Sentences with phrase «climate modelling uncertainty»

The primary consequence of considering this alternative paradigm is to narrow the climate modelling uncertainty.

Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly.

Some discussion is provided on how to practically estimate the climate modelling uncertainty based on an ensemble of opportunity.

Tim Palmer's presentation was superb and very relevant to our discussions of climate model uncertainty.

This is where the understanding of climate modeling uncertainty is lost in the scientific communications to the public by the politicians and vocal advocates that drive climate change discussions.

More complete exploration of climate model uncertainty, including unknowns and model structural uncertainty

Our estimates of key climate model uncertainties are constrained by observations of the climate system for the period 1906 - 1995, 7 and uncertainty in emissions reflect errors in measurement of current emissions and expert judgment about variables that influence key economic projections.

Using Multiple Diagnostics in Climate Change Detection to Assess Climate Model Uncertainty.

Not exact matches

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.

Modeling future climate scenarios is a notoriously tricky science, involving wide margins of uncertainty, myriad variables and a profusion of data.

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.

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).

Any detailed, careful reading of the climate models includes a great deal of uncertainty.

The uncertainty associated with future climate projections linked to economic possibilities of what people will do is far larger than the uncertainty associated with physical climate models.

Using a hierarchical model, the authors combine information from these various sources to obtain an ensemble estimate of current and future climate along with an associated measure of uncertainty.

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.

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

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

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 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.

But calculating the fraction of warming is a far more contentious task, points out climatologist Stephen H. Schneider of Stanford University, because of the inherent uncertainty and variability of climate models.

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

Gary Geernaert, director of DOE's Climate and Environmental Sciences Division, states that «it is critical that federal investments to advance climate science for use by both public and private stakeholders must place significant priority on incorporating uncertainty quantification methodologies into modeling framClimate and Environmental Sciences Division, states that «it is critical that federal investments to advance climate science for use by both public and private stakeholders must place significant priority on incorporating uncertainty quantification methodologies into modeling framclimate science for use by both public and private stakeholders must place significant priority on incorporating uncertainty quantification methodologies into modeling frameworks.

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.

That uncertainty is represented in the latest crop of global climate models, which assume a climate sensitivity of anywhere from about 3 to 8 degrees F.

Those data, to be collected this year and next, could improve climate models, which account poorly for these atmospheric interactions and contain «horrific» uncertainties about the levels and behaviour of water vapour at stratospheric altitudes, Austin says.

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.

«The model we developed and applied couples biospheric feedbacks from oceans, atmosphere, and land with human activities, such as fossil fuel emissions, agriculture, and land use, which eliminates important sources of uncertainty from projected climate outcomes,» said Thornton, leader of the Terrestrial Systems Modeling group in ORNL's Environmental Sciences Division and deputy director of ORNL's Climate Change Science Insclimate outcomes,» said Thornton, leader of the Terrestrial Systems Modeling group in ORNL's Environmental Sciences Division and deputy director of ORNL's Climate Change Science InsClimate Change Science Institute.

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.

As can be seen your graph, our climate models make a wide range of predictions (perhaps 0.5 - 5 degC, a 10-fold uncertainty) about how much «committed warming» will occur in the future under any stabilization scenario, so we don't seem to have a decent understanding of these processes.

Oppenheimer and his co-authors use a technique known as «structured expert judgment» to put an actual value on the uncertainty that scientists studying climate change have about a particular model's prediction of future events such as sea - level rise.

«New tool puts a consistent value on experts» uncertainty on climate change models.»

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.

In order to evaluate this uncertainty, Lauer et al. (2010) used 16 GCMs and the International Pacific Research Center (IPRC) Regional Atmospheric Model (iRAM) described in Lauer et al. (2009) to simulate clouds and cloud — climate feedbacks in the tropical and subtropical eastern Pacific region.

I would agree that unforeseen changes in ocean circulation could throw off model predictions, there are surely other wildcards too, but uncertainty like that is not your friend if you want to argue against avoiding climate change.

Leung and Qian also participate in the North American Climate Change Assessment Program to use multiple global and regional climate models to better quantify uncertainties in projecting climate Climate Change Assessment Program to use multiple global and regional climate models to better quantify uncertainties in projecting climate climate models to better quantify uncertainties in projecting climate climate change.

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

Click here for Part II, an accounting of Exxon's early climate research; Part III, a review of Exxon's climate modeling efforts; Part IV, a dive into Exxon's Natuna gas field project; Part V, a look at Exxon's push for synfuels; Part VI, an accounting of Exxon's emphasis on climate science uncertainty.

After the field campaign, Fast will perform computer simulations to help evaluate all of the field campaign data and quantify the uncertainties associated with using coarse grid global climate models to study megacity emissions and to determine the radiative impact of the Mexico City particulates on the local and regional climate.

Throughout its climate modeling phase, Exxon researchers, like outside scientists, grappled with the uncertainties inherent in climate model projections.

But while Lewis argues that the uncertainty in E is large and climate models do not give the value as accurately as we'd like, that does not justify ignoring that uncertainty entirely.

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.

One of the largest uncertainties in global climate models (GCMs) is the response of clouds in a warming world.

These current uncertainties are also reflected in future climate projections by these models.