tiger team project :

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Tiger Team project: Processes contributing to model differences in North American background ozone estimates NASA AQAST Meeting University of Wisconsin-Madison June 14, 2012 AQAST PIs: Arlene Fiore (Columbia/LDEO) and Daniel Jacob (Harvard) Co-I: Meiyun Lin (Princeton/GFDL) Project personnel: Jacob Oberman (U Wisconsin) Lin Zhang (Harvard) AQ management contacts: Joe Pinto (EPA/NCEA) Pat Dolwick (EPA/OAR/OAQPS)

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Tiger Team project : Processes contributing to model differences in North American background ozone estimates. AQAST PIs: Arlene Fiore (Columbia/LDEO) and Daniel Jacob (Harvard) Co-I: Meiyun Lin (Princeton/GFDL) Project personnel: Jacob Oberman (U Wisconsin) - PowerPoint PPT Presentation

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Page 1: Tiger Team project :

Tiger Team project:

Processes contributing to model differences in North American background ozone estimates

NASA AQAST Meeting University of Wisconsin-Madison

June 14, 2012

AQAST PIs: Arlene Fiore (Columbia/LDEO) and Daniel Jacob (Harvard) Co-I: Meiyun Lin (Princeton/GFDL)

Project personnel: Jacob Oberman (U Wisconsin) Lin Zhang (Harvard)

AQ management contacts: Joe Pinto (EPA/NCEA) Pat Dolwick (EPA/OAR/OAQPS)

Page 2: Tiger Team project :

Objective: Improved error estimates of simulated North American background O3 (NAB)

Problem: Poorly quantified errors in NAB distributions complicate NAAQS-setting and interpreting SIP attainment simulations To date, EPA NAB estimates have been provided by one model.

Approach: 1)Compare GFDL AM3 and GEOS-Chem NAB (regional, seasonal, daily)2)Process-oriented analysis of factors contributing to model differences

YEAR 2006 GEOS-Chem GFDL AM3

Resolution ½°x⅔° (and 2°x2.5°)½°x⅔° (and 2°x2.5°) ~2°x2°

Meteorology Offline (GEOS-5) Coupled, nudged to NCEP U and V

Strat. O3 & STE Parameterized (Linoz) Full strat. chem & dynamics

Isoprene nitrate chemistry

18% yield w/ zero NOx recycling

8% yield w/ 40% NOx recycling (obs based; Horowitz et al, 2007)

Lightning NOxtied to model convective clouds, scaled to obs. flash climat; higher NOx at N. mid-lat

tied to model convective clouds

Emissions NEI 2005 + 2006 fires (emitted at surface)

ACCMIP historical + RCP4.5 (2005, 2010); vert. dist. climatological fires

ALL DIFFERENT!

Page 3: Tiger Team project :

Seasonal mean North American background in 2006(estimated by simulations with N. American anth. emissions set to zero)

AM3 (~2°x2°) GEOS-Chem (½°x⅔°)

North American background (MDA8) O3 in model surface layer

AM3: MoreO3-strat + PBL-FT exchange?

GC: Morelightning NOx (~10x over SWUS column)+ spatial differences Summer (JJA)

Spring (MAM)

J. ObermanDifferent contributions from summertime Canadian wildfires?(use of 2006 in GC vs climatology in AM3)

ppb

Page 4: Tiger Team project :

Space-based constraints on mid-trop O3?Comparison with OMI & TES “500 hPa” in spring

Models bracket retrievals

Qualitative constraints where the retrievals agree in sign

L. Zhang

Bias vs. N mid-latitude sondessubtracted fromretrievals

Masked out where productsdisagree by > 10 ppb

Page 5: Tiger Team project :

Large differences in day-to-day and seasonal variability of N. American background: Eastern USA, Mar-Aug 2006

GEOS-Chem ( ½°x⅔° ) GEOS-Chem ( ½°x⅔° ) AM3 (~2°x2°) AM3 (~2°x2°) OBS.OBS.

AM3 NAB declines in Jul/Aug(when total O3 bias is worst)

GC NAB varies less than AM3(total O3 has similar variability)

GC NAB declines into summer

AM3 NAB too high in summer:Excessive fire influence?

Does model horizontal resolution matter?

Both models too high in summer

Similar correlations with obsGC captures mean AM3 +11 ppb bias: isop. chem.?

Georgia Station, GA: 84W, 33N, 270m

Voyageurs NP, MN: 93W, 48N, 429m

Mean(σ)Total model O3 Model NAB O3

Page 6: Tiger Team project :

Horizontal resolution not a major source of difference in model NAB estimates

Between

OBS

GC Higher resolution broadensdistribution + shifts closer to observed mean (lower)

GC 2°x2.5°GC ½°x⅔°

GC High-res shows slight shift towards higher NAB(vertical eddies [Wang et al., JGR, 2004])

GC NAB 2°x2.5°GC NAB ½°x⅔°

AM3 ~2°x2°

AM3 NAB ~2°x2°

AM3 represents distribution shape but biased high

Much larger differences between AM3 and GC distributions (both total and NAB O3) than between the 2 GC resolutions

SPRING (MAM) CASTNet sites above1.5 km

GC ½°x⅔°similar toGC 2°x2.5°

LARGEST DIFFERENCES OCCUR IN SUMMER at CASTNET SITES < 1.5 km

(CONUS except CA)

Page 7: Tiger Team project :

Large differences in day-to-day and seasonal variability of N. American background: Western USA, Mar-Aug 2006

Gothic, CO: 107W, 39N, 2.9km

Grand Canyon NP, AZ: 112W, 36N, 2.1km

Mean(σ)

GEOS-Chem ( ½°x⅔° ) GEOS-Chem ( ½°x⅔° ) AM3 (~2°x2°) AM3 (~2°x2°) OBS.OBS.

Total model O3 Model NAB O3

Models bracket Obs.

AM3 larger σ than GC(matches obs)

Mean NAB is similar

GC NAB ~2x smaller σthan AM3

AM3 NAB > GC NAB in MAM (strat. O3?);

reverses in JJA (lightning)

Fig 3-58 of O3 Integrated Science Assessment

Page 8: Tiger Team project :

How much does N. American background vary year-to-year?

Western CO experienceslargest year-to-year variability:What drives this?

NORTH AMERICAN BACKGROUND IN AM3 (ZERO N. Amer. emissions 1981-2007)

MEAN OVER 27 YEARS STANDARD DEVIATION

ppb ppb

Page 9: Tiger Team project :

Stratospheric O3: key driver of daily (+ inter-annual) variability, particularly late spring – e.g. 1999 shown here

Langford et al., 2009

AM3O3-strat

OBS

Examine observational constraints on strat. influence (M. Lin)M. Lin

r2=0.45 (vs. obs) r2=0.50 (vs. obs)

r2=0.44 (vs. obs) r2=0.31 (vs. obs)

Page 10: Tiger Team project :

Improved error estimates of simulated North American background O3 (NAB) that inform EPA analyses

AQ management outcomes: Improved NAB error estimates to support:(1) ongoing review of ozone NAAQS (EPA ISA for O3), (2) SIP simulations focused on attaining NAAQS, (3) development of criteria for identifying exceptional events

Deliverables: 1) Report to EPA on confidence and errors in NAB estimates & key factors leading to model differences (peer-reviewed publication)2) Guidance for future efforts to deliver estimates of sources contributing to U.S. surface O3

What next? satellite constraints: how quantitative? multi-model effort (more robust; error characterization)? -- focus on specific components of NAB tied to multi-platform

observations -- choose a common study period (2008? 2010-2011)?-- leverage AQAST IP + other TT projects where possible