THERE’S A RECTIFIER IN MY CLOSET: Vertical CO 2 Transport and Latitudinal Flux Partitioning

1. THERE’S A RECTIFIER IN MY CLOSET: Vertical CO2 Transport and Latitudinal Flux Partitioning [illustrations from There’s a Nightmare in my Closet by Mercer Mayer] Britton Stephens, National Center for Atmospheric Research TransCom Meeting, Purdue 2007

2. 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 TransCom3 Modelers: Kevin R. 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 Additional Modeling: Wouter Peters, Philippe Ciais, Philippe Bousquet, Lori Bruhwiler

3. Seasonal vertical mixing [figure courtesy of Scott Denning]

4. Annual mean accumulation near surface and depletion aloft Observed [Denning et al., Nature, 1995]

5. Transcom3 neutral biosphere flux response ppm Latitude

6. TransCom3 model results show a large transfer of carbon from tropical to northern land regions. Level 1 (annual mean) Level 2 (seasonal) Gurney et al, Nature, 2002 Gurney et al, GBC, 2004

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

8. TransCom 3 Level 2 annual-mean model fluxes (PgCyr-1) Comparison to other studies

9. Impact on predicted fluxes TransCom3 predicted rectifier explains most of the variability in estimated fluxes

10. Transcom3 neutral biosphere flux response pressure N S N S N S N S ppm

11. Airborne flask sampling locations 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). 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

12. Airborne flask sampling data

13. 20 -15 10 -10 10 -10 0 -5 Altitude-time CO2 contour plots for all sampling locations

14. Model-predicted NH Average CO2 Contour Plots Observed NH Average CO2 Contour Plot

15. Vertical CO2 profiles for different seasonal intervals

16. Observed and predicted NH average profiles

17. Estimated fluxes versus predicted 1 km – 4 km gradients • 3 models that most closely reproduce the observed annual-mean vertical CO2 gradients (4, 5, and C): • Northern Land = • -1.5 ± 0.6 PgCyr-1 • Tropical Land = • +0.1 ± 0.8 PgCyr-1 • All model average: • Northern Land = • -2.4 ± 1.1 PgCyr-1 • Tropical Land = • +1.8 ± 1.7 PgCyr-1 Observed value

18. Observational and modeling biases evaluated: • Interlaboratory calibration offsets and measurement errors • Diurnal biases • Interannual variations and long-term trends • Flight-day weather bias • Spatial and Temporal Representativeness WLEF Diurnal Cycle Observations All were found to be small or in the wrong direction to explain the observed annual-mean discrepancies [Schulz et al., Environ. Sci. Technol. 2004, 38, 3683-3688]

19. Estimated fluxes versus predicted 1 km – 4 km gradientsfor different seasonal intervals Observed values

20. Should annual-mean or seasonal gradients be used to evaluate model fluxes? • 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, but do not want to reject all models. • Errors in seasonal timing of fluxes make selection of seasonal criteria problematic. • Seasonal (rectifier) 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.

21. S S S N N N HIAPER Pole-to-Pole Observations of Atmospheric Tracers HIPPO ’08-’11 (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 Fossil fuel CO2 gradients over the Pacific UCI UCIs pressure N S N S JMA MATCH.CCM3 pressure N S N S ppm

22. Conclusions: • Models with large tropical sources and large northern uptake are inconsistent with observed annual-mean vertical gradients. • A global budget with less tropical-to-north carbon transfer is 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 And of course, watch out for the next monster. . . .

23. Representativeness