Light Aircraft CO 2 Observations and the Global Carbon Cycle

Light Aircraft CO2 Observations and the Global Carbon Cycle

Britton Stephens, NCAR EOL and TIIMES

Collaborating Institutions:

USA: NOAA GMD, CSU, France: LSCE, Japan: Tohoku Univ., NIES, Nagoya Univ., Russia: CAO, SIF, England: Univ. of Leeds, Germany: MPIB, Australia: CSIRO MAR

Expected from fossil fuel emissions

Motivation:

Atmospheric CO2 increase Climate change

Annual-mean CO2 exchange (PgCyr-1) from atmospheric O2

Surface Observations

TransCom1 fossil-fuel gradients

Global and hemispheric constraints on the carbon cycle

[courtesy of Scott Denning]

[courtesy of Scott Denning]

Seasonal vertical mixing

Transcom3 neutral biosphere flux response

349.5

350.0

350.5

351.0

351.5

352.0

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353.5

354.0

-90 -70 -50 -30 -10 10 30 50 70 90

CSU.gurney

GISS.fung

GISS.prather

GISS.prather2

GISS.prather3

J MA-CDTM.maki

MATCH.bruhwiler

MATCH.chen

MATCH.law

NIES.maksyutov

NIRE.taguchi

RPN.yuen

SKYHI.fan

TM2.lsce

TM3.heimann

GCTM.baker

Latitude

ppm

Gurney et al, Nature, 2002

TransCom3 model results based on surface data imply a large transfer of carbon from tropical to northern land regions.

Level 1 (annual mean)Level 2 (seasonal)

Gurney et al, GBC, 2004

Bottom-up estimates have failed to find large uptake in northern ecosystems and large net sources in the tropics

Model Model Name

NorthernTotal Flux

(1)

TropicalTotal Flux

(1)

NorthernLand Flux

(1)

TropicalLand Flux

(1)

1 CSU -4.4 (0.2) 3.7 (0.6) -3.6 (0.3) 3.3 (0.7)

2 GCTM -3.4 (0.2) 2.3 (0.7) -2.0 (0.3) 2.7 (0.8)

3 UCB -4.4 (0.3) 3.7 (0.6) -3.1 (0.3) 4.0 (0.7)

4 UCI -2.6 (0.3) 0.5 (0.7) -1.5 (0.3) -0.1 (0.8)

5 JMA -1.4 (0.3) -0.5 (0.8) -0.9 (0.4) -0.5 (0.9)

6 MATCH.CCM3 -3.0 (0.2) 2.2 (0.6) -2.1 (0.3) 2.3 (0.7)

7 MATCH.NCEP -4.0 (0.2) 3.2 (0.5) -4.0 (0.3) 3.4 (0.7)

8 MATCH.MACCM2 -3.7 (0.3) 3.1 (0.8) -3.0 (0.3) 2.5 (0.9)

9 NIES -4.0 (0.3) 2.2 (0.6) -3.5 (0.3) 2.7 (0.8)

A NIRE -4.5 (0.3) 1.6 (0.7) -2.8 (0.3) 1.2 (0.8)

B TM2 -1.6 (0.3) -1.4 (0.7) -0.5 (0.3) -1.0 (0.8)

C TM3 -2.4 (0.2) 1.4 (0.6) -2.2 (0.3) 1.0 (0.8)

fluxes in PgCyr-1 = GtCyr-1 = “billions of tons of C per year”

Transcom 3 Level 2 annual-mean model fluxes

@ $3 - $30 / ton, 3 PgCyr-1 ~ $10 - $100 billion / year

TransCom3 predicted seasonal effects explain most of the variability in estimated fluxes.

Response to neutral biosphere flux

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CSU.gurneyGISS.fungGISS.pratherGISS.prather2GISS.prather3J MA-CDTM.makiMATCH.bruhwilerMATCH.chenMATCH.lawNIES.maksyutovNIRE.taguchiRPN.yuenSKYHI.fanTM2.lsceTM3.heimannGCTM.baker

Impact on predicted fluxes

ppm

pres

sure

N S N S N S N S

Transcom3 neutral biosphere flux response

Northern Hemisphere sites include Briggsdale, Colorado, USA (CAR); Estevan Point, British Columbia, Canada (ESP); Molokai Island, Hawaii, USA (HAA); Harvard Forest, Massachusetts, USA (HFM); Park Falls, Wisconsin, USA (LEF); Poker Flat, Alaska, USA (PFA); Orleans, France (ORL); Sendai/Fukuoka, Japan (SEN); Surgut, Russia (SUR); and Zotino, Russia (ZOT). Southern Hemisphere sites include Rarotonga, Cook Islands (RTA) and Bass Strait/Cape Grim, Australia (AIA).

