Sentences with phrase «feedback uncertainties in climate models»

Dufresne, 2005: Marine boundary - layer clouds at the heart of tropical cloud feedback uncertainties in climate models.

Not exact matches

«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.

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 regioIn 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 regioin Lauer et al. (2009) to simulate clouds and cloud — climate feedbacks in the tropical and subtropical eastern Pacific regioin the tropical and subtropical eastern Pacific region.

They got 10 pages in Science, which is a lot, but in it they cover radiation balance, 1D and 3D modelling, climate sensitivity, the main feedbacks (water vapour, lapse rate, clouds, ice - and vegetation albedo); solar and volcanic forcing; the uncertainties of aerosol forcings; and ocean heat uptake.

However, in view of the fact that cloud feedbacks are the dominant contribution to uncertainty in climate sensitivity, the fact that the energy balance model used by Schmittner et al can not compute changes in cloud radiative forcing is particularly serious.

«Cloud climate feedback constitutes the most important uncertainty in climate modelling, and currently even its sign is still unknown.

They got 10 pages in Science, which is a lot, but in it they cover radiation balance, 1D and 3D modelling, climate sensitivity, the main feedbacks (water vapour, lapse rate, clouds, ice - and vegetation albedo); solar and volcanic forcing; the uncertainties of aerosol forcings; and ocean heat uptake.

Differences between high and low projections in climate models used by the IPCC stem mainly from uncertainties over feedback mechanisms - for example, how the carbon cycle and clouds will react to future warming.

A new study by Prof Jason Lowe and Dr Dan Bernie at the UK's Met Office Hadley Centre takes these CMIP5 models and tries to account for additional uncertainties in the carbon budget associated with feedbacks, such as carbon released by thawing of permafrost or methane production from wetlands, as a result of climate change.

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

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.

But we know that the mechanisms responsible for the variation of Ts are different in internal variability on these time scales and in forced climate change, then my questions is that: is it possible that the spread in ECS might not be so directly caused by low - cloud feedback, although the low cloud feedback is a very good indictor for the model uncertainty?

«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.»

Although the first two sources of model uncertainty - different climate sensitivities and regional climate change patterns - are usually represented in climate scenarios, it is less common for the third and fourth sources of uncertainty - the variable signal - to - noise ratio and incomplete description of key processes and feedbacks - to be effectively treated.

Second, the IPCC clearly states «models [of sea level rise] used to date do not include uncertainties in climate - carbon cycle feedbacks nor do they include the full effect of changes in ice sheet flow.»

In a broad sense this arises both from the social uncertainty about whether and when mitigation efforts will be agreed and achieved, as well as from the scientific uncertainty about how the many feedbacks in the Earth system operate, arising from imperfect climate modelling, the role of tipping points [9] and other limits to our understanding of the systeIn a broad sense this arises both from the social uncertainty about whether and when mitigation efforts will be agreed and achieved, as well as from the scientific uncertainty about how the many feedbacks in the Earth system operate, arising from imperfect climate modelling, the role of tipping points [9] and other limits to our understanding of the systein the Earth system operate, arising from imperfect climate modelling, the role of tipping points [9] and other limits to our understanding of the system.

However, some carbon cycle feedbacks are either poorly represented or omitted from climate models because of uncertainties in their underlying biological and geological processes.

``... the amplitude and even the sign of cloud feedbacks was noted in the TAR as highly uncertain, and this uncertainty was cited as one of the key factors explaining the spread in model simulations of future climate for a given emission scenario.

Although the most advanced theoretical climate models still leave uncertainty, particularly about the sign and magnitudes of the effects, on GHG feedbacks, of some low - and high - clouds, a consensus began to develop that threats of resulting increases in global temperature — and the very large risks associated with their possible consequences — deserved substantial increase in attention.

Feedbacks involving low - level clouds remain a primary cause of uncertainty in global climate model projections.