Hello everyone, my name is Iñigo Capellán Pérez and, after the session 5a on the human
interference in the climate system and climate modelling in MEDEAS, I will present the session
5b of the course, which is focused on the modelling of climate change damages in the
model.
As acknowledged in the Paris Agreement, “climate change represents an urgent and potentially
irreversible threat to human societies and the planet”.
The modelling of climate change damages to human societies is a very challenging topic
given the complex uncertainties that pervade the coupled human–Earth system, the long
time horizon of the problem as well as the heterogeneous nature of climate impacts across
regions, sectors and generations. Hence, large uncertainties exist for its assessment.
Global surface temperature has already increased around 1⁰ Celsius over pre-industrial levels
and climate change impacts are already affecting human societies.
What is clear is that natural disasters negatively affect the development of a country, causing
a lag, even after the recovery phase, due to a combination of direct and indirect impacts.
For example: intensification of extreme weather events such as cyclones, heat and cold waves,
provoking forest fires, drought episodes, etc. which together with long-run climate
changes, critically damage biosphere dimensions such as the water cycle and biodiversity.
These impacts may make large regions unlivable, raise mortality and trigger large-scale migrations
across the globe, cause loss of economic production, destroy goods, capital and infrastructure,
etc. In fact, adaptation to climate change is generally expected to only play a limited
role.
In this context, political accords such as the Paris Agreement have set the objective
to avoid global average temperature increase to be well “below two degrees and pursue
efforts to limit the temperature increase to one and a half degrees”.
Now let’s see how models address all these issues.
A review of the literature shows that there is a large gap between natural scientists’
understanding of climate change impacts and their representation in Integrated Assessment
Models.
For example, Hansen and colleagues studied paleoclimate data, climate modelling and modern
observations, concluding that 2 degrees of global warming above the preindustrial level
would be dangerous. Knutti and colleagues also showed that the common target of 2 degrees
is a political target, not having been explicitly recommended by any scientific assessment as
a “safe” target. One more example, the recently updated “Reasons for Concern”
figure from the IPCC Special Report on one and a half degrees shows that there are from
moderate to high impacts and risks for people, economies and ecosystems across sectors and
regions associated to this temperature increase level.
However, in integrated assessment models, temperature change typically increases in
business-as-usual scenarios between almost 4 and 5⁰C by the end of the century, with
negligible representation of impacts and damages to humans and the biosphere. Thus, the “potentially
irreversible threat to human societies and the planet” stated in the Paris Agreement,
is not currently being captured by models.
This discrepancy inevitably produces confusion in policy-makers and the citizens, as they
receive contradictory messages from the scientific community in relation to the potential damages
caused by climate change.
In this context, MEDEAS proposes a novel, simple and transparent methodology, based
on the concept of damage function, in order to introduce climate damages into the modelling
framework. Damage functions consider climate change impacts as highly aggregated monetary
damages. Although neglecting non-market impacts such as ecosystem functioning, conflict, illness,
etc. is a shortcoming, this approach allows to calibrate the damage function through top-down
induction consistently with climate change impact assessments.
The literature shows us 2 main lessons. First, climate damages should affect the drivers
of economic growth and not only the level of GDP. The rationale is that climate will
provoke direct and indirect damages which will reduce the level of expected production.
This is modelled through an energy losses function, which affects the final energy consumption
available for production after climate change impacts.
Second, this energy damage function is calibrated by applying an inductive method to assure
consistency with climate change impact assessments. Each user can calibrate this function through
the interpretation of “dangerous” or “catastrophic” climate change levels.
An example of energy losses damage function is shown in the slide. At current CO2 concentrations,
damages are negligible, while at high concentrations, damages will be catastrophic. A logistic function
is used in order to represent the non-linearity between climate change and the related impacts.
The parameters “a” and “b” can be selected by the user in the inputs excel file.
The parameter “a” indicates for which level of CO2 concentrations 50% energy losses
are expected to occur, while “b” controls the steepness of the curve.
To finish this session, let’s see what the implications of such a modelling for a business-as-usual
scenario would be up to 2100, assuming no other constraints such as energy availability.
We will focus on the evolution of 2 outputs: global GDP on the left and global average
temperature change on the right.
The grey curves represent the projections without considering climate change damages.
As expected, production increases exponentially and so does the temperature change, which
reaches similar levels to other business-as-usual scenarios in the literature.
Let’s see now how the introduction of the energy losses function affects the results.
Assuming a dangerous warming level of 750 ppm, and an intermediate steepness, the red
curves are obtained.
After 2050, climate change damages cause a global recession and expected GDP levels cannot
be attained.
These results are more consistent with climate impact assessments, in the sense that, if
current trends are maintained within a business-as-usual storyline, a severe crisis and even collapse
of the system is more likely than to reach four or five degrees without affecting the
socioeconomic dimension, as currently reflected by most models.
Concluding, the three main take-aways of the topic number 5 focused on Climate Change,
are the following:
First, MEDEAS-World incorporates a state-of-the-art simple climate emulator model to represent
the climate dimension.
Second, large uncertainties exist in the estimation of climate change damages, which nevertheless
have potential catastrophic consequences for humans and the biosphere.
Third, a novel, simple, transparent and consistent with climate impact assessments methodology
has been developed for the integration of climate damages in the modelYou will find
the supporting material in the following website, and the related bibliography and figure credits
in this slide.
The next and last video of this course will focus on the simulation of scenarios and policies
with the MEDEAS-World model.
Thank you very much for your attention.