However, this statement in the initial post was particularly interesting to me, «The algorithm (whose code can be downloaded here) is conceptually simple: it assumes that climate change
forced by external factors tends to happen regionally rather than locally.»
Not exact matches
They say
factors external to the cluster, such as shearing
forces produced
by the galaxy's rotation, disrupt the cluster more intensely and prevent stars from forming.
It is feasible that despite the similar internal muscle
forces under both stable and unstable conditions (because of greater synergist and antagonist activation), some of these
factors could still be influenced
by the greater
external load used when training under stable conditions.
Some of them are optimal fingerprint detection studies (estimating the magnitude of fingerprints for different
external forcing factors in observations, and determining how likely such patterns could have occurred in observations
by chance, and how likely they could be confused with climate response to other influences, using a statistically optimal metric), some of them use simpler methods, such as comparisons between data and climate model simulations with and without greenhouse gas increases / anthropogenic
forcing, and some are even based only on observations.
Natural internal variability and natural
external forcings (eg the sun) have contributed virtually nothing to the warming since 1950 — the share of these
factors was narrowed down
by IPCC to ± 0.1 degrees.
Recently I have been looking at the climate models collected in the CMIP3 archive which have been analysed and assessed in IPCC and it is very interesting to see how the
forced changes — i.e. the changes driven the
external factors such as greenhouse gases, tropospheric aerosols, solar
forcing and stratospheric volcanic aerosols drive the
forced response in the models (which you can see
by averaging out several simulations of the same model with the same
forcing)-- differ from the internal variability, such as associated with variations of the North Atlantic and the ENSO etc, which you can see
by looking at individual realisations of a particular model and how it differs from the ensemble mean.
Studies of the response to solar
forcing can thus provide a way to gauge how sensitive these modes are to being amplified or surpressed
by external factors.
«On
forced temperature changes, internal variability, and the AMO» «Tracking the Atlantic Multidecadal Oscillation through the last 8,000 years» «The Atlantic Multidecadal Oscillation as a dominant factor of oceanic influence on climate» «The role of Atlantic Multi-decadal Oscillation in the global mean temperature variability» «The North Atlantic Oscillation as a driver of rapid climate change in the Northern Hemisphere» «The Atlanto - Pacific multidecade oscillation and its imprint on the global temperature record» «Imprints of climate forcings in global gridded temperature data» «North Atlantic Multidecadal SST Oscillation: External forcing versus internal variability» «Forced and internal twentieth - century SST trends in the North Atlantic» «Interactive comment on «Imprints of climate forcings in global gridded temperature data» by J. Mikšovský et al.» «Atlantic and Pacific multidecadal oscillations and Northern Hemisphere temperatures&
forced temperature changes, internal variability, and the AMO» «Tracking the Atlantic Multidecadal Oscillation through the last 8,000 years» «The Atlantic Multidecadal Oscillation as a dominant
factor of oceanic influence on climate» «The role of Atlantic Multi-decadal Oscillation in the global mean temperature variability» «The North Atlantic Oscillation as a driver of rapid climate change in the Northern Hemisphere» «The Atlanto - Pacific multidecade oscillation and its imprint on the global temperature record» «Imprints of climate
forcings in global gridded temperature data» «North Atlantic Multidecadal SST Oscillation:
External forcing versus internal variability» «
Forced and internal twentieth - century SST trends in the North Atlantic» «Interactive comment on «Imprints of climate forcings in global gridded temperature data» by J. Mikšovský et al.» «Atlantic and Pacific multidecadal oscillations and Northern Hemisphere temperatures&
Forced and internal twentieth - century SST trends in the North Atlantic» «Interactive comment on «Imprints of climate
forcings in global gridded temperature data»
by J. Mikšovský et al.» «Atlantic and Pacific multidecadal oscillations and Northern Hemisphere temperatures»
The CSALT model is inspired
by this focus on explaining the variability in temperature
by the known
external forcings and free energy
factors that can compensate for temperature.
Then the question becomes: how likely is it that we have simultaneously overestimated the effect of GHGs
by a
factor of more than 2, and that some combination of natural internal variability and errors in our estimates of the other
external forcings can combine to make up the difference?
It's deemed a
forcing when it is caused
by a
factor external to the climate system otherwise it is considered an internally induced feedback that automatically results when a
forcing nudges things one way or another.
If we have a chaotic system with two attractors where the choice of the attractor is not controlled
by external forcing (like Milankovitch cycles) but
by random
factors then this does not work, but if the
external forcings dominate in the choice then there are no problems of the type you indicate.
Forcings Forcing represents any
external factor that influences global climate
by heating or cooling the planet.
AK, Interesting point and analysis, «The «Stadium Wave» hypothesis, per se, is outside the paradigm Gavin is defending, because it fails to acknowledge the fundamental assumption that the «climate» is essentially an «equilibrium system» that only leaves its «equilibrium» when «
forced»
by some
external factor.
Model «20th - century» simulations, with
external forcing by combined anthropogenic and natural
factors, are generally capable of replicating observed SST increases.»