XPost: alt.global-warming

Can climate change influence earthquake activity?
Yahoo, 02 Sep 2021 14:28Z
Changes in the landscape are putting an increased stress load on the
Earth's crust, which scientists say has been correlated ...


It's pretty well understood that in areas with (these days) melting
glaciers when the weight of the ice comes off the earth "rebounds" and
that can cause earthquakes.

But an interesting thing the AI's have picked up on is that major
quakes are actually decreasing in direct relationship with increasing
AGW. Potentially more startling, the programs find the best
explanation of the reduction in cat 5+ quakes from GFZ-Potsdam is the
notorious GHG "laughing gas" or N2O.

Even more interesting the AI's also pick up on a causal chain where
the complex growing season(s) for polar plankton -- which exhale N2O
as part of their normal metabolism -- are leading to part of the rise
in atm N2O. I.e. plankton are reducing earthquakes.

This is the kind of claim you have to get used to seeing from AI s/w.
Like human savants they make connections that seem bizarre yet can
back them up with facts and figures and logical reason using
well-known and accepted arguments.

Of course they also pick up on something that seems to be part of the
changing pattern of plankton growth that may appear "more
controversial". I'll leave that for later but include something below
that may attract the eye of the observant reader. :)

Finally, atm N2O is also being greatly increased by human activities
like agriculture. The s/w has picked up on a very strong link between
the usage of nitrogen fertilizer in particularly the US and atm N2O
and therefore the reduction in big quakes. I.e. US farming is reducing earthquakes.

A brief outline of the evidence.

The data is the date of each mag 5+ quake known since around 2005.
The database is kept ay <http://geofon.gfz-potsdam.de>.

The AI s/w then takes the monthly counts of mag 5+ quakes and tries to
find among its list of 10s of 1000s of other data including but not
limited to most things NOAA, NASA and Hadley curate, to try and find
"the best explanation" of the quake numbers.

The s/w uses hyper-robust statistical procedures. It uses a kind of
careful time-series regression with lots of bells and whistles to
establish a list of datasets that "look like" the quake time series
and are at most 1% possibly related to just luck. It then sorts the
various results in decreasing order of "explanation power" (R2
statistic) and uses some simple qualitative reasoning to remove links
that can not "possibly" be causal.

The remaining list is then the AI's assessment of what is "causing"
the reduction in quakes seen in the dataset.

The top 10 "best explanations" are:


Suspect variable Lag Log R2
(m)
gavn2o_NH 0 -y 0.52525751
gavn2o_SH 3 -y 0.51102974
gavnitfertlbperac 12 -y 0.41804492
co2 3 -y 0.40053350
gavsaturn-lonecl 4 -y 0.40051239
gavsaturn-v 4 -y 0.40045327
gavch4 6 -y 0.39817247
gavuranus-v 4 -y 0.39035179
gavsaturn-r 4 0.38990237
[timeseries] 0 -y 0.37348132

The first column is the AI coded name for the dataset being used to
explain the waxing and waning seen in the "target" dataset (the quake timeseries). The "lag" column shows most suspect variables had to
allow some number of months delay to pass for whatever effect to
achieve the best match between suspect and target. E.g. "3" would mean
some suspect variable was found to need a 3 month delay before it best
matched the target.

The "Log" column says whether a log transform was needed to maximize
the explanation power. It turns out all but 1 of the top 10 needed a
log transform. This means the the suspect is related to the target
by an exponential formula. Always interesting because of its
potential hyper-rapid growth (the exponential function grows faster
than any polynomial -- something politicians and even govt experts
are allays falling foul of these days).

Finally, the R2 columns shows how much of the month-to-month variation
in quake numbers matches up "is explained by" month to month
variations in the suspect variable. Bigger is better.

We see the "best explanation" out of the ones the AI tried, out of
20,000 it could have tried if it didn't use its knowledge base to rule a
lot of them out for one or other reason, is "atmospheric N2O in the N
Hem". The "gav" on the code means the effect of N2O on quake is not
direct, but requires the N2O to "build up" to have its effect. The
"gav" function is something the AI tinkered up on its own to match up
rainfall and soil moisture; soil moisture relates to what moisture may
have been left over from last month plus the rainfall for this
month. It seems N2O (and many other things) are similar in regard to quakes.

The s/w finds NH N2O "explains" about 1/2 the month to month variation
in big quakes. The other 1/2 is presumably down to other quakey
things, whatever they are.

Another item from the top10 is "nitrogen fertilizer lbs per acre" -- a
data series naffled from the USDA. Nitrogen fertiliser also increases
atm N2O as it decomposes, but it seems something in particular
associated with its usage is boosting the explanation power of
fertiliser up to a level almost equal to the atm N2O itself. Not the
12m lag time the AI found. This is presumably something like the
average time fertilizer takes to decay and produce N2O.

Interestingly we see CO2 and CH4 -- the 2 other better-known GHG's
driving AGW -- also appear in the top 10 explanations for big quake frequencies.

So it does indeed seem AGW is having an effect on earthquakes. At
least with the data used here -- cat 5+ quakes -- the numbers are
declining slowly month by month.

If other researchers have noticed that quakes are overall increasing
due to AGW it simply means that small quakes are REALLY increasing a
lot. As the land dries, or gets wetter, and/or rebounds from ice-melt
a lot of small quakes may happen as a result. The traditional
geophysics idea is that many small quakes can "relieve" the stress
that might otherwise have kept on building for a BIG quake.

--
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