«
Large uncertainties associated with estimates of past solar forcing (Section 2.7.1) and omission of some chemical and dynamical response mechanisms make it difficult to reliably estimate the contribution of solar forcing to warming over the 20th century.»
Large uncertainties associated with estimates of past solar forcing (Section 2.7.1) and omission of some chemical and dynamical response mechanisms (Gray et al., 2005) make it difficult to reliably estimate the contribution of solar forcing to warming over the 20th century.
Biological systems frequently have very
large uncertainties associated with them, much like the uncertainties reported in Bryden.
As I mentioned earlier, the observations are only consistnet with the models, because the models have such
a large uncertainty associated with them.
Not exact matches
But there is
uncertainty associated with all the forecasts and some forecasters are trying to estimate the extent of that
uncertainty, which in turn can be used to calculate probabilities of particular events (hung parliament,
largest party, etc..)
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.
But the
uncertainties associated with passing tipping points in the climate system are dangerously
large, the NRC committee finds.
The
large degree of
uncertainty associated with the effects of these policies logically led to a wide range of predictions from commentators and practitioners, including the downfall of the US dollar, rapidly rising inflation, and the build - up of a significant bubble in the Treasury bond market.
When comparing
with alternative models of plant physiological processes, we find that the
largest uncertainties are
associated with plant physiological responses, and then
with future emissions scenarios.
According to these researchers remaining
uncertainties are more in the realm of biology: «we find that the
largest uncertainties are
associated with plant physiological responses, and then
with future emissions scenarios.
While many scientists are optimistic about the prospects for such technology, there are still
uncertainties about the feasibility and cost of
large - scale storage, and also risks
associated with CO2 leakage.
Previous
large natural oscillations are important to examine: however, 1) our data isn't as good
with regards to external forcings or to historical temperatures, making attribution more difficult, 2) to the extent that we have solar and volcanic data, and paleoclimate temperature records, they are indeed fairly consistent
with each other within their respective
uncertainties, and 3) most mechanisms of internal variability would have different fingerprints: eg, shifting of warmth from the oceans to the atmosphere (but we see warming in both), or simultaneous warming of the troposphere and stratosphere, or shifts in global temperature
associated with major ocean current shifts which for the most part haven't been seen.
This ends up changing estimates of cumulative carbon emissions since the pre-industrial period, but given the
large uncertainties involved the authors caution against using these revisions to draw conclusions about remaining carbon budgets
associated with staying within the 2C or 1.5 C warming targets.
In short, the logic of mathematics is well equipped to deal
with large numbers of variables and the «
uncertainty»
associated with their relation e.g. multiple regression analysis.
This removes the need for a lot of work that must now be done (
with associated uncertainties) to estimate the «normal» temperature, but it makes the size of the regression very
large.
Indeed by producing
large ensembles, for multiple different emission scenarios, we do present the climate projections as a set of possible future climate risks,
with associated uncertainty.
When
uncertainty is very
large, an alternative for decision makers that is better than throwing the dice is to present a range of possible scenarios, each
associated with its story line (model or whatever).
In summary, our results show that in the CESM - LE, the range of
uncertainty in projected NAO trends and
associated influences on SAT and P over the next 30 years can be obtained to a
large degree from the Gaussian statistics of NAO variability during the historical period,
with some regional exceptions possibly
associated with AMOC variability.
The ISPM overview states: «Natural climatic variability is now believed to be substantially
larger than previously estimated, as is the
uncertainty associated with historical temperature reconstructions.»
There is no specific justification for the claim that «
uncertainty associated with historical temperature reconstructions» is
larger in TAR than in AR4, as no specific citation is given in the ISPM.
This range is
associated with uncertainty in the overlying
large - scale SLP regression pattern.
«However, Fig. 15 and the
associated uncertainties discussed in Section 3.4 show that long term estimates of time variable sea level acceleration in 203 year global reconstruction are significantly positive, which supports our previous finding (Jevrejeva et al., 2008a), that despite strong low frequency variability (
larger than 60 years) the rate of sea level rise is increasing
with time.»
There are significant risks, however,
associated with these technologies and approaches, including
uncertainty in their carbon retention, the consequences of
large - scale deployment, and costs and feasibility.
These experiments, however, often fail stringent quality checks and the
uncertainties associated with paleointensity data are generally
large (e.g., Donadini et al. 2010).
They include the difficulty of integrating
large amounts of renewable energy into the electricity system;
uncertainty on the timeline for meeting Renewables Portfolio Standards goals; environmental concerns
with the development of renewable facilities and
associated transmission; difficulty in securing project financing; delays and duplication in siting processes; time and expense of new transmission development; the cost of renewable energy in a fluctuating energy market; and maintaining the state's existing baseline of renewable facilities.
So far, it has only been possible to apply this test to the most recent termination because the dating
uncertainty associated with older terminations is too
large to allow phase relationships to be determined.
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.
Some key findings may be policy - relevant even though they are
associated with large uncertainties.
Some barristers are employed «in - house» at law firms and
large commercial organisations (such as the Government Legal Service), which takes away the
uncertainty associated with being self - employed and brings
with it regular income and benefits.