ONGOING GEOS-CHEM ACTIVITIES IN JACOB GROUP

1. ONGOING GEOS-CHEM ACTIVITIES IN JACOB GROUP • Tropospheric ozone-NOx-VOC chemistry (Mat Evans, Arlene Fiore, Qinbin Li, Rynda Hudman) • Aerosol chemistry (Rokjin Park, Becky Alexander, Duncan Fairlie, Yang Liu) • Oxygenated organics (Brendan Field) • Biogenic VOC emissions (Dorian Abbot, May Fu, with Randall Martin and Kelly Chance) • Methane (Yaping Xiao, with James Wang) • CO2(Parvadha Suntharaligam, Qinbin Li) • Methyl halides (Paul Palmer) • Mercury (Noelle Eckley, Rokjin Park) • Inverse modeling of CO and CO2 (Colette Heald, Paul Palmer, Dylan Jones, Parvadha Suntharalingam, with Yuxuan Wang) • CO/CO2 satellite OSSEs and chemical data assimilation (Dylan Jones) • Interface with GISS GCM (Loretta Mickley, Shiliang Wu) • fvDAS simulation capability (Brendan Field, Bob Yantosca) • MPI parallelization (Jack Yatteau, Bob Yantosca, with NCCS)

2. TROPOSPHERIC OZONE-NOx-VOC SIMULATION • ~80 species, 300 rxns–detailed oxidation pathways for ethane, propane, C4-5 alkanes, propene, isoprene • SMVGear chemical solver • Fast-J radiative transfer code including 1-D cloud, aerosol effects • Stratosphere: simple chemical processing, Synoz ozone (x-tropopause flux of 475 Tg yr-1). • Anthropogenic emissions from GEIA (NOx), Logan (CO), various sources (VOCs); biofuels/biomass burning from Logan; biogenic from GEIA (modified); lightning from Price/Pickering. • Yearly scaling of anthropogenic emissions using inventory/economic data, of biomass burning emissions using satellite firecounts. • Dry deposition from big-leaf resistance-in-series scheme (Wesely with extensions/modifications) • Wet deposition from convective updrafts, rainout/washout

3. Liu et al., JGR 2001: Constraints from 210Pb and 7Be on wet deposition and transport in a global three-dimensional model driven by assimilated meteorological fields [v2.2, 1991-1996] Development/evaluation of wet deposition algorithm for GEOS-CHEM • No global bias in simulation of surface 210Pb and 7Be data • Aircraft data are ambiguous viz. cirrus sink (not included in std code) • Algorithm extended to gases on basis of Henry’s law partitioning, retention efficiency upon freezing (Jacob document for GMI, to be published somewhere…)

4. Bey et al. JGR 2001a:Global modeling of tropospheric chemistry with assimilated meteorology: model description and evaluation [v3.2, 1994]General description of tropospheric ozone-NOx-VOC simulation • Ozone STE ~3x too high: problem still there in GEOS-3, circumvented with Synoz • Ozone (Ox) production on high side of literature range; fast-J treatment of clouds appears to be a factor. Rate went down in v4.27 due to revised chemistry (esp. O1D + N2) and has crawled down since • Simulation of ozonesonde data within 5-10 ppbv, no systematic bias

5. Global mean tropospheric OH concentration (methylchloroform lifetime) • observed MeCl lifetime: 5.7+/-0.7 yrs • model lifetime keeps going up! 5.1 yrs (Bey2001, v3.2), 5.6 yrs (Martin2003, v4.26), 6.4 yrs (Fiore, v4.33), 6.8 yrs (Park, v5.3) Benchmark 1-month run GEOS-3 (change in benchmark) aerosols (hv) O(1D)+N2 addn’l VOC sources of CO Additional VOC emissions, decline in OH have fixed 10-30 ppbv CO underestimate of Bey et al. [2001]

6. Li et al., GRL 2001: A tropospheric ozone maximum over the Middle East (v4.6, 1993-1997) Circles are sonde and MOZAIC obs • Middle East summer max in the model is due to outflow from S and E Asia in UT, and from Europe in LT • Observational evidence for this maximum in MOZAIC and SAGE-II observations, but not in TOMS residuals. More data are needed.

