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Lightning NO Production in the GMI Model

Lightning NO Production in the GMI Model. Kenneth E. Pickering Dale J. Allen Department of Meteorology University of Maryland College Park, MD. Outline. Current procedure in GMI model Necessity of co-locating lightning NO with convective transport Available parameterizations

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Lightning NO Production in the GMI Model

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  1. Lightning NO Productionin the GMI Model Kenneth E. Pickering Dale J. Allen Department of Meteorology University of Maryland College Park, MD

  2. Outline • Current procedure in GMI model • Necessity of co-locating lightning NO with convective transport • Available parameterizations • What can be done in the GMI model?

  3. Current Procedure • Climatological monthly spatial distributions of total (CG+IC) lightning flashes (Price et al., 1997) based on ISCCP deep convective cloud top heights (Price and Rind, 1992). • CG fraction based on cold cloud depth (Price and Rind, 1993) • PCG = 10 PIC ; PCG= 6.7 x 1026 molec/flash (Price et al., 1997) • Grid cell NO production values scaled such that global production equals a specified value (e.g., 5 TgN/yr) • Vertically distributed according to C-shape profiles derived from cloud-resolving model simulations of Pickering et al. (1998)

  4. Lightning NO and Convective Transport • Use of climatological lightning NO production results in lightning NO not being injected into the model at same times and locations as at which the model convective transport occurs • Therefore, lightning NO and convectively-transported species (HOx precursors, NO, CO, NMHC) are introduced to the upper troposphere in different locations • Results in “fuzzy” middle and upper tropospheric chemistry • Lightning and convection need to be co-located!

  5. Lightning and Convection • Therefore, it is not advisable to use climatological lightning based on ISCCP or based on OTD/LIS observations • Also, should not try to use OTD/LIS daily data (in addition to same location problem, daily data is a tiny, very unrepresentative sample of actual lightning • LIGHTNING FLASH RATES MUST BE PARAMETERIZED IN TERMS OF VARIABLES FROM THE MODEL CONVECTIVE SCHEME

  6. Available Parameterizations • Cloud-height-based approach Price and Rind (1992) • Cloud-mass flux based approach Allen and Pickering (2002) • Convective precipitation based approach Allen and Pickering (2002) All using fields from driving GCM/DAS IC/CG ratios calculated using cold cloud depths as before

  7. Available Parameterizations • IC/CG ratio from cold-cloud depth method vs. from OTD/NLDN measurements • NO production per flash: PCG = 10 PIC ??? - NO spikes observed from aircraft (mostly associated with IC flashes) show 2 orders of magnitude variability in terms of molecules NO per meter of flash length - STERAO-A results (DeCaria et al, 2000) show average NO production per IC flash nearly equal to that per CG flash

  8. Analyses of Observed NO Spikes For the midpoint of this range (3 x 1021) and a 30-km flash length  ~1 x 1026 molecules NO/flash

  9. STERAO-A July 12, 1996 NE Colorado CG: 460 CG: 460 IC: 345 IC:46 Moles NO Per Flash CG: 460 CG: 460 IC: 460 IC: 690 Model-simulated vs. Measured NOx Profiles For Four Lightning NO Production Scenarios DeCaria et al. (2000) 460 moles NO/flash  ~3 x 10 26 molecules NO/flash

  10. What can be done in the GMI model? • Run a flash rate parameterization for the year of interest, producing IC and CG flash rates for every meteorological data interval (e.g., 6 hours) • Calculate NO production for each grid cell for each meteorological data interval • Compute total global annual production • Scale time series of gridded production values to some reasonable desired global annual production • Input the scaled time series to the CTM

  11. Which flash rate parameterizationshould be used? • Cloud-top height method does not yield realistic variability in flash rates when implemented with GEOS-DAS data • Cloud mass flux method underpredicts flash rates in Africa and overpredicts flash rates in Western Pacific when used with GEOS/STRAT data - GEOS-3 cloud mass fluxes smaller than in GEOS-STRAT - GEOS-3 TRMM assimilation of precipitation over oceans (1998 – present) - Rondonia Brazil lightning network (’99-’01)

  12. GEOS-3 Control and GEOS-3 TRMM vs. OTD

  13. Apply cloud-top height and cloud mass flux parameterizations with: • GEOS-3/TRMM -DAS • GEOS-4 DAS • GISS • CCM3 • Others? Perform sensitivity runs in the GMI model and make a decision on the formulation to be used

  14. Time Line 1) Nov. 03 – Jan. 04: Work with GEOS-3 TRMM DAS and Brazil observed lightning at U. of MD to improve parameterizations in tropics 2) Feb 04 – Mar. 04: Compute lightning NO source using CLDHT and MFLUX parameterizations for each set of met. fields and perform sensitivity testing (collaboration of U. of MD and GMI Core Team) 3) Apr. 04 – June 04: Work on paper(s) concerning changes in model chemistry resulting from change to co-located lightning and convection (Chatfield, Pickering, Allen, others)

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