Global Carbon Climate Coupling Questions The lab exericise need to answer two parts questions, Assessing Impacts of Emissions and Exploring Terrestrial Fee

Global Carbon Climate Coupling Questions The lab exericise need to answer two parts questions, Assessing Impacts of Emissions and Exploring Terrestrial Feedbacks of Global Carbon-Climate Coupling.This lab exercise employs a nonlinear box model simulating the global carbon budget and its response to various forcings based on Raupach et al. (2011, 2013). It is applied to examine: how greenhouse gas emissions influence global mean temperature, and how terrestrial and oceanic feedbacks mediate that relationship. The model represents the coupled evolution of the global carbon cycle and climate system (temperature state) responding to GHG emissions, CO2 fertilization of terrestrial productivity and climate change effects on terrestrial productivity and respiration. Please confirm that you can complete this task before bidding. Lab 9: Global Carbon-Climate Coupling
1. Introduction
Anthropogenic emissions of carbon dioxide and other greenhouse gases, mainly from fossil fuel
combustion, cement production, and land use change (deforestation), are accumulating in the
atmosphere causing global warming and other changes to the climate system. Presently, only
about half of the CO2 emitted by human activities stays in the atmosphere. The remainder is
being absorbed by ocean and land uptake in roughly equal proportion. However, these carbon
sequestration mechanisms are expected to slow in the future, and are being opposed by the
warming climate.
This lab exercise employs a nonlinear box model simulating the global carbon budget and its
response to various forcings based on Raupach et al. (2011, 2013). It is applied to examine:
• how greenhouse gas emissions influence global mean temperature, and
• how terrestrial and oceanic feedbacks mediate that relationship.
The model represents the coupled evolution of the global carbon cycle and climate system
(temperature state) responding to GHG emissions, CO2 fertilization of terrestrial productivity and
climate change effects on terrestrial productivity and respiration.
1.1 Model Description and Forcings
The model’s state variables are (a) carbon stores in the atmosphere, in two land pools with
different storage rates (assigned to be notionally representative of forest and grassland ecosystem
types), and in a set of ocean mixed layer pools with different rates of turnover in exchange with
the deep ocean; (b) atmospheric concentrations of non-CO2 greenhouse gases; and (d) the global
mean annual temperature perturbation from a pre-industrial state (see Figure 1).
Land pools respond to inputs from net primary productivity, releases at a temperature-dependent
turnover rate representing heterotrophic respiration, and the net flux from land use change. The
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ocean-air CO2 flux is based on an air-ocean gas exchange rate applied to the gradient of the
partial pressure of CO2, pCO2, between the ocean mixed layer and the atmosphere. Ocean mixed
layer concentration is treated as a function of DIC and temperature effects on solubility. Ocean
inputs are allocated to four mixed layer pools, each with their own rate of transfer to the deep
ocean based on phenomenological equations representing a pulse response function that provides
a close fit to results from advanced ocean models.
Fossil fuel emissions of CO2, emissions of non-CO2 greenhouse gases (CFCs and N2O), aerosol
emissions, and net land use change emissions of CO2 are imposed based on historical estimates
for the period 1850 to 2010 followed by Representative Concentration Pathway (RCP) scenarios
out to 2100 as used by the Intergovernmental Panel on Climate Change in its Fifth Assessment
Report (IPCC AR5).
The perturbation to atmospheric temperature is simulated as a temporally-varying fractional
response to a unit step in radiative forcing relative to the start of the industrial era, applied with
the equilibrium climate sensitivity (λ, K W-1 m2). The weights and rates of the climate step
response function were derived from a fit to results from the HadCM3 model.
A number of parameterizations have been modified to improve consistency with published
estimates, as described below. This includes adjustments to the CO2 sensitivity of terrestrial net
primary productivity (NPP), the temperature sensitivity of heterotrophic respiration, and the
equilibrium climate sensitivity. The following new fluxes and processes are also included:
release of permafrost carbon prescribed according to Schneider von Deimling et al. (2012);
temperature sensitivity of terrestrial NPP.
1.2 New Parameterizations of Feedbacks and Climate Sensitivity
CO2 fertilization of terrestrial NPP is imposed with the familiar logarithmic biotic growth factor
(β-factor) approach (Bacastow & Keeling 1973; Friedlingstein et al. 1995) which expresses the
response as a function of the relative increase in [CO2] according to:
f NPP = f NPP 0 (1 +  ln( C A / C A0 ))
where CA is the time-varying atmospheric concentration of CO2 and the subscript 0 refers to
initial conditions (forcing time, t = 0). We adopt a normal distribution, N(µ, σ), for β of N(0.60,
0.15), reduced relative to the original value of 0.8 to mirror results from enrichment experiments
(Norby et al. 2005).
The effect of temperature on heterotrophic respiration is represented with the well-known q10
parameter describing the proportional increase in rate for a 10K warming, as:
T − T0
ln( k Bi ) = ln( k Bi 0 ) +
ln( q10 )
10
where kBi is the turnover rate for the ith carbon pool. The original value of q10 of 2.0 is typical for
many models but has been adjusted in part based on the recent assessment of FLUXNET data by
Mahecha et al. (2010), which suggested 1.4 ± 0.1. We adopt a normal distribution of N(1.7, 0.2).
The effect of temperature on the rate of terrestrial NPP was not included in the original model
but has been added here as:
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f NPP = f NPP 0 (1 +  ln( CA / CA0 )) +  NPP (T − T0 )
where γNPP (Pg C K-1) is inferred from Friedlingstein et al. (2006) (see Figure 3b therein) and
imposed as N(-2, 1.5).
Release of permafrost carbon as CO2 and CH4 is prescribed according to results presented in
Schneider von Deimling et al. (2012). Their results include releases for each of the four
Representative Concentration Pathways (RCPs).
We adopt the original model’s equilibrium climate sensitivity (λ = 1.235 K W-1 m2) to
incorporate long time-scale (centuries) responses in the earth system. Around this mean we
assume a lognormal probability distribution for λ because of sizeable uncertainty in this
parameter (Knutti et al. 2008). The wide distribution is asymmetric with a positive skew so we
adopted a lnN (6.006, 0.169). We note that this model’s equilibrium climate sensitivity is on the
upper end of synthesis findings reported by providing Knutti et al. (2008) who noted a likely
value of about 0.8 K W-1 m2 but with a wide range spanning 0.54 to 1.22 K W-1 m2, or 2 to 4.5 K
for a doubling of CO2 over pre-industrial (RF = 3.7 W m-2).
1.3 Emissions Scenarios
The model is forced with CO2 emissions from fossil fuels and other industrial processes, land use
change, and anthropogenic emissions of CH4, N2O, CFC-11, and CFC-12. Historical (1850 to
2005) fluxes are prescribed from data with fFOSS and fLUC provided by the Carbon Dioxide
Information and Analysis Center (CDIAC) (Boden et al. 2013; Houghton 2008), and non-CO2
GHGs from the RCP database (Meinshausen et al., 2011; IIASA, 2012).
Future forcings are prescribed based on the RCPs (Meinshausen et al. 2011; IIASA, 2012) out to
2100. The RCPs are named according to the approximate radiative forcing (W m-2) that they
impose by the year 2100, with a baseline present day trajectory toward RCP 8.5 and a most
extreme case of optimism with RCP 2.6 which assumes a rapid reduction in emissions plus largescale implementation of anthropogenic sequestration by carbon capture and storage or some
other technology. After 2100, fFOSS and fLUC and CFC fluxes are assumed to decrease linearly to
zero in 2200 while fCH4 and fN2O are held constant at the value in 2100. Natural emissions of CH4
and N2O are treated as time-independent and set to provide equilibrium with pre-industrial
concentrations. Aerosol forcing is modelled as proportional to total CO2 emissions from fFOSS
with a declining rate of aerosol emission with combustion representing transition to cleaner
combustion.
References
Bacastow RB, Keeling CD (1979) Models to predict future atmospheric CO2 concentrations, in: Workshop on the Global Effects of Carbon
Dioxide from Fossil Fuels, edited by: Elliott WP and Machta L, United States Department of Energy, Washington, D.C., 72-90.
Boden TA, Marland G, Andres RJ (2013) Global, Regional, and Naational Fossil-Fuel CO2 Emissions. Carbon Dioxide Information Analysis
Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. doi 10.334/CDIAC/00001_V2013.
Friedlingstein P, Fung I, Holland E, John J, Brasseur G, Erickson D, Schimel D (1995) On the contribution of CO2 fertilization to the missing
biospheric sink, Global Biogeochemical Cycles, 9(4), 541-556.
Houghton RA (2008) Carbon Flux to the Atmospher from Land-Use Changes: 1850-2005. In TRENDS: A Compendium of Data on Global
Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn.,
U.S.A.
IIASA: RCP Database, version 2.0, International Institute for Applied Systems Analysis, Laxenburg, Austria, February 2015.
IPCC: Climate Change 2013: Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis Contribution of Working Group
I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, TF, Qin D, Plattner G-K, Tignor M, Allen
SK, Boschung J, Naules A, Xia Y, Bex V, and Midgley PM (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA.
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Knutti R, Hegerl GC (2008) The equilibrium sensitivity of the Earth’s temperature to radiation changes, Nature Geoscience, 1, 735-743.
Mahecha MD, Reichstein M, Carvalhais N, et al. (2010) Global convergence in the temperature sensitivity of respiration at ecosystem level,
Science, 329, 838, doi: 10.1126/science.1189587.