Map of airborne flask sampling locations

Airborne flask sampling data

Altitude-time CO2 contour plots for all sampling locations

20

-15

10

-10

10

-10

0

-5

Northern Hemisphere average CO2

contour plot from observations

Model-predicted NH Average CO2 Contour Plots

Observed NH Average CO2 Contour Plot

Vertical CO2 profiles for different seasonal intervals

Observed and predicted NH average profiles

• 3 models that most closely reproduce the observed annual-mean vertical CO2 gradients (4, 5, and C):

northern land uptake = -1.5 ± 0.6 PgCyr-1 tropical land emission = +0.1 ± 0.8 PgCyr-1

• All model average:

northern land uptake = -2.4 ± 1.1 PgCyr-1

tropical land emission = +1.8 ± 1.7 PgCyr-1

Estimated fluxes versus predicted 1 km – 4 km gradients

Observed value

• Interlaboratory calibration offsets and measurement errors

• Diurnal biases

• Interannual variations and long-term trends

• Flight-day weather bias

• Spatial and Temporal Representativeness

Observational and modeling biases evaluated:

All were found to be small or in the wrong direction to explain the observed annual-mean discrepancies

Estimated fluxes versus predicted 1 km – 4 km gradients for different seasonal intervals

Observed values

Should annual-mean or seasonal gradients be used to evaluate models?

• Annual-mean fluxes are of most interest because they are relevant to annual ecosystem budgeting, to policy makers, and to projections of future greenhouse gas levels

• No model does well at all times of year. Models that do well in summer do poorly in other seasons.

• Errors in seasonal timing of fluxes make selection of seasonal criteria problematic

• Seasonal effects are inherently cumulative, such that a model with large seasonal errors that offset will do better in annual-mean that one with small seasonal errors that compound.

• Models with large tropical sources and large northern uptake are inconsistent with observed annual-mean vertical gradients.

• A global budget with less tropical north carbon transfer is also more consistent with bottom-up estimates and does not conflict with independent global 13C and O2 constraints.

• Simply adding airborne data into the inversions will not necessarily lead to more accurate flux estimates

• Models’ seasonal vertical mixing must be improved to produce flux estimates with high confidence

• There is value in leaving some data out of the inversions to look for systematic biases

Conclusions:

What is the role for heavier and lighter aircraft?

• Continuous instrumentation

• Multiple species

• Long-range operations

• Boundary-layer intensives

• Low-altitude flux legs

longitude/[deg]

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000 Maine => NoDak (northern legs) 8/18&19/2000

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000 Idaho => Maine (southern legs) 8/6-11/2000

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000 Maine => NoDak (northern legs) 8/18&19/2000

3 4 6

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3 5 43 5 4

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longitude/[deg]

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ude/

[m]

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000 Idaho => Maine (southern legs) 8/6-11/2000

1 0 0

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50 150 250 350CO2 [ppm] CO [ppb]

CO2 [ppm] CO [ppb]

a) b)

c) d)

North

South

CO2 CO

COBRA-NA 2000

First-Order Regional CO2 Flux Estimates

Transport Predictions and CO2 Profiles for July 29, 2004

Airborne Carbon in the Mountains Experiment (ACME-04)

All flights:

HIPPO (PIs: Harvard, NCAR, Scripps, and NOAA): A global and seasonal survey of CO2, O2, CH4, CO, N2O, H2, SF6, COS, CFCs, HCFCs, O3, H2O, and hydrocarbons

HIAPER Pole-to-Pole Observations of Atmospheric Tracers

Fossil fuel CO2 gradients over the PacificUCI UCIs

JMA MATCH.CCM3

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S N S N S N

N S

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N S

N S

TransCom3 Modelers:Kevin Robert Gurney, Rachel M. Law, Scott Denning, Peter J. Rayner, David Baker, Philippe Bousquet, Lori Bruhwiler, Yu-Han Chen, Philippe Ciais, Inez Y. Fung, Martin Heimann, Jasmin John, Takashi Maki, Shamil Maksyutov, Philippe Peylin, Michael Prather, Bernard C. Pak, Shoichi Taguchi

Aircraft Data Providers:Pieter P. Tans, Colm Sweeney, Philippe Ciais, Michel Ramonet, Takakiyo Nakazawa, Shuji Aoki, Toshinobu Machida, Gen Inoue, Nikolay Vinnichenko, Jon Lloyd, Armin Jordan, Martin Heimann, Olga Shibistova, Ray L. Langenfelds, L. Paul Steele, Roger J. Francey