1. EMS LJUBLJANA, 2006 Mathias D. Müller 1, C. Schmutz 2, E. Parlow 3 An ensemble assimilation and forecast system for 1D fog prediction 1,3) Institute of Meteorology, Climatology & Remote Sensing University of Basel, Switzerland Mathias.mueller@unibas.ch www.meteoblue.ch 2) MeteoSwiss

2. 1D fog modeling(COBEL-NOAH and PAFOG) Radiationland surface model Turbulencemicrophysics + initial (IC) and boundary conditions (BC)

3. Initial conditions Initialization: - observations of temperature & humidity - 3D model data: aLMo, NMM-22, NMM-4, NMM-2 Data assimilation

4. Boundary conditions Boundary conditions: From 3D models: aLMo, NMM-22, NMM-4, NMM-2 - Clouds - Advection of temperature & humidity Valley fog 3D t

5. Initialization – Data assimilation 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Temperature (°C) analysis (x) observation (y) background (x b ) error: „the magic“ Temperatur202221.5 observationbackgroundanalysis B and R determine the relative importance

6. NMM-4 1400 UTC large model and time dependence Assimilation - B for 3 different 3D models (Winter) NMM-22 00 UTC NMM-4 00 UTC aLMo 00 UTC

7. Initialization – Data assimilation (example) 28 Nov 2004 Zürich Airport 21 hour forecast of NMM-2

8. The ensemble forecast system variational assimilation B-matrices COBEL-NOAH PAFOG Obser - vations 3D-Model runs post-processing Fog forecast period NMM-4 NMM-2 NMM-22 aLMo 3D - Forecast time www.meteoblue.ch 1D-models Different IC and BC

9. Ensemble Forecast - Example fog HEIGHT (m) 2 m Temperature (°C) 2 m rel. Hum. (%) INITIALIZED: 14 OCTOBER 2005 1500 UTC 100 90 80 70 60 50 14 12 16 10 8 6 4

10. Verification of the 1D ensemble forecast - ROC FALSE ALARM RATE HIT RATE no skill 0 1 1 10 40 60 Fog (observation) = visibility < 1000 m Fog (model) = liquid water content > threshold has probability x ROC fog: 10 60 Fog – yes/no?

11. Importance of Advection Sensitivity to humidity assimilation Verification of the 1D ensemble forecast - ROC 03-11 UTC from 1 November 2004 until 30 April 2005

12. advection of cooler and drier air cool warm dry humid Hourly advection estimates (different 3D models) 03-11 UTC from 1 November 2004 until 30 April 2005

13. - Initialisierungszeitpunkt - Multimodel PAFOG MODEL-ENSEMBLE COBEL-NOAH 15:00 UTC 18:00 UTC 21:00 UTC00:00 UTC Verification of the 1D ensemble forecast - ROC

14. 1D ensemble forecast has the potential to improve fog prediction at Zürich airport: Advection (of cooler and drier air) is very important Humidity assimilation with large uncertainty → more observations, humidity ensemble COST-722 MeteoSwiss Conclusions EnsembleHit RateFalse Alarm rate COBEL-NOAH PAFOG 60 % 80 % 30 % 45 % 1D Thanks

15. 3D simulations even more promising Model satellite

18. Assimilation – R für Radiosonde in Payerne

19. Write in incremental Form Introduce T and U transform to eliminate B from the cost function (physical space) (Control variable space) Assimilation – inkrementelle cost function

20. NMC-Method (use 3D models): Assimilation – Error covariance Matrix