Preparing the Software Environment
You first need to connect your Julia installation with the central Mimi registry of Mimi models. This central registry is like a catalogue of models that use Mimi that is maintained by the Mimi project. To add this registry, run the following command at the julia package REPL:
pkg> registry add https://github.com/mimiframework/MimiRegistry.git
You only need to run this command once on a computer. The next step is to install MimiDICE013.jl itself. You need to run the following command at the julia package REPL:
pkg> add MimiDICE2013
You probably also want to install the Mimi package into your julia environment, so that you can use some of the tools in there:
pkg> add Mimi
Running the model
The model uses the Mimi framework and it is highly recommended to read the Mimi documentation first to understand the code structure. For starter code on running the model just once, see the code in the file
The basic way to access a copy of the default MimiDICE2013 model is the following:
using MimiDICE2013 m = MimiDICE2013.get_model() run(m)
Calculating the Social Cost of Carbon
Here is an example of computing the social cost of carbon with MimiDICE2013. Note that the units of the returned value are dollars $/ton CO2.
using Mimi using MimiDICE2013 # Get the social cost of carbon in year 2020 from the default MimiDICE2013 model: scc = MimiDICE2013.compute_scc(year = 2020) # You can also compute the SCC from a modified version of a MimiDICE2013 model: m = MimiDICE2013.get_model() # Get the default version of the MimiDICE2013 model update_param!(m, :t2xco2, 5) # Try a higher climate sensitivity value scc = MimiDICE2013.compute_scc(m, year=2020) # compute the scc from the modified model by passing it as the first argument to compute_scc
The first argument to the
compute_scc function is a MimiDICE2013 model, and it is an optional argument. If no model is provided, the default MimiDICE2013 model will be used.
There are also other keyword arguments available to
compute_scc. Note that the user must specify a
year for the SCC calculation, but the rest of the keyword arguments have default values.
compute_scc(m = get_model(), # if no model provided, will use the default MimiDICE2013 model year = nothing, # user must specify an emission year for the SCC calculation last_year = 2305, # the last year to run and use for the SCC calculation. Default is the last year of the time dimension, 2305. prtp = 0.03, # pure rate of time preference parameter used for constant discounting )
There is an additional function for computing the SCC that also returns the MarginalModel that was used to compute it. It returns these two values as a NamedTuple of the form (scc=scc, mm=mm). The same keyword arguments from the
compute_scc function are available for the
compute_scc_mm function. Example:
using Mimi using MimiDICE2013 result = MimiDICE2013.compute_scc_mm(year=2030, last_year=2300, prtp=0.025) result.scc # returns the computed SCC value result.mm # returns the Mimi MarginalModel marginal_temp = result.mm[:climatedynamics, :TATM] # marginal results from the marginal model can be accessed like this
Pulse Size Details
By default, MimiDICE2013 will calculate the SCC using a marginal emissions pulse of 5 GtCO2 spread over five years, or 1 GtCO2 per year for five years. The SCC will always be returned in $ per ton CO2 since is normalized by this pulse size. This choice of pulse size and duration is a decision made based on experiments with stability of results and moving from continuous to discretized equations, and can be found described further in the literature around DICE.
For a deeper dive into the machinery of this function, see the forum conversation here, which is focused on MimiFUND but has similar internal machinery to MimiDICE2013, and the docstrings in