1 / 35

Comprehensive Meteorological Driver for Chemical Transport Models

Understand the essential features of meteorological fields and their role in modeling and diagnostics for various scales, from large to street canyons. Learn about the iterative diagnostic procedure, numerical analysis of meteorological parameters, and model configurations for different spatial resolutions.

mvail
Download Presentation

Comprehensive Meteorological Driver for Chemical Transport Models

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Meteorological Driver for CTM Freie Universität Berlin Institut für Meteorologie Eberhard Reimer

  2. Chemical Transport Models LARGE and URBAN SCALE: • 3D-CTM REM/CALGRID (RCG) URBAN/LOCAL SCALE: • 3D-CTM MICRO-CALGRID FOR MULTIPLE STREET CANYONS • 2D-STREET MODEL CPB FOR A SINGLE STREET CANYON • PARTICLE MODEL

  3. aims • Presentation of meteorological fields for long term modeling and diagnostics: • large scales (Europe) • Urban/regional scales ( f.e. Berlin/Brandenburg) • Street canyon (f.e. Berlin)

  4. General Procedure Iterative diagnostic procedure: Use of observations: problem is resolution by network Use of forecasts: problem with forecast errors and cloud param. • First guess by large scale fields from statistical Interpolation or ECMWF analysis • Transformation to isentropic coordinates (inversions, local stability..) • Correction by statist. Interpolation, ~ 25km² grid • Correction by statist. Interpolation, ~ 2 or 4km² grid • Transformation to eta or hybrid coordinates • Adaptation to orography and landuse, ~ 1 to 4 km² grid

  5. CTM Coordinates Generalized horizontal coordinate systems, including latitude-longitude Multi layer system in terrain following coordinates, fixedheights or dynamically variing following the time depentent mixing height

  6. Vertical structure Mixing height spatially varying  irregular grid

  7. Numerical Analysis - Meteorological Parameter are analyzed in two steps - 25km und 2km horizontale Auflösung - Isentropic surfaces in the vertical, - Boundary layer parameters are modeled - Data from Wetterservices • Additional wind data from monitoring net of envir. admin. of Berlin and Brandenburg • Adjustment to topography (adjustment vertical velocity profiles, divergence minimization, blocking effects, sloping topography)

  8. Dreidimensionale Felder: temperature, relative humidity, wind vector, Montgomery potential, Exner function and local stability Zweidimensionale Felder: Surface temperature, surface relative humidity, wind vector, water temperature, surface pressure, pressure tendency, cloud coverage, cloud type, cloud top and ceiling, horizontal visibility, temperature inversions (height and thickness) precipitation 3 hourly or 1 hourly snow cover Planetarische Grenzschicht: mixing height, Monin Obukhov length, ustar, turbulent temperatur scale, wstar sensible heat flux, latent heat flux Z0, albedo in dependence to landuse

  9. Model Configuration 5 vertical layers: • a 20 m thick surface layer • two equal-thickness layers below the mixing height • 2 above the mixing height and extending to the domain top at 2500 m.

  10. large scale model domain RESOLUTION: 0.25° LATIDUDE, 0.5° LONGITUDE 82 x 125 grid cells

  11. urban/regional scale model domain Berlin-Brandenburg (Nest 1): 4x4 km2

  12. urban scale model domain Berlin-Brandenburg (Nest 2): 1x1 km2

  13. Street Canyon Model 1. Urban analysis parameters: • Wind vector • Local stability • Cloud cover • Stability classes (Klug – Manier) 2. Urban Model Miskam (Eulerian equations)

  14. European Domain

  15. 2m Temperature, 26.4.2002 12 UTC

  16. Wind Vector, 26.4.2002 12 UTC

  17. Large Precipitation, 26.4.2002 18 UTC

  18. Urban/Regional Domaintopography and met. observations

  19. Landuse

  20. 2m Temperature, 26.4.2002 12 UTC

  21. Wind Vector, 26.4.2002 12 UTC

  22. Total Cloud Coverage, 26.4.2002 12 UTC

  23. Low Cloud Coverage, 26.4.2002 12 UTC

  24. Mixing Height, 26.4.2002 12 UTC

  25. Urban/Regional Precipitation, 26.4.2002 18 UTC

  26. Winderosion in Brandenburg Potentielle Winderosionsgefährdung (MMK) Keine LN Gering Mittel Stark Thiere et al. Lieberoth 1988)

More Related