Note you said certainty not accuracy. I am interpreting this as precision, though even with certainty the answer is the same I think. You would have to ask the modelers for error bars to be sure.
Temperature from model to model varies greatly, while the precipitation numbers are within a narrower range.
As far as accuracy, 95% of models are overstating temperatures significantly.
I see the models something like this.
Imagine scientists had seen a car for the first time. They can't drive it but they can use all kinds of remote sensing apparatus to try and work out what is happening. They have measured the engine vibrations and the repetitive electrical impulses from the engine. They know about gearboxes, differentials, doors, thermodynamics, air fuel ratios, steering seats etc etc. They have now made an excellent model of a car. The car runs and they are very pleased with it.
Now someone has asked the question: "Where will the real car be in 10 years time?"
They can offer scenarios, that is, where it could be, but they cannot tell for sure where it will be.
Similarly, the current climate models can be used by scientists to increase their knowledge. The models still have some parts missing but are OK for projections and scenarios but not so good at actual forecasts. Going back to the car analogy, the random decisions of the driver cannot be modelled, yet. In fact, it might never be possible to model that randomness.
As others have said, as for forecasting current temperatures the models are not good. To all intents and purposes, they did not forecast the current hiatus in warming. Precipitation is even worse.
This question cannot be adequately answered. We do not have enough information to correctly determine the uncertainties of either of these climate models.
In other words, the uncertainty for any climate model is an estimation. Two different scientists are going to get two different answers. There is uncertainty in the uncertainty. As a matter of fact, this topic should be a much larger discussion than it is.
Read this for more information: http://journals.ametsoc.org/doi/pdf/10.1...
They fail miserably on both counts. 'Greater certainty' can be taken several ways. It certainly will fail or it certainly will be successful.
Climate models have been an abject failure.
Quote by Chris Folland of UK Meteorological Office: “The data don't matter. We're not basing our recommendations [for reductions in carbon dioxide emissions] upon the data. We're basing them upon the climate models.”
James Hansen admitted that he couldn't get any good results from his climate models because he couldn't factor in a workable formula for cloud cover. So the failure of both is the same reason, so it would seem.
B.
In a sense, precipitation projections are conditional probabilities of temperature projections. Also, they manifest themselves on different spatial scales - with precipitation tending toward more local-regional and temperature tending toward more regional-and larger..
'A' true
and they fail miserably with temperatures
Edit. No I did not miss type. they fail miserably at both
You need to do some searching the web so you can do your own schoolwork
Climate change modelling projections generally exhibit greater certainty with temperatures than they do with precipitation:
A. True
B. False – the other way around
C False – both the same
