Sentences with phrase «by uncertainties in the observations»

Not exact matches

Although some earlier work along similar lines had been done by other paleoclimate researchers (Ed Cook, Phil Jones, Keith Briffa, Ray Bradley, Malcolm Hughes, and Henry Diaz being just a few examples), before Mike, no one had seriously attempted to use all the available paleoclimate data together, to try to reconstruct the global patterns of climate back in time before the start of direct instrumental observations of climate, or to estimate the underlying statistical uncertainties in reconstructing past temperature changes.

If the predicted cooling by la Nina had not occurred then 2008 would probably have been the same temperature (given the uncertainties) as every year since 2001 and that in itself would require explanation.I am broadly in favour of the global warmingCO2 hypothesis but I know it is just that, a hypothesis — and that needs testing against real observations in the physical world.

* Indeed, possible errors in the amplitudes of the external forcing and a models response are accounted for by scaling the signal patterns to best match observations, and thus the robustness of the IPCC conclusion is not slaved to uncertainties in aerosol forcing or sensitivity being off.

*** «Perhaps concern over «uncertainty» in complex, adaptive, open systems should be investigated by inductive generalization from observations of the dynamics of a wide range of such systems: ecosystems, social systems, computer systems, immune systems, economic systems... It is curious that the following things are never admitted as «facts about the world,» but here goes: the observer would note of all of these systems that they undergo oscillations within apparent parameters and occasionally flip into new regimes; they often demonstrate novel emergence; and that increased forcing, whether of native elements or exotic ones, increases the rates of oscillation and catastrophic shifts, sometimes after a quieter period of sub-threshold build - up.

The high confidence level ascribed by the IPCC provides bootstrapped plausibility to the uncertain temperature observations, uncertain forcing, and uncertain model sensitivity, each of which has been demonstrated in the previous sections to have large uncertainties that were not accounted for in the conclusion.

In the mid 19th century the largest components of the uncertainty at annual time scales are the measurement and sampling uncertainty and the coverage uncertainty because there were few observations made by a small global fleet.

The measurement uncertainties account for correlations between errors in observations made by the same ship or buoy due, for example, to miscalibration of the thermometer.

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.»

Because the differences between the various observational estimates are largely systematic and structural (Chapter 2; Mears et al., 2011), the uncertainty in the observed trends can not be reduced by averaging the observations as if the differences between the datasets were purely random.

Climate science has been thrown into disarray by the hiatus, disagreement between climate model and instrumental estimates of climate sensitivity, uncertainties in carbon uptake by plants, and diverging interpretations of ocean heating (in the face of a dearth of observations).

In that case, if we have 10,000 observations in a year, the uncertainty on the annual average would be roughly 10 divided by the square root of 10,000, which is 0.1 degIn that case, if we have 10,000 observations in a year, the uncertainty on the annual average would be roughly 10 divided by the square root of 10,000, which is 0.1 degin a year, the uncertainty on the annual average would be roughly 10 divided by the square root of 10,000, which is 0.1 degC.

HYDRA will investigate the sensitivity to, and uncertainties in, rainfall, evaporation and river runoff to changes in land use and the carbon cycle by comparing models with observations from the last 50 years.

«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).»

The reasons for that are many: the timid language of scientific probabilities, which the climatologist James Hansen once called «scientific reticence» in a paper chastising scientists for editing their own observations so conscientiously that they failed to communicate how dire the threat really was; the fact that the country is dominated by a group of technocrats who believe any problem can be solved and an opposing culture that doesn't even see warming as a problem worth addressing; the way that climate denialism has made scientists even more cautious in offering speculative warnings; the simple speed of change and, also, its slowness, such that we are only seeing effects now of warming from decades past; our uncertainty about uncertainty, which the climate writer Naomi Oreskes in particular has suggested stops us from preparing as though anything worse than a median outcome were even possible; the way we assume climate change will hit hardest elsewhere, not everywhere; the smallness (two degrees) and largeness (1.8 trillion tons) and abstractness (400 parts per million) of the numbers; the discomfort of considering a problem that is very difficult, if not impossible, to solve; the altogether incomprehensible scale of that problem, which amounts to the prospect of our own annihilation; simple fear.

And this uncertainty is undoubtedly related to the high reliance on model simulations (rather than physical observations) and the poor parameterization of clouds in the models cited by IPCC.

let's take this to an extreme... suppose that internal variability is zero... then the «within group» s.d. is zero... suppose that models agree pretty well with each other and observations fall within the tight band of model projections... then by steve's method you create the average of models and call it a model... with an s.d. of zero... show that the model falls outside the observational s.d.... proclaim that the model fails... claim that this is a test of modelling... hence extrapolate that all models fail... even though observations fall slap bang in the model range... this result is nonsensical... per tco it isn't how models are used... where's structural uncertainty?

I, and evidently others who have posted at CA, have been at least somewhat surprised by the uncertainty in a number of conclusions coming out of climate science on the issue of AGW — and uncertainty that can be derived from some rather straight forward and simple analyses and observations.

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.

The uncertainties in global climate models vs empirical observations are equally great ranging from 10 C by 2100!

We consider uncertainties in the observations by using two independent datasets, listed in Table 3 of Y12.

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 did so by estimating monthly fluxes and their uncertainty over a one - year period between June 2009 and May 2010 from 1) observational data collected in existing networks of surface CO2 measurement sites (GLOBALVIEWCO2 2010; extrapolated to the year 2010) and 2) both the surface observations and column - averaged dry air mole fractions of CO2 (XCO2) retrieved from GOSAT soundings.