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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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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)
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!
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
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
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
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)
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
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
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)
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