Sentences with phrase «predictive understanding of»

Observational records of tropical storm and hurricanes are essential in order to discern how climatic changes have influenced tropical storms and hurricanes, and to build predictive understanding of the influence of climate on hurricanes.

Correcting this situation requires a predictive understanding of the processes responsible for land ice loss.

Their research is one of the first papers published in association with a new Department of Energy project called the Next - Generation Ecosystem Experiment (NGEE - Arctic), which seeks to gain a predictive understanding of the Arctic terrestrial ecosystem's feedback to climate.

Natural buoyancy variability may be beyond our capacity to measure accurately or sample adequately, but it contains important information about cause and effect that is essential if we are to gain a predictive understanding of the atmosphere.»

Blaser et al. (2016) Toward a predictive understanding of Earth's microbiomes to address 21st century challenges.

«It implied a deep mechanistic and predictive understanding of how mass extinctions unfold that I wasn't sure we actually had.»

Its influence on infectious disease is considered by Altizer and colleagues, who use examples from a wide range of host - pathogen systems to assess whether we are close to a predictive understanding of climate - disease interactions and their potential future shifts.

Not exact matches

«Most reputable data firms are using proven predictive modeling techniques on an individual level, whereas Cambridge was guilty of using fancy fake science terms on unwitting politicians who do not understand how data analytics work.

In contrast to claims being made for his technology in the 2014 contract, Kogan himself claimed in a TV interview earlier this month (after the scandal broke) that his predictive modeling was not very accurate at an individual level — suggesting it would only be useful in aggregate to, for example, «understand the personality of New Yorkers».

They understood this word not merely as predictive of their future.

This is too complex an issue to discuss here, but I would submit that if understanding rather than prediction is the goal of science, models can not be replaced by predictive mathematical formalisms.

*** Note - Click Here to read an ESPN article about predictive modeling and how millions have been made, to get a better understanding of what we do!

Dignity is understood to be much more than just the absence of humiliation and in its wholesome sense is far more predictive of the sustainability of societies.

Let's first give a very brief sketch of some of the main preoccupations of post-war liberal economic theory, which sought to understand the actual behaviour of economic agents under conditions of scarcity through the creation of predictive models.

This special section of Science focuses on the current state of knowledge about the effects of climate change on natural systems, with particular emphasis on how knowledge of the past is helping us to understand potential biological impacts and improve predictive power.

In order to improve the predictive power of climate models, it is now crucial to understand the biological processes in the soil better, say the scientists.

These kinds of maps have been attempted before, but how does this type of predictive mapping inform our understanding of, say, a particular strain of influenza?

The better understanding provided by MMS will help researchers to forecast where increases in reconnection occur and what flow of particles can get in, Burch says: «We'll have lots of predictive capability.»

«More importantly, such understanding would significantly improve our predictive ability of battery lifetime, which is of extremely high value to an electric car manufacturer,» Strmcnik added.

FIRST aims to develop scientific understanding and validated, predictive models of the nanoscale environment at fluid — solid interfaces important in electrical energy storage and electrocatalysis.

«We hypothesized that this might explain why laboratory mice, while paramount for understanding basic biological phenomena, are limited in their predictive utility for modeling complex diseases of humans and other free - living mammals,» said Rosshart.

Another major ethical challenge results from the variability in the predictive value of genotypic information and how such information can be used to inform risk management policy when our understanding of risk is inexact.

Insufficient observations and understanding impede the development of robust predictive skills regarding ocean acidification and impacts.

Jiacan Yuan is a climatologist who is interested in understanding the fundamental dynamical processes in the atmosphere and improving climate models, which could give us better predictive power and risk assessment of the changing climate.

Noteworthy is the establishment of a 20 + year long - term times series of lobster larval settlement in the US and Atlantic Canada; seeking to develop predictive tools for lobster population trends through an understanding of pre - and post-settlement processes.

His research explores the influence of live fuels on wildland fire behavior and it also explores ways to use this improved understanding to develop predictive tools that can help support strategic and tactical wildland fire management decisions.

In RA, a new understanding of the natural history of the disease has emerged demonstrating the presence of highly predictive patterns of RA - related autoantibodies prior to the onset of arthritis.

Understanding how this changes over time in conjunction with genetic analysis may permit the generation of predictive tools to identify patients at risk of developing cancer and those that are not.

The results could lead to better predictive models to inform future decisions about energy production and use, and a better understanding of changes in the climate.

