Ability of GEO-CAPE to Detect Lightning NOx and Resulting Upper Tropospheric Ozone Enhancement Conclusions When NO emissions from lightning were included in a month-long WRF/Chem simulation, the resulting ozone profiles showed better agreement with ozonesondes launched during the DISCOVER-AQ campaign Significant decreases of monthly mean OLR due to increased O3 from LNOx are seen over the Southeast US The increased temporal resolution available from a satellite like GEO-CAPE would allow detection of many more lightning-associated elevated NO 2 events, as well as their resulting UT O 3 enhancements Based on preliminary results, UT O 3 enhancements from lightning should be retrievable, regardless of the wavelength range used Conclusions When NO emissions from lightning were included in a month-long WRF/Chem simulation, the resulting ozone profiles showed better agreement with ozonesondes launched during the DISCOVER-AQ campaign Significant decreases of monthly mean OLR due to increased O3 from LNOx are seen over the Southeast US The increased temporal resolution available from a satellite like GEO-CAPE would allow detection of many more lightning-associated elevated NO 2 events, as well as their resulting UT O 3 enhancements Based on preliminary results, UT O 3 enhancements from lightning should be retrievable, regardless of the wavelength range used LNOx – Control : Monthly Means Lightning is an important source of NO x in the middle and upper troposphere Ozone production downwind of thunderstorms can lead to layers of enhanced ozone at these altitudes Ozone in the upper troposphere has a greater radiative forcing efficiency than in the lower troposphere, making it an important greenhouse gas This work aims to demonstrate the collaborative possibilities between the GOES-R Geostationary Lightning Mapper and GEO-CAPEBackground The WRF/Chem code was modified to allow the model ozone (rather than climatological ozone) to be interactive with the short-wave and long-wave radiation schemes, following the procedure of Martini (2012, PhD dissertation, Univ. of MD). Two simulations were performed, one with additional NO emissions from lightning (LNO x ), and one without (control). NLDN Cloud-to-Ground (CG) flash data for July 2011 were obtained from the Global Hydrology and Climate Center (GHCC) lightning team ( Climatological IC-to-CG ratios for July 2011 (Boccippio et al., 2001) were applied to the NLDN-observed CG flashes to calculate Intra-Cloud (IC) flash rates. Both CG and IC flashes were then mapped onto each WRF/Chem model domain on an hourly basis. These flash rates represent a proxy data set for what will be available from the Geostationary Lightning Mapper on GOES-R. Each flash was assumed to produce 500 moles of NO (Ott et al., 2010), and was vertically distributed into the 34 model layers based on: (i) the vertical distribution of lightning channel segments developed from the Northern Alabama Lightning Mapping Array by Bill Koshak at GHCC and (ii) lightning-NO (LNO) dependence on atmospheric pressure. Hourly 3-D LNO emissions were generated for each domain, for the July 2011 period. WRF/Chem simulations In this highlighted example, LNO x leads to enhanced O 3 at 300 mb over Missouri and southern Illinois The enhancement travels east towards Indiana and Ohio as the day progresses Max and min values on maps are for the box drawn on the map Simulation Details NO x hPa Difference (ppbv) O 3 – 300 hPa Difference (ppbv) OLR Difference (W m -2 ) Comparisons with ozonesondes from DISCOVER-AQ AGL (km) (model – sonde) / sonde (%) Including the lightning NO emissions improves the agreement between the model and ozonesondes launched during the July 2011 DISCOVER-AQ campaign LNO x – Control (12 km Domain) NO 2 OMI Overpass Time O3O3 The plots on the left show time series of the maximum values of tropospheric column NO 2 and O 3 for the box in the above maps The OMI overpass time is plotted as a dashed line Due to its low Earth orbit, OMI misses the largest column NO 2 and O 3 enhancements for this case 07/28/2011 : Retrieval Sensitivity Acknowledgements Dr. Follette-Cook would like to extend a special thanks to Vijay Natraj and Susan Kulawik for their work generating the averaging kernels used here, as well as their patience in answering my unending series of questions. Melanie Follette-Cook 1, K. Pickering 2, L.Wang 3, M. Newchurch 3, V. Natraj 4, S. Kulawik 4 1 GESTAR/MSU 2 GSFC 3 U. of Alabama - Huntsville 4 JPL 07/04/2011 : Comparison with OMI 15 Z 18 Z 21 Z NO hPaNO x hPaO hPa Difference (ppbv) Spectral RangeLNO x ControlDifference (DU) WRF/Chem (Truth) UV (290) UV (290)-VIS (500) UV (290)-TIR (900) UV (290)-VIS (500)-TIR (900) TIR (900) VIS (500)-TIR (900) Difference Control LNOx WRF/Chem Profiles WRF/Chem and Retrieved Profiles Tropospheric Column (DU) Maximum Tropospheric Column Amount (LNOx Run) LNOx – Control 36 km domain NO x – 300 mbO 3 – 300 mb Difference (ppbv) A profile with enhanced UT O 3 due to lightning was selected from the WRF/Chem output Using this profile, six averaging kernels at several different wavelength ranges were generated