Let us look at why predictions which may seem alarmist are important:
The first thing is that the general public and politicians in particular do
not have the scientific smarts to be able to make reasonable scenarios from
just data. The reaction is "so the CO2 is rising, it is such a small
fraction, so what?" or "Plants need CO2 so it is a good thing"... The
connections between melting glaciers, stronger weather systems, rising sea
levels are not likely to be made.
The second thing has to do with how people react. If you show a picture of
a starving child as part of a charitable appeal people open the wallets and
purses to give. But if you present statistics and data on how many starving
children there are, and where they are located, the giving is much lower.
People in general do not relate to just data. This was actually illustrated
in the movie "Independence Day". There was data, but it took some
foretelling to bring home the gravity of the situation. This idea comes
from research into what influences people, and is not just my imagination.
So I would say that predictions that are eventually accurate and which ring
true are very valuable in convincing and galvanizing them to action.
What about climate vs weather forcasters?:
Weather forecasters are often very skeptical about long range climate
predictions. This is because they know very well that long range weather
forecasts are not very reliable. 3 days is usually pretty good, but a week
is not very good, and a month impossible. They are looking at a chaotic
system, where the sort term variations are not possible to predict. In some
parts of the country the predictions are better when you have nice flat
terrain where you can chart the fronts, and in others the predictability is
low. So some statistics have the majority of weather forecasters as global
warming skeptics.
But climatologists are looking at trends over much longer periods of time,
and of course the individual fluctuations disappear. We understand this
because we routinely see laboratory data with fluctuations, but you can find
overall trends of analyze the fluctuations so as to show underlying
principles. The general public and politicians in particular do not
understand statistical data. Indeed if you were to make the Congress take
the Lawson test of scientific thinking you might find that only 30% score in
the formal operational range, and less than 1% understand the statistical
question.
Models vs theories:
I would say the problem with communication is the idea of a scientific
theory, vs the conventional "it's just a theory". So like JD I would use
the word sparingly and usually only when it is attached historically to a
name. A much better word is model because it implies a structure and
acknowledges that we created it. Indeed the word model conjures up pictures
of a complete structure which mirrors another very real object. So a
scientific model is attempting to mirror what we have observed. Quantum
mechanics already has a good word "mechanics" associated with it, and that
conjures up a detailed understanding of something. So maybe we should
switch to "the model of evolution" when talking about it. Similarly the
"model of global warming" might be a good phrase to use.
Already the wagons are circling in the Congress and are there any bets as to
when the first hearings will start featuring mainly skeptics of global
warming? Shades of McCarthy! They have already declared they are going to
do this.