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Tiger Team project : Model intercomparison of background ozone to inform NAAQS setting and implementation. AQAST PIs: Arlene Fiore (Columbia/LDEO) and Daniel Jacob (Harvard) Co-I (presenter) : Meiyun Lin (Princeton/GFDL) Project personnel: Jacob Oberman (U Wisconsin) - PowerPoint PPT Presentation

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<ul><li><p>Tiger Team project:Model intercomparison of background ozone to inform NAAQS setting and implementationNASA AQAST Meeting U.S. EPA, Research Triangle Park, NCNovember 16, 2011 AQAST PIs: Arlene Fiore (Columbia/LDEO) and Daniel Jacob (Harvard) Co-I (presenter): Meiyun Lin (Princeton/GFDL)</p><p>Project personnel: Jacob Oberman (U Wisconsin) Lin Zhang (Harvard)</p><p>AQ management contacts: Joe Pinto (EPA/NCEA) Pat Dolwick (EPA/OAR/OAQPS)</p></li><li><p>Objective: Improved error estimates of simulated North American background O3 (NAB) that inform EPA analyses Problem: Poorly quantified errors in NAB distributions complicate1) quantifying uncertainties in risk assessments for NAAQS-setting 2) interpreting SIP simulations aimed at attaining the O3 NAAQS. To date, EPA NAB estimates have been provided by one model. </p><p>Approach: Compare GFDL AM3 and GEOS-Chem NAB (regional, seasonal, daily)Process-oriented analysis of factors contributing to model differencesInitial project results c/o NOAA Hollings Scholar Jacob Oberman at GFDL summer 2011</p><p>GEOS-ChemGFDL AM3MeteorologyOffline (GEOS-5)Coupled, nudged to NCEP U and VStrat. O3 Parameterized (Linoz)Full strat. chem &amp; dynamicsIsoprene nitrate chemistry18% yield w/ zero NOx recycling8% yield w/ 40% NOx recycling (obs constrained; Horowitz et al, 2007)Lightning NOxtied to obs. flash climat. w/higher NOx yield at N. mid-lat tied to model convective cloudsEmissionsEMEP, Streets, NEI 2005, 2006 fires (emitted at surface), MECAN 2.0ACCMIP emissions w/ climat. fires, vertically distributed </p></li><li><p>Two models differ widely in day-to-day variability and seasonal cycle: CASTNet Mtn. West Sites AM3 predicts seasonal cycle in background, GC predicts ~ constant and biased high total in AugustAM3 predicts rising total and NAB for some observed high-O3 events in spring, GC predicts a decline Can NASA satellites offer constraints?2006Thick lines: base-caseThin lines: NA Background (zero out NA anthrop. emissions)OBS: 58.37.0OBS: 55.87.0</p></li><li><p>Stratospheric ozone intrusions: May 26-31 exampleGFDL AM3GEOS-CHEM500 hPa NA background (ppb)Bias in surface MDA8 (ppb) vs. CASTNet obsOMI Total Column O3OMI/MLS Trop. Column O3DUDU AM3 better captures the variability due to stratospheric influence, but the magnitude represents an upper limit (biased high w.r.t. surface obs)</p></li><li><p>Two models differ in seasonal mean estimates forNorth American background AM3GEOS-ChemSummer (JJA)North American background (MDA8) O3 in model surface layerSpring (MAM)AM3: MoreO3-strat + PBL-FT exchange?</p><p>GC: Morelightning NOx (~10x over SWUS column)+ spatial differencesRole for differences in O3 from wildfires? Biogenic emissions?</p></li><li><p>Model treatment of wildfires can contribute to model differences in NAB estimates: June 28, 2006 eventAM3Elevated PAN above PBL (750 mb)AM3[ppt]Need to use event-specific wildfire emissions (satellites)</p><p>Uncertainties will remain from vertical distribution of emissions (lower temp., higher PAN prod.)