Sentences with phrase «of uncertainty in climate projections»

They include those items ignored, glossed over, or deliberately misrepresented; projections are consistently wrong; the science has not advanced, a 2007 paper in Science by Roe and Baker concludes; «The envelope of uncertainty in climate projections has not narrowed appreciably over the past 30 years, despite tremendous increases in computing power, in observations, and in the number of scientists studying the problem»; and claims of impending disasters that simply do not make scientific sense.

«We used the MIT Integrated Global System Model (IGSM), which quantifies various sources of uncertainty in climate projections,» Gao told environmentalresearchweb.

Also, a very large source of uncertainty in climate projections is the unknown future development of emissions, land use and solar activity.

By Dr. Tim Ball It is not surprising that Roe and Baker explained in a 2007 Science paper that, «The envelope of uncertainty in climate projections has not narrowed appreciably over the past 30 years, despite tremendous increases in computing power, in observations, and in the number of scientists studying the problem.»

The natural climate variability induced by the low - frequency variability of the ocean circulation is but one of the causes of uncertainties in climate projections.

Not exact matches

We've narrowed the uncertainty in surface warming projections by generating thousands of climate simulations that each closely match observational records for nine key climate metrics, including warming and ocean heat content.»

An important goal of climate research is to reduce and characterize uncertainty in the climate change projections so that they can be more useful for assessing climate change impacts and developing adaptation and mitigation strategies.

Their survey uncovered significant uncertainties in current climate projections of the intensity and vertical structure of the low - level convergence of moisture to and upper - level divergence of heat away from the tropics.

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.

In the end the improvement of climate projections depends upon reducing both sources of uncertainty and arriving at joint probability profiles.

Much of the uncertainty in projections of global climate change is due to the complexity of clouds, aerosols, and cloud - aerosol interactions, and the difficulty of incorporating this information into climate models.

Scientists are using airborne observations of atmospheric trace gases, aerosols, and cloud properties from the North Slopes of Alaska to improve their understanding of global climate, with the goal of reducing the uncertainty in global and regional climate simulations and projections.

Prior to joining ECI, she completed her Ph.D. at Oregon State University, where she worked on the weather@home project over western US region, looking at drivers of extreme drought events in the US, future regional climate change projections over the western US, as well as investigating uncertainties due to internal variability and physical parameter perturbations.

It is not all that earthshaking that the numbers in Schmittner et al come in a little low: the 2.3 ºC is well within previously accepted uncertainty, and three of the IPCC AR4 models used for future projections have a climate sensitivity of 2.3 ºC or lower, so that the range of IPCC projections already encompasses this possibility.

The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state - dependent» http://www.pnas.org/content/110/35/14162.full

(in general, whether for future projections or historical reconstructions or estimates of climate sensitivity, I tend to be sympathetic to arguments of more rather than less uncertainty because I feel like in general, models and statistical approaches are not exhaustive and it is «plausible» that additional factors could lead to either higher or lower estimates than seen with a single approach.

In the end the improvement of climate projections depends upon reducing both sources of uncertainty and arriving at joint probability profiles.

The study of past warm climates may not narrow uncertainty in future climate projections in coming centuries because fast climate sensitivity may itself be state - dependent» http://www.pnas.org/content/110/35/14162.full

By putting the local climate into the context of the larger picture, analyzing the uncertainties, and evaluating the methods in terms of past changes, I think that local climate projections can provide useful information.

When I invoked 1944 and 1975 as being potentially (at least demonstrated to be possible) climate turning points which could be repeated today, I was trying to address the degree of uncertainty that could exist in our projections.

Projections of future climate changes in different emissions - scenarios are accompanied by error - bars representing the range of uncertainty.

I note that any reasonable climate change class should highlight appropriate sources of uncertainties (e.g., in future projections of hurricane changes, cloud feedbacks, etc) and I prefer when they open up discussing to students, but I find that Judith carries this further into making up uncertainties based on her gut feeling, interpreting them in ways that make little sense, and most importantly, failing to recognize the errors in flawed sets of reasoning on fundamental topics.

