Sentences with phrase «reduce modeling uncertainty»

The use of ensemble modeling framework enabled to reduce modeling uncertainty and present the local variation of the processes at unprecedented fine spatial resolution.

Doing so, I think, would reduce the model uncertainty.

Not exact matches

Candler's speech program was organized around a «linear - transmissions» model which arises from information theory, which can be stated as follows: «The essential feature of all messages is information, and people use the information in messages to reduce uncertainty and thereby adapt to the environment».

Reducing uncertainties in the models could lead to better long - term assessments of climate, Esposito says.

Further refinements in brown dwarf models should soon reduce that uncertainty, he says.

By improving the understanding of how much radiation CO2 absorbs, uncertainties in modelling climate change will be reduced and more accurate predictions can be made about how much Earth is likely to warm over the next few decades.

«A cloud system - resolved model can reduce one of the greatest uncertainties in climate models, by improving the way we treat clouds,» Wehner said.

A new integrated climate model developed by Oak Ridge National Laboratory and other institutions is designed to reduce uncertainties in future climate predictions as it bridges Earth systems with energy and economic models and large - scale human impact data.

A new integrated computational climate model developed to reduce uncertainties in future climate predictions marks the first successful attempt to bridge Earth systems with energy and economic models and large - scale human impact data.

By providing new data on how CO2 cycles through land and ocean plants, HIPPO will allow researchers to improve the accuracy of their climate models and reduce that uncertainty, Stephens said.

PNNL researchers play a key role in reducing uncertainty through improved process understanding and modeling of climate processes such as clouds and aerosols.

Understanding how well climate models represent these processes will help reduce uncertainties in the model projections of the effects of global warming on the world's water cycle.

But Bowman believes the team has taken the necessary steps — such as reducing and modeling their uncertainties and calibrating their instruments properly — to be confident their measurement is actually a link to the distant past.

By linking imaging methods to rock physics, and by discovering, understanding and modelling relations to other geological data, we will reduce the uncertainty associated with exploration through cover.

As climate models become increasingly complex, it becomes extremely challenging to reduce uncertainty.

Scientific knowledge input into process based models has much improved, reducing uncertainty of known science for some components of sea - level rise (e.g. steric changes), but when considering other components (e.g. ice melt from ice sheets, terrestrial water contribution) science is still emerging, and uncertainties remain high.

If we can get climate models to more credibly simulate current cloud patterns and observed cloud changes, this might reduce the uncertainty in future projections

And although there is a midsize Alfa crossover apparently coming in the first quarter of 2017 (nine months behind schedule), reduced R&D spending because of «uncertainties» in China and a desire to focus on Jeep products have slightly derailed the brand's plans for eight new models by 2018.

Available on all models, Pro Backup Trailer Assist reduces uncertainty when parking a tandem trailer or camper.

[Response: If you screen the models to have surface trends similar to that observed, you do reduce the tropospheric range of responses, but error bars still overlap with the uncertainty in the obs.

This greatly reduces the uncertainty in the overall radiosonde mean, and implies that the model uncertainty dominates in the calculation of (sigma - means).

In their rejoinder MW claim they didn't agree with reducing the data set to 59 as follows: «the application of ad hoc methods to screen and exclude data increases model uncertainty in ways that are unmeasurable and uncorrectable.»

The work of Schmittner et al. demonstrates that climates of the past can provide potentially powerful information to reduce uncertainty in future climate predictions and evaluate the likelihood of climate change that is larger than captured in present models.

It is expected that an appropriately designed research program, with emphasis on long - term observations and coupled climate modeling, would contribute to substantially reduce uncertainty about the future evolution of the AMOC.

I was wondering for some time now, how much the findings of the work of scientists, be it the IPCC, be it the PIK in Potsdam or what have you, can be taken for granted in order for policy makers to make valuable decisions (e.g. cutting carbon emissions by half by 2050) and if the uncertainties in the models might outweigh certain decisions to reduce carbon emissions so that in the end it might happen that these uncertainties make these decisions obsolete, because they do not suffice to avoid «dangerous climate change»?

New understanding on the essential mechanisms and simple analytical models can help us to reduce the uncertainty on cloud responses and feedbacks.

To reduce uncertainties in climate - change projections, it is essential to prioritize the improvement of the most important uncertain physical processes in climate models.