7. observations GEOS-CHEM model Liu et al., JGR 2002: Sources of tropospheric ozone along the Asian Pacific rim: an analysis of ozonesonde observations [v4.6, 1995-1997] Hong Kong sonde and model profiles, 12/24.96 and 1/8/97 Observed GEOS-CHEM Time series of ozone at Hong Kong, 1996 Model ozone concentrations and fluxes, 200 hPa Stratospheric ozone tracer at longitude of Hong Kong 300-120 hPa • Good unbiased simulation of climatologies at HK and Japanese stations except for summer monsoon • Success in simulating day-to-day variability over Hong Kong 700-300 hPa 850-700 hPa

8. GEOS-CHEM TOMS (CCD) DJF MAM JJA SON R = 0.66 MODEL BIAS = -0.5 DU Martin et al., JGR 2002: Interpretation of TOMS observations of tropical tropospheric ozone with a global model and in situ observations [v4.11, 1996-1997] • Include optical and chemical effects of dust eOH decreases by 9% • Overestimate of ozone (5-10 ppbv) and NOx (x2) over tropical Pacific

9. Martin et al., JGR 2003: Global and Regional Decreases in Tropospheric Oxidants from Photochemical Effects of Aerosols [ v4.26, 1996-1997] Inclusion of aerosol effects on photolysis frequencies and heterogeneous chemistry using off-line monthly mean aerosol fields from GOCART Difference in OH and ozone mixed layer concentrations in simulations with vs. without aerosol effects on photolysis rates and on reactive uptake of HO2, NO2, NO3  OH (%) August  O3 (ppbv)

10. Martin et al., JGR 2003 (cont.)LARGE MODEL OVERESTIMATE OF O3 OVER S. ASIA:aerosol effects are not enough to fix it MOZAIC aircraft observations (1995-99) GEOS-CHEM with full aerosol photochemistry GEOS-CHEM w/o radiative effects or uptake of HO2, NO2, or NO3 by aerosols …this is a very puzzling problem!

11. Fiore et al., JGR 2002: Background ozone over the United States in summer: origin, trend, and contribution to pollution episodes [v3.3, 1995] • uses SAMI inventory for eastern U.S. (never put in standard code; little difference with GEIA) • mean bias = +3 ppbv; good simulation of pdfs up to 70 ppbv, trends, precursors, correlations. • Background over Gulf of Mexico too high; excessive convection • Positive bias in urban coastal areas: BL horizontal resolution problem GEOS-CHEM

12. GEOS-CHEM 2°x2.5° OBS (AIRS) EOF 1: East-west r2 = 0.68 Slope = 1.0 r2 = 0.74 Slope = 1.2 EOF 2: Midwest- Northeast r2 = 0.54 Slope = 0.8 r2 = 0.27 Slope = 1.0 r2 = 0.78 Slope = 1.0 EOF 3: Southeast r2 = 0.90 Slope = 1.0 Fiore et al., JGR 2003a: Application of empirical orthogonal functions to evaluate ozone simulations with regional and global models [v3.3, 1995] • good GEOS-CHEM simulation when projected on observed EOFs esuccessful simulation of synoptic processes driving regional ozone episodes

13. * CASTNet sites Model at CASTNet Model entire region Background Natural O3 level Stratospheric + Fiore et al., ready to go to JGR: Variability in surface ozone background over the United States: implications for air quality policy [v4.33, 2000-2001] Monthly mean pm conc. Time series Good simulation of temporal variability; main problem is background overestimate in southeastern U.S. in summer (GEOS-3 did not fix problem)

14. GEOS-CHEM model N.America pollution events in model Observed [Simmonds] Li et al., JGR 2002a: Transatlantic transport of pollution and its effects on surface ozone in Europe and North America (v4.16, 1993-1997) 1993-1997 stats Mar-Aug 1997 time series • Excellent simulation of ozone and CO at Sable I., Mace Head, Iceland (means, pdfs, time series, correlations)

15. Li et al., JGR 2002b: Stratospheric versus pollution influences on ozone at Bermuda: Reconciling past analyses (v4.16, 1996) 3-d back-trajectory facility in GEOS-CHEM (T.D. Fairlie) r = 0.82, bias –1.8 ppbv model ozone source attribution • Tagging of ozone by region of origin identifies U.S. pollution as dominant contributor to high-ozone events in Bermuda

16. Ozonesonde observations (1988-2000) GEOS-CHEM model (1996) Li et al., JGR2002b (cont.) • Successful simulation of April ozonesonde data over N America strengthens case against stratospheric influence at Bermuda

17. 0-6 km 6-12 km NO PAN NO PAN O3 HNO3 O3 HNO3 Bey et al., JGR2001b: Asian chemical outflow to the Pacific in spring: origins, pathways, and budgets [V3.02, 1994] Simulation of PEM-West B data • Successful simulation of Asian outflow pathways (WCBs, mixing of fuel and biomass burning effluents) – verified in TRACE-P • Vertical profiles of NO and PAN, here and elsewhere, are usually within factor of 2, while HNO3 is biased high in remote FT by factor of 2-3 – HNO3 simulation is improved in GEOS-3 due to more frequent precip Triangles: obs Circles: model

