Further, these machine learning based results can be used to
validate the climate models so we have confidence in the future predictions of these models.
Not exact matches
CMIP was established as a resource for
climate modelers, providing a standard protocol for studying the output of coupled atmosphere - ocean general circulation
models so that these
models can be compared and
validated.
So, a
validated climate model would be one that takes in all the physical environment data it should have and omits all the data it shouldn't have, and then is able to processes the data in the proper sequences etc. to produce true results.
If it is true, as I believe, that
climate models have never yet been
validated, why should we believe anything the supporters of CAGW claim, when
so many of their analyses are based on the output of these
models?
CMIP was established as a resource for
climate modelers, providing a standard protocol for studying the output of coupled atmosphere - ocean general circulation
models so that these
models can be compared and
validated.
So if at this point all GCMs hypothetically turned out to share similar flaws - e.g. regarding the unknowns for which there's essentially no data - the responses at the LGM of water vapour, clouds, aerosols etc - wouldn't that undermine
validated model approaches to estimating
climate sensitivity from even the LGM?
No
climate model,
so far as I know, has been
validated for the task of predicting global temperature, which is what they're being used for.