Sentences with phrase «modelling uncertainty in»

By scaling spatio - temporal patterns of response up or down, this technique takes account of gross model errors in climate sensitivity and net aerosol forcing but does not fully account for modelling uncertainty in the patterns of temperature response to uncertain forcings.

Murphy, J.M., et al., 2004: Quantification of modelling uncertainties in a large ensemble of climate change simulations.

Statistics is all about modeling uncertainty in the world.

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.»

Not exact matches

Healthcare reforms will create significant uncertainty in long - term planning for 71.6 percent of franchisee respondents, and 10.4 percent agreed with the statement: «We are no longer confident that our business model is profitable.»

The model shown in the following painting attempts to diagram the three variables of Price, Expected Return and Uncertainty, resulting in a distribution of actual monthly returns shown at the bottom.

In their February 2017 paper entitled «Bayesian Model Averaging, Ordinary Least Squares and the Price of Gold», Dirk Baur and Brian Lucey analyze a large set of factors that potentially influence the price of gold via two methods: Ordinary Least Squares (OLS, scatter plot) and Bayesian Model Averaging (BMA, accounting for model uncertaiModel Averaging, Ordinary Least Squares and the Price of Gold», Dirk Baur and Brian Lucey analyze a large set of factors that potentially influence the price of gold via two methods: Ordinary Least Squares (OLS, scatter plot) and Bayesian Model Averaging (BMA, accounting for model uncertaiModel Averaging (BMA, accounting for model uncertaimodel uncertainty).

Risk is randomness in which events have measurable probabilities, wrote economist Frank Knight in 1921 in Meaning of Risk and Uncertainty.1 Probabilities may be attained either by deduction (using theoretical models) or induction (using the observed frequency of events).

These new discoveries as well as degrees of uncertainties has created a third monumental evolution in the use of persona development to inform strategies on the design of products and services, customer conversation, marketing, and business models that foster engagement with customers.

While many in the coworking industry have questioned WeWork's business model and staggering $ 20 billion dollar valuation, there seems to be no uncertainty within the flexible office industry of valuation and business prospects for Blackstone's new majority stake acquisition of The Office Group, «the pioneer of the shared workspace concept» in the United Kingdom.

Since the average error in a 2 - day forecast is about 90 miles, it is important to remember that the models may still have additional shifts, and one must pay attention to the NHC cone of uncertainty.

The assumptions that we make in running our models inject uncertainty throughout the policy - making process.

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».

It is against this background of a wider examination of religious models, initiated by a heightened doctrinal uncertainty, that I would enter a new version of religious humanism in the theological flesh market.

Personally I think the FiveThirtyEight team are right to allow for more uncertainty in their model.

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

Some of the largest uncertainties in current climate models stem from their wide - ranging estimates of the size and number of dust particles in the atmosphere.

This is because clouds have more - complex microphysics than the open sky, so even small errors in the models can cascade into large uncertainties in the forecast.

«It's safer to... be looking at the full range of uncertainty in the models rather than picking and choosing,» he said.

However, while they are valuable tools in a broad range of fields, predictive models are still plagued by uncertainties, or errors, and a great deal of effort is directed at determining the extent and effects of these errors.

«Model perfect: Researchers document new approach to dealing with uncertainties in mathematical models.»

Out of that came a system that models the multiple layers of uncertainty that occur in the processes of generating seismic events and in detecting them.

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

The method, called computational Bayesian phylogenetics, forces researchers to explicitly quantify the uncertainty in the models, says linguist Claire Bowern of Yale University, a pioneer of the approach and co-author of the new study.

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.

Animal models come with some uncertainty, cautions biochemist James Stevens of the Scripps Research Institute in La Jolla, Calif., but he says «it's probably the hemagglutinin switch which is going to be one of the critical events» in a future pandemic.

Therefore, Caldeira said, the more important question - and one of the largest sources of uncertainty in climate models - is «will the end of oil usher in a century of coal, or will it usher in a transition toward low - carbon - emitting technologies?»

Three approaches were used to evaluate the outstanding «carbon budget» (the total amount of CO2 emissions compatible with a given global average warming) for 1.5 °C: re-assessing the evidence provided by complex Earth System Models, new experiments with an intermediate - complexity model, and evaluating the implications of current ranges of uncertainty in climate system properties using a simple model.

