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Summer School Rio de Janeiro March 2009 6. MODELING CONVECTIVE PBL

Summer School Rio de Janeiro March 2009 6. MODELING CONVECTIVE PBL. Amauri Pereira de Oliveira. Group of Micrometeorology. Topics. Micrometeorology PBL properties PBL modeling Modeling surface-biosphere interaction Modeling Maritime PBL Modeling Convective PBL. Modeling Convective PBL.

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Summer School Rio de Janeiro March 2009 6. MODELING CONVECTIVE PBL

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  1. Summer SchoolRio de JaneiroMarch 20096. MODELING CONVECTIVE PBL Amauri Pereira de Oliveira Group of Micrometeorology

  2. Topics • Micrometeorology • PBL properties • PBL modeling • Modeling surface-biosphere interaction • Modeling Maritime PBL • Modeling Convective PBL

  3. Modeling Convective PBL

  4. Convective PBL Nieuwstadt, F.T.M. and Duynkerke, P.G., 1996: Turbulence in the boundary layer, Atmospheric Research, 40, 111-142.

  5. Similarity Theory - CBL Mixing Layer Similarity Monin and Obukhov similarity Free Convection Similarity Holstlag and Neuiwastadt 1988.

  6. LES MODEL Investigation of Carbon Monoxide in the city of Sao Paulo using LES

  7. Codato, G., Oliveira, A.P., Soares, J., Marques Filho, E.P., and Rizza, U., 2008: Investigation of carbon monoxide in the city of São Paulo using large eddy simulation. Proceedings of 15th Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA, 88th Annual Meeting, 20-24 January 2008, New Orleans, LA (CDROM). Codato. G., 2008: Simulação numérica da evolução diurna do monóxido de carbono na camada limite planetária sobre a RMSP com modelo LES. Dissertação de Mestrado. Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, SP, Brasil, 94 pp. Available at http://www.iag.usp.br/meteo/labmicro/index_arquivos/Page1519.htm

  8. Objective • To investigate the statistical properties of the convective planetary boundary layer (PBL) over a homogeneous urban surface using LES. • Emphasis in the characterization of the turbulent transport of carbon monoxide at the top of the PBL during daytime.

  9. Metropolitan region of São Paulo (MRSP) • Conurbation of 39 cities • 20 million habitants • 7 millions vehicles • 1.48 tons of CO per year

  10. Air pollution problem in São Paulo is particularly dramatic during winter

  11. Location LES domain CO measurements Air pollution monitoring Network Stations 8,051 km2 23º33’S, 46º44’W Altitude 742m 60 km far from Atlantic ocean

  12. Topography Metropolitan Region of São Paulo Valley

  13. LES domain LES domain Relatively flat

  14. Carbon Monoxide – Seasonal Evolution(1996 to 2005) WinterMaximum

  15. Carbon Monoxide – Diurnal evolutionJune (1996 -2005) Firstmaximum Secondmaximum

  16. Wind – Seasonal evolution (1996 -2005) Winds in São Paulo are weak.

  17. Wind – Diurnal evolution - June (1996 -2005) Morning winds are weaker than in the afternoon Stronger SE wind in the afternoon is due to Sea Breeze

  18. Time rate of change of CO in June

  19. LES Model

  20. LES Model The motion equation are filtered in order to describe only motions with a length scale larger than a given threshold.

  21. Reynolds Average f

  22. LES Filter f large eddies

  23. Convective Boundary Layer Cross section Updraft Source: Marques Filho (2004)

  24. Convective PBL – LES Simulation ( zi /L ~ - 800) Source: Marques Filho (2004)

  25. Spectral Properties – LES Simulation Fonte: Marques Filho (2004)

  26. TKE budget Caso DA2=

  27. It was developed by Moeng (1984) and modified by Sullivan et al. (1994): • 6 prognostic equations • 1 diagnostic LES Model – Moeng Filtering all variables by

  28. Set of equations used in the LES model (1) (2) (3) (4) (5) (6) (7)

  29. homogeneous non-homogeneous Sullivan et al. (1994) subgrid parametrization

  30. Sub Grid TKE equation where Turbulent diffisivity coefficients Convective Stable

  31. LES Model- Moeng Boundary conditions • Periodic in the lateral • Rigid at surface • Radiative at the top Surfaces Horizontally Homogeneous • Sensible heat flux (prescribed) • Momentum flux (MOST)

  32. Grid points (128, 128, 128) ug,vg (2ms-1; 0ms-1) (Lx, Ly, Lz) (10 km; 10 km; 2 km ) θini 295 K Δx=Δy 78.125 m 5 K Δz 15.625 m Γθ 5 K km-1 Time step 1 sec z0 0.16 m Total time 36000 time steps cini 2.5 ppm zini 300 m 2.30 ppm  93.75m(6 levels). Γc 0 ppm km-1 Numeric Model

  33. Initial Conditions – Vertical profiles

  34. Boundary ConditionSensible heat flux Bθ = 0.209 K m s-1 t = time in hours

  35. Boundary Condition – CO flux at surface The amplitude of CO flux at the surface is based on the total emission of CO in the MRSP (1.48 million of tons per year) divided by number of days in one year and by the area representative of traffic in São Paulo (8,051 km2). In reality the value of Bco was set equal to 1/6 of the value above. This was obtained by trial and error and there is no apparent reason.

  36. Boundary condition CO flux at the surface BCO = 0.024 ppm ms-1 t1 = 9 hour t2 = 19 hour = 3 hour

  37. Results • The results are based on the three-dimensional fields generated after turbulence has reached quasi-steady equilibrium; • The statistics were obtained ensemble averaging 15 outputs, separated by 1200 time steps each, corresponding to 20 minutes. Important to emphasize that the time step is 1 second; • Statistical properties are estimated at 8:30, 9:30, 10:30, 11:30 and 12:30 LT.

  38. Quasi-steady equilibrium after 1000 s Time evolution of turbulent kinetic energy per unit of mass volume-averaged in the PBL. E= 0.5 (u´2+v´2+w´2). Initial jump

  39. PBL characteristic scales

  40. PBL height

  41. Potential temperature and sensible heat flux

  42. Zonal component and momentum flux

  43. Variance of the wind speed components and TKE

  44. CO concentration and vertical flux

  45. Comparison with observation – Potential temperature at the surface

  46. Comparison with observation – CO concentration at the surface

  47. Entrainment intensity

  48. Surface emission, entrainment and hypothetical horizontal advection 48

  49. Conclusion • Simulation of daytime evolution PBL over the MRSP carried out using LES model indicated several characteristics consistent with a convective PBL. • The simulated diurnal evolution of CO concentration indicates that entrainment of clean air at the top of the PBL is one of the dominant mechanism reducing the concentration of CO at the surface as observed in São Paulo during the winter.

  50. Conclusion • Comparison between entrainment, surface emission and hypothetical horizontal advection indicates that this late mechanism could be responsible by considerable reducing in the CO diurnal evolution in the city of Sao Paulo. • Next step would be evaluated the role of horizontal advection.

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