Sentences with phrase «model dynamical processes»
(SW - CLR is related to the distribution of atmospheric water vapour and aerosol which has a close link to the model dynamical processes).
https://link.springer.com/ Not exact matches
«This camera has the potential to greatly enhance our understanding of very fast biological interactions and chemical processes that will allow us to build better models of complex, dynamical systems such as cellular respiration, or to help doctors better deliver and monitor light - based therapies,» says Richard Conroy, Ph.D., program director for Optical Imaging at NIBIB.
«These ultrafast cameras have the potential to greatly enhance our understanding of very fast biological interactions and chemical processes and allow us to build better models of complex, dynamical systems.»
The first group participates in an intensive 4 - week collaborative learning experience on dynamical systems (broadly understood to include stochastic processes), modeling, and computational methods.
Jiacan Yuan is a climatologist who is interested in understanding the fundamental dynamical processes in the atmosphere and improving climate models, which could give us better predictive power and risk assessment of the changing climate.
• Dynamical processes related to ice flow not included in current models but suggested by recent observations could increase the vulnerability of the ice sheets to warming, increasing future sea level rise.
The vulnerability of the ice sheets to warming could be increased by dynamical processes related to ice flow (not included in current models but suggested by recent observations) thereby increasing future sea level rise.
[Our study] reinforces the need for climate models to include fully coupled stratospheric dynamical - radiative - chemical processes if they are to more accurately simulate and predict future climate variations.»
The meeting will mainly cover the following themes, but can include other topics related to understanding and modelling the atmosphere: ● Surface drag and momentum transport: orographic drag, convective momentum transport ● Processes relevant for polar prediction: stable boundary layers, mixed - phase clouds ● Shallow and deep convection: stochasticity, scale - awareness, organization, grey zone issues ● Clouds and circulation feedbacks: boundary - layer clouds, CFMIP, cirrus ● Microphysics and aerosol - cloud interactions: microphysical observations, parameterization, process studies on aerosol - cloud interactions ● Radiation: circulation coupling; interaction between radiation and clouds ● Land - atmosphere interactions: Role of land processes (snow, soil moisture, soil temperature, and vegetation) in sub-seasonal to seasonal (S2S) prediction ● Physics - dynamics coupling: numerical methods, scale - separation and grey - zone, thermodynamic consistency ● Next generation model development: the challenge of exascale, dynamical core developments, regional refinement, super-parametrization ● High Impact and Extreme Weather: role of convective scale models; ensembles; relevant challenges for model deProcesses relevant for polar prediction: stable boundary layers, mixed - phase clouds ● Shallow and deep convection: stochasticity, scale - awareness, organization, grey zone issues ● Clouds and circulation feedbacks: boundary - layer clouds, CFMIP, cirrus ● Microphysics and aerosol - cloud interactions: microphysical observations, parameterization, process studies on aerosol - cloud interactions ● Radiation: circulation coupling; interaction between radiation and clouds ● Land - atmosphere interactions: Role of land processes (snow, soil moisture, soil temperature, and vegetation) in sub-seasonal to seasonal (S2S) prediction ● Physics - dynamics coupling: numerical methods, scale - separation and grey - zone, thermodynamic consistency ● Next generation model development: the challenge of exascale, dynamical core developments, regional refinement, super-parametrization ● High Impact and Extreme Weather: role of convective scale models; ensembles; relevant challenges for model deprocesses (snow, soil moisture, soil temperature, and vegetation) in sub-seasonal to seasonal (S2S) prediction ● Physics - dynamics coupling: numerical methods, scale - separation and grey - zone, thermodynamic consistency ● Next generation model development: the challenge of exascale, dynamical core developments, regional refinement, super-parametrization ● High Impact and Extreme Weather: role of convective scale models; ensembles; relevant challenges for model development
As the researchers point out, the findings reinforce the need for climate models to include fully coupled stratospheric dynamical - radiative - chemical processes.
Dynamical physical oceanography focuses primarily upon the processes that govern the motion of fluids with emphasis upon theoretical research and numerical models.
In our work we use observations as well as a hierarchy of numerical models to study dynamical processes in the atmosphere, and climate variability.
«Our climate simulations, using a simplified three - dimensional climate model to solve the fundamental equations for conservation of water, atmospheric mass, energy, momentum and the ideal gas law, but stripped to basic radiative, convective and dynamical processes, finds upturns in climate sensitivity at the same forcings as found with a more complex global climate model»
Our climate simulations, using a simplified three - dimensional climate model to solve the fundamental equations for conservation of water, atmospheric mass, energy, momentum and the ideal gas law, but stripped to basic radiative, convective and dynamical processes, finds upturns in climate sensitivity at the same forcings as found with a more complex global climate model [66].
Dynamical processes related to ice flow — which are not included in current models but suggested by recent observations — could increase the vulnerability of the ice sheets to warming, increasing future sea level rise.
Jiacan Yuan is a climatologist who is interested in understanding the fundamental dynamical processes in the atmosphere and improving climate models, which could give us better predictive power and risk assessment of the changing climate.
Aires, F., and W.B. Rossow, 2003: Inferring instantaneous, multivariate and nonlinear sensitivities for the analysis of feedback processes in a dynamical system: The Lorenz model case study.
In general, the histogram of climate variables only related to dynamical process (SLP, SW clear - sky radiation) tend to be U-shape in SMEs, possibly because model parameters related to dynamical processes are not generally perturbed in the SMEs.
Thus neither the dynamical cascade nor the forcings are accurate and the entire modeling process is doubtful.
Such accelerated flow leads to increased ice discharge into the ocean, but the relevant dynamical processes are not properly understood nor included in continental ice - sheet models, the main difficulty being the treatment of grounding - line migration in response to increased melting of ice by the ocean.