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WSN-05 TOULOUSE, Sept. 2005. Fog prediction in a 3D model with parameterized microphysics. Mathias D. Müller 1 , Matthieu Masbou 2 , Andreas Bott 2 , Zavisa I. Janjic 3. 1) Institute of Meteorology Climatology & Remote Sensing University of Basel, Switzerland

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slide1
WSN-05 TOULOUSE, Sept. 2005

Fog prediction in a 3D model with

parameterized microphysics

Mathias D. Müller1, Matthieu Masbou2, Andreas Bott2, Zavisa I. Janjic3

1) Institute of Meteorology Climatology & Remote Sensing

University of Basel, Switzerland

2) Meteorological Institue, University of Bonn

3) NOAA/NCEP

slide2
NMM_PAFOG

Janjic, Z. I., 2003: A Nonhydrostatic Model Based on a New Approach. Meteorology and Atmospheric Physics, 82, 271-285.

Droplet number concentration

Liquid water content

NMM (Nonhydrostatic Mesoscale Model) dynamical framework

PAFOG microphysics

Condensation/evaporation in the lowest 1500 m is replaced by PAFOG

slide3
PAFOG microphysics

Detailed condensation/evaporation (parameterized Köhler [Sakakibara 1979, Chaumerilac et. al. 1987])

Evolving droplet population (prognostic mean diameter)

Droplet size dependent sedimentation

Positive definite advection scheme (Bott 1989)

slide4
PAFOG microphysics

Supersat.

where S is the Supersaturation

Assumption on the droplet size distribution : Log-normal function

D droplet Diameter

Dc,0 mean value of D

σc Standart deviation of the given droplet size distribution (σc=0.2)

slide5
Boundary conditions for dNc

HEIGHT

PAFOG TOP

1000 m

σc

1000m

PAFOG TOP

slide6
Nesting

GFS

NMM-22

NMM_PAFOG

GRID: 50 x 50 x 45 (+11 soil layers)

dx: 1 km

dt: 2s (dynamics) / 10s (physics)

CPU: 40 min/24hr on 9 Pentium-4

(very efficient!)

NMM_PAFOG

NMM-4

NMM-2 15 UTC

slide7
19:00 MEZ (3 hr forecast)

DROPLET NUMBER CONCENTRATION

LIQUID WATER CONTENT

PAFOG

STANDARD

27 Nov 2004

slide8
22:00 MEZ (6 hr forecast)

DROPLET NUMBER CONCENTRATION

LIQUID WATER CONTENT

PAFOG

STANDARD

27 Nov 2004

slide9
02:00 MEZ (10 hr forecast)

DROPLET NUMBER CONCENTRATION

LIQUID WATER CONTENT

PAFOG

STANDARD

Accurate sedimentation in PAFOG

due to dNc computation.

28 Nov 2004

slide10
08:00 MEZ (16 hr forecast)

DROPLET NUMBER CONCENTRATION

LIQUID WATER CONTENT

PAFOG

STANDARD

28 Nov 2004

slide11
10:00 MEZ (18 hr forecast)

DROPLET NUMBER CONCENTRATION

LIQUID WATER CONTENT

PAFOG

STANDARD

28 Nov 2004

slide16
1D Ensemble prediction system

Obser -

vations

3D-Model runs

1D-models

aLMo

NMM-2

Fog forecast period

B-matrices

variational assimilation

PAFOG

post-processing

COBEL-NOAH

NMM-22

NMM-4

www.meteoblue.ch

3D - Forecast time

slide17
With assimilation – CASE 1 15:00

observed fog

27-28 Nov 2004

slide19
Conclusions

3D model with detailed microphysics

Promising first results

Computationally very efficient and feasible in todays operational

framework

More cases and ‘verification’ needed

Solves advection problem of 1D approach

slide21
GRID of NMM_PAFOG

50 x 50 x 45

27 layers in the lowest 1000 m

11 soil layers

Thickness(cm):

0.5

0.75

1.2

1.8

2.7

4.0

6.0

10

30

60

100

slide22
Advection statistics

Deviation often stronger than signal

1 December 2004 – 30 April 2005, all forecasthours and levels

slide24
Assimilation example

21 hour forecast

of NMM-2

28 Nov 2004

Zürich Kloten Airport

slide25
References

Berry, E.X & Pranger, M. P. (1974), Equation for calculating the terminal velocities of water drops, J. Appl. Meteor.13, 108-113.

Bott, A. (1989), A positive definite advection schemme obtained by nonlinear renormalization of the advective fluxes, Monthly Weather Review117, 1006-1015.

Bott, A. & Trautmann, T. (2002), PAFOG – a new efficient forecast model of radiation fog and low-level stratiform clouds, Atmospheric Research64, 191-203.

Chaumerliac, N., Richard, E. & Pinty, J.-P. (1987), Sulfur scavenging in a mesoscale model with quasi-spectral microphysic : Two dimensional results for continental and maritime clouds, J. Geophys. Res.92, 3114- 3126.

Janjic, Z. I., 2003: A Nonhydrostatic Model Based on a New Approach. Meteorology and Atmospheric Physics, 82, 271-285.

Janjic, Z. I., J. P. Gerrity, Jr. and S. Nickovic, 2001: An Alternative Approach to Nonhydrostatic Modeling.  Monthly Weather Review, 129, 1164-1178

slide26
References

Sakakibara, H. (1979), A scheme for stable numerical computation of the condensation process with large time step, J. Meteorol. Soc. Japan57, 349-353.

Twomey, S. (1959), The nuclei of natural cloud formation. Part ii : The supersaturation in natural clouds and the variation of cloud droplet concentration, Geophys. Pura Appl.43, 243-249.

slide27
Cost function for variational assimilation

(physical space)

Write in incremental Form

Introduce T and U transform to

eliminate B from the cost function

(Control variable space)

slide28
Error covariance matrix

NMC-Method (use 3D models):

slide29
NMC estimates of B (winter season)

NMM-4 1400 UTC

large model and time dependence

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