It may be resistant to falsification, but an accumulation of discordant data can not be dismissed
if empirical testing is to be maintained.25
Not exact matches
I still hope that
if we can clarify our two models sufficiently, we will find what
empirical tests are possible.
If I make a statement about the objective world, which includes everything apart from my subjective world: my thoughts, my feelings, my beliefs, etc., I need to back it up with
empirical evidence that can be
tested and retested experimentally.
In technical terms this process is known as falsification:
testing a hypothesis against
empirical data and then dismissing it
if it fails to match up with reality.
We have no evidence
if the matching algorithms stand up to
empirical testing, and we can't
test that because these are private companies and thus their algorithms are proprietary.
Alternatively, veterinarians may not proactively
test any cat — healthy or ill — specifically for heartworm disease, because, among other reasons, they may believe asthma or bronchitis is instead the cause of clinical signs (which heartworm disease often mimics) or because no specific treatment is available for heartworm - infected cats (even
if heartworm disease is confirmed).3 They may instead administer and prescribe
empirical therapies to prevent, lessen, or resolve any clinical signs.
Thing is with all those models I used, there were
empirical tests to proof the model as well as real world
tests to see
if what we «modelled» actually gave us the projected results — often an iterative process to «tune» the models.
Fifth, even
if real scientific investigation (which doesn't stop with modeling but
tests models by
empirical observation) could tell us that, say, falling 50 % short of net zero «carbon» emissions would raise GAT by, say, 3 ° C and that that, in turn, would cause significant harms, that wouldn't tell us how we ought to respond.
Popper also states: «But I shall certainly admit a system as
empirical or scientific only
if it is capable of being
tested by experience.
If empirical evidence, based on raw data,
tested and verified by skeptical scientists, using the same code, algorithms and methods used by Michael Mann, Phil Jones, the IPCC or anyone else showed a cause and effect relationship between rising anthropogenic CO2 emissions followed by rising global temperatures, the amount of which could be quantified and measured, I would have to accept that catastrophic AGW was the likely cause.
So while I expect that climate scientists will argue against «
empirical AR1» coefficients as too severe a pseudoproxy
test, I, for one, do not think that «
empirical AR1» coefficients are too severe a
test —
if anything, they are probably not severe enough.
So I really do not see why those like Pekka Pirilä or Vaughan Pratt are so opposed to simply
TESTING the hypothesis, to see
if it is falsified or corroborated by
empirical evidence.
If you have no
empirical test, you have to let the authors give their view.
If it is corroborated by
empirical testing (Feynman) we are getting closer to having a «corroborated hypothesis».
That's just not a valid «
if» — it reduces scientific hypothesis
testing as a deterministic toolkit working from one necessity to the next, and goes about everything we know about
empirical matters.
In they days before» post normal science» when hypothesese were falsified or not with real
empirical data it was expected that
if one wanted to determine a change in some factor — for example response in corn yields to different rates of types of fertilsier the
test was done on the same soil type in the same years.
And
if one of your Briffa or Mann collaborations shows where they've done
empirical field
tests, please point me at it.
If the system is capable of exhibiting sufficient capacitance to produce the recent hiatus, there is no valid argument against why it could not also have produced the entire modern warming, unless that can be disproven with
empirical data or I / O
test results.