On 5/12/2015 12:22 PM, Telmo Menezes wrote:
With climate change and cures for cancer you need statistics, because there
are no
such laws in these fields. There is no equation where you can plug-in a CO2
concentration and get a correct prediction on global temperature change.
There's a law where you can plug in atmospheric composition and solar
radiance and
get a correct prediction of the equilibrium temperature. That's what
Arrhenius did
in 1890. It's precisely because we do have equations for the energy
balance of the
Earth and how CO2 affects it, that anthropic global warming is as solid a
fact as
evolution and nuclear fission. If it were *just* observations there might
be room
for doubt as to why temperature has gone up. But the mechanism is well
known and
has been for a century.
How can we know that the greenhouse effect is the only thing to consider when dealing
with something as complex as the earth and its biosphere? Ok, CO2 in the atmosphere
reflects back some percentage of the infrared radiation which leads to more solar energy
being trapped in the system. But what about the clouds?
Clouds, especially high clouds have some effect. They reflect visible bands back to space
and they also absorb and reemit IR. Low clouds tend to increase heat load because they
reflect in the day, but they insulate day and night. It's not magic, it's just calculation.
And the vegetation? Don't these things have a role in infraread blocking and sun light
refraction/absorption?
Vegetation may be less reflective than say snow or bare ground.
And many other things we might not be thinking about... My point is: who's to say that
there isn't some negative feedback loop that keeps the temperature stable?
Sure there is. As the Earth gets hotter it's energy loss rate goes up as T^4, so that's
what establishes a new equilibrium. The Earth's temperature won't run away like Venus's did.
It's not such a silly hypothesis if you think in terms of self-sampling. The Earth must
be stable enough to maintain the conditions for uninterrupted biological evolution for
almost 4 billion years.
It's gone through hotter periods with higher CO2 levels - but not while homo sapiens
roamed the Earth. And the rapidity of the rise is faster than anything that can be
resolved the paleoclimate record.
It's not that the long term temperature rise is so hard to predict, at least within a
certain range. What's hard to predict is the effects. There's a lot of focus on sea
level rise because that's relatively easy. But there will also be big changes in weather
patterns and where which crops will grow. And changes that might be dealt with fairly
easily by a rational world government will, in the real world, result in migration,
famine, and war.
But if you'd like to actually formulate the alternative
hypothesis I
might do the analysis.
Ok. My alternative hypothesis is that there is no trend of global
temperature
increase in the period from 1998 to 2010 (as per Liz's chart's
timeframe),
when compared to temperature fluctuations in the 20th century (as
defined by
the metric in the chart).
OK. Here's one way to do it. The ten warmest years in the century from
1910 to
2010 all occurred in the interval 1998 to 2010, the last 13yrs of the
century.
Under the null hypothesis, where the hottest year falls is uniform
random, so
the hottest year had probability 13/100 of falling in that interval.
The next
hottest year then had probability 12/99 of falling in the remaining
12yr of
that interval, given the hottest had already fallen it. The third
hottest year
had probability 11/98 of falling in that interval, given the first two
had
fallen in it, and so on. So the probability of the 10 hottest years
falling in
that 13yr period is
P = (13*12*...5*4)/(100*99*...*92*91) = 1.65e-11
To this we must add the probability of the more extreme events, e.g. the
probability that the ten hottest years were in the last 12
P = (12*11*...*5*4*3)/(100*99*...*92*91) = 3.81e-12
and that they were in the last 11
P = (11*10*...*5*4*3*2)/(100*99*...*92*91) = 6.35e-13
and that they were in the last 10
P = (11*10*...*5*4*3*2)/(100*99*...*92*91) = 5.77e-14
Summing we get P = 2.10e-11
A p-value good enough for CERN. But this isn't a very good analysis
for two
reasons. First, it's not directly measuring trend, it's the same
probability
you'd get for any 10 of the observed temperatures falling on any
defined 13
years. So you have infer that it means a trend from the fact that
these are
the hottest years and they occur in the 13 at the end. Second, it
implicitly
assumes that yearly temperatures are independent, which they aren't. If
temperatures always occurred in blocks of ten for example the observed
p-value
would be more like 0.1. But this shows why you need to consider well
defined,
realistic alternatives. Your alternative was "no trend", but no trend
can mean
a lot of things, including random independent yearly temperatures.
A better analysis is to select two different years at random and count
how many
instances there are in which the later year is hotter. Under the null
hypothesis only half should count. This directly counts trends. And
this is
independent of whether successive years are correlated. There are 10000
possible pairs in a century which is large enough we can just sample
it. I got
the NOAA data from 1880 thru 2013, so I used a little more than a
century.
For example taking a sample of 100 pairs gives 86 in which the later
year was
warmer (I counted ties as 0.5). The null hypothesis says this is like
getting
86 heads in 100 tosses, which obeys a binomial distribution. The
probability
of getting 86 or more heads in a 100 tosses is 4.14e-14.
Brent, I tip my hat to you.
I was preparing to write some objections after reading your first analysis,
but
your pair sampling analysis already addresses them. You convinced me that
there is,
in fact, a global temperature increase trend in the last century.
So are you also convinced that increased CO2 is causing it?
I am still worried about the reliability of the temperature values themselves. I would
be less worried if the raw data was made public.
It is public. But what good does that do. You notice a discontinous drop at a handfull
of weather stations in Paraguay. There's no official record but you're told that they
planted grass under the monitoring stations (which was supposed to be there before but
wasn't). Nobody worried about it at the time because they weren't trying to see 0.1 degC
changes. What are you going to do?
Normally I trust scientists. In this case, the thing got so mixed up with politics that
it makes me uneasy.
It got mixed up in politics the same way smoking and lung cancer got mixed up in
politics. The business interests who saw that they might be regulated because of CO2
emission hired lawyers and PR firms (the *same* firms hired by the tobacco industry) to
spread obfuscation and doubt - that you repeat. And of course they contribute to the
campaigns of politicians who then invite their "experts" like McKintyre to testify before
Congress and give them an excuse not to act "because the science isn't in yet".
Mainly because I observe politicians to be caught lying too often about very
big things.
Forget the politicians; read the peer reviewed science.
Brent
I know, you are going to say that this is absurd because the Koch Bros have much deeper
pockets. Maybe so. You are probably right, but if I am being too paranoid, perhaps you
can at least understand why I would think like that, given recent history.
Assuming the temperature values are correct, I would say that it seems very plausible
that increased CO2 is causing the warming.
Telmo.
Brent
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