FastOpt A prototype Carbon Cycle Data Assimilation System (CCDAS) Inferring interannual variations of vegetation- atmosphere CO 2 fluxes Marko Scholze.

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Presentation transcript:

FastOpt A prototype Carbon Cycle Data Assimilation System (CCDAS) Inferring interannual variations of vegetation- atmosphere CO 2 fluxes Marko Scholze 1, Peter Rayner 2, Wolfgang Knorr #3, Thomas Kaminski 4, Ralf Giering 4 # presenting 1 234

FastOpt Biosphere Model: BETHY Parameters: 58 Atmospheric Transport Model: TM2 Fluxes: 800,000 Misfit to Observations Station Conc. 10,000 Misfit 1 1. Parameter Optimisation: Forward: Parameters –> Misfit Adjoint or Tangent linear: ∂ Misfit / ∂ Parameters 2. Parameter Uncertainties: Hessian: ∂ 2 Misfit / ∂ Parameters 2 Error covariance=Inverse of Hessian 3. Uncertainty of Diagnostics: Adjoint or Tangent linear Carbon Cycle Data Assimilation using automatic differentiation

FastOpt CCDAS Setup CCDAS Step 2 IMBETHY+TM2 only Photosynthesis, Energy&Carbon Balance CO 2 + Uncert. Calibrated Params + Uncert. Diagnostics + Uncert. veg. index Satellite CCDAS Step 1 full BETHY Phenology Hydrology Assimilated Prescribed Assimilated Background CO 2 fluxes* * * ocean: Takahashi et al. (1999), LeQuere et al. (2000); emissions: Marland et al. (2001), Andres et al. (1996); land use: Houghton et al. (1990)0

FastOpt BETHY (Biosphere Energy-Transfer-Hydrology Scheme) GPP: C3 photosynthesis – Farquhar et al. (1980) C4 photosynthesis – Collatz et al. (1992) stomata – Knorr (1997) R aut : maintenance respiration = f(N leaf, T) – Farquhar, Ryan (1991) growth respiration ~ NPP – Ryan (1991) R het : fast/slow pool resp. = w   Q 10 T/10 C fast/slow /  fast/slow  slow –> infin. average NPP =  average R het (at each grid point)  <1: source  >1: sink  t=1h  t=1day  lat,  lon = 2 deg

FastOpt Concentrations

FastOpt Parameters relative error reduction: examples:

FastOpt Processes 1 global fluxes Carbon source anomaly: drop in GPP exceeds drop in resp Carbon sink anomaly: stronger decr. in resp. than GPP El Niño events Pinatubo eruption La Niña Carbon sink: GPP slightly exceeds respiration

FastOpt Processes 2 normalized CO 2 flux and ENSO 4-month lagged: ENSO and terr. biosph. CO 2 : correlation seems strong lag correlation (low-pass filtered) correlation between Niño-3 SST anomaly and net CO 2 flux shows maximum at 4 months lag, for both El Niño and La Niña states Pinatubo eruption: shows up as largest deviation in the low-pass filtered curve

FastOpt Processes 3 lagged correlation at 99% significance El Niño (>+1  ) net CO 2 flux to atm. gC / (m 2 month)

FastOpt net carbon flux gC / (m 2 year) Euroflux (1-26) and other eddy covariance sites* Carbon Balance latitude N *from Valentini et al. (2000) and others

FastOpt CCDAS with 58 parameters can already fit 20 years of CO 2 concentration data Significant reduction of uncertainty for ~13 parameters, some important covariances terr. biosphere response to climate fluctuations dominated by ENSO and Pinatubo Can be explained by small perturbations of 3 large fluxes (GPP, Raut, Rhet) Conclusions

FastOpt explore more parameter configurations include fire as a process with uncertainties include more constraints (isotopes, eddy fluxes) extend approach to ocean carbon cycle Outlook