Within the Outlook project, there may be differences in how each group obtains their area (e.g.,
model grid cells of varying resolution, sea ice charts, and satellite observations); each of these could produce a different value for ice extent.
Not exact matches
The
grid -
cell model is striking not just for its elegance, but also because (as Edvard Moser notes) it forms a key link between perception and memory.
(I'd have to train an emulator on the full
model output instead of just the data - present
grid cells.
They keep track of mass exchange of water between the
grid cells in the
model.
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.
Starting with Arakawa and Lamb's second - order C -
grid scheme, this paper describes the modifications made to the dynamics to create a C -
grid atmospheric
model with a variable number of
cells for each vertical column.
In a cross-validation hindcast, the
model (PHENOM) is able to explain 63 % of the variance in onset date for
grid cells containing at least 50 % mixed and boreal forest.
Yet to
model tropical comvection
cells (Tstorms) responsible for Lindzen's adaptive IR iris,
grid cells need to be on the order of 10 Km (and certainly finer than 30).
So the 3.7 W m - 2 calculation for global radiative forcing could be refined perhaps by an improved experimental design (not necessarily by improved radiative transfer
models) running RT
models at each
grid cell over the globe, over the diurnal cycle and the annual cycle for say 30 years, for the two different CO2 concentrations, such a detailed calculation would refine the 3.7 value.
Now we can start getting into more real climate
models, but ghu, you need a
grid cell resolution of a few kilometers, not 250 or 100 km, and you need to analyse each
cell as its own navier - stokes thermodynamic / fluid dynamic system, not just a basic heat in vs heat out childs toy.
Instead of trying to
model individual droplets, scientists instead approximate their bulk behavior within each
grid cell.
Cloud droplets, for example, might be a couple hundredths of a millimeter in diameter, while the smallest
grid cells that are considered in a
model may be more like a couple hundred kilometers across.
My question is: how does the
model specifically output a 2 metre near - surface temperature for each
grid cell given the setup described above?
--
modelling procedure requires crude approximations over large
grid cells, ignoring local climate and weather phenomena as large as hurricances —
model projections are demonstrably unreliable at regional and local level: even those that appear to simulate the evolution of global temperature do so only by averaging hundreds of more or less wrong results for the
grid cells.
This is not the typical way of conducting a sensitivity study since the reanalysis
models are multivariate spectral
models (not
grid point / lat / lon) and the radius of influence of data is not limited to individual
grid cells.
Is the solution in still larger
models of smaller
grid cells?
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.
GFDL is currently working on the creation of a higher resolution coupled
model with smaller
grid cells.
Model thermodynamics are compared by creating single column versions of the climate model, just looking at what goes on in a single vertical grid
Model thermodynamics are compared by creating single column versions of the climate
model, just looking at what goes on in a single vertical grid
model, just looking at what goes on in a single vertical
grid cell.