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 2) MeteoSwiss

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

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

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

Initialization – Data assimilation Temperature (°C) analysis (x) observation (y) background (x b ) error: „the magic“ Temperatur observationbackgroundanalysis B and R determine the relative importance

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

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

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 1D-models Different IC and BC

Ensemble Forecast - Example fog HEIGHT (m) 2 m Temperature (°C) 2 m rel. Hum. (%) INITIALIZED: 14 OCTOBER UTC

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

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

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

- 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

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

3D simulations even more promising Model satellite

Assimilation – R für Radiosonde in Payerne

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

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