coupling the land use decisions and carbon cycles of earth ... · pdf file• the iesm...
TRANSCRIPT
DOE BER Climate Modeling PI Meeting, Potomac, Maryland, May 12-14, 2014 Funding for this study was provided by the US Department of Energy, BER Program. Contract # DE-AC02-05CH11231. This study used NERSC resources, and additional support was provided by NASA.
SUMMARY
METHODS
DISCUSSION
RESULTS
Coupling the land use decisions and carbon cycles of earth system and integrated assessment models
iESM and IA Boutique Di Vittorio, AV1, B Bond-Lamberty2, LP Chini3, J Mao4, K Calvin2, A Jones1, X Shi4, P Patel2, J Truesdale5, A Craig5, WD Collins1, J Edmonds2, G Hurtt3, A Thomson2, P Thornton4, Y Zhou2
1Lawrence Berkeley National Laboratory (LBNL); 2Joint Global Change Research Institute, Pacific Northwest National Laboratory; 3University of Maryland; 4Climate Change Science Institute, Oak Ridge National Laboratory; 5Independent Contractor with LBNL
• The integrated Earth System Model (iESM) is the first fully coupled model capable of examining two-way interactions between human and earth system processes
• Feedbacks of climate on terrestrial carbon are successfully passed from CESM to GCAM
• Net Primary Productivity (NPP) and Heterotrophic Respiration (HR) are effective proxies
• The forward coupling from GCAM to CESM, which is based on CMIP5, contains dramatic inconsistencies in land cover and land use
• Only 22% of RCP4.5 afforestation by 2100 was simulated by CESM for CMIP5
• We have significantly improved the iESM land cover consistency through modification of the Land Use Translator (LUT)
• The iESM simulated RCP4.5 afforestation increased from 17% to 66% of that prescribed by GCAM through 2040
• This increases vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040
• Further work is needed to implement consistent land cover and land use representations among IAMs and ESMs
• This will ensure that ESMs are simulating the scenarios prescribed by IAMs
Global Change Assessment Model (GCAM)
Global Land-use Model (GLM)
Land Use Translator
Community Land Model(CLM)
NPP
HR
16 plant functional types (0.5° maps) aggregated to AEZand used to modify
C densities
Annual land use area, forest area,
and harvest C
Crop, pasture, primary, secondary, and harvest area (0.5° maps)
PFT-specific mapsForest harvest
Make Surface Data
Resolution change
Get reference year PFT data
Set current year harvest data
Get current year crop and pasture data
Crops increased?
Pasture increased?
Increase capped by amount of available land, including bare
ground
Trees PFTs replace decreased crop PFT
Increased crop PFT replaces tree PFTs until gone, then
herbaceous PFTs until gone, then bare ground PFT if
necessary
Tree PFTs replace decreased herbaceous PFTs
Increase capped by amount of previous year tree and shrub
PFTs
Increased grass PFTs replace tree PFTs until gone, then
shrub PFTs until gone
no
yes
no
yes
20%
40%
60%
80%
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0 1 2 3 4 5LUC effect (1=none)
Cells
subje
ct to
LUC Climate
effect error●
●
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0%100%200%300%
• Lack of consistency across models/components precludes robust ESM simulations of IAM generated scenarios
• Afforestation is important for achieving the RCP4.5 climate stabilization target
• Similar land cover inconsistencies exist in the CMIP5 archive
• Land cover mismatch significantly affects the global carbon cycle for RCP4.5
• Linear extrapolation to include all prescribed afforestation by 2100 gives increases in vegetation carbon of 100 PgC and decreases in atmospheric CO2 of 40 ppmv
• Land cover and land use need to be harmonized among ESMs and IAMs to provide robust comparisons and simulations of scenarios
• IAM to ESM coupling is still incomplete, even after CMIP5 and iESM efforts to develop this coupling
• ESM to IAM coupling is still limited by inconsistent carbon cycle representations (e.g. potential vs. actual carbon stock) and ESM land change artifacts
No land cover information!
Figure 1. iESM land coupling
Figure 2. New iESM Land Use Translator (LUT)
Figure 3. NPP is a good proxy for potential carbon stock
Figure 4. Efficacy of method to filter out land change artifacts from climate feedback signal
CMIP5 iESM Climate feedbacks
Filtered to exclude land change artifacts
Trees replace crops and pasture
iESM pixels
removed
14
15
45
50
55
60
30
32
34
36
38
a) croplandb) forest
c) pasture
2010 2020 2030 2040Year
Area
(milli
on k
m^2
) Simulation● CLM−NEWLUT
CLM−OLDLUTGCAM−NEWLUTGCAM−OLDLUTGLM−OLDLUT
Global area42
46
50
22.5
25.0
27.5
30.0
32.5
35.0
a) forestb) pasture
2025 2050 2075 2100Year
Area
(milli
on k
m^2
) Legend● RCP4.5
GLMCLM forest PFTsCLM shrub and grass PFTsCLM grass PFTs
Global area
42
46
50
22.5
25.0
27.5
30.0
32.5
35.0
a) forestb) pasture
2025 2050 2075 2100Year
Area
(milli
on k
m^2
) Legend● RCP4.5
GLMCLM forest PFTsCLM shrub and grass PFTsCLM grass PFTs
Global area
14
15
45
50
55
60
30
32
34
36
38
a) croplandb) forest
c) pasture
2010 2020 2030 2040Year
Area
(milli
on k
m^2
) Simulation● CLM−NEWLUT
CLM−OLDLUTGCAM−NEWLUTGCAM−OLDLUTGLM−OLDLUT
Global area
Figure 5. CMIP5 Figure 6. iESM
Figure 7. Difference in Net Ecosystem Exchange (NEE)
(NEWLUT – OLDLUT)
Increased land carbon uptake due to additional
afforestation
22%
17%
66%
shrub+grass
94%
Initial (2005-2009) NPP, MgC ha-1 yr-1
Fina
l (20
90-2
094)
bio
mas
s, M
gC h
a-1
Cel
ls s
ubje
ct to
land
cha
nge
Land change effect (1 = none)