(2) fire plume chemistry GCNorth American background (MDA8) [ppb]</p></li><li><p>Two models show different strengths in capturing distributions of base-case and N. American background O3 Observed GEOS-Chem total AM3 total GEOS-Chem NAB AM3 NABSurface MDA8 O3 [ppb] below 1.5 km+ above 1.5 kmZhang et. al.,2011U.S. CASTNet sites20 40 60 800.08</p><p>0.06</p><p>0.04</p><p>0.02</p><p>0.002006 MAM sites &gt; 1.5 km 0 20 40 60 80 1000.06</p><p>0.04</p><p>0.02</p><p>0.002006 JJA sites &lt; 1.5 km Capitalize on model strengths to inform policyDevelop bias-corrections to harness info on variability / process-level Isop. nitrate chem may play a role AM3 biased high but may better represent distribution shape (wider background range) GC and AM3 bracket observed distribution GC NAB lower, more peakedFrequency per ppb</p></li><li><p>Improved error estimates of simulated North American background O3 (NAB) that inform EPA analyses </p><p>AQ management outcomes: Improved NAB error estimates to supportthe next revision of the ozone NAAQS, SIP simulations focused on attaining the current ozone NAAQS, development of criteria for identifying exceptional events.</p><p>Deliverables (Sept. 30, 2012): Report to EPA on confidence and errors in NAB estimates &amp; key factors leading to model differences; documented in peer-reviewed publicationGuidance for future efforts to deliver more robust NAB satellite constraints (next step, OMI/TES c/o L. Zhang) design multi-model effort (more robust, as in climate research) Possible Long-term Goal: Establish an integrated multi-model and observational analysis framework to inform policy on a sustained basis</p></li><li><p>Extra Slides</p></li><li><p>Transport event driven by biomass burning emissionsCO biomass burning emissions June 2006 (log-scale)AM3GCmoles / km2 / day Why is event only in AM3? Hypothesis: Higher vertical distribution in AM3 affects transport and chemistry (PAN only forms at low temperatures)Case 3: Biomass burning</p></li><li> Neither model fully captures trend in observations AM3 predicts seasonal cycle in PRB, GC predicts ~constant Overestimate of total ozone by AM3 Models agree on trend in PRB&gt;1.5 km sitesexcluding CA sites </li><li><p>Biogenic isoprene emissions in AM3MEGAN 2.1 emission factors [Guenther et al., 2006]AVHRR and MODIS PFT and LAI mapped to MEGAN vegetation typesTied to model surface air temperature24-30 Tg C/yr within NA (235-300E, 15-55N)16-23 Tg C/yr within the United States 366-405 Tg C/yr globally</p></li><li><p>Two models have similar isoprene emissions, but differ in isoprene nitrate chemistryNested GEOS-ChemAM3/C48 (~200 km)</p></li><li><p>Transects along the 40N parallel</p></li><li><p>Compare w.r.t. satellite products?</p></li><li><p>Nested GEOS-ChemZhang et al., 2011 Distribution merged for March-August, canceling GEOS-Chem low distribution in spring (MAM) and high distribution in summer (JJA)</p><p>* STE driven by meteorology in GEOS-Chem. If by meteorology, why GC can not produce the events? Global total lightning NOx is 6.0 Tg N/yr in GEOS-Chem and 3.0 Tg N/yr AM3. Differ mainly in spatial distribution, 4x higher NOx yield per flash in GEOS-Chem over the Northern mid-latitudes than over the tropics</p><p>*Can NASA satellites offer constraints on conditions (fires, lightning, stratosphere) under which models agree/disagree most, and thus help refine best estimates?*OMI/MLS tropospheric column ozone confirms the penetration of stratospheric ozone into the troposphere*High-altitude southwest US is more exposed to ozone produced from lightning NOx than the lower elevation southeastern US. *Low PAN for the same event in GC? Higher vertical distribution in AM3 affects transport and chemistry (PAN only forms at low temperatures). </p><p>*Frequency unit?*TO DATE, EPA HAS RELIED ON PRB ESTIMATES FROM ONE MODEL. Can NASA satellites offer constraints on conditions (fires, lightning, stratosphere) under which models agree/disagree most, and thus help refine best estimates?*</p></li></ul>

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