In fact, uncertainties in how clouds change with warming are the primary source of the large spread in climate projections for the next century (Bony and Dufresne 2005; Vial et al. 2013; Brient and Schneider 2016In fact, uncertainties in how clouds change with warming are the primary source of the large spread in climate projections for the next century (Bony and Dufresne 2005; Vial et al. 2013; Brient and Schneider 2016in how clouds change with warming are the primary source of the large spread in climate projections for the next century (Bony and Dufresne 2005; Vial et al. 2013; Brient and Schneider 2016in climate projections for the next century (Bony and Dufresne 2005; Vial et al. 2013; Brient and Schneider 2016).

In a previous post, I described the concept of emergent constraints, which allow us to narrow uncertainties in climate change projections through empirical relationships that relate a model's climate response to observable metricIn a previous post, I described the concept of emergent constraints, which allow us to narrow uncertainties in climate change projections through empirical relationships that relate a model's climate response to observable metricin climate change projections through empirical relationships that relate a model's climate response to observable metrics.

To reduce uncertainties in climate - change projections, it is essential to prioritize the improvement of the most important uncertain physical processes in climate models.

The sensitivity of the climate system to an imposed radiative imbalance remains the largest source of uncertainty in projections of future anthropogenic climate change.

Contribution from working group I to the fifth assessment report by IPCC TS.5.4.1 Projected Near - term Changes in Climate Projections of near - term climate show small sensitivity to Green House Gas scenarios compared to model spread, but substantial sensitivity to uncertainties in aerosol emissions, especially on regional scales and for hydrological cycle varClimate Projections of near - term climate show small sensitivity to Green House Gas scenarios compared to model spread, but substantial sensitivity to uncertainties in aerosol emissions, especially on regional scales and for hydrological cycle varclimate show small sensitivity to Green House Gas scenarios compared to model spread, but substantial sensitivity to uncertainties in aerosol emissions, especially on regional scales and for hydrological cycle variables.

The best example I've found of clear thinking about how to develop strategies for dealing with the uncertainties that inevitably arise when moving from the abstract to the specific is contained in the UK Climate Projections report of 2009 on London.

Data from our «eyes» in space allow us to verify our simulations of past and current climate, which, in turn, helps us reduce uncertainties in projections of future climate,» said Josh Fisher, a co-author on the study who works at NASA's Jet Propulsion Laboratory in a release.

In this way the climate scientists can ensure that the projections are understood with their associated uncertainties, and the impacts / adaptation researchers can ensure that the climate scientists are aware of the parts of the climate system they are most sensitive to, providing a focus for climate model development efforts.

Eli, Yet again we see an»em ergent pattern» in climate science: no compromise, little discussion of uncertainty, and most of all, no possibility that the projections of doom are horribly wrong.

Of course, this relies on the uncertainty in the regional TYPE 4 climate projection OF CHANGES IN CLIMATE STATISTICS IN THE COMING DECADES being small enough for the information to be useful in a risk assessment procesOf course, this relies on the uncertainty in the regional TYPE 4 climate projection OF CHANGES IN CLIMATE STATISTICS IN THE COMING DECADES being small enough for the information to be useful in a risk assessment procesin the regional TYPE 4 climate projection OF CHANGES IN CLIMATE STATISTICS IN THE COMING DECADES being small enough for the information to be useful in a risk assessment pclimate projection OF CHANGES IN CLIMATE STATISTICS IN THE COMING DECADES being small enough for the information to be useful in a risk assessment procesOF CHANGES IN CLIMATE STATISTICS IN THE COMING DECADES being small enough for the information to be useful in a risk assessment procesIN CLIMATE STATISTICS IN THE COMING DECADES being small enough for the information to be useful in a risk assessment pCLIMATE STATISTICS IN THE COMING DECADES being small enough for the information to be useful in a risk assessment procesIN THE COMING DECADES being small enough for the information to be useful in a risk assessment procesin a risk assessment process.