18. Li et al., ready to go to JGR: Export of NOy from the North American boundary layer: a global model analysis of aircraft observations [v4.26, 1997] • Simulation of NARE 1997 aircraft observations of N American outflow off Nova Scotia • Good unbiased agreement for CO, O3, NO; • Overestimates in the free troposphere of NOy (35%) and PAN (50%) reflect a northern midlatitudes problem that is most severe in GEOS-STRAT

19. HNO3 4x5 96-97 2x2.5 96-97 4x5 2001 2x2.5 2001 4x5 1994 Obs. (GEOS-1; v. 3.2) (GEOS-STRAT, v. 4.26) (GEOS-3; v. 4.33) MAR Easter Island FEB Japan Coast MAR Hawaii MAR Tahiti SEP South Pacific SEP Easter Island AUG Eastern U.S.A. JUL Alaska Aircraft HNO3 evaluation: comparison of different model versions (A. Fiore)

20. 4x5 96-97 2x2.5 96-97 4x5 2001 2x2.5 2001 4x5 1994 Obs. (GEOS-STRAT, v. 4.26) JUL Eastern Canada JUL Central Canada AUG Eastern U.S. JUL Alaska AUG Western U.S. AUG U.S. W. Coast MAR Hawaii Aircraft PAN evaluation: comparison of different model versions (A. Fiore) PAN (GEOS-1; v. 3.2) (GEOS-3; v. 4.33)

21. Mat Evans: gN2O5 = 0.1 in standard model is too high: implications for NOx, O3 Improved representation: • = f(T, RH) for sulfate, sea salt • = 0.01 for dust • = 0.005 for carbonaceous Snapshot for January 1: global mean gN2O5= 0.025

22. Ozone increase for April 2001 with gN2O5 =0.01 vs. 0.1 …effect with best estimate of g still TBD

23. Mat Evans: Simulation of TRACE-P Asian outflow of NOy (gN2O5=0.01) • Tropical overestimate probably due to biomass burning source • g =0.01 (vs. 0.1) helps simulation of NO in free troposphere NOy PAN NOy PAN HNO3 + NO3- HNO3 + NO3- NO NO (HNO3+ NO3-))/NOy (HNO3+NO3-)) /NOy PAN/NOy PAN/NOy

24. HCHO vertical columns (July 1996): GEOS-CHEM uses GEIA inventory of isoprene emissions GEOS-CHEM GOME Comparisons to surface HCHO data using different isoprene emission inventories Palmer et al., 2001:Air mass factor formulation for spectroscopic measurements from satellites: application to formaldehyde retrievals from GOMEPalmer et al., 2003b: Mapping isoprene emissions over North America using formaldehyde column observations from space, JGR [v4.4, 1996] GEIA BEIS2 • GEIA isoprene emission inventory as used in GEOS-CHEM results in 20% high bias in HCHO simulation • “GOME isoprene inventory” derived from top-down constraints and isoprene-HCHO relationship from GEOS-CHEM gives better simulation (but has not been implemented in the standard GEOS-CHEM) GOME

25. Abbot et al., GRL 2003: Seasonal and interannual variability of isoprene emissions as determined by formaldehyde column measurements from space [v4.26, 1997] GOME GEOS-CHEM (GEIA) GOME GEOS-CHEM (GEIA) MAR JUL APR AUG MAY SEP JUN OCT • Regional discrepancies to be investigated after updating GEOS-CHEM isoprene emissions to GBEIS (in progress) • Should we update our land surface data base? To MODIS?

26. INTEGRATION OF TRACE-P, MOPITT, AND GEOS-CHEM TO QUANTIFY CARBON MONOXIDE SOURCES FROM ASIA Fossil and biofuel [D.R. Streets, ANL] Daily biomass burning (satellite fire counts) TRACE-P CO DATA (G.W. Sachse) A PRIORI EMISSIONS (customized for TRACE-P) chemical forecasts GEOS-CHEM CTM top-down constraints validation INVERSE ANALYSIS • CONCLUSIONS: • A priori Chinese emissions too low by 50% • (domestic burning) • A priori SE Asian biomass burning emissions • too high by 60% • Japan, Korean emissions correct within 20% MOPITT CO March-April 2001

27. Liu et al., JGR2003: Transport pathways for Asian combustion outflow over the Pacific: Interannual and seasonal variations [v4.13; 1994, 1996, 1998, 2000-2001] Simulation of TRACE-P outflow pathways using CO as tracer • Successful simulation of WCB motions; altitude of outflow is often a few km off but unbiased; • excellent simulation of post-frontal boundary layer advection; • difficulty with timing of convection.

