Dispersion modelling in complex terrain: Sensitivity studies with the CALMET model

Dispersion modelling in complex terrain: Sensitivity studies with the CALMET model

Author: Matic Ivančič

Milan Vidmar Electric Power Research Institute

Ljubljana, 15.12.2011

Matic Ivančič Ljubljana, 15.12.2011

CONTENTES

Introduction - air pollution modeling

CALMET model Three different wind field

initializations Results


INTRODUCTION

Air pollution modeling: Advection with wind

3D wind fields Dispersion in cross-section

Stability of atmosphere

ALADIN - operative meteorological forecast in Slovenia


INTRODUCTION

ALADIN – CALMET – CALPUFF are online coupled

Two-days prediction are available on web: www.okolje.info


CALMET

Diagnostic wind model (DFW)

3 main parts: Initial field (first guess) First step Second step


First step

Kinematic effects of terrain

Slope flows Blocking effects 3D divergence minimization


Second step Interpolation

Smoothing

O’Brien adjustment of vertical velocities

2D divergence minimization


Divergence minimization

Varitional technique (Sherman 1978) Minimization of following functional:

Strong condition:

New functional:


Divergence minimization Solution with EL equations :

numerical solution for λ:


TEST AREA

Šoštanj basin

Biggest thermal power plant in Slovenia

9 meteorological and air quality stations


9 surface stations – only 6 stations has representative wind data


Radio-sounding measurements in Zagreb


ALADIN points


3 DIFFERENT WIND FIELD INITIALIZATIONS

A Data from surface stations and upper air data from radio-sounding

B Meteorological analysis from ALADIN

C Combination of data from surface stations and meteorological analysis from ALADIN


Experiment A

First guess: from measurements First step:

Terrain effects 3D divergence minimization

Second step: Again interpolation of measurements


Experiment B

First guess is prepared with data from model ALADIN

First step

Second step


Experiment C

First guess: from model ALADIN First step:

Terrain effects 3D divergence minimization

Second step: Import measurements with objective

analysis procedure


RESULTS – stability calculation

0%

10%

20%

30%

40%

50%

very unstable unstable slightlyunstable

neutral slightly stable stable

PGT stability class

A

B

C


Wind rose – station YA


Wind rose – station YC


Wind rose – station YD


Wind rose – station YE


Wind rose – station YF


Wind rose – station YG


CALPUFF results

Dispersion calculation of SO2


CONCLUSION

It is hard to judge which model initialization gives better results

Radio-sounding measurements are far away ALADIN analysis have better space but time

interpolation required ALADIN predictions may improve results –

hourly data Case B: for areas without meteorological

measurements and for predictions Case C: maximum number of inputs


Acknowledgements

Author would like to thank the Environmental Agency of the Republic of Slovenia for providing all fields from ALADIN model


THANK YOU FOR YOUR ATTENTION


LITERATURE Sherman, C. A., 1978: A mass-consistent model for

wind fields over complex terrain. J. Appl. Meteor., 17, 312–319.

Scire J. S., F. R. Robe, M. E. Fernau, R. J. Yamartino, 2000: A User’s Guide for the CALMET Meteorological Model, Version 5, Earth Tech, Inc, Concord.

Scire J. S., D. G. Strimaitis, R. J. Yamartino, 2000: A User’s Guide for the CALPUFF Dispersion Model, Vesrion 5, Earth Tech, Inc, Concord.

Dispersion modelling in complex terrain: Sensitivity studies with the CALMET model

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