In his talk, «Statistical Emulation of Streamflow Projections: Application to CMIP3 and CMIP5 Climate Change Projections,» PCIC Lead of Hydrological Impacts, Markus Schnorbus, explored whether the streamflow projections based on a 23 - member hydrological ensemble are representative of the full range of uncertainty in streamflow projections from all of the models from the third phase of the Coupled Model Intercomparison ProjecIn his talk, «Statistical Emulation of Streamflow Projections: Application to CMIP3 and CMIP5 Climate Change Projections,» PCIC Lead of Hydrological Impacts, Markus Schnorbus, explored whether the streamflow projections based on a 23 - member hydrological ensemble are representative of the full range of uncertainty in streamflow projections from all of the models from the third phase of the Coupled Model IntercomparisProjections: Application to CMIP3 and CMIP5 Climate Change Projections,» PCIC Lead of Hydrological Impacts, Markus Schnorbus, explored whether the streamflow projections based on a 23 - member hydrological ensemble are representative of the full range of uncertainty in streamflow projections from all of the models from the third phase of the Coupled Model IntercomparisProjections,» PCIC Lead of Hydrological Impacts, Markus Schnorbus, explored whether the streamflow projections based on a 23 - member hydrological ensemble are representative of the full range of uncertainty in streamflow projections from all of the models from the third phase of the Coupled Model Intercomparisprojections based on a 23 - member hydrological ensemble are representative of the full range of uncertainty in streamflow projections from all of the models from the third phase of the Coupled Model Intercomparison Projecin streamflow projections from all of the models from the third phase of the Coupled Model Intercomparisprojections from all of the models from the third phase of the Coupled Model Intercomparison Project.

In the second part, the downscaling methods were used to make projections of future climate extremes, which were then examined for consistency and to determine the contribution of individual factors, such as choice of downscaling method and climate model, to the overall uncertainty.

Uncertainty... whether a blip in the Five Year Plan or fifteen year projections in weather, even predictions of April's showers by climate modellers in cloud towers.

«uncertainty» (in the IPCC attribution of natural versus human - induced climate changes, IPCC's model - based climate sensitivity estimates and the resulting IPCC projections of future climate) is arguably the defining issue in climate science today.

These examples demonstrate that the IPCC both cited Hulme et al. (2001) and transparently discussed the complexity of Africa's climate and the uncertainty in African climate projections.

Abstract The purpose of this review - and - research paper is twofold: (i) to review the role played in climate dynamics by fluid - dynamical models; and (ii) to contribute to the understanding and reduction of the uncertainties in future climate - change projections.

Analyses of tide gauge and altimetry data by Vinogradov and Ponte (2011), which indicated the presence of considerably small spatial scale variability in annual mean sea level over many coastal regions, are an important factor for understanding the uncertainties in regional sea - level simulations and projections at sub-decadal time scales in coarse - resolution climate models that are also discussed in Chapter 13.

But then came Climategate plus the revelation of IPCC screw - ups and, with them, the growing suspicion that the «science» had been «cooked» — or, at least, that IPCC had understated uncertainties in the attribution of climate change as well as in the projections for the future.

Uncertainty in natural climate drivers, for example how much solar output will change over this century, also affects the accuracy of projections.

Uncertainty in climate sensitivity is a main source of uncertainty in projections of future climUncertainty in climate sensitivity is a main source of uncertainty in projections of future climuncertainty in projections of future climate change.

There are several major sources of uncertainty in making projections of climate change.

Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear obser - vational constraint that favors one version of the authors» model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.»

N (3) The computer climate models are not reliable or consistently accurate, and projections of future climate states are little more than speculation as the uncertainty and error ranges are enormous in a non-linear climate system.

As it is now the matter of uncertainty of the projections is handled in an absurd way by the Intergovernmental Panel on Climate Change (IPCC).

However, there remains uncertainty in the rate of sea ice loss, with the models that most accurately project historical sea ice trends currently suggesting nearly ice - free conditions sometime between 2021 and 2043 (median 2035).12 Uncertainty across all models stems from a combination of large differences in projections among different climate models, natural climate variability, and uncertainty about future rates of fossil fueluncertainty in the rate of sea ice loss, with the models that most accurately project historical sea ice trends currently suggesting nearly ice - free conditions sometime between 2021 and 2043 (median 2035).12 Uncertainty across all models stems from a combination of large differences in projections among different climate models, natural climate variability, and uncertainty about future rates of fossil fuelUncertainty across all models stems from a combination of large differences in projections among different climate models, natural climate variability, and uncertainty about future rates of fossil fueluncertainty about future rates of fossil fuel emissions.

• Reduce uncertainties in climate change projections by applying experimental design to make more efficient use of computational resources.

The Process Study and Model Improvement (PSMI) Panel's mission is to reduce uncertainties in the general circulation models used for climate variability prediction and climate change projections through an improved understanding and representation of the physical processes governing climate and its variation.

Since then, despite a massive improvement in models and in our understanding of the mechanisms of climate change, the uncertainty in our projections of temperature change has stubbornly refused to narrow (Houghton et al. 2001).