28. Heald et al., , JGR 2003a: Biomass burning emission inventory with daily resolution: application to aircraft observations of Asian outflow[v4.20, 2001] (AVHRR) Climatology 2001 monthly 2001 daily Biomass burning emissions • Using 2001 vs. climatological emissions improves simulation • No further improvement by using daily vs. monthly emissions

29. Palmer et al., JGR 2003a: Inverting for emissions of carbon monoxide from Asia using aircraft observations over the western Pacific [v4.33, 2001] • Simulation of CO aircraft observations in TRACE-P shows that • Model transport error is 20-30% at all altitudes • Streets inventory of Chinese anthrop emissions is 50% too low (Logan inventory used in standard GEOS-CHEM is OK) • GEOS-CHEM biomass burning in SE Asia is 3x too high Relative error in model simulation of TRACE-P CO observations

30. Mar-Apr 2001 mean Heald et al., JGR 2003b: Transpacific satellite and aircraft observations of Asian pollution [v4.33, 2001] MOPITT • GEOS-CHEM sampled with MOPITT averaging kernels and along MOPITT orbit track • R2 = 0.87, bias -4.6 ppbv • Regional underestimate in SE Asia (need to reduce biomass burning by 50-60%); consistent with Palmer et al. TRACE-P inversion • (not shown here) Succesful model simulation of events of Asian outflow, transpacific pollution GEOS-CHEM Difference

31. A priori: Streets (FF, BF), Logan (BB) A posteriori Colette Heald: Inverse modeling of Asian CO sources using MOPITT data [v4.33, 2001] Objective: Develop top-down constraints on Asian sources of CO based on synthesis of MOPITT and TRACE-P aircraft observations a priori a posteriori Preliminary Results (MOPITT only) FFCHKJ FFSEA FFIN BBCH BBSE BBIN ROW/10

32. Use GEOS-CHEM chemical forecasts of CO for TRACE-P, assume that differences between successive (48-hr and 24-hr) forecasts are representative of the covariant error structure (NMC method) Dylan Jones: constructing the covariance matrix for the model transport error Square root of variancebased on 49 pairs of forecasts for Feb-April, 2001 8 km 1.5 km CO Mixing Ratio (ppb)

33. Qinbin Li, Rynda Hudman, Yuxuan Wang: hindcast simulations for summer 2004 field studies (v. 5.04) Nested 1°x1° Grid Over North America 1ox1o CO at 0.5 km altitude, July 1 2001 • Conduct multi-year (1997, 2000-2002) simulations (CO, O3, aerosols) to examine interannual variability in export pathways.

34. Parvadha Suntharalingam: CO2 Simulation Capability in GEOS-CHEM BIOSPHERIC EXCHANGE FOSSIL FUEL Includes diurnal cycle BIOFUELS BIOMASS BURNING OCEAN EXCHANGE MID MLO Model evaluated against measurements from NOAA-CMDL sites BME NWR

35. Parvadha Suntharalingam: constraints on Asian CO2 fluxes from CO/CO2 correlations in Asian outflow REGION Offshore China • Modeled CO2/CO ratios higher than observations • Modeled boundary layer CO2 is higher than observations • Reconciliation of modeled CO2 with observed CO2 and CO2/CO ratios requires a reduction in a source with a high CO2/CO emissions ratio • Better agreement between model and observations achieved with a 40% reduction in Chinese biospheric emissions MODEL OBS

36. Yaping Xiao: Global ethane simulation (v4.33, 1994) • New info from TRACE-P: • Streets’ Asian emission • Russian ind. emission * 2.5 • Biomass burning * 0.3 Global evaluation: Columns, aircraft profiles, surface sites

37. Yaping Xiao: Improve understanding of CH4 sources with TRACE-P aircraft observations (v4.33, 2001) Preliminary inventory from James Wang Superimpose Streets’ Asian emissions European anth. * 0.7 • Asian anth. total: Streets’ 95Tg/yr (as compared to Wang et al. 135 Tg/yr) • Constraint from CH4-C2H6-CO correlations: scale down Eurasian anth. by 30% • With the optimized emissions, no distinct bias in comparing with TRACE-P or CMDL

