Sentences with phrase «physical model results»

The results look a lot like physical model results.

Not exact matches

Until now, there have always been separate physical models for threads and spheres, which would predict in each case whether the resulting solution would be liquid or glassy.

Random fluctuations and three physical reasons come into question to explain this: The model calculations are based on different amounts of radiant energy from the sun that impinge on Earth's surface and are stored as a result of the greenhouse effect, e.g. due to atmospheric carbon dioxide.

«Our modeling results suggest that the physical aspects of the kelp — its sheer size and its presence, the shade that it casts, its effect on flow and the habitat it provides for predators — affect the reef ecosystem more than its productivity,» Miller said.

Physicists look for results inconsistent with those predicted by the Standard Model to expand knowledge of the physical world — but that didn't happen here.

«Our theoretical model helped us decipher the experimental results and fully understand the physical mechanism governing defect motion,» said Pearce, «but also allowed us to go beyond the current experimental evidence.»

The team has already used results from their technique to create a new model for the way particulate matter behaves, which is concurrently published in the journal Physical Review E.

The models also include the greenhouse gas emissions and other pollutants that result from these processes, and they incorporate all of that information within a global climate model that simulates the physical and chemical processes in the atmosphere, as well as in freshwater and ocean systems.

The results, which appear in the January Physical Review D, also constitute the Standard Model's most stringent test to date, says Knuteson, who has since left active research.

So far, these early results showed that physical conditions where the air and the ocean interact must be a vital part of any successful hurricane forecasting model and would help explain, and predict, how a storm might intensify as it moves through across the water based on the physical stress at the ocean's surface.

«This would seem to refute — or at least make less likely — models in which the behavior effects are the result of direct physical action of parasites on specific parts of the brain,» Eisen wrote in a blog post about the research.

Using conjoined results of carbon - cycle and physical - climate model intercomparison projects, we find the median time between an emission and maximum warming is 10.1 years.»

This is in accord with physical expectations and most model results, which demonstrate the role of increasing greenhouse gases in tropospheric warming and stratospheric cooling; ozone depletion also contributes substantially to stratospheric cooling.

In their work examining intergranular attack of alloys under hydrothermal conditions, scientists from PNNL's ACMD Division Computational Mathematics group, Physical Sciences Division, and Energy and Environment Directorate developed a mathematical model that is directly comparable to experimental data in predicting how fast oxygen penetrates binary alloys and the resulting depletion of select elements in the materials that leads to failures.

The integrative medical model of medicine understands that healing can occur on many levels (physical, emotional / feelings, mental / thoughts and beliefs, etc.) and disease and stress may be the result of underlying imbalances.

In further models, the association with 2 - year incidence attenuated but the association with 5 - year incidence remained (Table 3) and further adjustments for BMI, central obesity and physical health (not shown) resulted in an OR for highest vs. lowest tertile of: 1.23, 95 % CI: 1.02, 1.48, P for trend = 0.03.

Adding other factors, such as assay batch, family history of breast cancer, age at menarche, breastfeeding, physical activity, childhood BMI, smoking, drinking status, and intake of fat and fiber into the multivariable model did not change the result appreciably, but reduced the precision.

As a result, I intend to tie a reality constructed and modeled from representations and the virtual world of pictorial illusion with the physical interactive space created by the painting's materials and hypnotic conditions.

It's something of an abstract concept, but with real world implications, and the universality of such physical models, based on things like radiative balance, atmospheric composition and density, distance from the local Sun, etc., is a very strong argument in favor of general acceptance of the results of climate models and observations on Earth.

They do this by seeing whether the same result is seen in other simulations, with other models, whether it makes physical sense and whether there is some evidence of similar things in the observational or paleo record.

So, a validated climate model would be one that takes in all the physical environment data it should have and omits all the data it shouldn't have, and then is able to processes the data in the proper sequences etc. to produce true results.

From what is written about the models, even the scientists running them admit the effects of those are really just estimates, not results from first physical principles.

Here we present results from Byrne & Schneider (2016) in which we combine basic theory and idealised climate - model simulations to investigate the physical processes determining the width of the ITCZ and its sensitivity to climate change.

The mistake so obvious to a trained physical scientist and so ubiquitous among climate modelers: the inability or unwillingness to perform physical reliability analyses on their model results.

