The approach uses the PETIT
atmospheric model grid to calculate spectral indices.
Not exact matches
The global climate
models assessed by the Intergovernmental Panel on Climate Change (IPCC), which are used to project global and regional climate change, are coarse resolution
models based on a roughly 100 - kilometer or 62 - mile
grid, to simulate ocean and
atmospheric dynamics.
Using a computer
model that fused air pollution and
atmospheric chemistry data, they estimated what annual average levels of ozone (a key smog ingredient) and fine particulates smaller than 2.5 microns (PM2.5) were in 2010 within 100 - km - by -100-km
grid squares across the world.
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?
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.
The resolution of the
atmospheric model is set to TL159L91 (IFS version 41r2), which corresponds to a 1.125 ° horizontal
grid (125 km) with 91 vertical levels going up to 0.1 hPa.
Emissions of other short - lived gases (CO, NOx, NMVOCs, and CH4) also needed to be mapped to a global
grid for use in
atmospheric chemistry
models.
Our lab is actively developing global
atmospheric climate
models with roughly 50 and 25 km
grid spacing (even finer
models are being run very experimentally), and there are a number of related efforts around the world.
The eastward component of the wind in the lower troposphere (850 hPa) simulated by an
atmospheric model with roughly 50 km horizontal
grid.
To characterize observational uncertainty, four
atmospheric reanalyses are used as climate
model surrogates and two
gridded observational data sets are used as downscaling target data.
Principal changes in the physics in the current version of the
model are use of a step - mountain C -
grid atmospheric vertical coordinate [109], addition of a drag in the
grid - scale momentum equation in both atmosphere and ocean based on subgrid topography variations, and inclusion of realistic ocean tides based on exact positioning of the Moon and Sun.
Step - mountain technique applied to an
atmospheric C -
grid model, or how to improve precipitation near mountains
Russell, G.L., 2007: Step - mountain technique applied to an
atmospheric C -
grid model, or how to improve precipitation near mountains.
The technique was originally developed to examine the storm tracks produced by
atmospheric general circulation
models (GCMs), but it is directly applicable to other
gridded SLP datasets, such as those derived in weather forecasts or reanalysis projects.