1. A NASA Model for Improving the Lightning NOx Emission Inventory for CMAQ William Koshak 1, Maudood Khan 2, Arastoo Biazar 3, Michael Newchurch 3, Richard McNider 3 1 Earth Science Office, NASA-MSFC, Huntsville, AL 35805 2 Universities Space Research Association, Huntsville, AL 35805 3 University of Alabama in Huntsville, Huntsville, AL 35805

2. Motivation  State & local air quality agencies use CMAQ to determine compliance with the National Ambient Air Quality Standards (NAAQS), so CMAQ predictions must be accurate.  Currently, emissions from lightning are either omitted or are poorly represented in CMAQ. The variability of lightning is typically (and unrealistically) ignored.  CMAQ model predictions suffer as a result, especially in the middle and upper troposphere.

3. LNOM  Lightning Nitrogen Oxides Model (LNOM)  Presently under development at NASA/MSFC  Builds spatio-temporal NOx emission inventory for CMAQ  Employs state-of-the-art lightning measurements in a unique way to model the variable nature of lightning

4. LNOM Part of an Ongoing Project … Improve Boundary & Initial Conditions Improve Lightning NOx Emission Inventory NASA Data (Aura/TES, CALIPSO/CALIOP) CMAQ NASA LNOM Improved Forecasts Improved Decisions RPC Project (UAH, Mike Newchurch et al.)

5. Basic Datasets Employed by LNOM  National Lightning Detection Network (NLDN) »Ground Flash Number, N g »Ground Flash Location, (x,y) »Ground Flash multiplicity, m »Ground Flash Peak Current, I  LIS/OTD Lightning Climatology Data »Provides satellite-inferred climatological “Z s ” ratio (# cloud flashes to # ground flashes). »Cloud Flash Number Estimation: N c = Z s N g  VHF Lightning Channel Mapping Data »Used to generate Channel Length pdfs, L »Channel altitude statistics, z

6. Current US VHF Networks LMA networks (NMT) North Alabama (MSFC) Oklahoma City (OU & NSSL) White Sands Missile Range (Army) Washington, D.C. Area (MSFC, NOAA, NMT) LDAR II networks (Vaisala) Dallas-Fort Worth Houston (Texas A&M, NSF) Kennedy Space Center (Air Force) [Adapted from D. Buechler, Univ. of Alabama in Huntsville]

7. LNOM Details:

8. LNOM Details (cont.)

9. Summary  Development of LNOM continues.  Implementation of LNOM is described in the paper »H. Peterson (NASA Post Doc.) is presently writing IDL code to produce channel length probability distribution functions from North Alabama LMA data. »H. Peterson is considering ways to employ radar data to improve cloud flash count in a CMAQ grid volume.  There is a desire to assess the specific impact of LNOM on CMAQ results by applying LNOM to an August 2006 baseline run of CMAQ (see paper for details).