DGVM runs for Trendy/RECCAP S. Sitch, P. Friedlingstein, A. Ahlström, A. Arneth, G. Bonan, P. Canadell, F. Chevallier, P. Ciais, C. Huntingford, C. D.,

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Presentation transcript:

DGVM runs for Trendy/RECCAP S. Sitch, P. Friedlingstein, A. Ahlström, A. Arneth, G. Bonan, P. Canadell, F. Chevallier, P. Ciais, C. Huntingford, C. D., P. Levy, M. R. Lomas, B. Mueller, M. Reichstein, S. Running, S. I. Seneviratne, N. Viovy, F. I. Woodward, S. Zaehle, M. Zhao

Modelled Natural CO 2 Sinks Le Quéré et al. 2009, Nature-geoscience

Global Annual Budget Regional Trends in Land C-Sinks (Trendy) Compare DGVM-based estimates with other evidence - Satellite derived data - Fluxtower data - Atmospheric Monitoring Stations Regional Trends in C-sinks and Annual Global Budget

GCP- Land trends: modelling protocol Contact: Stephen Sitch & Pierre Friedlingstein Goal: To investigate the trends in NEE over the period Participating models JULES, LPJ, LPJ-GUESS, O-CN, Orchidee, HyLand, SDGVM, NCAR-CLM4, GFDL/Princeton, VEGAS Model simulations The models were forced over the period with changing CO 2, climate (CRU/NCEP) and land use: S1: CO2 only S2: CO2 and climate S3 (optional): CO2, climate and land use Trendy Protocol

Land Source trend positive NPP trend < positive RESP trend negative NPP trend < negative RESP trend negative NPP trend, positive RESP trend Land Sink trend positive NPP trend > positive RESP trend negative NPP trend > negative RESP trend positive NPP trend, negative RESP trend Trends in Land Processes

Land Sink trend positive NPP trend > positive RESP trend negative NPP trend > negative RESP trend positive NPP trend, negative RESP trend Land Source trend positive NPP trend < positive RESP trend negative NPP trend < negative RESP trend negative NPP trend, positive RESP trend Climatic Drivers of Trends in Land Processes

B. Mueller, ETH Zurich Satellite Evidence: Trends in Soil Moisture

Remarkable Similarity between NPP evolution from DGVMs

Global NPP explains most of the NEE variability

DGVM sink vs MODIS-NPP M Zhao

Alternative Upscaling Approaches Multidimensional flux patterns... Color: GPP... models to be cross-evaluated against. Reichstein remote sensing of CO 2 Temporal scale Spatial scale [km] hour day week month year decade century local global forest inventory plot CountriesEU plot/site tall tower obser- vatories Forest/soil inventories Eddy covariance towers Landsurface remote sensing

JJA Stippled areas > 90% of the models agree in the sign of the change Future Precipitation Changes (Summer Droughts?)

 Use set-up to produce global/regional annual C-budgets  Drought may be an important driver of the present-day trends in the land carbon cycle  Climate Models Project Summer Drought in Continental Regions  Drought may be an important driver of the future trends in the land carbon cycle  Critical to understand Ecosystem Response to Drought for future Earth System feedbacks Summary