thierry. Météo-France. WSN05 september 2005. Outlines. + COBEL-ISBA numerical prediction model.

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SEASONAL sensitivity study on COBEL-ISBA LOCAL FORECAST SYSTEM for fog and low clouds

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  1. SEASONAL sensitivity study on COBEL-ISBA LOCAL FORECAST SYSTEM for fog and low clouds at Paris CDG airport ROQUELAURE Stevie and BERGOT Thierry Météo-France WSN05 september 2005

  2. Outlines + COBEL-ISBA numerical prediction model + Advection sensitivity on 2002-2003 winter season + Cloud (fluxes) sensitivity on 2002-2003 winter season + 3h data assimilation vs 1h data assimilation (winter 2003-2004) + Conclusions Météo-France WSN05 september 2005

  3. Aladin forecasts (3D) Observations ISBA offline guess 3h -Assimilation : 1D-Var + fog and low clouds initialisation COBEL/ISBA – 1D ? 12h local forecasts: • Detection of LVP conditions (fog and low clouds) on 30minutes • Visibility < 600m & ceiling < 200ft forecasters Cobel-Isba numerical prediction Météo-France WSN05 september 2005

  4. Aq - std Aq + std Advection (T,q) sensitivity + Simulations set (2002-2003 winter season): - ref : without advections - adv : temperature & humidity advections - AT + std : advections + temperature std - AT – std : advections - temperature std - Aq + std : advections + humidity std - Aq – std : advections - humidity std AT Aq ref (no advections) Météo-France WSN05 september 2005

  5. Advections (T,q) STD distributions + Advection are calculated from NWP model Aladin - spatial and temporal consistency  advection std distributions constant constant linear linear linear linear Météo-France WSN05 september 2005

  6. Advections (T,q) effects on LVP forecasts + All scores are from: - 2002-2003 winter season (5 months dec-April) - 3h assimilation scheme (0Z, 3Z …., 21Z)  (~1200 simulations) + Scores are calculated from all initialisations time - Hite Rate = ( forecasted&observed LVP / observed LVP ) - False Alarm Rate = ( forecasted&non-observed LVP / non-observed LVP) Météo-France WSN05 september 2005

  7. Advections (T,q) effects on LVP forecasts Advection effect + No improvements with advections (HR & FAR) + Adv is slightly better than persistence (HR) Météo-France WSN05 september 2005

  8. Temperature advection std effects on LVP forecasts cold effect + AT std impact is important on LVP (colder advection) + No symetrical effect (cold/warm advection) + No major degradation in FAR Météo-France WSN05 september 2005

  9. Humidity advection std effects on LVP forecasts humidification + AQ std impact is important on LVP (moist advection) + No symetrical effect (moist/dry advection) + Degradation in FAR (~10%) with moist advection Météo-France WSN05 september 2005

  10. Clouds initialisation + Initialisation of fog and low clouds  iterative method for minimizing the divergence between observed & cobel radiation fluxes + Simulations set (2002-2003 winter): - ref : with low clouds & fog initialisation - no : no low clouds & fog initialisation - aladin : low clouds & fog initialisation + cloud cover from aladin (IR and VIS) - obs : low clouds & fog initialisation + persistence of observed clouds (IR) Météo-France WSN05 september 2005

  11. Ref Bias=-16.6 W/m2 Aladin Bias=-6.4 W/m2 Obs Bias=-2.3 W/m2 Clouds (oberved IR vs COBEL IR) No Bias=-44.2 W/m2 Météo-France WSN05 september 2005

  12. Clouds effects on LVP forecasts Météo-France WSN05 september 2005

  13. LVP: 3h data assimilation vs 1h data assimilation + This result is from the work of MARZOUKI Hicham (master student), for winter season 2003-2004 + The only difference between the 2 simulations is the data assimilation frequency (3h  1h) 8 initialisations/day  24 initialisations/day Météo-France WSN05 september 2005

  14. LVP: 3h data assimilation vs 1h data assimilation + Improvements can be observed in HR (5%) & FAR by decreasing the data assimilation frequency to 1 hour. Météo-France WSN05 september 2005

  15. CONCLUSIONS + Advections have a important impact on LVP forecasts - moist/cold advections impact is more significant dry/warm advections - advections impact is cumulative  more important for long term simulation (4 -12 hours) + Fog and low clouds initialisation is very important - IR radiative impact  significant improvement in FAR + Improvements can be observed in HR & FAR by decreasing the data assimilation frequency to 1 hour. Météo-France WSN05 september 2005

  16. Thank you Météo-France WSN05 september 2005

  17. 00Z 06Z 12Z 18Z 24Z 30Z R=10 km site Time UTC Advection STD computation On all levels: + 1- Advection spatial mean & std 2- Advection temporal mean & std Météo-France WSN05 september 2005

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