This framework will be built upon available open - source deep learning platforms that can be adapted to address different aspects of the cancer process as represented by JDACS4C's challenge topics: 1) understand the molecular basis of key protein interactions; 2) develop predictive models for drug response; and 3) automate the extraction and analysis of information from millions of cancer patient records to determine optimal cancer treatment strategies.

«Understanding the stabilizing mechanisms of the turbulence is definitely an important task in order to gain a predictive capability in the design of future fusion reactors,» said Ruiz.

Natural variability is primarily controlled by exchange of heat between the ocean and the atmosphere, but it is an extremely complex process and if we want to develop better near - term predictive skills — which is looking not at what's going to happen in the next three months but what's going to happen between the next year and 10 years or 20 years or so — if we want to expand our understanding there, we have to understand natural variability better than we do today.

Through a research - validated predictive assessment that identifies which students are at risk and why; research - based curricula that guides students to understand the importance of education and set attainable goals; and comprehensive professional development, ScholarCentric ensures that all students have the support, knowledge and confidence they need to be successful in school and beyond.

MGLS: 2017 has been designed to foster an understanding of the development and learning that occur during students» middle grades years and that are predictive of future success, along with the individual, social, and contextual factors that are related to positive outcomes.

Since student perception data is empirically linked to and predictive of academic outcomes, understanding students» experiences in their K - 12 classes can give educators and school leaders rapid feedback to inform instructional practices.

Rob, understood, regarding the predictive power of CAPE, indices and individual stocks.

Now, of these three models that need to be taken into consideration if you want to understand where the market may go, unfortunately the valuation thought model is the least predictive.

The cats and dogs in the long tail of the distribution deserve further analysis, since understanding what features are predictive of a long wait for a new home might lead to new strategies for accelerating their adoptions.

eg pg xii To improve our predictive capability, we need: • to understand better the various climate - related processes, particularly those associated with clouds, oceans and the carbon cycle • to improve the systematic observation of climate - related variables on a global basis, and further investigate changes which took place in the past • to develop improved models of the Earth's climate system • to increase support for national and international climate research activities, especially in developing countries • to facilitate international exchange of climate data

About 1980ish, some old ideas like the greenhouse effect were brought out of mothballs and re-examined with new tools and techniques; simultaneously several researchers and theoreticians released their notes, published, or otherwise got together and there was a surprising consilience and not a small amount of mixing with old school hippy ecologism on some of the topics that became the roots of Climate Change science (before it was called Global Warming); innovations in mathematics were also applied to climate thought; supercomputers (though «disappointing» on weather forecasting) allowed demonstration of plausibility of runaway climate effects, comparison of scales of effects, and the possibility of climate models combined with a good understanding of the limits of predictive power of weather models.

Otherwise the work risks being regarded as one more statistics - driven model, of innumerably many already published in the literature, that in the long run (for the reasons that George Box explains) have yielded little in the way of deeper climate understanding and predictive confidence.

The «stadium wave» as a partial systemic or meta explanation of the natural evoultion of climate affecting factors is an intersting, cogent and logical step to understanding this sort of thing — it might mot be right, but at least it's an attempt, even if it will take years or decades to determine if it's on the right track and what other factors need to be added / removed to make it an effective and usefully predictive tool.

I take this to mean that climate models are not predictive mechanisms but seek to further our understanding of the climate system using real historical data.

«understand that the entire catastrophic AGW case is built on the outputs of heavily parameterized (a.k.a. tuned) GCMs which have never demonstrated any predictive skill.

Throughout its life, the USGCRP has created and maintained a mix of atmospheric, oceanic, land, and space - based observing systems; gained new theoretical knowledge of Earth System processes; advanced understanding of the complexity of the Earth System through predictive modeling; promoted advances in computational capabilities, data management, and information sharing; and developed and harnessed an expert scientific workforce.

Thus, physical processes such as vertical and isopycnal mixing that drive large scale circulations need to be better understood to improve the predictive capability and accuracy of the models.

Identify new sources of predictive skill and improve predictions of weather, water, and climate through observations, understanding, and modeling of physical processes and phenomena of the coupled Earth system.

Given such a challenge, risk assessment would depend more on our predictive understanding and process - based probabilistic prediction than on statistical early warning signs of approaching a tipping point.

If you're measuring something historically and doing a predictive analysis based on the past, why would you need an understanding of climate science — at all?

The response of storms, blocks and jet streams to external forcing, basin - to - basin and tropical — extratropical interactions, and non-linear predictive theory, are highlighted as strategic areas to advance understanding of regional climate dynamics