Sentences with phrase «numerical prediction of»

After all, CFDers like myself can publish papers on esoteric topics like numerical prediction of steam droplet nucleation, and no one asks us for stability proofs or verification studies.

«Given the promise shown by the research and the ever increasing computing power, numerical prediction of hailstorms and warnings issued based on the model forecasts, with a couple of hours of lead time, may indeed be realized operationally in a not - too - distant future, and the forecasts will also be accompanied by information on how certain the forecasts are.»

Not exact matches

Stumm said the study would include «putting a network of outpost wells, filling in gaps in information, and using the information in a numerical model to make predictions for management.

«Some scholars... have flatly denied the prediction, while others have struggled to find a numerical cycle by means of which the prediction could have been carried out,» writes astronomer Miguel Querejeta.

They represent a unique type of atmospheric motion whose forcing mechanism is known with great precision, allowing us to test our numerical models and theoretical predictions.

Apart from ground stations, weather forecasts are heavily dependent on weather satellites for information to start or «initialize» the numerical weather prediction models that are the foundation of modern weather prediction.

Though the ultimate impacts of the numerical experiments will take some time to realize, its potential motivates Snook and the severe hail prediction team.

I was working for the Omani Meteorological Department when the implementation of a numerical weather forecasting model prompted the need for some local knowledge in numerical weather predictions.

By incorporating the complexities of channel geometry, fluid flow rates, diffusion coefficients and possible chemical interactions into a numerical model, the behavior of a particular system can be accurately predicted when an intuitive prediction may be extremely difficult.

The astronomers» long - term goal is to find about ten similar examples of these cold flows, which would allow for a much more detailed comparison of their observations with the predictions of numerical models.

In addition, atmospheric scientist Dr. Hendrik Tennekes, a scientific pioneer in the development of numerical weather prediction and former director of research at The Netherlands» Royal National Meteorological Institute, recently compared scientists who promote computer models predicting future climate doom to unlicensed «software engineers.»

Even with the best numerical model of ice flow available, if the data going into it is not accurate, then the predictions will not be reliable.

By its very nature, a model is a simplification of reality, so the final step when we consider predictions made by numerical models is to assess the uncertainty in our predictions.

He combines this expertise with the gained skills of numerical weather prediction, electrical engineering, and economics.

Potential topics include: (1) Advanced numerical modelling of magnetic flux tubes / loops in the low solar atmosphere (2) Forward modelling of spectroscopic and narrowband EUV observations of the low solar atmosphere, (3) Solar Rotational Tomography of EUV and / or coronagraph coronal observations, (4) Automated detection and prediction of coronal mass ejections, (5) Analysis of solar wind turbulence observations by in situ spacecraft, (6) Eclipse instrumentation, observations and data analysis.

But all of the inputs are approximations (parameter estimates, equations, numerical methods), and the output to date shows that they have made bad predictions about «out of sample» data — the trend since they were published.

Specializing in the parameterization of land - atmosphere exchange for use in Global Climate, Regional Mesoscale, and Local Cloud - Resolving numerical weather prediction models.

I create parameterizations of land - atmosphere interactions which are incorporated into climate models and numerical weather prediction models.

Success at prediction is enhanced by maximizing the number of different hypotheses (models) you can generate and test against numerical data and other available information.

This claim is complemented with a broad literature synthesis of past work in numerical weather prediction, observations, dynamical theory, and modeling in the central U.S. Importantly, the discussion also distills some notoriously confusing aspects of the super-parameterization approach into clear language and diagrams, which are a constructive contribution to the literature.

However, 95 % of the time, each model is performing at about the same skill level as quiescent weather is not particularly challenging for today's numerical prediction systems.

Similar conclusions are reached in a numerical weather prediction context by T. Jung et al. at ECMWF (GRL 2011: http://www.agu.org/pubs/crossref/2011/2011GL046786.shtml) who performed very detailed sensitivity analysis of the origin of the very persistent negative NAO (blocked phase) during the winter of 2009 - 10.

Sea surface temperature (SST) measured from Earth Observation Satellites in considerable spatial detail and at high frequency, is increasingly required for use in the context of operational monitoring and forecasting of the ocean, for assimilation into coupled ocean - atmosphere model systems and for applications in short - term numerical weather prediction and longer term climate change detection.

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

The study group was headed by the noted American meteorologist Jule G. Charney, who played an important role in developing numerical weather prediction and was Alfred P. Sloan Professor of Meteorology at the Massachusetts Institute of Technology.

Promote the development of new methods for numerical weather prediction and climate simulation.

Promote the development of data assimilation methods for application to numerical weather and climate predictions, and for the estimation of derived climatological quantities.

Atmospheric Scientist Tennekes: «Sun may cause some cooling» — «No evidence at all for catastrophic global warming» — July 14, 2008 (By Atmospheric scientist Dr. Hendrik Tennekes, a scientific pioneer in the development of numerical weather prediction and former director of research at The Netherlands» Royal National Meteorological Institute.)

