Download Temperature feedbacks to the carbon cycle in - Mistra

von Below, Newsletter 2:10, December 2010
Temperature feedbacks to the carbon cycle in climateeconomy models
David von Below, IIES, Mistra-SWECIA Project 2
A paper on how the results with a well-known climate-economy model change when feedbacks
from rising temperatures to the carbon-cycle dynamics are taken into account was recently
presented at the 9th NCCR Summer School (29 August – 3 September 2010 in Grindelwald,
Switzerland). The paper was titled “Temperature Feedbacks to the Carbon Cycle in ClimateEconomy Models”, and has resulted from a collaboration with Anders Ahlström (MistraSWECIA Project 3).
Climate-economy models
Climate-economy models are models of the world economy and the global natural system, and
the links between the two. The economic system concerns how goods and services are produced
in the world economy, and how the associated consumption of fossil fuels leads to emissions of
carbon dioxide (CO2). These emissions end up in the atmosphere. A large proportion of emitted
CO2 is taken up by the oceans and by the terrestrial biosphere (i.e. vegetation). The processes by
which atmospheric carbon dioxide interacts with the biosphere and the oceans are referred to
collectively as the carbon cycle. The CO2 that remains in the atmosphere affects the Earth's
energy balance: the greenhouse effect is strengthened, and the global temperature increases,
leading to yet other subsequent changes in the climate system. This then feeds back to the
economic system through climate impacts affecting human societies through sea-level rise, health
impacts, changes to agricultural productivity, etc.
The carbon cycle
The potential temperature dependence of the carbon cycle is the focus of this study. It is believed
that oceans as well as vegetation will be less prone to take up carbon as atmospheric temperatures
rise, but this effect is not captured well by the very simple formulation for the carbon cycle in
many climate-economy models, e.g. DICE, which is the climate-economy model used for this
study.
Using a Dynamic Vegetation Model...
We have augmented the carbon cycle component in DICE in a way that it captures how carbon
uptake by global vegetation becomes less efficient as climate change causes temperatures to rise.
We estimate this temperature response by using output from a dynamic vegetation model (LPJ–
GUESS), which is run for different scenarios for what the future climate will look like. Running
LPJ-GUESS involves specifying how atmospheric CO2 evolves over time, and also how various
climate aspects are affected across the Earth (e.g. temperature change, rainfall, etc.).
1
von Below, Newsletter 2:10, December 2010
Figure 1
Figure 1 illustrates the effect in question. Two runs with the dynamic vegetation model are
shown, in red and green respectively. For both runs, the same amount of CO2 emissions are
assumed over time (the SRES A2 scenario). The circles represent annual global mean temperature
from climate models run over the same time span and the same CO2 emissions. As the figure
shows, the climate model represented by the red circles has a stronger temperature response for
the same CO2 emissions. Using the CO2 data and the climate model data we then run the
vegetation model to see how much carbon is taken up by the biosphere globally, i.e. how much
biomass is produced (the lines in the figure). We see that as temperature goes up quite a lot (red),
less carbon gets transformed into biomass. In the case that temperature increases less (green), the
biosphere takes up more carbon.
...to extend the carbon cycle in DICE
We use this relationship between the global mean temperature and carbon uptake by the
biosphere to extend the carbon cycle description in the climate-economy model DICE. In order
to see how the original and the extended carbon cycle descriptions differ, we run DICE with a
range of values for the climate-sensitivity parameter. This parameter measures how much the
global temperature will go up if the amount of carbon in the atmosphere is doubled, relative to
before the industrial revolution. It is believed that this parameter is around 3, the uncertainty
range spanning from somewhat lower to higher values.
2
von Below, Newsletter 2:10, December 2010
Comparing the extended DICE model to the original formulation
The difference between the carbon-cycle formulations is visualised in Figure 2. The black curve
shows the amount of carbon in the atmosphere over time with the original carbon-cycle
formulation in DICE. This curve is the same no matter what value of climate sensitivity is used,
since the carbon cycle is not affected by changing temperatures in the original model. The
coloured areas show the development of atmospheric carbon, with the same CO2 emissions as
underline the black curve, but now with the extended carbon cycle depiction. Here climate
sensitivity matters: higher climate sensitivity leads to higher temperatures for the same CO2
emissions. The lower edge of the darkest green represents a climate sensitivity of 1 degree
Centigrade, and each colour change corresponds to a climate sensitivity of one degree higher.
The coloured fan thus represents atmospheric carbon for climate sensitivies ranging from 1 to
10.
Taking into account temperature feedbacks to the carbon cycle matters, especially if also
considering the substantial uncertainty about climate sensitivity. In addition, we see that once we
stop emitting CO2, atmospheric carbon falls slower if we take these temperature feedbacks to the
carbon cycle into account (here around 2170 and onwards). This is true for any value of climate
sensitivity. Possible climate impacts on the carbon cycle has also policy implications, e.g. the
optimal carbon tax suggested by the DICE model. In general, when considering temperature
effects on the carbon cycle, optimal carbon taxes are higher than in the original model (and
optimal consumption of fossil fuels correspondingly lower). How much higher depends on how
heavily we discount the future, and how climate change will damage human society.
Figure 2
3