1. Radiation Fog Forecasting Using a 1-D Model
Lionel Peyraud
MétéoSwiss – Geneva
Switzerland

2. Possible Solutions 3-D mesoscale numerical forecasting (i.e. MM5)
Statistical regression forecasting (i.e. MOS)
Link between observations/model forecast and visibility based on archived cases in database.
Most statistically significant predictors retained
Expert systems, various empirical rules and conceptual models And also…
High resolution 1-D forecasting of the boundary layer
-MM5: Current finest resolution with model ~ large computer time necessary with added finer vertical rez.
- MOS: Model Output Statistics currently has obstruction to visibility forecasts including fog.

3. Objectives
To establish a baseline performance for the COBEL 1-D model for radiation fog forecasting
Get model simulations in close agreement with actual weather observations.
Tune the model so that the simulations portray realistic fluctuations of weather parameters with respect to the incorporated model parameterizations.

4. Objectives
Interface COBEL with various 3-D high resolution numerical models and determine optimal coupled configuration.
Establish a list of weather parameters that affect fog the most and attribute to them a range that span the observed forecasting outcomes obtained through the One-Dimensional Ensemble Technique (ODEP).
Incorporation of an assimilation technique utilizing relevant instrumentation at airport sites.

5. Objectives Run the coupled COBEL model in a semi-operational mode.
Synthesize results and establish a useful forecasting scheme with revisions as necessary.
Run coupled COBEL model as a real-time forecasting tool.

6. A Little History on COBEL…
Developed in France for the study of physical processes in nocturnal BL (Univ. Paul Sabatier, 1988)
Used as a fog forecasting tool (1993)
Paul Sabatier + Météo France (Nord pas de Calais)
Adapted to day conditions, more external forcings, data assimilation, wake vortex studies
(UQAM, )
Stratus dissipation forecasting at SFO
(UQAM, present)
Radiation fog forecasting for Ohio River Basin
Texas A&M + ILN NWSFO ( present)

7. A Little History on COBEL…
Low Ceiling & reduced visibility study in NYC area (NCAR, present)
Various cobel projects in France, Belgium (ongoing)

8. Methodology
Based on: sounding data input into 1-D model integrated through time.
Data
12Z vertical profiles from Payerne, CH
(Temp, q, u & v wind components)
Soil data (temp & moisture)
Hard-coded data obtained from various sources
External forcings (advections,clouds over grid, etc…) from coupled 3-D model

9. Methodology Local modification of variables for forecast site
Soundings, soil temps, soil moisture
Assimilation technique using ceilometers and sodars

10. COBEL Model Time Steps Dry conditions: 60 seconds
Cloudy conditions: 30 seconds
IR radiative calculations: 15 minutes
SW radiative calculations: 1 minute
Output frequency: 1 minute

11. Hard coded input variables into COBEL
Soil moisture (2 layers=>0-5cm, 5cm-1m)
Incoming solar flux at top of radiative grid (5.3km)
Soil temperatures (3 levels=>0cm, -10cm, -1m)
Roughness lengths (momentum & heat)
Coriolis parameter
Soil specific heat
Surface emissivity
Surface albedo
Soil type
Surface atmospheric pressure
Vegetation parameters (currently not validated)

12. 1-Dimensional Modeling
1-D (Column)
Boundary Layer Model
A Detailed Look at
the Physical Processes
High Vertical
Resolution
Radiative Transfer
Turbulent Mixing
Soil-Atmosphere
Interactions
- momentum
- heat
- humidity

13. Simulated Physical Processes
LW radiative transfer (emission, absorption)
SW radiative transfer
(scattering, transmission, reflection, absorption)
Turbulent mixing w/ variable stratification
(very stable, stable, neutral, unstable profiles)
Surface/atmosphere exchanges
(heat, moisture, momentum)
Soil moisture vertical transport
(diffusion, conductivity)
Diabatic effects (condensation, evaporation)
Precipitation physics
(autoconversion, collection, evaporation)

14. Physical Processes (continued)
Gravitational settling of cloud droplets
TKE production
(by wind shear, buoyancy, transport, dissipation)
Horizontal pressure force (external forcing)
Horizontal advection (external forcing)
(temperature, humidity, momentum)
Vertical advection (by mesoscale vertical motion)
Pressure tendency (external forcing)

15. COBEL Vertical Resolution
2 staggered grids
Log-linear increase in resolution (0-1.4km)
Finest: 0.5 meters
Coarsest: 30 meters
Above 1.4km=> 5 levels for radiative calc. Only
Secondary grid=>radiative fluxes, turbulent fluxes, TKE (31 levels)
Primary grid =>temp, wind, humidity, cloud water, TKE flux (30 levels)
“Extension of primary grid”
(5 levels=> soil temp only)

16. Boundary Conditions Fluxes
Top: turbulent fluxes of θ, q, ql = 0 (above 1.4km),
IR flux from clouds above rad. grid
Bottom: flux of TKE=0 (z0), sfc albedo & emissivity
Temperature
Soil temp assumed constant at –1meters
Wind
Top: no boundary condition used
Bottom: u=v=0, TKE flux=0

17. Initialization Above ground
Observed vertical profiles of T, q, u&v wind from z=0-5.3 km
Tweaked soil temps, soil moisture and lower sounding winds
Altitude of stratus/fog base and top obtained via ceilometers and sodars
Below ground
Soil temperatures at 0cm, 10cm, 1m
Soil moisture between 0-5cm, 5cm-1m

18. Sensitive Parameters with Ranges
Parameter Range
21 June August
Soil Temperature 0cm=> C 0cm=>25-26C
-10cm=> C cm=>18-21C
-100cm=>14-17C cm=>17-20C
Soil Moisture m3/m m3/m3
Initial RH %-69% %-75%
Low-level winds 0-5 m/s m/s
Dew deposition % %
Sfc. emissivity

19. Less sensitive weather parameters
Soil heat capacity
Surface atmospheric pressure
Surface albedo
Soil type
Roughness length

20. 1-D Ensemble Prediction
Current Method Proposed ODEP

21. Conclusions
The COBEL 1-D model has been rather successful at reproducing fog events in the past and we are rather optimistic about its present/future applications in various locations.
Some improvements are needed.
Gravitational settling scheme
Include vegetation parameters
Soil model coupling process
Coupling the model to various high resolution 3-D models and the usage of an assimilation technique should provide interesting results.

22. Thank You http://people.sca.uqam.ca/~tardif/COBEL/cobel_enter.htm