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Development of Alternative Methods For Estimating Dry Deposition Velocity In CMAQ

UNC-CH. Development of Alternative Methods For Estimating Dry Deposition Velocity In CMAQ. UNC-CH. Kiran Alapaty University of North Carolina at Chapel Hill. Dev Niyogi North Carolina State University. Sarav Arunachalam Andrew Holland Kimberly Hanisak

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Development of Alternative Methods For Estimating Dry Deposition Velocity In CMAQ

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  1. UNC-CH Development of Alternative Methods For Estimating Dry Deposition Velocity In CMAQ

  2. UNC-CH Kiran Alapaty University of North Carolina at Chapel Hill Dev Niyogi North Carolina State University Sarav Arunachalam Andrew Holland Kimberly Hanisak University of North Carolina at Chapel Hill Marvin Wesely (Posthumous) Argonne National Laboratory

  3. UNC-CH INTRODUCTION Dry Deposition Velocity estimation

  4. UNC-CH Time Series of Dom Avg Resistances Log Scale

  5. UNC-CH Relation of Rc to Stomatal Resistance • Rc  sum of several resistance for the • Soil-vegetation Continuum. • One of them is the Stomatal Resistance • for a gas (Rsg) • Rsg is proportional to Rsw • Rsw Plays an important role in Land • surface Modeling.

  6. UNC-CH • Stomatal Resistance: • A key Parameter in • Land surface Modeling • Why ? • Stomata Controls Water Vapor Exchange

  7. UNC-CH Stoma (pore) through which CO2 enters for use in Photosynthesis; releases O2 & H2O Depending on the applications, Rs is modeled using a variety of forcings. For environmental Applications: - Wesely scheme - Jarvis scheme - Ball–Berry scheme

  8. UNC-CH • JARVIS method is used in many LSMs • (traditional in Met Models) • WESELY method is used many AQMs • Micro-Met and GCMs use • Photosynthesis/CO2 assimilation

  9. UNC-CH Stomatal Resistance Formulations WESELY JARVIS Ball-Berry (GEM)

  10. UNC-CH • JARVIS & WESELY methods • Based on Minimum Stom. Resist. • Ball – Berry method • Based onPhotosynthesis approach • (e.g., Farquhar, Collatz, Niyogi et al. , • Wu et al.)

  11. UNC-CH WESELY

  12. UNC-CH JARVIS

  13. UNC-CH GEM

  14. UNC-CH OBJECTIVES Introduce and evaluate a Photosynthesis-based Vegetation Model for estimating stomatal resistance in MM5 and deposition velocity in CMAQ Intercompare results from Jarvis-, Wesely-, GEM (photosynthesis) – type methods

  15. UNC-CH • Methodology • Photosynthesis Model Development: • Testing in 1D mode • Integrate GEM, Wesely, and Jarvis • within a LSM • Couple Unified LSM (with three schemes) • to MM5 • Develop 3D model simulations using MM5 • Use Vd estimates from the three schemes • in CMAQ

  16. UNC-CH GEM development results 1-D Model Results

  17. UNC-CH MM5 Simulation Details • 28 Layers • MRF ABL • Noah LSM • Grell • RRTM • FDDA • 5.5 days • 23 Aug 2000 • TDL hourly Data Simulation Domain – 36 km grids for Texas Air Quality Study

  18. UNC-CH Will Present: • Discussion of MM5 / Unified Noah (with three Rs schemes) model Results • Model performance statistics with surface observations • Model diagnostics for the 3 schemes (surface parameters – energy fluxes, temperature, and estimated Rs values,….)

  19. UNC-CH Surface Observations used in STATS

  20. UNC-CH Time Series for Temp1.5

  21. UNC-CH Temperature Bias (Model – Obs)

  22. UNC-CH

  23. UNC-CH Mod. Lowest Vs Obs. Surface Level Qv

  24. UNC-CH

  25. UNC-CH Diagnostic & Other Parameters

  26. UNC-CH Land Domain Avg. ABL Depths (m)

  27. UNC-CH Land Domain Avg. TRF (cm/h)

  28. UNC-CH Canopy Conductance Sfc. Latent Heat Flux

  29. UNC-CH Sfc. Sensible Heat Flux Sfc. Latent Heat Flux

  30. UNC-CH Agriculture Land (26%)

  31. UNC-CH RANGE Land (34%)

  32. UNC-CH Land Use Patterns

  33. UNC-CH Coniferous (14%)

  34. UNC-CH URBAN Land (0.13%)

  35. UNC-CH ABL Depths at 20 UTC GEM WES JAR (Acquire Lidar & other ABL obs)

  36. UNC-CH TRF per hour GEM WES JAR (Acquire Stage IV Radar)

  37. UNC-CH Cloud Fraction GEM WES JAR (Acquire GOES)

  38. UNC-CH MCIP  was modified to generate Dep Vel fields using M3-DryDep for CMAQ

  39. UNC-CH Dep. Vel. for Ozone at 22 UTC GEM WES JAR

  40. UNC-CH Dep. Vel. for NO2 at 22 UTC GEM WES JAR

  41. UNC-CH Domain Averaged Vd for O3

  42. UNC-CH We are still doing analysis of MET fields Once completed, we will perform CMAQ simulations by keeping all MET fields identical except Dep Vel

  43. UNC-CH • These Schemes are also being • tested in WRF model • WRF-CMAQ driver is also • Under construction

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