Sentences with phrase «scale climate prediction»

317 (2007); N.S. Keenlyside, M. Latif, J. Jungclaus, L. Kornblueh, and E. Roeckner, «Advancing Decadal - Scale Climate Prediction in the North Atlantic Sector,» Nature, Vol.

Keenlyside, N. S., Latif, M., Jungclaus, J., Kornblueth, L. & Roeckner, E. Advancing decadal - scale climate prediction in the North Atlantic sector.

Advancing decadal - scale climate prediction in the North Atlantic Sector, Nature, 453, 84 - 88.

Part of the basis for the Mail's claims appears to be Latif et al's 2008 Nature paper, Advancing decadal - scale climate prediction in the North Atlantic sector.

Not exact matches

Martin King hopes that renewed interest in the seasonal variation of El Niño tele - connections in Europe will contribute to further progress in climate predictions on monthly and seasonal scales.

«Based on what we've found, it is possible that sea - level rise over decadal time scales will be a key storyline in future climate predictions,» he said.

Predictions of weather and climate for months, seasons and decades ahead lie between normal weather forecasts and climate projections for the coming century — concerning both what influences the climate on these time - scales, and the methods required to make such pPredictions of weather and climate for months, seasons and decades ahead lie between normal weather forecasts and climate projections for the coming century — concerning both what influences the climate on these time - scales, and the methods required to make such predictionspredictions.

To get some idea of what climate change will likely mean for the reefs, the World Heritage Centre asked coral experts at NOAA and elsewhere to produce what they claim is a first of its kind study «that scientifically quantifies the scale of the issue, makes a prediction of where the future lies, and indicates effects up to the level of individual sites,» says Fanny Douvere, marine program coordinator at the center.

Better predictions would require improved climate - measurement tools, more sophisticated climate models that work on regional scales, and a better organized system to integrate all the data, the report concludes.

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.

Scientists are involved in the evaluation of global - scale climate models, regional studies of the coupled atmosphere / ocean / ice systems, regional severe weather detection and prediction, measuring the local and global impact of the aerosols and pollutants, detecting lightning from space and the general development of remotely - sensed data bases.

SPARC, together with others in the WCRP community, focuses on understanding atmospheric dynamics and climate variability to provide better climate predictions on scales from seasonal all the way to centennial.

A new buzz - word is the concept of «seamless prediction», in which predictions ranging from nowcasting all the way to future scenarios are provided with a sliding time scale and that doesn't make distinction of incremental types such as «weather forecasts» «seasonal predictions» and «climate scenarios».

A few climate models have been tested for (and shown) capability in initial value predictions, on time scales from weather forecasting (a few days) to seasonal forecasting (annual).

Claiming that the forced climate response must be larger than the weather noise for climate prediction on all time scales is just silly.

For the future, data assimilation might help us to keep the state of a climate model closer to the real world's, allowing us to improve predictions on seasonal and decadal time scales.

For weather predictions, accuracy disappears within a few weeks — but for ocean forecasts, accuracy seems to have decadal scale accuracy — and when you go to climate forcing effects, the timescale moves toward centuries, with the big uncertainties being ice sheet dynamics, changes in ocean circulation and the biosphere response.

The National Oceanic and Atmospheric Administration's Climate Prediction Center in May projected between a dozen and 16 named storms, including 2 to 5 major hurricanes (those above Category 3 on the Saffir - Simpson scale of storm strength).

that climate models can not account for the observations we already have let alone make adequate predictions about what will happen in the future.that century - scale variations in tropical Pacific climate modes can significantly modulate radiatively forced shifts in global temperature.»

Comparing model predictions of GHG - induced warming with recent natural temperature fluctuations also indicates the potential scale of man - made climate change.Early modelling experiments focused on the total long - term change resulting from a doubling of carbon dioxide (CO2) levels.

There has been a recent emphasis in decadal - scale prediction, and also creating a marriage between climate and fields such as synoptic - dynamic meteorology... something relatively new (and a different sort of problem, than say, estimating the boundary condition change in a 2xCO2 world); as Susan Solomon mentioned in her writing, a lot of people have become much more focused on the nature of the «noise» inherent within the climate system, something which also relates to Kevin Trenberth's remarks about tracking Earth's energy budget carefully.

A Global Climate Model (GCM) can provide reliable prediction information on scales of around 1000 by 1000 km covering what could be a vastly differing landscape (from very mountainous to flat coastal plains for example) with greatly varying potential for floods, droughts or other extreme events.

This, given the climate change requirements, and technology cost forecasts for wind and solar, the emergence of battery storage and home management systems, as well as solar thermal plus storage at utility scale, not to mention the fuel cost of coal and gas, and the financing risk attached to that, seems an extraordinary prediction.