Although the age model gives some uncertainty in the timings, it appears that storminess increased at the onset and close of North Atlantic cold events associated with oceanic changes, with reduced storm activity at their peak.

The global Aerosol Model Intercomparison project, AeroCom, has also been initiated in order to improve understanding of uncertainties of model estimates, and to reduce them (Kinne et al., 2Model Intercomparison project, AeroCom, has also been initiated in order to improve understanding of uncertainties of model estimates, and to reduce them (Kinne et al., 2model estimates, and to reduce them (Kinne et al., 2003).

In other words, the analysis neglects structural uncertainty about the adequacy of the assumed linear model, and the parameter uncertainty the analysis does take into account is strongly reduced by models that are «bad» by this model - data mismatch metric.

reduce uncertainties of fossil coral reconstructions by replication studies and numerical modeling.

Climate predictions do not depend exclusively on models, but the models reduce the levels of quantitative uncertainty.

I agree that the application of higher resolution model equipment does not help to reduce the uncertainty range of the sea level in the Amsterdam harbours: assumptions about changes in the heat storage, icecap melting and changes in the gravity field dominate this uncertainty range (although some regiona features related to oceanic circulation and heat redistribution may be better resolved in higher resolution models).

Improving the scientific understanding of all climate feedbacks is critical to reducing the uncertainty in modeling the consequences of doubling the CO2 - equivalent concentration.

• Reduce uncertainty, make ever more complex models • Tools: quantification, Monte Carlo, Bayesian belief networks

As regional modeling gains skill it should be able to reduce uncertainty and direct resources in a more focused way on those assets at greatest risk of loss, but no matter what the level of skill, the information they provide should not be ignored!

Over decades, improvements in observations of the present climate, reconstructions of ancient climate, and computer models that simulate past, current, and future climate have reduced some of the uncertainty in forecasting how rising temperatures will ripple through the climate system.

Leaving aside the possibility of sampling issues (we have to acknowledge that the number of model contributions is small), it is encouraging first to note that the uncertainty relative to both initial conditions / atmospheric forcing are systematically reduced as time goes by.

This general approach has been used before, for other aspects of climate system models, and has often significantly reduced overall uncertainty.

Innovative new approaches to climate data analysis, continued improvements in climate modeling, and instigation and maintenance of reference quality observation networks such as the U.S. Climate Reference Network (http://www.ncdc.noaa.gov/crn/) all have the potential to reduce uncertainties.

If the forcing uncertainty could be reduced by 1/2, most of the model diagnosed sensitivity values would (I think) be clearly much too high.

The optimal decision making model works in the following way: more research reduces uncertainty, which builds a scientific and political consensus that results in meaningful action.

Computer models (hansen's particularly for IPCC) are also used to reduce the uncertainty in the energy budget items.

In fairness, there remains considerable uncertainty in aerosol effects, but if there will be real progress in narrowing the credible range for climate sensitivity, it has to come from reducing the still too wide uncertainty in aerosol effects, not from flogging climate models which assume aerosol offsets inconsistent with the best available measured effects.

Reducing these uncertainties by improving models of the processes that cause ice sheets to lose mass is, therefore, a critical goal of Earth Science research.

The Process Study and Model Improvement (PSMI) Panel's mission is to reduce uncertainties in the general circulation models used for climate variability prediction and climate change projections through an improved understanding and representation of the physical processes governing climate and its variation.

Knowing that the spread in ECS is mostly related to uncertainties in low - cloud feedback, it seems obvious that constraining how low clouds respond to global warming can reduce the spread of climate sensitivity among models.

«Reducing the wide range of uncertainty inherent in current model predictions of global climate change will require major advances in understanding and modeling of both (1) the factors that determine atmospheric concentrations of greenhouse gases and aerosols, and (2) the so - called «feedbacks» that determine the sensitivity of the climate system to a prescribed increase in greenhouse gases.»

And beyond the post-facto model evaluation, it will be interesting to see whether new climate models will take advantage of emergent constraints to improve their simulation of present - day climate and to reduce uncertainties in future projections.

The Stadium Wave is actually a useful model (via the LOD measure) and allows us to reduce the uncertainty in the attribution of the atmospheric CO2 concentration to the current global temperature rise.