tiger team project :

Tiger Team project:Model intercomparison of background ozone to inform NAAQS setting and implementation

NASA AQAST Meeting U.S. EPA, Research Triangle Park, NC

November 16, 2011

AQAST PIs: Arlene Fiore (Columbia/LDEO) and Daniel Jacob (Harvard)

Co-I (presenter): 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) that inform EPA analyses Problem: Poorly quantified errors in NAB distributions complicate

1) 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.

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

Initial project results c/o NOAA Hollings Scholar Jacob Oberman at GFDL summer 2011

GEOS-Chem GFDL AM3

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

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

Isoprene nitrate chemistry

18% yield w/ zero NOx recycling

8% 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 clouds

Emissions EMEP, Streets, NEI 2005, 2006 fires (emitted at surface), MECAN 2.0

ACCMIP emissions w/ climat. fires, vertically distributed <6 km, MEGAN2.1

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 August

• AM3 predicts rising total and NAB for some observed high-O3 events in spring, GC predicts a decline

Can NASA satellites offer constraints?

2006

Thick lines: base-caseThick lines: base-caseThin lines: NA Background (zero out NA anthrop. emissions)

OBS: 58.3±7.0

OBS: 55.8±7.0

Stratospheric ozone intrusions: May 26-31 exampleGFDL AM3 GEOS-CHEM

500 hPa NA background (ppb)

Bias in surface MDA8 (ppb) vs. CASTNet obs

OMI Total Column O3

OMI/MLS Trop. Column O3

DU

DU

AM3 better captures the variability due to stratospheric influence, but the magnitude represents an upper limit (biased high w.r.t. surface obs)

Two models differ in seasonal mean estimates forNorth American background

AM3 GEOS-Chem

Summer (JJA)

North American background (MDA8) O3 in model surface layer

Spring (MAM)

AM3: MoreO3-strat + PBL-FT exchange?

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

Role for differences in O3 from wildfires? Biogenic emissions?

Model treatment of wildfires can contribute to model differences in NAB estimates: June 28, 2006 “event”

AM3

Elevated PAN above PBL (750 mb)

AM3

[ppt]

Need to use event-specific wildfire emissions (satellites)

Uncertainties will remain from (1)vertical distribution of emissions

(lower temp., higher PAN prod.)(2) fire plume chemistry

GC

North American background (MDA8) [ppb]

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 NAB

Surface MDA8 O3 [ppb]

• below 1.5 km+ above 1.5 km

Zhang et. al.,2011

U.S. CASTNet sites

20 40 60 80

0.08

0.06

0.04

0.02

0.00

2006 MAM sites > 1.5 km

0 20 40 60 80 100

0.06

0.04

0.02

0.00

2006 JJA sites < 1.5 km

Capitalize on model strengths to inform policy Develop 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 peaked

Fre

qu

ency

per

pp

b

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

AQ management outcomes: Improved NAB error estimates to support(1)the next revision of the ozone NAAQS, (2)SIP simulations focused on attaining the current ozone NAAQS, (3)development of criteria for identifying exceptional events.

Deliverables (Sept. 30, 2012): 1)Report to EPA on confidence and errors in NAB estimates & key factors leading to model differences; documented in peer-reviewed publication2)Guidance 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

Extra Slides

Transport event driven by biomass burning emissions

CO biomass burning emissions June 2006 (log-scale)AM3 GC

moles / 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

• 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

>1.5 km sites

excluding CA sites

<1.5 km sites

Biogenic isoprene emissions in AM3

• MEGAN 2.1 emission factors [Guenther et al., 2006]

• AVHRR and MODIS PFT and LAI mapped to MEGAN vegetation types

• Tied 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

Two models have similar isoprene emissions, but differ in isoprene nitrate chemistry

Nested GEOS-Chem

AM3/C48 (~200 km)

Transects along the 40N parallel

Compare w.r.t. satellite products?

Nested GEOS-Chem

Zhang et al., 2011

• Distribution merged for March-August, canceling GEOS-Chem low distribution in spring (MAM) and high distribution in summer (JJA)