At the heart of this new perspective is the realization that all climate system predictions, regardless of time scale, share common processes and mechanisms; moreover, interactions across time and space scales are fundamental to the climate system itself.

The potential benefits of this commonality are significant and include improved predictions on all time scales and stronger collaboration and shared knowledge, infrastructure, and technical capabilities among those in the weather and climate prediction communities...

Stainforth explained how climate modellers are told policymakers need local and regional scale predictions for 40 years ahead to enable them to plan mitigation and adaptation.

Can the models provide skillful predictions of changes in regional climate statistics on multi-decadal time scales?»

Their work encompasses a range of problems and time scales: from five - day model predictions of hurricane track and intensity, to understanding the causes of changes in extremes over the past century, to building new climate prediction models for seamless predictions out to the next several years, to earth system model projections of human - caused changes in various extremes (heat waves, hurricanes, droughts, etc.) over the coming century.

To discuss gaps in current knowledge and identify areas where advances in fire prediction can be made over the next decade, the Columbia University Initiative on Extreme Weather and Climate, with support from the Center for Climate and Life, hosted the Fire Prediction Across Scales conference from October 23 — 25, 2017 in New prediction can be made over the next decade, the Columbia University Initiative on Extreme Weather and Climate, with support from the Center for Climate and Life, hosted the Fire Prediction Across Scales conference from October 23 — 25, 2017 in New Prediction Across Scales conference from October 23 — 25, 2017 in New York City.

Prediction Continued improvements in modeling decadal - scale dynamics — and longer, when ice - sheet and deep - ocean dynamics are included — will continue to affirm the multi-decade arc of strong climate science that concludes «Hansen's worldview is right.»

Review the development of atmospheric models for use in weather prediction and climate studies on all scales, including the diagnosis of shortcomings.

There are some source of predictability that are still not fully resolved (including those dealing with improving climate models, but also related to unexplored initial conditions or driving conditions), and a great benefit of these predictability studies is that they mimic the practice of weather prediction by confronting models with observations at the relevant time and spatial scales, leading to the necessary inspiration for this model improvement.

Projections of these changes of risk using models in which changes in the background climate are incorporated, and applied using models that do a fair job at the short time scale (like high resolution weather prediction, or hydrological discharge, or...) is thus a viable procedure, and does yield added value.

A climate prediction focuses at the predictable time scale, which depends a lot on the spatial scope.

Roger states that one can not consider climate model predictions (his type 4) at the regional scale when their predictive skill in hindcast mode is not demonstrated.

Pielke and Wilby (2012) discuss the lack of potential of RCMs to increase the skill of climate predictions at the regional scale.

As they have matured, climate models are being increasingly used to provide decision - relevant information to end users and policy makers, whose needs are helping define the focus of model development in terms of increasing prediction skill on regional and decadal time scales.

I agree that the ambition to make (regional) climate predictions even at decadal or longer time scales can not be supported by the current apparent feasibility, given the studies that demonstrate the lack of predictive skill.

However, to understand the large scale patterns in climate and their changes and drivers, climate models are not only useful, but increasingly necessary to make skillful predictions for the future.

The mechanics of the models produce regional scale results, but, until the multi-decadal regional predictions of changes in climate statistics can be shown to be skilful, the added spatial resolution provides an erroneous illusion of skill.

If we really want to know who's cherry picking data — land - based measurements vs geological time scales vs models, the answer is to create a betting market for climate prediction and get the people who think they know put their money where their mouths are.

Dynamic and statistical downscaling is widely used to refine predictions from global climate models to smaller spatial scales.

The missing variability in the models highlights the critical need to improve cloud modeling in the tropics so that prediction of tropical climate on interannual and decadal time scales can be improved.»

In this paper, af - ter a brief tutorial on the basics of climate nonlinearity, we provide a number of illustrative examples and highlight key mechanisms that give rise to nonlinear behavior, address scale and methodological issues, suggest a robust alternative to prediction that is based on using integrated assessments within the framework of vulnerability studies and, lastly, recommend a number of research priorities and the establishment of education programs in Earth Systems Science.

«The large - scale winds would look better because the release of latent heat drives a lot of those winds, and climate sensitivity would be better constrained because not only is the base state highly dependent on convective parameterization but the model predictions for future climate change are also very sensitive to that as well.»

The development of a fully coupled ocean - ice - atmosphere prediction system is a key issue for a better Outlook and for climate predictions on a decadal time scale.

The key is accurately representing the large - scale ocean circulation and associated heat transport in the climate models used to make the decadal predictions.

The improved robust and reliable forecasting can help meteorological and climate services to better deliver tailored predictions and advice, including sub-seasonal to seasonal time scales, will take Arctic climate prediction beyond seasons and to teleconnections over the Northern Hemisphere.

Weather is predictable for a week or so — initialised and nested models at different scales may be able to integrate weather into short term climate prediction.