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WP11 highlights: introduction and overview

EU FP6 Integrated Project CARBOOCEAN ”Marine carbon sources and sinks assessment” 5 th Annual & Final Meeting – Solstrand Hotel Norway 5-9 October 2009.

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WP11 highlights: introduction and overview

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  1. EU FP6 Integrated Project CARBOOCEAN ”Marine carbon sources and sinks assessment” 5th Annual & Final Meeting – Solstrand Hotel Norway 5-9 October 2009 WP11 highlights: introduction and overview

  2. WP11 Model performance assessment and initial fields for scenarios Objectives: To determine, how well biogeochemical ocean general circulation models (BOGCMs) are able to reproduce carbon cycle observations from the real world with respect to temporal and spatial distributions. To refine criteria for model performance with respect to observations and other model. To establish a quality check for the initial conditions for future scenarios with BOGCMs (BOGCM = biogeochemical ocean general circulation model).

  3. Still to come, see SOLAS OSC, Barcelona, Nov 2009. …Observed oceanic pCO2 trends are a valuable metric of climate change, because they integrate the changes in dissolved inorganic carbon (DIC), alkalinity, salinity and temperature; we separate the observed pCO2 trends into components driven by each of these fields to assess how well they are captured by the models…

  4. Benchmarking coupled climate-carbon models against long-term atmospheric CO2 measurements Patricia Cadule, Pierre Friedlingstein, Laurent Bopp, Stephen Sitch, Chris Jones, Philippe Ciais, Shilong Piao, Philippe Peylin CARBOOCEAN Annual Meeting – Solstrand, Norway 5-9 October 2009 WP11 Highlights: (IPSL & Hadley Center)

  5. “Traditional” model evaluation 300 ppm in 2100 5 Historical period Future period 60 ppm in 2005 In 2005 Obs: 379 ppm (Foster et al. 2007) C4MIP: 380 ± 14 ppm SRES A2 scenario No deforestation Friedlingstein et al., 2006 • Simulate the evolution of the atmospheric CO2 concentration at the global scale is a necessary condition • To evaluate a model • Be confident in future projections

  6. Atmospheric CO2Available data 6 How can we exploit the spatio-temporal variation of the atmospheric CO2 to evaluate the numerical models? • Spatial variations • Temporal variations • Seasonal cycle (SC) • Vast network of measurement stations across the globe • Inter-annual variability (IAV) • Long term trend (TR)

  7. Methodology Objective: evaluate the simulated carbon exchange against observation data from atmospheric monitoring stations 3 coupled carbon-climate models H: HadCM3LC (Cox et al., 2000) I: IPSL-CM2-C (Dufresne et al., 2002) L: IPSL-CM4-LOOP (Cadule et al., 2009a) Protocol Same anthropogenic CO2 emissions for the 3 models (fossil fuel and land use) Study period: 1979-2003 Same transport model (LMDZ4) forced by observed winds 7 Cadule et al. 2009b, GBC (in revision)

  8. Evaluation of atmospheric CO2 8 Mauna Loa (MLO) Latitude : 19°32’N Longitude : 155°35’W Constraint on sinks Constraint mainly on the terrestrial ecosystems of the mid and high latitudes Signal decomposition according to the method of Thoning et al. (1989): Fourier transform and low-pass filters Constraint on the terrestrial ecosystems of the Tropics year Cadule et al. 2009b, GBC (in revision)

  9. Examples • Seasonal Cycle (SC): Atm. CO2 (phase, amplitude,…) at selected stations • Interannual Variability (IAV): Relationship bewteen ENSO and CO2 growth rate

  10. Evaluation of atmospheric CO2Results: Seasonal cycle (SC) Atm. CO2 (ppm) Atm. CO2 (ppm) Atm. CO2 (ppm) 10 SC Phase and amplitude mark Change of amplitude of the peak-to-peak year Cadule et al. 2009b, GBC (in revision)

  11. Evaluation of atmospheric CO2Analysis: Seasonal cycle (SC) At Harvard and at regional scale, HadCM3LC simulates A carbon sink too soon A carbon source during summer At Harvard, IPSL-CM2-C simulates a too weak sink 11 North American Temperate Harvard Cadule et al. 2009b, GBC (in revision)

  12. Evaluation of atmospheric CO2 IAV: Sensitivity of the CO2 variability to climate variability 12 Climatevariability(ENSO) Climate anomalies(Tropics) Anomalies of the CO2 fluxes (Tropics) Anomalies in measured atmospheric CO2 IPSL-CM2-C HadCM3LC IPSL-CM4-LOOP Inter-annual variability of atmospheric CO2 growth rate (solid) and SST anomalies (dash) September 17th, 2009 Cadule et al. 2009b, GBC (under review)

  13. Evaluation of atmospheric CO2Results: Sensitivity of the CO2 variability to the climate variability • Evaluation of the sensitivity of the atmospheric CO2 growth rate to the SST anomalies is based on slope and intercept 13 Mauna Loa • Analysis performed at 12 stations At global scale the three models do not reproduce well the sensitivity of the CO2 growth rate to the climate variability Cadule et al. 2009b, GBC (in revision)

  14. Evaluation of atmospheric CO2Global metrics results 14 Cadule et al. 2009b, GBC (in revision)

  15. Conclusions 15 • The CO2 metrics constitute a stronger constraint than the evaluation based on atmospheric CO2 concentration at global scale • These metrics help identify processes needing better representation & aid model improvement • Atm. CO2 (SC, IAV) mainly used to evaluate the land carbon cycle models. • For the ocean carbon cycle, other tracers (APO) may do a better job. • Use also other CAARBOOCEAN models (MPI, NCAR, BCCR): in progress • More research is required to turn this analysis into a constraint on future climate-carbon cycle feedbacks. Cadule et al. 2009b, GBC (in revision)

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