Authors concludes that — to the extent that we have simple plausible physical arguments that support the model consensus — we believe that one should have nearly as much confidence in these results as one has in the increase in temperature itself

I would be interested to see a range of results based on a plausible range of the free parameters, constrained where possible by physical models of the underlying phenomena.

Scientists that evaluate climate models, develop physical process parameterizations, and utilize climate model results are convinced (at least to some degree) of the usefulness of climate models for their research.

Nearly all physical measurements that are collected in large quantities are based on models relating some output (usually electrical current or voltage) to some input, and the model results are evidence of the quantity of the measured attribute.

In contrast to climate models, which can only approximate the physical processes and may exclude important processes, the empirical result includes all processes that exist in the real world — and the physics is exact.

When we wish to infer about alternative physical models we must study, how consistent they are with the empirical result is taking all uncertainties of the empirical analysis into account.

I won't repeat what I said on an earlier forum, but a quick look at Paul Williams» presentation on numerical errors in climate modeling shows a host of issues that would lead me to assign a rather high uncertainty to the model results, and then we have the uncertainties in the physical models themselves.

Yet tracking down its origin is difficult — it seems to have originated by fitting a log formula to some numerical results from a radiative forcing model, not from the analytical solution of a physical model.

Why isn't a TCR type of simulation, but instead using actual history and 200 year projected GHG levels in the atmosphere, that would produce results similar to a TCR simulation (at least for the AGW temp increase that would occur when the CO2 level is doubled) and would result in much less uncertainty than ECS (as assessed by climate model dispersions), a more appropriate metric for a 300 year forecast, since it takes the climate more than 1000 years to equilibrate to the hypothesized ECS value, and we have only uncertain methods to check the computed ECS value with actual physical data?

«But to make sure whether it's just an outlier, or really some reliable physical result, you have to check other models.»

This inconsistency between model results and observations could arise either becaise «real world» amplification effects on short and long term time scales are controlled by different physical mechanisms, and models fail to capture such behavior, or because non-climatic influences remaining in some or all of the observed tropospheric datasets lead to biased long - term trends, or a combination of these factors.

No, then because you are using a model and correlating the results of the model to the time series, which is why you need physical models of course:)

Several steps have been carried out in various workshops and meetings resulting in a compilation of relevant physical effects, a general modeling framework, a first compilation of important terminology, and handbook chapter structure.

Scientists will use data from other field campaigns to determine which set of physical and chemical representations in the models produce results more consistent with observations and why.

As we have extensively documented in, Roy Spencer has a propensity for performing curve fitting exercises with a simple climate model by allowing its parameters to vary without physical constraints, and then making grandiose claims about his results.

To be valid RCP 8.5 would need to have some relevance in order to consider policy based on it's results, fudging models to produce results with parameters that have no bearing on the real physical world is pointless.

His research results have been published in the Journal of Physical Oceanography, the Journal of Geophysical Research, the Journal of Climate, Monthly Weather Review, Geophysical Research Letters, Ocean Modeling, Deep Sea Research, and other scientific journals.

Our approach has been to develop two models with different ocean dynamical / physical cores while keeping all other components the same in order to test the sensitivity of our results to our assumptions inherent in our ocean configuration.

The fact of the matter is that IPCC has relied in AR4 on models, which assume a strongly positive net feedback from clouds, while subsequent physical observations show that the primary impact of clouds with warming is increased albedo and higher SW reflection resulting in an overall negative cloud feedback.

The model needs to properly reflect the underlying physical structure in order to have any chance at an end result that is meaningful with properly estimated parameters and measures of uncertainty for those parameters.

Because climate changes result from dynamic interactions between the oceans and the atmosphere, collaborations between sedimentologists, geochemists, marine geologists, paleontologists, planetary scientists, and physical oceanographers will be necessary to develop, test, and calibrate reliable models using the sedimentary record (e.g., Kutzbach, 1987).

Finally, it is therefore inescapable that: if the official GAST data from NOAA, NASA and Hadley CRU are invalid, then both the «basic physical understanding» of climate and the associated climate models will also be invalid — resulting in tens of billions in wasted climate research funding.

«Our confidence in our conclusion... is based on the fact that the results of the radiative - convective and heat - balance model studies can be understood in purely physical terms and are verified by the more complex GCM's.

Answer: The growing confluence of model results and the increasingly similar physical representations of the climate system from model to model may well look like sharing code or tweaking'til things look alike.

... the results depend on the statistical model used, and more complex models are not as transparent and often lack physical realism.

What type of physical model would yield these results?