Atmospheric chemistry analysis and modeling at LDEO: Connecting global composition, climate, and air quality

Atmos. Chem at CUGroup Meeting

9-19-13

Arlene M. Fiore

83520601

Group members: Olivia Clifton (CU), Gus Correa (LDEO), Jean Guo (CU), Nora Mascioli (CU), Keren Mezuman (CU), Lee Murray (LDEO), Luke Valin (LDEO)

Close Collaborators: Elizabeth Barnes (now at CSU), Larry Horowitz (GFDL), Meiyun Lin (Princeton/GFDL), Vaishali Naik (UCAR/GFDL), Jacob Oberman (former NOAA Hollings intern), Harald Rieder (now at U Graz, Austria), Lorenzo Polvani (CU), Mike Previdi (LDEO)

Today’s Focus

How and why might extreme air pollution events change?

Meanshifts

Variabilityincreases

Symmetrychanges

Figure SPM.3, IPCC SREX 2012http://ipcc-wg2.gov/SREX/

Need to understand how differentprocesses influence the distribution

pollutant sources

Degree of mixing

• Meteorology (e.g., stagnation vs. ventilation)

Shift in mean?

Change in symmetry?

• Changing global emissions (baseline)

• Changing regional emissions (episodes)

T Fires NOxOH

PANH2OVOCs

Deposition

• Feedbacks (Emis, Chem, Dep)

Extreme Value Theory (EVT) methods describe the high tail of the observed ozone distribution (not true for Gaussian)

JJA MDA8 O3 1987-2009 at CASTNet Penn State site

Gaussian (ppb)

Obs

erve

d M

DA

8 O

3 (p

pb)

Obs

erve

d M

DA

8 O

3 (p

pb)

Generalized Pareto Distribution Model (ppb)

EVT Approach: (Peak-over-threshold)for MDA8 O3>75 ppb

Gaussian:Poor fitfor extremes

1988-19981999-2009

Rieder et al., ERL 2013

EVT methods enable derivation of “return levels” for JJA MDA8 O3 within a given time period

CASTNet site: Penn State, PA

Return level: describes probability of observing value x (level) within time window T (period)

Rieder et al., ERL 2013

1988-19981999-2009 Sharp decline in return levels

between early and later periods

(NOx SIP call) Consistent with prior work [e.g.,

Frost et al., 2006; Bloomer et al., 2009, 2010]

Translates air pollution changes intoprobabilistic language

Applied methods to all EUS CASTNet sites; projections for future changes with GFDL CM3 chemistry-climate model

The GFDL CM3/AM3 chemistry-climate model

6000+ years of CM3 CMIP5 simulations [John et al., ACP, 2012 Turner et al., ACP, 2012 Levy et al., JGR, 2013 Barnes & Fiore, GRL, 2013]

Options to nudge AM3 to reanalysis; also global high-res (~0.5°x0.5°) [Lin et al., JGR, 2012ab]

Donner et al., J. Climate, 2011; Golaz et al., J. Climate, 2011

Naik et al., JGR, 2013

cubed sphere grid ~2°x2°; 48 levels

Atmospheric Chemistry 86 km

0 km

Atmospheric Chemistry 86 km

0 km

Atmospheric Dynamics & PhysicsRadiation, Convection (includes wet

deposition of tropospheric species), Clouds, Vertical diffusion, and Gravity wave

Atmospheric Dynamics & PhysicsRadiation, Convection (includes wet

deposition of tropospheric species), Clouds, Vertical diffusion, and Gravity wave

Chemistry of gaseous species (O3, CO, NOx, hydrocarbons) and aerosols

(sulfate, carbonaceous, mineral dust, sea salt, secondary organic)

Dry Deposition

Aerosol-Cloud Interactions

Chemistry of Ox, HOy, NOy, Cly, Bry, and Polar Clouds in the Stratosphere

ForcingSolar Radiation

Well-mixed Greenhouse Gas ConcentrationsVolcanic Emissions

ForcingSolar Radiation

Well-mixed Greenhouse Gas ConcentrationsVolcanic Emissions

Ozone–Depleting Substances (ODS)

Ozone–Depleting Substances (ODS)

Modular Ocean Model version 4 (MOM4)&

Sea Ice Model

Modular Ocean Model version 4 (MOM4)&

Sea Ice Model

Pollutant Emissions (anthropogenic, ships,

biomass burning, natural, & aircraft)

Pollutant Emissions (anthropogenic, ships,

biomass burning, natural, & aircraft)

Land Model version 3(soil physics, canopy physics, vegetation

dynamics, disturbance and land use)

