High performance computing (HPC) will drive a sharp increase in our
ability to more accurately model and predict climate change effects,
as well as other complex systems. One of the biggest challenges
about understanding the effects of climate change and working to
mitigate them is that the models used to predict the measures of
climate change (temperature, ocean currents, atmospheric circulation,
etc) are quite inaccurate. Smith et al noted in a 2020 paper that
"modelling and internal variability uncertainties are each large enough
to allow opposite projections of European winters" particularly at the
decadal timescale. UN projections, which are the basis of many
countries' climate policies, predict change on the 100-year timescale,
which is, frankly, too long to be useful, and on a global dimension,
which is too general to provide explanatory power for regional
effects of climate change, which can vary substantially by latitude,
geography, etc.
High performance computing will make it possible to do a couple of
things that should make climate modeling exponentially more
accurate and more available. First, the amount of data, and the myriad
of types of data, that are needed for complex models is enormous,
and the task of data cleansing and preparation laborious. This is, for
most organizations, prohibitively expensive (Vogels, 2020). Second,
the amount of compute power needed to run a complex model is also
massive and difficult & expensive to procure (Vogels, 2020). In recent
years, this technology (e.g. distributed high performance computing,
and the ability for multiple models to feed each other in real time) has
migrated out of the federal/academic research space and into the
commercial sphere, where it is becoming more of a commodity. f The
ability to use these kinds of tools will make it easier to get better
climate predictions that can then be used to refine the policy options
available and hopefully drive improved decision making.
Smith, D.M., Scaife, A.A., Ead, R., et. al. (2020 July 29). North Atlantic
climate far more predictable than models imply. Nature. 583, 796-
800. https://doi.org/10.1038/s41586-020-2525-0
Vogels, W. (2020 November 19). Understanding climate change using
high performance computing and machine learning. All Things
Distributed (Blog).
https://www.allthingsdistributed.com/2020/11/science-of-climate-
change.html
