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. c 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
