DGVM runs for Trendy/RECCAP - globalcarbonproject.org · JULES, LPJ, LPJ-GUESS, O-CN, Orchidee, HyLand, SDGVM, NCAR-CLM4, GFDL/Princeton, VEGAS. Model simulations. The models were

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 CO2 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 ([email protected]) & Pierre Friedlingstein ([email protected]) http://dgvm.ceh.ac.uk

Goal: To investigate the trends in NEE over the period 1980-2009

Participating modelsJULES, LPJ, LPJ-GUESS, O-CN, Orchidee, HyLand, SDGVM, NCAR-CLM4, GFDL/Princeton, VEGAS

Model simulationsThe models were forced over the 1901-2009 period with changing CO2 , climate (CRU/NCEP) and land use:S1: CO2 onlyS2: CO2 and climateS3 (optional): CO2, climate and land use

Trendy Protocol

Land Source trendpositive NPP trend < positive RESP trendnegative NPP trend < negative RESP trendnegative NPP trend, positive RESP trend

Land Sink trendpositive NPP trend > positive RESP trendnegative NPP trend > negative RESP trend positive NPP trend, negative RESP trend

Trends in Land Processes

Land Sink trendpositive NPP trend > positive RESP trendnegative NPP trend > negative RESP trend positive NPP trend, negative RESP trend

Land Source trendpositive NPP trend < positive RESP trendnegative NPP trend < negative RESP trendnegative NPP trend, positive RESP trend

Climatic Drivers of Trends in Land Processes

B. Mueller, ETH Zurich

Satellite Evidence: Trends in Soil Moisture

0.95

1

1.05

1.1

1.15

1.2

1.25

1.3

1.35

1900 1920 1940 1960 1980 2000

Fraction

al NPP

 Change

Year

TRIF FNPP

LPJ FNPP

SDGVM FNPP

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...

0 2000LE [MJ m-2 yr-1]

0

2000

H [M

J m

-2 y

r-1]

Color: GPP

... models to be cross‐evaluated against.Reichstein

remote sensing

of CO2

Tempo

ral scale

Spatial scale [km]

hour

day

week

month

year

decade

century

local   0.1         1           10           100         1000   

10 000   global

forest

inventory

plot

Countries EUplot/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 changehttp://www.ipcc.ch/

Future Precipitation Changes (Summer Droughts?)

Use set-up to produce global/regional annual C-budgetsDrought may be an important driver of the present-day

trends in the land carbon cycleClimate Models Project Summer Drought in Continental

RegionsDrought may be an important driver of the future trends

in the land carbon cycleCritical to understand Ecosystem Response to Drought

for future Earth System feedbacks

Summary