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T3 evolution Level 1: Annual mean control inversion (Nature paper) Annual mean flux sensitivity and model-to-model (Tellus) Annual mean data sensitivity.

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Presentation on theme: "T3 evolution Level 1: Annual mean control inversion (Nature paper) Annual mean flux sensitivity and model-to-model (Tellus) Annual mean data sensitivity."— Presentation transcript:

1 T3 evolution Level 1: Annual mean control inversion (Nature paper) Annual mean flux sensitivity and model-to-model (Tellus) Annual mean data sensitivity (Tellus) Level 2: Cyclostationary control (in preparation – GBC) Cyclo sensitivity, model-to-model? IAV in progress (Baker, Law, Gurney) Level 3 in progress (Houweling) Offshoots Isotope networks Satellite etc

2 Kevin Gurney, Scott Denning, Rachel Law*, Peter Rayner*, Bernard Pak † Colorado State University, *CSIRO Australia, † UC Irvine Philippe Bousquet, Lori Bruhwiler, Yu-Han Chen, Philippe Ciais, Songmiao Fan, Inez Y. Fung, Emanuel Gloor, Martin Heimann, Kaz Higuchi, Jasmin John, Shamil Maksyutov, Philippe Peylin, Michael Prather, Jorge Sarmiento, Shoichi Taguchi, Taro Takahashi, Takashi Maki, Ken Yuen May 2003 TransCom control results for the estimation of seasonal carbon sources and sinks

3 T3 regions

4 Inversion set-up Flux Priors Land: CASA NEP (presub) + Ocean: Takahashi (presub) composite inventory from Level 1 (distributed over particular months) Prior Flux Uncertainties Land: Level 1 (annual GSNF) + + Ocean: 2.0 * Level 1 30% of CASA |resp| 30% of CASA |NPP|

5 Set-up continued CO 2 Observations Monthly mean for 1992-1996 period (filled data) from GV2000 75 stations (dropped DAA) meeting 70% criteria “Data Uncertainties” Setting the floor: If then

6 Presub results: surface maps  Strong northern seasonality for MATCH variants, NIES, NIRE, and TM3 MATCH:NCEP and NIES show widespread Winter max  Weak northern seasonality for CSU, JMA, UCI, and TM2  GCTM has average Winter max but strong Summer minimum

7 Presub results: at stations

8 Aggregated model mean results Uncertainties  Greatest uncertainty reduction in the northern extratropics and Southern Ocean  Model spread is greatest in the tropics but varies in the north – greatest at height of growing season  Model spread goes up where there is data and vice-versa Fluxes  Northern Land: less emission during March, April, and September and greater uptake in July relative to prior  Oceans: greater seasonality……may be ‘contamination’ from land

9 Disaggregated model mean results Land  Boreal NA: deviations in April, June, and August….uptake occurring later in the growing season  Europe: greater net uptake - June through September  Boreal Asia: Reduction in early Spring emissions. Less net uptake in June, more in July  Temperate NA: lessened seasonal amplitude. Significant deviations in Spring and late Fall  Temperate Asia: Large phase disagreement. CASA error or real advance?

10 Disaggregated continued Ocean  Heightened seasonality in northern and tropical ocean regions  North Pacific and North Atlantic: out of phase with prior  Southern Ocean winter uptake lessened compared to prior  Tropical Oceans: net uptake as an annual mean and large negative fluxes centered on July to September months

11 Sensitivity to prior flux uncertainty  Observationally constrained regions show little change  Boreal NA, Temperate NA, Boreal Asia, Temperate Asia, Europe, Northern Ocean, Southern Ocean, South Indian  Tropics (land mainly) are generally sensitive to the prior flux uncertainty Lower uncertainty (4x lower) on Northern Ocean, N Atlantic, and N. Pacific Northern Land: Combined flux difference (Gt C/year)

12 Predicted CO 2 Difference between model mean predicted CO2 and observed (by station, by month)

13 X 2 per station Two or more months with a  2 exceeding 4: CRI, GMI, IZO, UTA, CARR (5000m), PRS, HUN Driven by Feb value (14.7) which results from small 

14 Station sensitivity  Most pronounced changes in tropical regions – primarily the removal of GMI and CRI  Some stations in the southern high latitudes (SPO, SYO, MAA, PSA, HBA, Bass Strait) had  2 of < 0.25 implying uncertainties that may be 2x too loose  Tightening uncertainty on these 6 stations (factor of 2) imparts small changes in the South Indian Ocean

15 Comparison to annual mean inversion

16 Posterior Northern Flux Amplitude R 2 = 0.75

17 Posterior Northern Flux R 2 = 0.6

18 Posterior Northern Flux continued R 2 = 0.82

19 When is the net uptake?

20 Wild speculation on Biogeochemistry  Greater net uptake in Boreal Asia and Europe at the height of the growing season……..  greater NPP or lessened respiration?  The use of air temperature versus soil to drive respiration in CASA? Would explain some of the Winter flux differences  NPP could be wrong in CASA  Phase difference in Temperate Asia  Aggregation error (big region spanning large latitudinal gradient)  Real Springward shift in growing season?  Delay in the onset of the growing season in Boreal regions  Earlier Spring thaw causing respiration to precede photosynthesis  Could heightened ocean seasonality be real?

21 Conclusions  Amplitude of N background flux response is inversely related to N posterior flux amplitude. This is directly related to N land mean uptake and strength of rectifier  Land posterior flux: deviations from the prior occur in Summer and Winter  Europe: greater uptake in growing season  Temperate Asia: ~2 month uptake timing discrepency  Spring timing in Coreal land  Ocean posterior flux  Heightened seasonality in Northern oceans  Southern Ocean discrepency with prior is primarily during Austral Winter  Northern extratropics are insensitive to prior flux information  Northern extratropics are insensitive to high  2 per station instances  Good agreement with annual mean inversion  Phase and amplitude differences from CASA may be biogeochemically interpretable

22 PTP versus rectifier


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