CIM-EARTH: a climate change policy modeling framework

The Community Integrated Model for Energy and Resource Trajectories for Humankind (CIM-EARTH) is an open-source modeling framework that allows for the easy specification of computable general equilibrium models, running the resulting simulations, and analyzing the results.  This framework is meant to increase both the quality and transparency of integrated assessment modeling by providing open source modeling tools that incorporate the most modern computational methods.  

Frameworks:

  • The AMPL-Source CIM-EARTH Framework (ASCEF) is a first version of the CIM-EARTH framework.
  • To facilitate adoption and the integration of advanced data processing and analysis services, we undertook an effort to move the implementation from AMPL to C++ and to adopt standard input and output formats. The result is what we call the Open-Source CIM-EARTH Framework (OSCEF).

Models:

  • CE-Trade: The trade model is used for studying the impacts on international trade of policies relevant to carbon mitigation. In particular, this model is used to assess carbon leakage and mechanisms such as border tax adjustments to reduce leakage.
  • CE-Energy: The energy model expands core capabilities of CIM-EARTH in order to represent the energy sector in ways more appropriate for policy analysis> The model disaggregated the representation of the U.S. electric power system to include renewable and non-renewable sources, peak and base-load power, and transmission.
  • CE-Bio: The bio model simulates the economics and lifecycle of biofuel production and use, including a detailed representation of the biofuels market, agriculture, and related services.
  • CE-Life: The distributional impacts model disaggregates the US consumers in the CE-Trade model by income and age, resulting in a model with 720 distinct consumers. 

Structure of the production functions in the baseline CE model:

 NOTE: Each node represents a production function. Nodes with vertical line inputs use Leontief functions; the other nodes are labeled with their elasticities of substitution. Table 2 shows the elasticities of substitution between domestic and imported commodities and the Armington international trade elasticities.

NOTE: Each node represents a production function. Nodes with vertical line inputs use Leontief functions; the other nodes are labeled with their elasticities of substitution. Table 2 shows the elasticities of substitution between domestic and imported commodities and the Armington international trade elasticities.


Publications

Climate Emulator

To characterize climate change impacts in long range simulations using economic and Integrated Assessment (IA) models, we are also developing statistical emulators (i.e. response functions) that map from inputs (e.g. irrigation and fertilizer application) and atmospheric conditions (e.g. atmospheric CO2 and regional temperature and precipitation measures) to agricultural productivity measures at a variety of scales. We are developing a number of aggregation and scaling methodologies to translate high-resolution gridded products to decision-relevant environmental and political scales (e.g. county, watershed, or national boundaries). These methodologies must be versatile enough to map vulnerability, impact, and adaptation (VIA) measures to arbitrary spatial scales, while consistently tracking ensemble uncertainty information throughout.

The emulation tool provides statistical representations of the behaviors of a number of general circulation models (GCMs) from different research groups. The emulator is designed to mimic how the larger models would have responded, and can provide projections of regional temperatures for any user-chosen scenario of future CO2 concentrations.

The emulator is ‘trained’ on publicly-available model simulations of scenarios specified for the IPCC 5th Assessment Report. Users can explore emulated model responses to three IPCC scenarios (RCPs 2.6, 4.5, and 8.5) and one scenario of continuous exponential growth in CO2. Users can also upload their own CO2 scenarios.

 
 Projecting temperature change

Projecting temperature change

 Comparing regions

Comparing regions

 

SCREENSHOTS OF THE CLIMATE EMULATOR TOOL


Statistical Emulation

Statistical emulation of climate model output involves using a ‘training set’ of simulations for each model to fit the parameters of a simple statistical model that describes the climate response to changing CO2 concentrations. In the tool here, each region is fit separately.

 Radiative forcing associated with the different RCP scenarios. RCP 8.5 represents 'business-as-usual'.  Click here for further description

Radiative forcing associated with the different RCP scenarios. RCP 8.5 represents 'business-as-usual'. Click here for further description

The training set used is archived GCM simulations made as part of the Coupled Model Intercomparison Project 5 (CMIP5), and archived at the Earth Systems Grid database (available from various sites, including here or here). The simulations use CO2 scenarios developed for the Intergovernmental Panel on Climate Change 5th Assessment Report. These ‘Representative Concentration Pathways’, or RCPs, describe the CO2 concentrations associated with various potential emissions scenarios (see graphic on the left). Where available, we use RCP 4.5, RCP 6.0, and RCP 8.5 as the training set. For some models that did not archive all scenarios, we use only RCP 4.5 and RCP 8.5.

The statistical model used for emulation is described in detail in Castruccio et al 2013