Meinshausen M, Smith SJ, Calvin K, Daniel JS, Kainuma MLT, Lamarque JF, Matsumoto K, Montzka SA, Raper SCB, Riahi K, Thomson A,
Velders GJM, van Vuren DPP (2011) The RCP greenhouse gas concentrations and their extensions from 1765 to 2300, Climate Change,
109, 213-241.
Raupach MR, Canadell JG, Ciais P, Friedlingstein P, Rayner PJ, Trudinger CM (2011) The relationship between peak warming and cumulative
CO2 emissions, and its use to quantify vulnerabilities in the carbon-climate-human system, Tellus, 63B, 145-164.
Raupach MR (2013) The exponential eigenmodes of the carbon-climate system, and their implications for ratios of responses to forcings, Earth
Syst. Dyn., 4, 31-49.
Schneider von Deimling T, Meinshausen M, Levermann A, Huber V, Frieler K, Lawrence DM, Brovkin V (2012) Estimating the near-surface
permafrost-carbon feedback on global warming, Biogeosciences, 9, 649-665.
2. Assessing Impacts of Emissions
2.1 Historical
2.1.1 The Role of Fossil Fuel versus Land Use Change Emissions of CO2
Figure 1
Figure 2
Figure 3
Figure 4
1. How much of the warming by 1950 can be attributed to LUC emissions and how much to the
net effect of all other emissions? Answer in [degrees C]. (see Figure 1) (Note: The net effect of all
other emissions includes warming from fossil CO2, CH4, N2O, CFCs, as well as cooling from aerosols)
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2. How much of the warming by 2010 can be attributed to LUC emissions and how much to the
net effect of all other emissions? Answer in [degrees C]. (see Figure 1)
3. How much of the cumulative emission by 1950 was derived from net LUC and how much
from fossil sources? Answer in [Pg C]. (see Figure 3) (Note: Gross LUC emissions have been far larger
than net LUC emissions but gross regrowth of forests has re-sequestered roughly half of that emitted.)
4. How much of the cumulative emission by 2010 was derived from net LUC and how much
from fossil sources? Answer in [Pg C]. (see Figure 3 showing results from the simulation with
LUC)
5. How has NPP responded to the two scenarios (with LUC and without LUC) and why? (see
Figure 1)
6. Why does NPP differ between the case with LUC and the case without LUC? (see Figure 1)
7. How has forest carbon responded to the two scenarios and why does the response differ? (see
Figure 1)
8. How has ocean carbon responded to fossil and LUC emissions and why? (see Figure 2)
9. How has the biosphere-atmosphere flux responded to the two scenarios and why do they
differ? (see Figure 2) (Note that the term Fba, the biosphere-atmosphere flux, does not itself include the LUC
emissions though the magnitude of Fba is still influenced by whether or not the atmosphere is loaded with LUC
emissions.)
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10. What fraction of the total emissions (fossil plus net LUC) stays in the atmosphere, ends up in
the oceans, and ends up in the land stores? (see Figure 4 showing results from the simulation
with LUC)
11. Are all of the emissions (Fossil + LUC + permafrost) accounted for by uptake in the ocean,
land biosphere, and atmosphere? Explain what confirms this. (see Figure 3)
3. Exploring Terrestrial Feedbacks
This set of simulations assesses the strength of three different feedbacks from the land surface:
CO2 fertilization of terrestrial productivity, warming effect on heterotrophic respiration, and
warming effect on terrestrial productivity.
Figure 1
Figure 2
Figure 3
Figure 4
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Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
24. Describe how the effect of each feedback is determined with the model experiments. What
procedure allows us to assess each independent effect?
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25. What does the CO2 fertilization effect (“CO2 Fert”) do to atmospheric CO2 concentration
(Ca) in the year 2100 and why? Report the magnitude of the effect in [ppm] for the different
scenarios. (Note: 2.13 Pg C = 1 ppm)
26. What does the CO2 fertilization effect (“CO2 Fert”) do to the forest carbon stock and why?
27. Why does the strength of the CO2 fertilization effect on atmospheric CO2 vary between the
RCPs?
28. What does the CO2 fertilization effect do to atmospheric temperature?
29. Does the effect of CO2 fertilization on atmospheric temperature vary across the scenarios?
Why or why not?
30. What do the climate warming effects on respiration (“q10”) and NPP (“γnpp”) do to
atmospheric CO2 concentration?
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31. Which of the two effects is stronger, q10 or γnpp?
32. Summarize the combined effects of all three land feedbacks (CO2 fertilization and both
climate warming effects) on atmospheric temperature.
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Appendix I. Radiative Forcings for 1750 to 2011 by Emissions and Drivers from the IPCC
AR5 WG1 Report
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