Prabir K. Patra, Shamil Maksyutov, A. Ito and TransCom-3 modellers Jena; 13 May 2003 An evaluation of an ecosystem model for studying CO2 seasonal cycle.

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Presentation transcript:

Prabir K. Patra, Shamil Maksyutov, A. Ito and TransCom-3 modellers Jena; 13 May 2003 An evaluation of an ecosystem model for studying CO2 seasonal cycle TransCom-3 (Level-1) related activities at FRSGC

Goals… To configure optimal observation system –Measurement network optimisation (surface) –Estimate benefits of satellite data in inversion –Evaluate of their relative performance

Tools  Inverse Modelling  Least squares fitting of observed data and model simulations  Matrix multiplication and SVD  TransCom-3 setup for 11 land and 11 ocean regions  HiRes setup for 42 land and 11 ocean regions  Forward Modelling  16 global transport models of TransCom-3  Advection, PBL, Convection etc. are treated differently  ECMWF, NCEP, GCM meteorological fields  Simulation of monthly-mean source/basis functions

Network Optimization Patra and Maksyutov, GRL, 29, 28 May 2002 C D =RSD 2

Incremental Optimization of Surface Network (Case 1) O basic [] Model Ensemble

Average uncertainty for TransCom-3 models Total Source Covar C =  C S ; Average Unc =  C/ No. of Region

Signal gradients at optimal stations

Model Dependent Uncertainty Reduction 1:UCB 2:UCI 3:UCI:s 4:UCI:b 5:JMA 6:MATCH:b 7:MATCH:c 8:MATCH:l 9:NIES:FRSGC 10:NIRE-CTM 11:RPN:SEF 12:SKIHI 13:TM2 14:TM3 15:CSU Patra et al., Tellus, 55B(2), 2003

Signal gradients within NH regions

Occultation based satellite measurements (Case 2) C D =RSD 2 + Inst. Err. 2

Regional flux uncertainty at several satellite data precision

Satellite vs Surface data inversion (inst err=0)

Ecosystem production distribution : a justification for high resolution inverse model The fossil fuel emission do not have seasonality. Oceanic sources and sinks are weaker compared to the land and less heterogeneous.

HiRes Inverse Model (42 Land and 11 Ocean Regions)

Inverse Model Intercomparison

Optimal Networks: TransCom-3 vs HiRes

Comparison of average flux uncertainty C_D=RSD^2

Satellite vs Surface Observations TransCom-3 HiRes setup C_D=RSD^2 + P^2

Multimodel Inversion of SOFIS data Three model groups: 1. High, Low and Intermediate signal in the “global” middle-upper troposphere High C_Ds compared to the signal – flat flux unc. with precision

Multimodel Inversion (no RSDs) Is the use of RSDs (derived from NIES model only) in satellite data inversion justified?

Comparisons for different latitude belts

 Flux uncertainty reduction with surface network extension depends on vertical profiles near the surface  Diving the Tracom-3 region into four smaller regions do seem to pose a severe aggregation problem  The use to different ATM simulations effect the pseudo-satellite inversion results Conclusions

An evaluation of an ecosystem model for studying CO2 seasonal cycle

Tests with an Ecosystem Model Outputs  Optimisation of SimCYCLE model parameters: –1. Q10 for respiration change with temperature –2. Leaf-level Photosynthetic Capacity (PC)  Both parameters were changed by -20%, -10%, -5%, -3%, -1%, +1%, +3%, +5%, +10%, and +20% SimCYCLE: SIMulation model of the Carbon cYCle in Land Ecosystem (Ito and Oikawa, Eco. Mod., 2002)

Flowchart of SimCYCLE model Source: A. Ito

Light-photosynthesis relationship with different maximum rate Source: A. Ito

Temperature-respiration relationship with different Q 10 Source: A. Ito

Procedure  Monthly-mean SimCYCLE outputs are transported using NIES/FRSGC model  Signals are sampled at 8 background stations in NH high latitude: Alert, Greenland Zeppelin St., Norway Mould Bay, Canada Barrow, Alaska Atlantic Ocean, Norway Storhofdi, Iceland Baltic Sea, Poland Cold Bay, Alaska Mace Head Shemya Island, Alaska  The simulations are then fitted to the Observed seasonal cycles of CO2

Fitting at Alert Q10 is not so sensitive Best fit at PSR=-10%

(Bad) Fitting at Baltic Sea Best fit at PSR=-10%

(Good) Fitting at Mace Head Good fit at PSR=-5%

SummarySummary Recommended: 5 to 10% Q10 & -5 to -10% PSR

Thanks for your attention TransCom-3 Modellers: D. Baker (NCAR), P. Bousquet (LSCE), L. Bruhwiler (CMDL), Y-H. Chen (MIT), P. Ciais (LSCE), A. S. Denning (CSU), S. Fan (PU), I. Y. Fung (UCB), M. Gloor (MPI), K. R. Gurney (CSU), M. Heimann (MPI), K. Higuchi (MSC), J. John (UCB), R. M.Law (CSIRO), T. Maki (JMA), P. Peylin (LSCE), M. Prather (UCI), B. Pak (UCI), P. J. Rayner (CSIRO), J. L. Sarmiento (PU), S. Taguchi (NIAIST), T. Takahashi (LDEO), C-W. Yuen (MSC)