Simulations of carbon transport in CCM3: uncertainties in C sinks due to interannual variability and model resolution
James Orr
(LSCE/CEA-CNRS and IPSL, France)
Co-authors: B. Govindasamy & P. Duffy (LLNL/DOE), and J. A. Taylor (ANL/DOE)
Funding: LLNL LDRD et LLNL URP sabbatical program
TransCom WorkshopJena, Germany
12—15 May 2003
Resolution:~ 50 km
CCM3: T239
Resolution:~ 300 km
CCM3: T42
*How to measure model improvement?
Quantitative improvement for T170
Key relationship:
*Taylor, K. E., J. Geophys. Res., 106, D7, 7183-7192, 2001
Duffy et al.., Climate Dyn.., submitted, 2003
TRANSCOM-1 Models
*Law et al. (1996, GBC)
Fossil Emissions Scenario (TRANSCOM3)
*Gurney et al. (2002, Final TRANSCOM3 Report)
Neutral Biosphere Scenario(TRANSCOM)
Transcom1 (1996)Transcom3 (2002)
*Gurney et al. (2002, Final TRANSCOM3 Report) *Law et al. (1996, GBC)
Rectifier correlated with N.H. Land Sink
*Gurney et al (2002): Rectifier is the major uncertainty regarding the magnitude of the Northern Hemisphere C sink
-3.5-3.0-2.5-2.0-1.5-1.0-0.50.0
-0.5 0.0 0.5 1.0 1.5
Interhemispheric in rect response (ppmv)
Infe
rred
N. H
em L
and
F
lux
(Gt
C/y
ear) 16 different annual mean
model responses to purely seasonal forcing
Interhemispheric difference in Rectifier (ppmv)
N. H
. La
nd
Sin
k (P
g C
yr1 )
*
Objectives of this study
1. Test sensitivity of rectifier to horizontal resolution
2. Investigate interannual variability of rectifier in CCM3 model.
Simulations
TRANSCOM-3 Boundary Contidtions:• Fossil Emissions: Andres• Ocean : observed air-sea flux (Takahashi et al., 1999)
• “Neutral Biosphere” (or Rectifier from CASA model)
Other:• Rn-222
Some model details:
•18 Vertical levels•Climatological SST forcing•Three-year spin-up
•Change horizontal resolution only
Simulation Grid Cells Size Approx Grid Size
Years of Simulation
T21 64x32 5.6° 600 km 27
T31 96x48 3.8° 450 km 21
T42 128x64 2.8° 300 km 23
T63 192x96 1.9° 225 km 16
T85 256x128 1.4° 150 km 21
T170 512x256 0.7° 75 km In Progress
T239 720x360 0.5° 50 km
Taylor Diagram: Precipitation (Effect of Resolution)
Resolution effect: 20-year means
Resolution effect: 20-year means
Rectifier in CCM3 (T42) has large interannual variability
*Normalized to South Pole
Variability = f(resolution)
T42T31T21
T85T63
Interannual Variability: Zonal Mean (T42)
TRANSCOM-3 Stations
Interannual Variability: TransCom3 Stations (T42)
Spatial distribution of interannual rectifier?
Mean
Std. Dev.
Range
Rectifier:
T42 (1983-2001)
Causes of interannual variability in the rectifier
Mechanisms invoked to explain seasonal rectifier:• Changes in local PBL height (Denning, 1995)• Changes in wind direction (Taguchi, 1996)• Changes in wind speed/”mixing volume” (Taylor,
1998)• Meridional transport
– Pearman and Hyson (1980)
– Keeling et al. (1989)
Interannual Varib. of PBL Height (m): CCM3 T42 Annual Means (1983—
2002)
Winter differences drive interannual variability
R2 for winter monthly anomalies of rectifier vs. surface wind
speed(arrows: climatological winter surface
winds)
“Neutral Biosphere” : seasonal boundary condition (mol C cm-2
yr-1)
*TRANSCOM3 Boundary Condition (also used in this study)
Maximum in Rectifier occurs North of maximum in N.B.
forcing
Rectification: Horizontal Control
Source Sink
Source+Sink Source-Sink
*Taguchi (1996, JGR, 101, 15099-15109)
Seasonal Prevailing Surface Winds:
CCM3, T42 (1983—2002)NE: Region of Maximum
Interannual Rectifier
SW: Region of High Corr.
(wind, pbl, rectifier)
Interannual variability in MBL pCO2
(Globalview Zonal Mean, Detrended 1979-2002)
Interannual variability in MBL pCO2
(Globalview Zonal Mean, Detrended 1979-2002)
Conclusions:
• Resolution effect: differences but no clear tendency– Systematic bias due to insufficient resolution? – Interannual variability increases with model resolution – Need long high-resolution simulations
• Interannual variability of the rectifier: large in CCM3– Importance of interannual variability of horizontal transport– Comparable to the range of TRANSCOM models– Comparable to observed interannual variability of pCO2 in MBL– Atm. CO2 Growth rate = f(SMS, Interannual Var. in Transport)– Interannual variability in transport likely to differ among models
• Inversions with AGCM not appropriate• Effect of Nudging?• Different reanalysis products; different models?
• Call for new efforts to constrain effect of interannual variability in atmospheric transport on inverse estimates of C sources and sinks
