05_Matic_Ivancic_Dispersion modelling in complex terrain

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Transcript 05_Matic_Ivancic_Dispersion modelling in complex terrain

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

Author: Matic Ivančič Milan Vidmar Electric Power Research Institute Ljubljana, 15.12.2011

CONTENTES     Introduction - air pollution modeling CALMET model Three different wind field initializations Results Matic Ivančič Ljubljana, 15.12.2011

INTRODUCTION  Air pollution modeling:   Advection with wind  3D wind fields Dispersion in cross-section  Stability of atmosphere  ALADIN - operative meteorological forecast in Slovenia Matic Ivančič Ljubljana, 15.12.2011

INTRODUCTION  ALADIN – CALMET – CALPUFF are online coupled  Two-days prediction are available on web: www.okolje.info

Matic Ivančič Ljubljana, 15.12.2011

CALMET  Diagnostic wind model (DFW)  3 main parts:  Initial field (first guess)  First step  Second step Matic Ivančič Ljubljana, 15.12.2011

First step  Kinematic effects of terrain    Slope flows Blocking effects 3D divergence minimization Matic Ivančič Ljubljana, 15.12.2011

Second step  Interpolation  Smoothing  O’Brien adjustment of vertical velocities  2D divergence minimization Matic Ivančič Ljubljana, 15.12.2011

Divergence minimization   Varitional technique (Sherman 1978) Minimization of following functional:  Strong condition:  New functional: Matic Ivančič Ljubljana, 15.12.2011

Divergence minimization  Solution with EL equations :  numerical solution for λ: Matic Ivančič Ljubljana, 15.12.2011

TEST AREA  Šoštanj basin  Biggest thermal power plant in Slovenia  9 meteorological and air quality stations Matic Ivančič Ljubljana, 15.12.2011

9 surface stations – only 6 stations has representative wind data Matic Ivančič Ljubljana, 15.12.2011

Radio-sounding measurements in Zagreb Matic Ivančič Ljubljana, 15.12.2011

ALADIN points Matic Ivančič Ljubljana, 15.12.2011

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 Matic Ivančič Ljubljana, 15.12.2011

Experiment A    First guess: from measurements First step:  Terrain effects  3D divergence minimization Second step:  Again interpolation of measurements Matic Ivančič Ljubljana, 15.12.2011

Experiment B  First guess is prepared with data from model ALADIN  First step  Second step Matic Ivančič Ljubljana, 15.12.2011

Experiment C    First guess: from model ALADIN First step:  Terrain effects  3D divergence minimization Second step:  Import measurements with objective analysis procedure Matic Ivančič Ljubljana, 15.12.2011

RESULTS – stability calculation 50% 40% 30% 20% 10% 0% very unstable unstable slightly unstable neutral

PGT stability class

slightly stable stable A B C Matic Ivančič Ljubljana, 15.12.2011

Wind rose – station YA Matic Ivančič Ljubljana, 15.12.2011

Wind rose – station YC Matic Ivančič Ljubljana, 15.12.2011

Wind rose – station YD Matic Ivančič Ljubljana, 15.12.2011

Wind rose – station YE Matic Ivančič Ljubljana, 15.12.2011

Wind rose – station YF Matic Ivančič Ljubljana, 15.12.2011

Wind rose – station YG Matic Ivančič Ljubljana, 15.12.2011

CALPUFF results  Dispersion calculation of SO2 Matic Ivančič Ljubljana, 15.12.2011

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 Matic Ivančič Ljubljana, 15.12.2011

Acknowledgements  Author would like to thank the Environmental Agency of the Republic of Slovenia for providing all fields from ALADIN model Matic Ivančič Ljubljana, 15.12.2011

Matic Ivančič

THANK YOU FOR YOUR ATTENTION

Ljubljana, 15.12.2011

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.

Matic Ivančič Ljubljana, 15.12.2011