Sentences with phrase «climate system parameters»

Until the climate science community routinely uses noninormative priors for Bayesian studies of climate system parameters, the results of many of those studies are likely to be significantly biased.

Not exact matches

Murali Haran, a professor in the department of statistics at Penn State University; Won Chang, an assistant professor in the department of mathematical sciences at the University of Cincinnati; Klaus Keller, a professor in the department of geosciences and director of sustainable climate risk management at Penn State University; Rob Nicholas, a research associate at Earth and Environmental Systems Institute at Penn State University; and David Pollard, a senior scientist at Earth and Environmental Systems Institute at Penn State University detail how parameters and initial values drive an ice sheet model, whose output describes the behavior of the ice sheet through time.

So the reference system climate sensitivity parameter is based on a negative feedback due to Stefan's law.

Another approach uses the response of climate models, most often simple climate models or Earth System Models of Intermediate Complexity (EMICs, Table 8.3) to explore the range of forcings and climate parameters that yield results consistent with observations (Andronova and Schlesinger, 2001; Forest et al., 2002; Harvey and Kaufmann, 2002; Knutti et al., 2002, 2003; Forest et al., 2006).

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There may be reason to strongly suspect that in any sufficiently complicated dynamical system model (such as climate) with stochastic parameters (e.g., exactly when and where a lightning strike starts a major wildfire or a major submarine earthquake perturbs ocean circulation in a region or a major volcanic eruption introduces stratospheric aerosols), it is almost certain that any given run of the model will have periods of significant deviation from the mean of multiple runs.

For many key parameters, the climate system is already moving beyond the patterns of natural variability within which our society and economy have developed and thrived.

The working hypothesis is that even if the climate system may have the possibility of long - term chaos, it is nonetheless more like William's example of what happens when you change a parameter of the Lorentz model, than it is like the problem of predicting a single day's weather a year ahead.

The climate system is all the main physical parameters which together with physics and chemistry cause weather and its average & variance.

Often, the proximate cause of the climate change is some parameter of the climate system that can be set off from the general collective behavior of the system and considered as a «given,» even if it is not external to the system strictly speaking.

No reasonable person would consider the CO2 as independent bifurcation parameter since the CO2 is continously produced and consumed in large quantities within the «climate - generating» system depending upon interplay of other variables.

Although such methods estimate climate system properties indirectly, the models concerned, unlike AOGCMs, have adjustable parameters controlling those properties that, at least in principle, are calibrated in terms of those properties and which enable the entire parameter space to be explored.

In recent years one of the most important methods of estimating probability distributions for key properties of the climate system has been comparison of observations with multiple model simulations, run at varying settings for climate parameters.

The GTP metric requires knowledge of the same parameters as the GWP metric (radiative efficiency and lifetimes), but in addition, the response times for the climate system must be known, in particular if the lifetime of component x is very different from the lifetime of the reference gas.

These parameters are guesses, because there just isn't enough understanding of the complex and chaotic climate system to parse out their different values, or to even be clear about cause and effect in certain processes (like cloud formation).

The forcings consist of the external parameters that drive the state of the climate system and would, for the future, consist of educated guesses.

So, all other things been equal, if the only parameter we change in the climate system is to double the level of atmospheric CO2, then the IPCC says that the earth will warm by about one degree.

Agree with you there Jim C. Climate time series data is like economic time series in that the system is non-ergodic and that any parameters from this are non repeating and unpredictable.

Hi charles d, You should not be suspicious that it is extremely difficult to reconstruct climate changes that occured long before anyone was around to measure and observe the multitude of parameters involved in a complex, dynamic system.

We revisit a recent claim that the Earth's climate system is characterized by sensitive dependence to parameters; in particular, that the system exhibits an asymmetric, large - amplitude response to normally distributed feedback forcing.

At a recent debate at Oxford University, organized by the OU Engineering Society, I gave the undergraduates an argument from process engineering (which you will find in outline in my Union College presentation, and in more detail in my Hartford College lecture) to the effect that the closed - loop temperature - feedback gain in the climate system (i.e., the product of the Planck parameter and the net sum of all unamplified feedbacks) can not much exceed 0.1, implying at most 1.3 K of warming per CO2 doubling, compared with the IPCC's central estimate of 3.3 K.

I think the climate system is the exact same, and by having enormous forcings, we're going out of the «design parameters» of the control system, with unknown consequences.

Climate sensitivity is then defined mathematically as the derivative of an appropriate functional or other function of the systems state with respect to the bifurcation parameter.

The primary triggers for ice ages and inter-glacials are well understood to be changes in the astronomical parameters related to the motion of our planet within the solar system and natural feedback processes in the climate system.

«Climate sensitivity is then de fined mathematically as the derivative of an appropriate functional or other function of the systems state with respect to the bifurcation parameter.

«These model - based studies provide invaluable insight into the functioning of the climate system, because it is possible to vary processes and parameters independently, thus examining the role and importance of different climate mechanisms.

With one such «control parameter» one could control exactly one property of the climate system, for example, the global mean temperature or the temperature in China or the rainfall in the United States.

Climate, like all science outside of perhaps basic chemistry and physics, operates in an open system where you can never prevent changes in other parameters.

Using the University of Victoria Earth System Climate Model adapted to include a permafrost response module, the researchers calculated the contribution to climate warming of thawing permafrost over a range of varying paraClimate Model adapted to include a permafrost response module, the researchers calculated the contribution to climate warming of thawing permafrost over a range of varying paraclimate warming of thawing permafrost over a range of varying parameters.

«The assessment is supported additionally by a complementary analysis in which the parameters of an Earth System Model of Intermediate Complexity (EMIC) were constrained using observations of near - surface temperature and ocean heat content, as well as prior information on the magnitudes of forcings, and which concluded that GHGs have caused 0.6 °C to 1.1 °C (5 to 95 % uncertainty) warming since the mid-20th century (Huber and Knutti, 2011); an analysis by Wigley and Santer (2013), who used an energy balance model and RF and climate sensitivity estimates from AR4, and they concluded that there was about a 93 % chance that GHGs caused a warming greater than observed over the 1950 — 2005 period; and earlier detection and attribution studies assessed in the AR4 (Hegerl et al., 2007b).»

«Climate sensitivity is then defi ned mathematically as the derivative of an appropriate functional or other function of the systems state with respect to the bifurcation parameter.

The NCAR Community Climate System model 20th century simulations for CMIP5 (Gent et al. 2011) arguably qualifies as a completely forward calculation, with forcing data sets being selected a priori and no tuning of parameters to the 20th century climate other than the sea ice albedo and the low cloud relative humidity thrClimate System model 20th century simulations for CMIP5 (Gent et al. 2011) arguably qualifies as a completely forward calculation, with forcing data sets being selected a priori and no tuning of parameters to the 20th century climate other than the sea ice albedo and the low cloud relative humidity thrclimate other than the sea ice albedo and the low cloud relative humidity threshold.

In UKCIP08, for example, we are handling this problem by combining results from two different types of ensemble data: One is a systematic sampling of the uncertainties in a single model, obtained by changing uncertain parameters that control the climate system; the other is a multi-model ensemble obtained by pooling results from alternative models developed at different international centers.