38. COUPLED AEROSOL-CHEMISTRY SIMULATION CAPABILITY IN GEOS-CHEM • H2SO4-HNO3-NH3- H2O aerosol thermodynamics • GEIA sulfur emissions (scaled) • GEIA ammonia emissions w/ T-dep seasonal variation • ISORROPIA (slow) or RPMARES (fast) thermo module • Sulfur oxidant chemistry: OH, H2O2, O3, NO3 • OC and EC (hydrophillic and hydrophobic) • Soil dust (four size classes) • Sea salt (two size classes) • Coupling of aerosol with ozone chemistry through • Aerosol effects on photolysis rates • Sulfur oxidants • HNO3(g)/NO3- partitioning • Heterogeneous chemistry • Aerosol simulation can be either coupled (“on-line”) or uncoupled (“off-line”)

39. model observations observations Park et al., JGR 2003: Sources of carbonaceous aerosols over the United States and implications for natural visibility (v4.23, 1995, 1998) • Fuel combustion sources from Cooke et al., with biofuels and seasonal variation (N America) added; GEOS-CHEM biomass burning; secondary OC from terpenes • Top-down constraints applied to improve U.S. emission estimates; biofuel source increased by 65%, other changes smaller Model vs. observed (IMPROVE) 1998 annual concentrations OC EC

40. Rokjin Park: background SO42—NO3—NH4+ aerosols in U.S. and implications for AQ standards (v5.03, 2001) • SULFATE 2001 comparison for non-urban U.S. sites: high correlation, 25% low bias in summer (excessive scavenging?), other seasons better

41. Rokjin Park: comparisons to U.S. NH4+ and NO3- observations • NH4+: 2x high bias in fall, 5-25% bias in other seasons GEOS-CHEM vs. Gilliland seasonal variation of NH3 emissions: • NO3-: 3x high bias in summer-fall, better but still high in other seasons. • …appears to be driven by NH4+ overestimate

42. Rokjin Park: evaluation with EMEP 2001 aerosol observations in Europe • Good simulation for sulfate, no apparent bias • 40-60% overestimate of ammonium in summer-fall (25% annual) • confusing picture for nitrate; high bias in summer-fall

43. Yang Liu and Rokjin Park: simulation of surface PM2.5 and MISR satellite AOT over U.S. [v5.3, 2001] Note: this comparison does not include model dust or sea salt yet!

44. Yang Liu and Rokjin Park, cont. • General model overestimate in midwest (ammonia) • General model underestimate in west (don’t include dust – also urban bias in obs?), but overestimate in NW in summer (probably OC)

45. Rokjin Park and Yang Liu, very preliminary: GEOS-CHEM AOTs

46. Becky Alexander, Rokjin Park: oxygen isotope tracers of sulfate chemistry [v5.03, 2001] D17O sulfate (tracer of oxidation by O3) in standard GEOS-CHEM simulation is only significant during winter at high northern latitudes (when H2O2 is titrated) D17O sulfate simulation January 2001 July 2001 D17O is too low compared with measurements from various locations in California, Antarctica, and the 1997 pre-INDOEX cruise

47. Becky Alexander (cont.) …fix by adding aqueous oxidation of S(IV) in sea-salt aerosols Estimate that 44 -74% of marine SO2 originating from DMS is oxidized to sulfate by O3 on sea-salt aerosols May 2001 GEOS-CHEM 2001 sea-salt emissions: 5700 Tg/year 95% supermicron 35% northern hemisphere

48. Li et al., GRL2000: Atmospheric hydrogen cyanide (HCN): biomass burning source, ocean sink? (v3.2, 1993-1994)Li et al., JGR2003: Model Evaluation of the Atmospheric Budgets of HCN and CH3CN: Constraints From Aircraft and Ground Measurements [v4.33, 2001] • Simulation of HCN and CH3CN includes two-film model for ocean uptake (applied since to acetone, methanol, DMS) TRACE-P data

49. Bell et al., JGR 2002: Methyl iodide: atmospheric budget and use as a tracer of convection in global models [v4.3, 1993-1994] Observations Model (GEOS-CHEM) MCI: 0.40 (obs) 0.22 (mod) MCI: 0.16 (obs) 0.14 (mod) • Define Marine Convection Index (MCI) as ratio of upper tropospheric (8-12 km) • to lower tropospheric (0-2.5 km) CH3I concentrations • MCI over Pacific ranges from 0.11 (Easter Island dry season) to 0.40 (observations over tropical Pacific • GEOS-CHEM reproduces observed MCI with little global bias (+11%) but poor correlation (r2 = 0.15, n=11) Simple model for ocean source

50. Paul Palmer: Inverse modeling of CH3Br and CH3Cl sources using constraints from aircraft data CH3Br a priori budget terms CH3Br has been declining by 5% yr-1 in 1990s – need slab ocean model to represent?