As important as
assumptions about feedbacks may be for climate models, it's important not to allow the complexity of the system to effect our interpretation of basic physics.
I understand it's not an overtly direct extrapolation, but fundamentally it more or less still is if the underlying
assumptions about the feedbacks are presumed to not only be correct but also operate proportionally the same to the forcing from the LGM as they do in reponse to future forcings in the current climate.
No photons are running about in the GCMs, just estimates, dodgy estimates of forcing and dodgy
assumptions about feedback.
Not exact matches
21:30: User
feedback challenged the LinkedIn's initial
assumptions about what job seekers wanted from a product the company was working on in partnership with Microsoft.
Feedback's piece
about Classic FM radio (10 October), which questioned Classic's
assumption that all scientists are men, set reader Mary Mulvihill thinking.
Houman Harouni offered the most challenging and detailed
feedback on my work and pushed me to question my basic
assumptions about education and the roles I play in it.
Presumably the water vapour
feedback in models is dealt with by determining / estimating / calculating the radiative forcing from water vapour and then making some
assumption about the water vapour response to atmospheric warming (e.g. assuming constant relative humidity).
Far better this than running a dozen GCMs with funamentally different
assumptions about climate
feedbacks, plotting them on a graph and claiming that as a measure of the uncertainty in the behaviour of the real climate.
The no -
feedback climate senstiivity of
about 1 C for a doubling of CO2 is based on the
assumption that this imbalance can only be countered by a change in the radiation component of how energy is transmitted through the atmopshere.
However, given that the CAGW position doesn't rest on specific numbers, but is instead an unorganized collection of anecdotal evidence, coupled with heavily - tweaked computer models, unfounded
assumptions about positive
feedbacks, and a healthy imagination
about possible future disasters, a lower warming number for the 20th century will simply be brushed over with claims
about aerosols being stronger than previously thought, more warming still waiting in the «pipeline» or similar ad hoc «explanations» that keep the overall story alive.
The steepness of these reductions curves is somewhat controversial because any calculation of a carbon budget which determines the steepness of the the needed reduction curve must make
assumptions about when positive
feedbacks in the climate system will be triggered by rising temperatures, yet these controversies are reflected in giving different probabilities
about the likelihood of achieving a specific warming limit.
I wonder if you might invite some control theorists / engineers to ponder and post on the
assumptions, and their limitations,
about feedback in climate science and suggest how critical measurements might be made?
As specified by the RCPs, which encompass a multitude of
assumptions about the future but entirely elide key carbon cycle
feedbacks.
BUT, other important / related parameters — BRDF (bidirectional reflectance distribution function)-- albedo i. /: 00 solar local time Neural network based on CYCLOPES and MODIS / wrong ALSO Need to make
assumptions about carbon lost via respiration to go from GPP to / Cox et al. (2000) Acceleration of global warming due to carbon - cycle
feedbacks in a coupled / / JRC / FastOpt: http://www.fastopt.com/topics/publications.htmlhttp://www.fastopt.com/topics/publications.html 50 0 = water; 1 /
Models amplify that warming with
assumptions about positive
feedback (see the blue region of model estimates in the graph below).
Lackof accurate boundary conditions, insufficient understanding of key variables i.e, air pollution and aerosols and most of all wrongheaded
assumption about the existence of positive
feedback.
Alex — You make valid points
about some of the
assumptions, but the point I would emphasize is that kappa was relatively constant between the models and so TCR was primarily dependent on the
feedbacks that determined climate sensitivity, which is why it is a fairly good surrogate.
Things like
assumptions about linearity (which means more or less, they make the mistake of assuming that all forcings and
feedbacks operate at similar ratios and strengths when the planet is an iceball as they do when Earth hits a rare warm phase).
I will then discuss the econometric forecasts they are founded on, the
assumptions about CO2 sensitivity and
feedback processes, and finally model tuning and their ability to match history.
The point is, there is no real scientific justification in assuming a strong positive vapour
feedback in the first place as it all comes down to your initial
assumptions about a) natural variation, and b) aerosols, both of which are acknowledged to be too uncertain to make such
assumptions.
I see an argument between Curry and Colose (and others) here that seems to me to be more
about defining what no -
feedback means than
about scientific calculations under a well - defined set of
assumptions.
Based on their
feedback, are you making
assumptions about what the judge might know
about your case?
Unfortunately, providing little
feedback indicates there is little to say that is good
about you (
assumption: there is plenty to say that is bad
about you).