Tutorial 1: Orienting inside a “Climate Solution” Simulator#
Week 2, Day 2: The Socioeconomics of Climate Change
Content creators: Maximilian Puelma Touzel, Paul Heubel
Content reviewers: Mujeeb Abdulfatai, Nkongho Ayuketang Arreyndip, Jeffrey N. A. Aryee, Jenna Pearson, Abel Shibu, Ohad Zivan
Content editors: Paul Heubel, Jenna Pearson, Chi Zhang, Ohad Zivan
Production editors: Wesley Banfield, Paul Heubel, Jenna Pearson, Konstantine Tsafatinos, Chi Zhang, Ohad Zivan
Our 2024 Sponsors: CMIP, NFDI4Earth
Tutorial objectives#
Estimated timing of tutorial: 30 minutes
During the first week of the course, you applied computational tools to climate data (measurements, proxies, and model output) to characterize past, present, and future climate. During day one of this second week (W2D1), you began to explore climate model data from Earth System Model (ESM) simulations conducted for the recent Climate Model Intercomparison Project (CMIP6) that are presented in the report from the Intergovernmental Panel on Climate Change (IPCC). However, the dominant source of uncertainty in those projections arises from how human society responds: e.g. how our emissions reduction and renewable energy technologies develop, how coherent our global politics are, how our consumption grows (cf. Rogelj et al. (2018)(Global Warming of 1.5°C. An IPCC Special Report […])). For these reasons, in addition to understanding the physical basis of the climate variations projected by these models, it’s also important to assess the current and future socioeconomic impact of climate change and what aspects of human activity are driving emissions.
This day’s tutorials focus on the socioeconomic projections regarding the future of climate change and are centered around the Shared Socioeconomic Pathways (SSP) framework used by the IPCC. However, in this first tutorial, you will use the En-ROADS simulator to get some intuition about different socioeconomic variables and their consequences for climate. Additionally, you will analyze potential economic and population scenarios to learn about the complex and intertwined dynamics of socioeconomic variables, as well as how this model informs modern-day climate challenges.
Unlike the rest of the days of this course, this day will be highly conceptual and discussion-driven, and focus much less on analyzing datasets.
In this tutorial, you will:
Get familiar with the interface of the simulator named En-ROADS
Explore the impact of different growth variables on the temperature increase by 2100 projected from the En-ROADS model.
Understand why it is necessary to implement various actions against climate change, not a single one.
Explore the assumptions and limitations of this model
# import
import matplotlib.pyplot as plt
Install and import feedback gadget#
Show code cell source
# @title Install and import feedback gadget
!pip3 install vibecheck datatops --quiet
from vibecheck import DatatopsContentReviewContainer
def content_review(notebook_section: str):
return DatatopsContentReviewContainer(
"", # No text prompt
notebook_section,
{
"url": "https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab",
"name": "comptools_4clim",
"user_key": "l5jpxuee",
},
).render()
feedback_prefix = "W2D2_T1"
[notice] A new release of pip is available: 24.2 -> 24.3.1
[notice] To update, run: pip install --upgrade pip
Figure settings#
Show code cell source
# @title Figure settings
import ipywidgets as widgets # interactive display
%config InlineBackend.figure_format = 'retina'
plt.style.use(
"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle"
)
Helper functions#
Show code cell source
# @title Helper functions
def pooch_load(filelocation=None, filename=None, processor=None):
shared_location = "/home/jovyan/shared/Data/tutorials/W2D2_TheSocioeconomicsofClimateChange" # this is different for each day
user_temp_cache = tempfile.gettempdir()
if os.path.exists(os.path.join(shared_location, filename)):
file = os.path.join(shared_location, filename)
else:
file = pooch.retrieve(
filelocation,
known_hash=None,
fname=os.path.join(user_temp_cache, filename),
processor=processor,
)
return file
Video 1: Orienting inside a ‘Climate Solution’ Simulator#
Submit your feedback#
Show code cell source
# @title Submit your feedback
content_review(f"{feedback_prefix}_Orienting_inside_a_Climate_Solution_Simulator_Video")
If you want to download the slides: https://osf.io/download/mtyrb/
Submit your feedback#
Show code cell source
# @title Submit your feedback
content_review(f"{feedback_prefix}_Orienting_inside_a_Climate_Solution_Simulator_Slides")
Section 1: Exploration of a Climate Solution Simulator#
The following introductory video gives a quick overview of the En-ROADS simulator, a simple climate model (SCM), developed by Climate-Interactive for teaching purposes. It is used in policy workshops, role-plays, and other activities to explore the possibilities and obstacles of scenarios and human solutions to climate change.
To get familiar with modeling societal and economic mechanisms in combination with climatic variables, the so-called socio-economic model, you will examine its ‘control knobs’, limitations, and assumptions. In later tutorials you will compare these findings with those of Integrated Assessment Models (IAMs) which are state-of-the-art models for projecting scenarios and those used in the socioeconomic pathways of the IPCC.
Video 2: Overview of the En-ROADS Climate Solutions Simulator#
Exercise 1: Can you limit human-caused global warming to “well-below 2ºC”?#
Estimated timing: 20 minutes
We jump right in with an exercise, adapted from En-ROADS, that allows you to explore the Climate Solution Simulator.
Open En-ROADS here. (Note the control panel is available in various languages - check the left of the panel of the simulator that should by default show “English”.)
Develop a scenario: By moving the sliders, find a scenario (i.e. a combination of slider positions of different variables) that results in less than 2°C of temperature increase by the end of the century. Don’t worry if you don’t find a scenario that works right away - keep exploring. Use the following cheatsheet to help you get started. Have fun!
Answer the following questions:
How many variables did you have to adjust to reach the “well-below 2ºC” target?
Which variables had the most individual impact? Did the magnitude of impact surprise you for any variables?
How feasible is this scenario? That is, what actions would have to be taken by governments, businesses and people over the next few years to make the proposed scenario possible?
Note that your changes are reflected in the light blue graph, while the baseline scenario remains a black line.
Submit your feedback#
Show code cell source
# @title Submit your feedback
content_review(f"{feedback_prefix}_Exercise_1")
Section 2: Limitations of the En-ROADS Model Approach#
We conclude this tutorial by stepping back and discussing the limitations of En-ROADS.
Exercise 2: Limitations#
Estimated timing: 5 minutes
Think about limitations that arise from the En-ROADS model approach. List a few mechanisms that seem oversimplified or phenomena that might be not or misrepresented. Discuss with your pod.
Submit your feedback#
Show code cell source
# @title Submit your feedback
content_review(f"{feedback_prefix}_Exercise_2")
Summary#
In this tutorial, you got an intuition for various ‘control knobs’ that can be turned in a socio-economic model environment. We discussed why no policy alone can be a silver bullet to solve all problems but a mixture of many actions, in particular, the energy transition to renewables and carbon pricing. At last, we discussed a few limitations of the En-ROADs model approach.
Resources#
This tutorial is inspired by teaching material from Climate Interactive and other documents. A few important resources are linked below: