Sentences with phrase «physics parameters of the model»

Not exact matches

Re 516: I was under the following impression: GCMs use physics only and are adjusted for better understanding of physical phenomena or inclusion of new physical parameters; temps are used as an indicator of how well the model performs.

Even though the dynamics of a model is given by basic laws of physics you will still have quite a few parameters that you need to specify, both for the initial conditions at the time where you start running the model and also to specify that it is actually this planet you are simulating.

Physics perturbation merely shows the limits of model variability, given a range of parameter uncertainty.

«Perturbed physics» means that model parameters are varied across their range of physical uncertainty.

As Sorokhtin et al. (2007) mention, until recently a sound theory using laws of physics for the greenhouse effect was lacking and all numerical calculations and predictions were based on intuitive models using numerous poorly defined parameters.

Part of the process involves adjusting model parameters within limits dictated by observations and the principles of physics so as to coax the simulations into good agreement with the real world climate.

This connection is not an emergent property of the model's physics, since we don't really know enough about the H2O cycle to model it — instead this feedback connection is one of the many «Parameters» in the model that are adjusted to attempt to match the prior data.

The egregious and misleading stuff from the warmists IMO consists of a) overstating the quality of the physics in their models and the confidence we should have that they are correct; b) treating the ad hoc parameter of «feedback» or «sensitivity» as something they can set on heuristic grounds, and then optimizing the other parameters of their models around it.

In these models there are dozens and dozens of assignable parameters, because you don't really know the physics well enough to write equations.

The Blogosphere is full of fake skeptics that think they have a good model just because they can get an arbitrary series of equations (usually «cycles») with arbitrary fitting of parameters, all while ignoring the known physics.

The difference between the two is [that] my model directly fits known physics initially, and has excellent explanatory power without using a sinusoid at all in an effectively one - parameter fit across the entire range of the data.

However, like all statistical models that do not reflect the real underlying physics of a situation, assuming a form of climate sensitivity — a constant sensitivity parameter for instance, is simply an assumption that may or may not be useful.

Here we extend the evaluation to those variables and analyse several ensembles; two multi-model ensembles (MMEs) from CMIP3 and four structurally different single model ensembles (SMEs, sometimes also referred to a perturbed physics or perturbed parameter ensembles) with different ranges of climate sensitivity.

1) statistical models — parameters are allowed to vary until a best - fit to the data is found 2) dynamical model — parameters are fixed by the best available science (physics, etc.) regardless of how this makes the model fit the data.

There is a massive amount of calculation effort which goes into creating the detail from «basic physics» models when the big picture depends heavily on assumed «guestimates» of poorly constrained parameters.

There's a ton physics in the models, a lot of it correct with parameters estimated with high precision.