Dr. Nehrkorn's 30 year research tenure at AER has included work on numerical weather prediction models, data assimilation systems, humidity to cloud relationships, three dimensional analysis of atmospheric quantities and studies of the angular momentum budget of the atmosphere.

Their prediction is based on the quantity of incoming solar radiation and uses 16 - day forecasts from a numerical weather prediction model (WRF).

My friend, Climate Science is not a science since it has no precise numerical variables, no laws, and statistics are not applicable because there is no physically meaningful time intervals over which to take averages and no periodicity The system is not stationary — meaning that the earth and its atmosphere and the sun, and the molten interior and the cosmic radiation present a constantly changing environment far beyond the capabilities of prediction.

As Sorokhtin et al. (2007) mention, until recently a sound theory using laws of physics for the greenhouse effect was lacking and all numerical calculations and predictions were based on intuitive models using numerous poorly defined parameters.

Zhang (Applied Physics Lab, University of Washington); 4.1 ± 0.6; Model This is based on numerical ensemble predictions starting on 6/1/2011 using the Pan-arctic Ice - Ocean Modeling and Assimilation System (PIOMAS).

Radiosonde data is a crucially important component of numerical weather prediction.

We can perhaps learn from numerical weather prediction where the benefits of developing global prediction models with high vertical and horizontal resolution are clear cut (confirmed most recently by predictions of Sandy).

That requires considerable sensitivity research with state - of - the art numerical weather prediction (and climate) models... This hand - waving theory may not hold up when a rigorous scientific hypothesis is tested, yet McKibben does not provide a citation or reference aside from Masters» quotations, which are not peer - reviewed in the slightest.»

«We have groups doing numerical weather prediction, hurricanes, climate, oceans, but in the international arena, countries have whole institutions doing the functions of these individual groups,» said Dr. Ronald J. Stouffer, who designs and runs climate models at the Geophysical Fluid Dynamics Laboratory in Princeton, N.J., a top Commerce Department center for weather and climate work.

JIGSAW (GEO) is a set of algorithms designed to generate complex, variable resolution unstructured meshes for geophysical modelling applications, including: global ocean and atmospheric simulation, numerical weather prediction, coastal ocean modelling and ice - sheet dynamics.

Atmospheric scientist Dr. Hendrik Tennekes, a scientific pioneer in the development of numerical weather prediction and former director of research at The Netherlands» Royal National Meteorological Institute, and an internationally recognized expert in atmospheric boundary layer processes, «I find the Doomsday picture Al Gore is painting - a six - meter sea level rise, fifteen times the IPCC number - entirely without merit,» Tennekes wrote.

In addition, atmospheric scientist Dr. Hendrik Tennekes, a scientific pioneer in the development of numerical weather prediction and former director of research at The Netherlands» Royal National Meteorological Institute, recently compared scientists who promote computer models predicting future climate doom to unlicensed «software engineers.»

Tennekes, is an scientific pioneer in the development of numerical weather prediction and former director of research at The Netherlands» Royal National Meteorological Institute, and an internationally recognized expert in atmospheric boundary layer processes.

The results can be applied in numerical weather prediction, weather services and climate research, for example in the speciality areas of solar energy forecasting and aviation support.

The Sea Ice Outlook, an activity of the Sea Ice Prediction Network and a contribution to SEARCH, produces reports in June, July, and August containing a variety of perspectives on Arctic sea ice — from observations of current conditions, to advanced numerical models, to qualitative perspectives from citizen scientists.

Yano J. - I., M. Z. Ziemiański, M. Cullen, P. Termonia, J. Onvlee, L. Bengtsson, et al. (November 2017): scientific challenges of convective - scale numerical weather prediction.

Much of this progress is due to advances in numerical weather prediction, that is, the use of computer models which approximate the fluid motions of the atmosphere to create forecasts of the weather at some time in the future.

This would be a sterile activity indeed without the input of experimental observation to guide the development of theoretical prediction methods and to keep the relevant numerical models «honest».

The predictions may match the observations for a while, but very soon random fluctuations smaller than the distance between the measurements (they are called «sub-grid-scale eddies» in the vernacular of numerical modellers) grow in size and — as far as the model is concerned — appear out of nowhere and swamp the eddies we thought we knew something about.

This study examines the horizontal distribution of cirrus clouds by means of satellite imagery analyses and numerical weather prediction model forecasts.

With the advent of Newton and computers, we have developed numerical prediction methods, which are basically a summation of countless small predictions that, by their nature, are MOSTLY correct.

Thus, in numerical weather prediction out to a mere few days, one tends to neglect the intrinsic variability of the oceans and concentrates on the atmosphere, with sea surface temperatures prescribed as a boundary condition; the sea surface temperature field can either be kept constant in time or allowed to vary in some prescribed manner, e.g., according to a diurnal cycle.