«I had been watching
several weather models for several days which had been indicating this area would have an environment capable of supporting supercells, the type of storm responsible for tornadoes,» he says.
Not exact matches
They said the real strength of the Jacobson study — now in press at the Journal of Geophysical Research - Atmospheres — is that it relies on a new computer
model of climate, air pollution and
weather that accounts for
several different ways black carbon influences the environment.
In the past
several years, researchers have used AI systems to help them to rank climate
models, spot cyclones and other extreme
weather events — in both real and
modelled climate data — and identify new climate patterns.
It's just that the noise within the
models is not correlated in time with the real noise; getting that right would be like predicting the
weather several years out.
When the weathermen can't accurately predict the
weather out more than a few days at best, why should anyone believe that global warming
models going out even
several decades are reliable?
About 1980ish, some old ideas like the greenhouse effect were brought out of mothballs and re-examined with new tools and techniques; simultaneously
several researchers and theoreticians released their notes, published, or otherwise got together and there was a surprising consilience and not a small amount of mixing with old school hippy ecologism on some of the topics that became the roots of Climate Change science (before it was called Global Warming); innovations in mathematics were also applied to climate thought; supercomputers (though «disappointing» on
weather forecasting) allowed demonstration of plausibility of runaway climate effects, comparison of scales of effects, and the possibility of climate
models combined with a good understanding of the limits of predictive power of
weather models.
Training consisted of running the
model repeatedly over
several days using as input eight years of Albuquerque's historical
weather data taken from NREL's SOLMET database.
Good straightforward tests of the
model would require data that extends over a period covering
several periods of «climate» as opposed to
weather or oscillations that the
model is not even supposed to present correctly.
I have used
weather model output extensively for forecasting
weather and air quality and it is amazing how well our modern
weather models can forecast the
weather for
several days compared to what I saw in college days in the early 1970's.
Several days ago, Andy Revkin did a nice post querying a number of
weather forecasters and researchers about the relative merits of the different forecast
models [link], particularly since everyone seemed to be paying attention to the European
model (ECMWF) rather than NOAA's GFS
model.
We have also developed computer
models that predict body temperatures to within
several degrees using data from
weather stations and satellites, and current efforts under way in David Wethey's lab will eventually allow us to predict patterns of temperature on a global basis.
There's now strong agreement on
several of the
weather and climate patterns that future Arctic sea ice loss will create, provided that the right types of climate
models are put on the task —
models that capture the interplay among atmosphere, oceans, and sea ice.