
What the Euro model ‘win’ over the American model means for weather forecasting - cryptoz
https://www.washingtonpost.com/blogs/capital-weather-gang/wp/2015/10/06/what-the-european-model-win-over-the-american-model-means-for-weather-forecasting/
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Afforess
The Euro model win only demonstrates the effects of budget cutting on results.
Meteorology computer modeling is nearly entirely dependent on supercomputer
time, and the time and quality of supercomputing resources is a direct
function of money available. Meteorologists can discover better equations for
modeling the atmosphere, but without the computer resources to implement these
models, they are useless.

Weather models are an O(n^4) problem (you solve in x, y, z, and time), so the
computing resources needed to model the globe are vast. Right now, the GFS
(Global Forecast System) resolution is 18 miles. That means it has to treat
the globe as a grid of 18 mile cubes. 18 miles is big; it allows for a lot of
smaller-scale weather features to slip through the cracks.

Ultimately, Less money -> Less computer time -> Worse model resolution ->
Worse model output -> Worse forecast. Meteorology is one of those rare places
where throwing money at the problem does fix the issue.

[https://www.ncdc.noaa.gov/data-access/model-data/model-
datas...](https://www.ncdc.noaa.gov/data-access/model-data/model-
datasets/global-forcast-system-gfs)

~~~
chatmasta
Why give money to a solution before exploring other options? Decentralization,
for example, seems like a more natural way of distributing meterological
forecasting workload across the planet, by colocating sensors and computation
on clusters of devices in close proximity. Decentralized computing is a
natural fit for weather problems.

~~~
dalke
Distributed computing "across the planet" only works with low-bandwidth/low-
latency tasks. Take a look at the various distributed internet projects (the
Great Internet Mersenne Prime Search, Folding@Home, etc) and they are ones
that process for a long time and send back a small amount of data, typically
to a single server.

People use supercomputers for problems, like weather forecasting, which depend
on high-bandwidth, low latency interconnects. For example, the Cray CS-Storm
(which the Swiss National Supercomputing Centre will be using) supports "QDR
or FDR InfiniBand with Mellanox ConnectX®-3/Connect-IB, or Intel True Scale
host channel adapters" (quoting
[http://www.cray.com/sites/default/files/resources/CrayCS-
Sto...](http://www.cray.com/sites/default/files/resources/CrayCS-Storm.pdf) ).

To prevent congestion, the supercomputer network topology might even be wired
so each pair of neighboring nodes has a dedicated connection.

~~~
dalke
Err, "with low-bandwidth/ _high_ -latency tasks".

------
raus22
"Essentially, all models are wrong, but some are useful."

\--- Box, George E. P.; Norman R. Draper (1987). Empirical Model-Building and
Response Surfaces, p. 424, Wiley. ISBN 0471810339.

~~~
lutorm
Aren't models "wrong" by definition, that's why they're _models_.

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rasz_pl
>The European model has a more powerful computer

I seem to remember a story on slashdot ~2 years ago(?) about US upgrading
supercomputer for their forecast despite it already being 2x more powerful
than European one while still being less accurate.

~~~
burnte
That's because while we're upgrading the hardware and software, for some
reason government restrictions force the new models to be tweaked until they
give the same output as the old models. Apparently someone feels that similar
results are more "reliable" and don't see that maybe different results means
BETTER, more accurate results than the old model.

~~~
thelambentonion
Funny anecdote: where I work, one of our departments had a model we used to
predict the working characteristics of our most popular product. Over time, we
noticed that real-world data deviated from our calculations, so the model was
regularly adjusted to bring the predictions in line.

Recently we had to model a new system, and none of our numbers looked remotely
right. Looking at the code, the whole program had essentially been turned into
a lookup table that was completely useless at actually 'predicting' anything
we hadn't seen before. Since then, the system's been completely overhauled,
and now it much more accurately predicts general characteristics even if it
appears less precise than before.

My point's kind of gotten away from me, but I guess it's just easy to see how
people can fall into the trap of leaning on perceived reliability and using it
to avoid making radical changes.

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bcoates
Did they call their shot in advance, or is this another case of arbitrarily
picking the best model by hindcasting?

~~~
gwern
As the quotes in the article indicate, it was an active debate whether the
European model should be trusted more well before the outcome became clear.

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hguant
The last line was a bit of a bummer, but it's in line with the US's non-
military spending habits.

~~~
adventured
US military spending is nearing a 70 year low as a percentage of GDP. It has
fallen by about $150 billion since 2009. By 2019 it's projected to hit about
3% of GDP. By comparison, France and the UK are around 2%. Military spending
right now is not the primary problem facing the US fiscally.

Entitlements are the priority when it comes to US spending. They take up 60%+
of the federal budget. When you throw in the State and Local budgets (which
combined are nearly the size of the federal spending), military spending is a
modest fraction of US spending habits.

~~~
hackuser
There are many ways to characterize numbers, but in the 2015 budget the US
spends over $600 billion on the military, an enormous amount. The nation
spends amounts of the similar magnitude on Medicare, Social Security, etc.

I'm not sure grouping line items into arbitrary categories like "entitlements"
is meaningful for analysis (it's more for ideological contests). The questions
are, what do we get for each investment? Is there a better use for that money?

~~~
vizeroth
Or, to put it another way, the US GDP is over 6 times that of the UK or
France, so a 1% difference in GDP amounts to spending almost 10 times as much
money. By comparison, China, the #2 spender by $ spends a smaller percentage
of their GDP than either France or the UK. Further, the countries which tend
to spend the largest percentages of their GDP on military spending tend to be
countries with low stability, high chances of conflict with neighboring
countries, and a large reliance on outside involvement to maintain some
semblance of stability.

Entitlements, by definition, are paid for by the recipients in some way, and
are often capped by how much the individual paid into the system. At times
when the entitlements are especially needed, these limits are sometimes waived
or modified, which is one source of entitlement problems. Another source of
entitlement problems comes when there is less need for those entitlements and
government is attracted by the large amounts of money going into those
entitlements. The US (and much of the west) happens to be in a long period
when there has been great need which also happens to have followed a very long
period when there was very little need. So, most of the money was stolen to
pay the bills for everything else in the 90s and the early years of the wars
in Iraq and Afghanistan, then anything left in the markets was destroyed by
the economic situations which followed, and eventually the entitlement systems
will no longer be able to meet the demands placed upon them. Add the Baby
Boomers to the Social Security system with a heavier reliance on it for
retirement income (thanks to the near elimination of corporate retirement when
they decided the massive amounts of cash on their books waiting for Baby
Boomers to start collecting looked bad for their bottom line), and I'm sure
the outlook is just wonderful for my chances of ever collecting the money I've
put into any number of entitlements, unless I find myself in the most
miserable situation of my life before the government finds a way to cut every
last remnant of the safety net.

