parameterize

(redirected from parameterizations)
Related to parameterizations: parametrized

pa·ram·e·ter·ize

 (pə-răm′ĭ-tə-rīz′) also pa·ram·e·trize (-ĭ-trīz′)
tr.v. pa·ram·e·ter·ized, pa·ram·e·ter·iz·ing, pa·ram·e·ter·iz·es also pa·ram·e·trized or pa·ram·e·triz·ing or pa·ram·e·triz·es
To describe in terms of parameters.

pa·ram′e·ter·i·za′tion (-tə-rĭ-zā′shən) n.

parameterize

(pəˈræmɪtəˌraɪz) or

parameterise

vb (tr)
to describe or characterize in terms of a parameter. Also: parametrize or parametrise

pa•ram•e•ter•ize

(pəˈræm ɪ təˌraɪz)

v.t. -ized, -iz•ing.
to describe by the use of parameters.
[1935–40]
pa•ram`e•ter•i•za′tion, n.
Translations
parametrisieren
References in periodicals archive ?
Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave-driven turbulent mixing in global ocean models.
For this, we will (1) use clustering techniques to separate different cloud regimes in model and satellite data, (2) explore the parameters and processes which the simulated phase distribution is most sensitive to, (3) investigate whether closure is reached between state-of-the art cloud resolving models and satellite observations, and how this closure can be improved by consistent and physically justified changes in microphysical parameterizations, and (4) use our results to improve the representation of mixed-phase clouds in weather and climate models and to quantify the impacts of these improvements.
The first volume, Theoretical Background and Formulation, addresses scale separation, quasi-equilibrium, closure, and mass-flux convection parameterization, as well as atmospheric convection and tropical dynamics, while the second, Current Issues and New Theories, covers the actual behavior of convection parameterizations in the context of weather prediction and climate models, including operational implementations and model performance, scale separation, tailored verification approaches, the role and representation of cloud microphysics, alternative parameterization approaches like similarity theory and the subgrid-scale distribution density function, stochasticity, criticality, and symmetry constraints.
Many authors have used different parameterizations of these models to describe animal, vegetable and fruit growth curves (GBANGBOCHE et al.
In multidimensional cases the item parameterizations can be used in conjunction with cluster analysis to identify groups of items which measure different ability dimensions.
It contains nine chapters addressing the advantages of polygon meshes for digital geometry processing, efficient data structures for the implementation of polygon meshes, fundamental concepts of differential geometry, algorithms for mesh smoothing, methods for computing surface parameterizations, general remeshing methods, mesh simplification and approximation techniques, sources of input data methods and methods for removing geometric and topological degeneracies and inconsistencies, and techniques for shape deformation.
To show how effective formulation of wind induced breaking wave effect will be, three parameterizations of turbulence are considered.
1994) has been chosen to be used in this study with five combinations of the model parameterizations and two initial boundary conditions.
Code reconstruction, integrated field bus connectivity, simplified installations without need of interfacing units or gateways and simple parameterizations are some of the many features of the new BCL 500i Series of bar code readers.
Two such parameterizations are the multinomial logit and a parameterization method described by Heifetz and Fujioka (1991).
Suppose the simulations of four different parameterizations result in the following assessment vectors, with components mortality, median height, and crown depth:
As one of FIRE's main goals, researchers hope to develop better parameterizations by gathering detailed data on real clouds and testing the basic assumptions within their models.