Sentences with phrase «model grid size»

I think the modelers know their model grid size is too big to model tornados or thunderstorms.

Or perhaps the theory only really applies at scales much smaller than the model grid size.

The model outputs are generally presented as an average of an ensemble of individual runs (and even ensembles of individual runs from multiple models), in order to remove this variability from the overall picture, because among grownups it is understood that 1) the long term trends are what we're interested and 2) the coarseness of our measurements of initial conditions combined with a finite modeled grid size means that models can not predict precisely when and how temps will vary around a trend in the real world (they can, however, by being run many times, give us a good idea of the * magnitude * of that variance, including how many years of flat or declining temperatures we might expect to see pop up from time to time).

Not exact matches

Models of mountain (alpine) glaciers are applied to solve similar problems to those models used for polar ice sheets, but typically have a higher resolution (a smaller grid size) and need to consider the effects of steep and often variable bed slopes, and the transverse stresses found in valley glaModels of mountain (alpine) glaciers are applied to solve similar problems to those models used for polar ice sheets, but typically have a higher resolution (a smaller grid size) and need to consider the effects of steep and often variable bed slopes, and the transverse stresses found in valley glamodels used for polar ice sheets, but typically have a higher resolution (a smaller grid size) and need to consider the effects of steep and often variable bed slopes, and the transverse stresses found in valley glaciers.

Or do any of the models out there dynamically change the grid size, keeping the total number of points the same, but putting more grid points in at places where gradients in variables are largest?

However, some processes occur at scales too small to be captured at the grid - size available in these (necessarily global) models.

When GCMs are used to model atmospheric conditions and spatial grid size is reduced is there a scale at which chaotic conditions prevail and make modeling difficult in the same way that weather is harder to model than climate?

I know that some models attempt to have dynamic grid cell size, so they only have high resolution where it is needed — this is a nice computational trick that saves time, but is probably limited in applicability.

My point was that attempting to model the world climate response to increasing CO2 levels with a model that has the grid size small enough to model thunderstorms is not feasible.

So... the models don't give better answers to questions like climate sensitivity despite getting larger, faster, and using smaller grid sizes... and your conclusion is that because they have not improved, we should trust them?

There are many diverse limitations on models — computer power and grid size, processes that happens at sub-grid scale and how well they are defined, how well known the starting point or boundary conditions are, etc..

The first model appeared in the late 1960's and the emphasis has been on reducing grid size as computer power increased and on implementing plausible phyics.

However, as Essex and McKitrick point out in the chapter on «Climate Theory versus Models and Metaphors» in their book «Taken by Storm,» that no computer model has a grid size small enough to include any of them.

Our selection aims to highlight the variety in the small living movement and includes a tiny house that can sleep up to eight people, another model that can operate completely off - the - grid, and a home that can expand in size at the push of a button.

Problems arise because practical constraints on the size of computers ensure that the horizontal distance between model grid - points may be as much as a degree or two of latitude or longitude — that is to say, a distance of many tens of kilometres.

The resolution of the models is far too course (the «grid size» is too large) to actually model could behavior directly, and even if that were possible, the computing resources would be astronopmical... far beyond the range of any existing (or near future) computer).

However, global model projections have coarse resolution, with grid cell sizes of 200 × 200 km or more, reflecting limitations of the ocean GCM component of global coupled climate and ocean circulation — biogeochemical models.

While these high resolution models don't resolve all of the vertical transports, global models with horizontal grid size of 1 km or so will clearly help a lot.

The narratives decribing parameterizations in papers discussing climate models themselves don't seem to suggest LES like parameterization, as the parameterization does not depend on the computational grid size of the length scale of the turbulent like motions.

Convection can not be explicitly resolved in general circulation models given their typical grid size of 50 km or larger.