Land Model version 3(soil physics, canopy physics, vegetation

dynamics, disturbance and land use)

SSTs/SIC from observations or CM3 CMIP5 Simulations

SSTs/SIC from observations or CM3 CMIP5 SimulationsGFDL-CM3GFDL-AM3

Generating policy-relevant statistics from biased models

Applying correction to projected simulations assumes modelcaptures adequately response to emission and climate changes

Rieder et al., in prep

CM3 Historical simulation (3 ensemble-member mean)

Corrected CM3 simulation (regional remapping)

CASTNet sites (observations)

Average (1988-2005) number of summer days with O3 > 75 ppb

GFDL CM3 generally captures NE US JJA surface O3 decrease following NOx emission controls (-25% early 1990s to mid-2000s)

Rieder et al., in prep

Implies bias correction based on present-day observations can be applied to future scenarios with NOx changes (RCPs)

Caveat: Model response on low-O3 days smaller than observed

Observed(CASTNet) Model

(CM3)

JJA MDA8 O3 (ppb)

Climate and Emission Scenarios for the 21st Century:Representative Concentration Pathways (RCPs)

RCP8.5RCP4.5RCP4.5_WMGG

Percentage changes from 2005 to 2100

GlobalCO2

GlobalCH4

GlobalNOx

NE USANOx

Enables us to isolate role of changing climate

Change in Global T (°C) 2006–2025 to 2081–2100(>500 hPa) in GFDL CM3 chemistry-climate model

[John et al., ACP, 2012]

How will surface O3 distributions over the NE USevolve with future changes in emissions and climate?

How does climate warming change extreme O3 events over the NE USA?

Base Years (2006-2015)

Change: (2091-2100) – (2006-2015)

1-year MDA8 O3 Return Levels in GFDL CM3 RCP4.5_WMGG (corrected)

Much of region sees ‘penalty’ (Wu et al., 2008) but some ‘benefit’, up to 4 ppb Signal from regional ‘climate noise’ with only 3 ensemble members?

Robust across models?

Change: (2091-2100) – (2046-2055)

Rieder et al., in prep

Large NOx reductions offset climate penalty on O3 extremes

1-year Return Levels in CM3 chemistry-climate model (corrected)Summer (JJA) MDA8 Surface O3 [Rieder et al., in prep]

ppb

2046-2055

RCP4.5_WMGG:Pollutant emissions held constant (2005) +climate warming

2091-2100

RCP4.5:Large NOx

decreases + climate warming

All at or below 60 ppbNearly all at or below 70 ppb

Rieder et al., in prep Ongoing work examining relationship between

NOx reductions and 1-year return levels

Does aerosol forcing influence extreme weather events?

N. Mascioli

1860-2005 “Aerosol only” forcing scenario in GFDL CM3 chemistry-climate modelWarm Spell Duration (consecutive warm days) over Eastern North America

Consecutive warm days

(1980-2006) – (1860-1890)

Decrease in warm spell duration over ENA following increase in anthropogenic aerosol(preindustrial conditions except for aerosol)

Identifying key factors contributing to OH variability

Murray et al., 2013 Can this explain large inter-model differences in OH changes (e.g., Naik et al., 2013; Voulgarakis et al. 2013)?

Linearity with photochemical steady-state relationship holds for some models but not others: what factors are missing?

Transient (CMIP5) and Time-slice (ACCMIP) simulations 1850-2100

Annual mean tropospheric [OH] (106 molec cm-3)

GFDL CM3 model

Incorporating additional term for sulfate achieves linearity: aerosol influence on HOx sink OR correlated causal mechanism?

Space-based CH2O: often used to constrain biogenic emissions; what can we learn from background variability?

Atmospheric Column CH2O as retrieved by OMI on Aura satellite

Jun-Aug

Dec-Feb

L. Valin, NOAA/LDEOConstraints on variability in background (CH4) oxidation?

Over the Sahara, model formaldehyde columns correlate strongly with year-to-year variations in CH4 loss rates

Dec-Feb

L. Valin, NOAA/LDEO Exploring whether this is detectable with current space-based measurements

GFDL AM3 model nudged to NCEP meteorology (1981-2007)Regional averages over 20-28N, 2.5-25E

satellites

suborbital platforms

models

AQAST

Pollution monitoringExposure assessmentAQ forecastingSource attribution Quantifying emissionsNatural & foreign influencesAQ processesClimate-AQ interactions

AQAST

All AQAST projects connect Earth Science and air quality management: active partnerships with air quality managers with deliverables/outcomes self-organizing to respond quickly to demands flexibility in how it allocates its resources INVESTIGATOR PROJECTS (IPs): members adjust work plans each year to

meet evolving AQ needs “TIGER TEAM” PROJECTS (TTs): multi-member efforts to address

emerging, pressing problems requiring coordinated activity

Our projects for 2013• Stratospheric and Asian influence on inter-annual WUS surface O3 variations (M. Lin)• climate versus emissions impacts on 21st C U.S. baseline O3 (seasonality)• Analysis of background O3 influence on O3 measured at new NV sites (M. Lin).

