Sentences with phrase «microphysical models»
Measurements from the winter of 1994 — 95 indicating removal of total reactive nitrogen from the Arctic stratosphere by particle sedimentation were used to constrain a microphysical model.
http://science.sciencemag.org/ Not exact matches
«Modeling the details of cloud microphysical properties is very computationally intensive, so models don't usually include them,» said Fan.
«The model simulations can isolate factors and explain the complex microphysical interactions in clouds that can not be directly observed.»
The research team for this study used these data in sophisticated numerical models to examine cloud microphysical processes that are important for cloud maintenance but can not be directly observed, even with the most advanced instrumentation.
What's Next: With this new knowledge of the complex interactions between dynamic and microphysical processes in mixed - phase clouds, researchers can improve the representation of these clouds in climate models.
Both of these issues relate to microphysical effects and atmospheric chemistry — neither of which are accounted for in simple models.
The microphysical cloud processes, aerosol interactions, etc which are not resolved (spatially) by models or are not reducible to simple algebraic answers must be constrained heavily and talked about with uncertanity.
Professor William Happer of Princeton, one of the world's foremost physicists, says computer models of climate rely on the assumption of the CO2's direct warming effect that is about a factor two higher, owing to incorrect representation of the microphysical interactions of CO2 molecules with other infrared photons.
The aci effect (associated with clouds) is either specified in the model as forcing, or the model allows the aerosols to interact directly with the cloud microphysical processes.
Lee, Y.H., P.J. Adams, and D.T. Shindell, 2015: Evaluation of the global aerosol microphysical ModelE2 - TOMAS model against satellite and ground - based observations.
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 development
«In order to develop climate models, we have to consider microphysical processes, such as how a cloud droplet gets formed and how such droplets and physical conditions inside and outside of a cloud are changed by the presence of aerosols,» she said.
Microphysical theories regarding CR - cloud links via ion - mediated nucleation are well developed, and several studies have attempted to incorporate these effects within atmospheric models to estimate the magnitude of potential affects to aerosols and clouds.
In the context of models that include cloud processes, ranging from small - scale models of clouds and atmospheric chemistry to global weather and climate models, the unified theoretical foundations presented here provide the basis for incorporating cloud microphysical processes in these models in a manner that represent the process interactions and feedback processes over the relevant range of environmental and parametric conditions.
Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced.