Not exact matches
In a new study, a team
of researchers from Case Western Reserve University and Gebze Technical University (GTU) in Turkey used data science to determine and
predict the
effects of exposure to
weather and other conditions on materials in solar panels.
Professor David Schultz, one
of the authors
of the guest editorial, said: «One
of the long - term
effects of climate change is often
predicted to be an increase in the intensity and frequency
of many high - impact
weather events, so reducing greenhouse gas emissions is often seen to be the response to the problem.
The more that we can understand about the Sun, the better we will be able to
predict solar
weather and hopefully avoid the outages
of satillite communications and the potential damaging
effects that large streams
of high energy particles can have on power grids.
While meteorologists may
predict weather patterns, Rockman reminds us that the devastating
effects of the elements are often unpreventable.
Of course, there are some differences — the butterfly effect has a basis in physical reality, so as our understanding of physical processes and the ability to mathematically model them improves, so will our ability to bridge the gap between predicting weather and climat
Of course, there are some differences — the butterfly
effect has a basis in physical reality, so as our understanding
of physical processes and the ability to mathematically model them improves, so will our ability to bridge the gap between predicting weather and climat
of physical processes and the ability to mathematically model them improves, so will our ability to bridge the gap between
predicting weather and climate.
Factoring in the
effects of global warming on
weather, food production and pollution, the index's average score drops 8 percent worldwide from what would otherwise be
predicted (and it drops by 12 percent in sub-Saharan Africa and South Asia).
Broader definitions
of the the different patterns and greater effort at determining the specific
effect would be far more useful in
predicting the
weather and the climate.
Many crop yields are
predicted to decline due to the combined
effects of changes in rainfall, severe
weather events, and increasing competition from weeds and pests on crop plants (Ch.
``... Emanuel says, and (Lorenz) made it clear that even if tracing the
effects of small things is too hard to let anyone
predict the
weather a month ahead, the
effects of large things, like the increase
of carbon dioxide in the atmosphere, are not hard to discern.»
In
effect, any pattern
of weather change could be blamed on it — but a hypothesis that
predicts anything and can't be proven false is not science
So what is left here appears to be an assertion that we can not
predict the
weather for more than a couple
of weeks at best, and that in the < 5 year time frame internally generated
effects can swamp a longer term climate signal.
Maybe, or just maybe there's the small detail that
predicting weather is a complete irrelevance to questions
of predicting the
effects of climate change and therefore likely to be a distinct line
of research involving different people?
«Prediction
of weather and climate are necessarily uncertain: our observations
of weather and climate are uncertain, the models into which we assimilate this data and
predict the future are uncertain, and external
effects such as volcanoes and anthropogenic greenhouse emissions are also uncertain.
The claim that «we can not
predict next month's
weather in London, so how in the world can we
predict the
effect of human - made greenhouse gases in 50 years!»
Also, as anyone who has tried to grow something would tell you,
weather (and not climate) has significant
effects on how things grow; therefore, unless the climate scientists can accurately
predict how variations in the global climate (which the AGW statement addresses) manifest themselves in the behavior
of raw proxy data, the proxy data becomes highly suspect.
It is very hard to
predict the
weather and it is very hard to avoid the harmful
effects of nature.