Mission leaders were relieved and eager to begin their studies of cloud and haze effects, which «constitute the largest uncertainties in our models of future climate — that's no exaggeration,» says Jens Redemann, an atmospheric scientist at NASA's Ames Research Center in Mountain View, California, and the principal investigator for ObseRvations of Aerosols above CLouds and their IntEractionS (ORACLES).

While the uncertainty in the results from Jacobson's model and his own experiments is large, Ramanathan said he «wouldn't rule out that black carbon is the second - largest global warmer.»

She adds, however, that although there is good evidence that countershading acts as a defense mechanism, there will always be some uncertainty about interpreting countershading in dinosaurs, because we can't present a model Psittacosaurus to their natural predators to see which type of pattern provides the best protection.

The Standard Model of Physics predicts such one - in - ten - billion odds with an uncertainty of less than ten percent.

Its behaviour looks like what happens in the real world, but Erickson stresses that «the uncertainties remain large», and that much more work needs to be done before such models can be used to predict future climate trends.

At nearly a dozen other sites, the authors report, the chronological results are neither reliable nor valid as a result of significant statistical flaws in the analysis, the omission of ages from the models, and the disregard of statistical uncertainty that accompanies all radiometric dates.

It's a well - known fact that clouds are the major uncertainty in any climate model.

In her doctoral thesis, Henni Pulkkinen, Researcher at the Natural Resources Institute Finland (Luke), explored how the various sources of uncertainty can be taken into account in fisheries stock assessment by using Bayesian statistical models, which enable extensive combining of informatioIn her doctoral thesis, Henni Pulkkinen, Researcher at the Natural Resources Institute Finland (Luke), explored how the various sources of uncertainty can be taken into account in fisheries stock assessment by using Bayesian statistical models, which enable extensive combining of informatioin fisheries stock assessment by using Bayesian statistical models, which enable extensive combining of information.

An environmental modeler presents how the science works, but a decision scientist uses decision theory to take into account both the scientific information in a model and its uncertainty, and to help policymakers weigh that information against other factors, Crawford - Brown says.

Clouds also are the largest source of uncertainty in present climate models, according to the latest report of the Intergovernmental Panel on Climate Change.

In her doctoral thesis, Pulkkinen also discusses model uncertainty (structural uncertainty), which results from the fact that the phenomenon being researched can be explained with several — even contradicting — theories.

The paper is a technical analysis of the uncertainties involved in computer modeling studies that use the amount of phosphorus entering Lake Erie in the spring to predict the size of late - summer cyanobacteria blooms, which have grown larger since the mid-1990s.

Uncertainty about rain, little uncertainty about sea level rise Climate change could also affect precipitation in California, though the two models USGS used in its research produced differeUncertainty about rain, little uncertainty about sea level rise Climate change could also affect precipitation in California, though the two models USGS used in its research produced differeuncertainty about sea level rise Climate change could also affect precipitation in California, though the two models USGS used in its research produced different results.

A recent study in the Journal of Environmental Management carried out by researchers at the European Forest Institute and their partners in the FP7 funded MOTIVE project (Models for Adaptive Forest Management) discusses how forest managers and decision makers can cope with climate uncertainties.

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

In fact, cloud and mesoscale, or medium - scale, processes in the atmosphere are among the biggest uncertainties in today's climate models, Rasmussen saiIn fact, cloud and mesoscale, or medium - scale, processes in the atmosphere are among the biggest uncertainties in today's climate models, Rasmussen saiin the atmosphere are among the biggest uncertainties in today's climate models, Rasmussen saiin today's climate models, Rasmussen said.

For example, when examining hurricanes and typhoons, the lack of a high - quality, long - term historical record, uncertainty regarding the impact of climate change on storm frequency and inability to accurately simulate these storms in most global climate models raises significant challenges when attributing assessing the impact of climate change on any single storm.

She also explores the value of scientific thinking in our everyday lives, including the importance of scale, scientific modeling, uncertainty, and risk assessment.

However, he says, «Aerosol effects on climate are one of the main uncertainties in climate models.

By 2100, the choice of driving climate model conditions dominates the uncertainty, but by 2200, the uncertainty in the ice sheet model and the elevation scheme are larger.

The models take account of uncertainties in the quality of the fossil data and the reconstructed evolutionary tree, and the result was clear.

The BICEP2 team has now excluded that model from its analysis because of «unquantifiable uncertainty,» the researchers note in a footnote to their article.