DECAYING MOTHER EARTH
BEGAT
CLIMATE MODELING
AND CLIMATE MODELING
BEGAT
CLIMATE CHANGE
ANTHROPOGENIC CLIMATE CHANGE
In my previous posts I have
talked about believers in, and doubters of climate change, that is man-made
climate change. Doubters doubt man-made climate change because of the means by
which man-made climate change is determined- climate modeling. And this
methodology, climate modeling, is what is being used to make noise about
current climate change which is believed to be hitting tipping point. Climate
modeling is the methodology the Intergovernmental Panel on Climate Change
(IPCC) uses to make pronouncements on climate change. In this post I intend to attempt to look at
climate modeling as methodology for determining climate change.
DEFINITION
The Geophysical Fluid Dynamics
Laboratory (https://www.gfdl.noaa.gov/climate-modeling/
) defines climate model thus: “A global climate model (GCM) is a complex
mathematical representation of the major climate system components (atmosphere,
land surface, ocean, and sea ice), and their interactions. Earth’s energy balance between the four
components is the key to long-term climate prediction. The main climate system components treated in
a climate model are:
The atmospheric component, which
simulates clouds and aerosols, and plays a large role in transport of heat and
water around the globe.
The land surface component, which
simulates surface characteristics such as vegetation, snow cover, soil water,
rivers, and carbon storing.
The ocean component, which
simulates current movement and mixing, and biogeochemistry, since the ocean is
the dominant reservoir of heat and carbon in the climate system.
The sea ice component, which
modulates solar radiation absorption and air-sea heat and water exchanges.”
NEED
“The societal need for reliable
climate predictions and a proper assessment of their uncertainties is pressing.
However, the climate system is complex with a multitude of spatial and temporal
scales. Although the governing equations of the underlying fluid dynamics are
known essentially exactly in the continuum limit, an accurate resolution of
their solutions down to the smallest energized scales is well beyond the
capacity of any computers that are available now or foreseeable in the future.
In addition, many climate-critical processes such as convection and clouds are
represented only approximately in climate simulations, and perhaps always will
be. Such processes may not be amenable to a representation by physically based
deterministic equations and may in fact be inherently stochastic. For all these
reasons, uncertainties in climate predictions arise not only from uncertainties
in initial conditions and forcing scenarios (including future emissions of
volcanic aerosols and greenhouse gases), but also from inherent uncertainties
in model formulation.
The ability to make predictions of
the climate system as a whole is hindered because of a lack of accepted
physical principles that control the overall behaviour, such as the global-mean
temperature. Without such principles, it is impossible to estimate the error of
a prediction made with an inevitably imperfect model over a long evolution
time. Nevertheless, reliable climate predictions are needed urgently, not least
because they influence the risk assessments used by policy makers. Therefore,
it is essential that climate predictions sample all the possible sources of
uncertainty and encompass all the possible outcomes, as discussed by
Collins et al. [1]. Recent Theme Issues of this journal relevant to this topic
include those compiled by Collins [2], Palmer & Williams [3], Thompson [4], Nikiforakis [5], Palmer & Hardaker [6] and Thompson & Sieber [7].
From the perspective of an applied
mathematician, there are two approaches to studying the climate system. The
first approach uses simple, conceptual models with only a few degrees of
freedom. These models are designed to capture the observed relationships
between components relevant to a particular phenomenon, such as time series of
key integrated variables like global surface air temperature and global
atmospheric composition, without attempting to represent the full
three-dimensional evolution. The simplicity of these models makes it easier to
focus on relationships between selected processes and to explore parameter
dependencies. The simplicity often makes simple models amenable to analytic
progress. However, the simplicity also limits the usefulness of simple models
as tools for quantitative prediction
The second approach is to use
general circulation models (GCMs), which contain a wide range of physical
processes represented through millions of degrees of freedom. These models are
designed to capture the full spatial and temporal evolution of the
atmosphere–ocean–land system. Also in this category are Earth-system models and
Earth-system models of intermediate complexity, which include comprehensive,
interactive representations of the cryosphere and the global carbon cycle.
Similarly, large-eddy simulations (LESs) of the atmospheric flow are designed
to represent interactions spanning several time and space scales. The
complexity of these models makes them useful as tools for quantitative
prediction, but heavy supercomputing infrastructure is required and analytic
progress is impossible.”
FIGURATIVE
Let me figure out climate
modeling in political election scenario. Elections do take place in democratic
nations. Eligible voters numbering millions are expected to go to the polls to
cast their votes, that is by their votes, to determine the one to apply their
manifesto over them. But, you see, every human wants to know what their future
should be! Even before votes are cast, one wants to know whether their party is
going to win the elections or not. Tory or Labor? Democrats or Republics? Or in
my country Ghana, National Patriotic Party or National Democratic Party? How is
that done? How do you get an idea of the party or candidate to win the
elections? A survey is done or an opinion poll is conducted to conjecture a
prediction! There may be ten million eligible voters to determine who is to
rule them. The opinion poll cannot cover all the ten million eligible voters. Yet
there must be a forecast to pacify those who are anxious, and for strategic
reasons. What pollsters then do is to sample the ten million. Take say 5000
persons out of the 10,000,000 eligible voters and pick their minds as to who or
what they are going to vote for! A mere 5000 out of the 10,000,000. Out of this
methodology of sampling it is determined that Tory or Labor is going to win the
pending elections. Polls do give positive projections sometimes. Exit polls did
predict accurately a win for Boris Johnson (Tory) over Labor in a December 2019
Brexit elections. But polls sometimes go horribly wrong! Before the 2016
elections in Ghana, West Africa, a pollster, Ben Epson predicted a win for the
incumbent, Mr. John Mahama. That was not to be. The incumbent lost miserably!
CONJECTURE
In trying to figure out how
climate modeling works I have had to use political polling as an analogue. They
both take samples, so to speak, out of the real time and big situation and
subject them to observation and examination to determine what should happen to
the real time and big situation as a whole! In climate modeling climate in the
natural environment is copied on a small scale and subjected to observation and
examination by computerization and mathematical representation to tell what
should happen in the climate in the natural environment at large. Since man do
not have the tools to capture the entirety of climate to learn in real time the
processes within its components, intra-actively and interactively, what man do
with the limited tools they have now must result in a conjecture!
CONCLUSION
The Intergovernmental Panel on
Climate Change (IPCC), under the aegis of the United Nations Organization uses
the methodology I have attempted to explain here to make decisions relating to
the state of the world’s climate with a view to galvanizing the world into
mitigative action. So when you hear about terms or targets like 1.5°,
2.0°
or tipping point, it is through this methodology that they are determined. The
climate modeling methodology play a substantial role in providing data for the
assessment reports of the IPCC.
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