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Adam Butler & Glenn Marion, Biomathematics & Statistics Scotland •

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Presentation on theme: "Adam Butler & Glenn Marion, Biomathematics & Statistics Scotland •"— Presentation transcript:

1 Impact of climate uncertainty upon trends in outputs generated by an ecosystem model
Adam Butler & Glenn Marion, Biomathematics & Statistics Scotland Ruth Doherty, Edinburgh University Jonathan Rougier,University of Durham Probabilistic Climate Impacts workshop, September 2006

2 Some background Aims BIOSS
To quantify uncertainties in projections of global and regional vegetation trends for the 21st century from the LPJ ecosystem model, based on future climate uncertainty BIOSS Public body providing quantitative consultancy & research to support biological science Funded by ALARM: a 5 year EU project to assess risks of environmental change upon European biodiversity

3 The LPJ Ecosystem Model
“The Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ) combines process-based, large-scale representations of terrestrial vegetation dynamics and land-atmosphere carbon and water exchanges in a modular framework…”

4 Drivers Vegetation Dynamics (annual) Fluxes (daily)

5 LPJ-Lund Potsdam Jena Vegetation Model
Based on climate and soils inputs LPJ simulates: Vegetation dynamics and competition amongst 10 Plant Functional Types (PFTs) Vegetation and soil carbon and water fluxes Average grid-cell basis with a 1-year time-step Spin-up period of 1000 years to develop equilibrium vegetation and soil structure at start of simulation

6 LPJ-Lund Potsdam Jena Vegetation Model
Inputs: Soils: FAO global soils dataset: 9 types inc coarse-fine range (CRU) Climate: monthly temperature, precipitation, solar radiation CO2: provided for ; updated to 2002 from CDIAC Model output scale determined by driving climate Acknowledgements: LPJ code- Ben Smith, Stephen Sitch, Sybil Schapoff CRU data- David Viner (CRU), GCM data (PCMDI)

7 Tropical Broadleaf Evergreen Tree (FPC)

8 C3 Grasses (FPC)

9 LPJ Model Uncertainty Model inputs: future climate uncertainty
Representation of mechanisms driving model processes (Cramer et al. 2001; Smith et al tests different formulations of relevant processes)- generally use most up-to date formulations from literature Parameters within the model (Zaehle et al , GBC)

10 Zaehle et al. 2005 Latin hypercube sampling
Assume uniform PDF for each parameter Exclude unrealistic parameter combinations Simulations at sites representing major biomes (81) 400 model runs (61-90 CRU climatology and HadCM ) Identified 14 functionally important parameters Differences in parameter importance in water-limited regions Estimated uncertainty range of modelled results: 61-90: NPP=43.1 –103.3 PgC/yr; cf Cramer et al. (2001) Which Allows for interactions between different parameter combinations 14- for ecosystem carbon cycling

11 Zaehle et al (2005) NBP = NEE+Biob Uc=full uncertainty range
NPP accounting for parameter uncertainty NBP = NEE+Biob Uc=full uncertainty range C=excluding unrealistic parameters

12 Increases in 2050s due to increased CO2 and WUE, thereafter a decline
Parameter uncertainty increases in the future Uncertainty estimates in NBP/NPP comparable to those obtain from uncertainty amongst 6 DGVMs Uncertainty in NPP and NBP -cramer et al and in parameter uncertainty are equal? (veg C ; cramer )

13 Future Climate Uncertainty based on IPCC 4th Assessment GCM simulations

14 IPCC-AR4 simulations

15 GCMs contributing to SRES A2

16 CO2 concentrations

17 Investigating the effect of Future Climate Uncertainty for LPJ predictions
Perform 19 separate runs of LPJ at the global scale one run using CRU data for at 0.5o x 0.5o results from 18 simulations from 9 GCMs for the period (20th Century and A2) running at the native scale of each GCM GCMs with multiple ensembles CCCMA-CGCM3, MPI-ECHAM5, NCAR-CCSM3 GCMs with single ensemble member CNRM-CM3, CSIRO-MK3, GFDL-MK2, MRI-CGCM2-3, UKMO-HADCM3, UKMO-HADGEM

18 Global mean temperature anomaly relative to 61-90

19 LPJ Outputs For each grid cell LPJ produces annual values for:
Net Primary Production Net Ecosystem Production Plant Functional Type Heterotrophic respiration Vegetation carbon Soil carbon Fire carbon Run-off Evapotranspiration Net Primary Production Net Ecosystem Production Plant Functional Type Heterotrophic respiration Vegetation carbon Soil carbon Fire carbon Run-off Evapotranspiration …we focus on globally averaged values of these variables… Adam to continue …


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