TTs (pending selection)• (PIs: Fiore, Holloway) Source attribution for high-O3 events over EUS• (PI: Streets) Satellite-derived NOx emissions and trends• In progress: Multi-model W126 analysis (vegetation exposure)• In progress: Estimates of background O3 from 2 models

www.aqast.org: click on “projects” for brief descriptions + link to pdf describing each project

What makes AQAST unique?How is our group contributing?

Surface O3 seasonal cycle over NE USA reverses – cold season increases- under extreme warming scenario (RCP8.5)

in the GFDL CM3 model

NOx

decreases

?

Monthly mean surface O3 (land only) over the NE USA (36-46N, 70-80W)pp

b

month

3 ensemble members for each scenario

O. Clifton

Why does surface O3 increase in winter/spring over NE USA under RCP8.5?

Change in monthly mean surface O3 (land only) over the NE USA (36-46N, 70-80W)(2091-2100) – (2006-2015)

ppb NOx

decreases

RCP8.5 (3 ensemble members)

?

O. Clifton

Doubling methane raises surface O3 over NE USA ~5-10 ppb

Change in monthly mean surface O3 (land only) over the NE USA (36-46N, 70-80W)(2091-2100) – (2006-2015)

ppb

RCP8.5 but chemistry sees 2005 CH4

RCP8.5 (3 ensemble members)

Doubling CH4

does not fully explain wintertime increase

O. Clifton

Will the NE USA resemble present-day remote, high-altitude W US sites by 2100?

Setting achievable standards requires accurate knowledge of background levels

120 ppb 1979 1-hr avg

84 ppb1997 8-hr

75 ppb 2008 8-hr

40 60 80 100 120O3 (ppbv)

20

U.S. National Ambient Air Quality Standard for O3 has evolved over time

Future?(proposed)

typical U.S.“background” (model estimates)[Fiore et al., 2003;Wang et al., 2009;Zhang et al., 2011]

Allowable O3 produced from U.S. anthrop. sources (“cushion”)

Lowering thresholds for U.S. O3 NAAQS implies thinning cushion between regionally produced O3 and background

backgroundevents over WUS

[Lin et al., 2012ab]

2008 O3 NAAQS revision relied on background estimates from one model Compare N. Amer Background in GFDL AM3 vs. GEOS-Chem

AM3 (~2°x2°) GEOS-Chem (½°x⅔°)

Fourth-highest North American background MDA8 O3 in model surface layer between Mar 1 and Aug 31, 2006

ppb

Estimates of North American background in 2 models (simulations with N. American anth. emissions set to zero)

Models robustly agree N. American background is higher at altitude in WUS Multi-model enables error estimates, in context of observational constraints Need to account for biases to estimate useful policy-relevant statistics

Higher background (spring):More exchange with surface?Larger stratospheric influence?

35 42 50 57 65

High AM3 bias in EUS;caution on N. Amer. Background here!

Excessive lightning NOx in summer

J. Oberman

Fiore et al., in prep

Connecting atmospheric composition, climate, and air quality: from background oxidation to extreme pollution events

• Variability in background CH4 oxidation (OH) Space-based constraints from formaldehyde columns? Determine key driving factors (multi-model CMIP5/ACCMIP)

Extend to other regions, seasons, with a focus on extremes Develop robust relationships with changes in meteorology +

feedbacks from the biosphere

• “Climate penalty” can be offset by NOx reductions which preferentially decrease the highest O3 events

• Background ozone and its specific sources over the U.S. Future shifts in regional vs. transported ozone (incl. CH4)? Harnessing power of multiple models + observations Variability on scales from daily to multi-decadal Process-oriented analysis (Asian polln, strat, storms, jets)

• New Directions Role of aerosol forcing on extreme weather events Process studies (lightning NOx, deposition) Climate variability and composition

Change in 1-yr O3 RL: (2091-2100) – (2046-2055)

Change in monthly mean NE USA O3 : (2091-2100) – (2006-2015)

Sahara region

Change in WSDI (days)(1980-2006) – (1860-1890)