Introduction to atmospheric dispersion modelling. M.Sofiev

Transcription

1 Introduction to atmospheric dispersion modelling M.Sofiev

2 Content Main parts of the atmosphere Basic terms atmospheric tracer temporal and spatial scales life time in the atmosphere life cycle of atmospheric tracers Dispersion equation Langrangian and Eulerian dispersion models Parts of a dispersion model Model Quality Assurance Summary

3 Major layers of the atmosphere Troposphere (tropos=mixing): interaction with surface e her p s mo ther 100 Stratosphere: ozone-uv heating Mesosphere: mixing again Altitude, km Exosphere: fast molecules escape to the open space m e er h p os s e 10-1 stratopause 40 1 e r e h sp o t a r st tropopause troposphere Temperature, C Pressure, hpa Ionosphere: ions mesopause 80 Thermosphere: O2, N2 solar radiation heating 10-3

4 micro scale 100yr Basic terms local scale - - meso scale regional scale global scale CFCs N2O 10yr Atmospheric tracer: a compound, which is transported CH CCl Inter-hemispheric with atmospheric flows but does notchaffect them mixing time Br (sufficiently low concentration) Hemispheric 1yr CO CH Aerosols mixing time some impact exists always: feedback to meteorological processes Trop O3 Tracer lifetime: a time periodsoneeded for 2-fold (or e-fold) Boundary layer 1 dayof amount of the tracer in the atmosphere reduction mixing time HO Time scale condition- and process-dependent: e.g. lifetime with regard to NOx advection DMS 1hr C3H6 is related to relaxation times for any general meaning: lifetime process involving this (not 1:1 though) C5Htracer 8 CH O scales Spatial100sec and temporal 3 2 HO2 related to lifetime NO3 temporal scales are translated into spatial ones via wind speed 1sec OH processes and their imporatnce are related to scales 1m 10m 100m 1km 10km 100km 1000km 10,000km Spatial scale

5 Pollution cycle in the troposphere Chemical & physical reactions Transport Emission LOAD LOAD Diffusion in deep layers Diffusion in deep layers

6 Content Main parts of the atmosphere Basic terms atmospheric tracer temporal and spatial scales life time in the atmosphere life cycle of atmospheric tracers Dispersion equation Langrangian and Eulerian dispersion models Parts of a dispersion model Model Quality Assurance Summary

7 Dispersion equation y Mass conservation transport sources sinks Scale separation mean flow turbulence Closure problem x w(z0+ z/2) z v(y0+ y/2) (x0,y0,z0) u(x0- x/2) u(x0+ x/2) v(y0- y/2) 3 c (ui c ) E R t i 1 xi K-theory turbulent diffusion coefficient w(z0- z/2) C (C / ) LC (U i C ) R(C ) E Kii t xi xi xi

8 From concentration to load M dt T 0 C p dx (C, p ) load functional p is a weight (sensitivity) function of the load: Population exposure p( x, t ) ( x xcity ) Ecosystem damage p( x, t ) p(t ) 1( Aecosystem ) p ( x, t ) (x xsite ) 1(t, tbeg, tend ) Observational site

9 Alternative way to get the load function Consider some function C* satisfying L* C* = p, where L* is adjoint to L. Then M (C *, E ) (C *, LC ) ( L*C *, C ) ( p, C ) L*C * p adjoint dispersion equation L (U i ) Kii R(C ) t xi xi xi * x C, C * 0 C *(t T ) 0

10 Dual features of dispersion problem Forward problem: (1/ ) Kii (U i ) R; L t xi xi xi LC E ; M ( p, C ) Inverse (adjoint) problem R; L (U i ) Kii t xi xi xi * L*C * p; M ( E, C * )

11 Content Main parts of the atmosphere Basic terms atmospheric tracer temporal and spatial scales life time in the atmosphere life cycle of atmospheric tracers Dispersion equation Langrangian and Eulerian dispersion models Parts of a dispersion model Model Quality Assurance Summary

12 Classifications of models Model principles Eulerian Lagrangian Gaussian statistical Monte-Carlo Scales global continental regional local/urban

13 Classifications of models.2 Chemicals acid ozone greenhouse gas inert aerosol/dust radio-activity toxic persistent pollutants Model media atmospheric multi-media integrated models

14 Classifications of models.3 Input data climatological real-time data Time dimension: direction, horizon re-analysis now-casting forecasting Problem to solve forward inverse

15 Content Main parts of the atmosphere Basic terms atmospheric tracer temporal and spatial scales life time in the atmosphere life cycle of atmospheric tracers Dispersion equation Langrangian and Eulerian dispersion models Parts of a dispersion model Model Quality Assurance Summary

16 SILAM v.5: outlook Simulation control forward adjoint 4D-Var 8 chemical and physical transformation modules (6 open for operational use), 6 source terms (all open), Acid-basic 2 aerosol dynamics (one open) CB4 3D- and 4D- Var Domains: from global to betameso scale (~1km resolution) Meteo input: Transformations ECMWF HIRLAM, AROME, HIRHAM, ECHAM, and any other who can write GRIB-1 or GRIB-2 WRF Passive self-decay Long-lived multi-media Point Basic Nuclear bomb Transformation Pollen Radioactive Source types Simple SOx General PM Aerosol dynamics Area Transformation Map of species masses Bio-VOC Emission Modules Pollen Sea salt Deposition Dry Initialization, 3D-Var Advection diffusion Dynamics Wet

17 FMI regional AQ assessment and forecasting platform AQ products Fire Assimilation System Satellite observations Phenological observations Phenological models Aerobiological observations SILAM CTM model EVALUATION: NRT model-measurement comparison Physiography, forest mapping CLRTAP/EMEP emission data Online AQ monitoring AROME NWP model HIRLAM-MBE NWP model HIRLAM-RCR NWP model Aerobiological observations WRF Global boundary cond. + own simulations Meteorological data: ECMWF TVM Satellite observations

18 SILAM scales Global Continental Regional Meso-scale SO

19 Content Main parts of the atmosphere Basic terms atmospheric tracer temporal and spatial scales life time in the atmosphere life cycle of atmospheric tracers Dispersion equation Langrangian and Eulerian dispersion models Parts of a dispersion model Model Quality Assurance Summary

20 Model vs reality Model is never a copy of reality It represents only those features, which are deemed to be important for a specific application The extent of their similarity is to be established in each specific case I.Repin. Zaporozhje Cossacks are writing a letter to Turkish sultan W.Kandinski. Cossacks

21 Model Quality Assurance (QA) Tests of individual modules (development stage) Sensitivity runs Model-measurement comparison Model-model comparison

22 Model-measurement comparison The only connection between model and reality Data sets from different origin point observations vs grid-mean model results representativeness error instrumental errors Observations are expensive => sparse Limited number of observed variables Specific statistical methods are required to obtain nontrivial conclusions

23 Model inter-comparison Useful if lacking measurements Similar features of data Large data sets => high accuracy Wide variety of analytical methods Ensemble model Possibly, no connection to reality

24 Summary Distribution of an atmospheric pollutant is described via dispersion equation, which is a representation of the mass conservation law Duality of dispersion problem allows for usage of forward and adjoint dispersion equations identical final results the load choice depends on specific task Model quality assurance implies several actions and covers ALL stages of the model development