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 trend positive NPP trend < positive RESP trend negative NPP trend < negative RESP trend negative 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 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
0.95
1
1.05
1.1
1.15
1.2
1.25
1.3
1.35
1900 1920 1940 1960 1980 2000
Frac
tiona
l NPP
Cha
nge
Year
TRIF FNPP
LPJ FNPP
SDGVM FNPP
Remarkable Similarity between NPP evolution from DGVMs
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
-4
-3
-2
-1
0
1
2
3
4
NEE_4DGVMs_anomaly
NPP_4DGVMs_anomaly
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 sensingof CO2
Tem
pora
l sca
le
Spatial scale [km]
hour
day
week
month
year
decade
century
local 0.1 1 10 100 1000 10 000 global
forestinventory
plot
Countries EUplot/site
talltowerobser-
vatories
Forest/soil inventories
Eddycovariance
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
