Starting in the late 1990s, big companies whose profits were tied to fossil fuels recognized they could use this journalistic practice to amplify the
inherent uncertainties in climate projections and thus potentially delay cuts in emissions from burning those fuels.
Years of results regarding secondary organic aerosols reduce uncertainty in climate projections
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.»
But, each data source also has a degree of
uncertainty in its climate projection,» says Heaton.
The AGU recognizes that the climate system is complex, and there are
uncertainties in climate projections that are made.
Given
the uncertainty in climate projections, there can be surprises that may cause more dramatic disruptions than anticipated from the most probable model projections.
The book does a good job of explaining
the uncertainties in the climate projections.
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.»
It is not likely that
the uncertainty in climate projections will be much reduced by adhering to the current paradigm of running ever more complex global climate models, and the desire to have a consensus may be discouraging new approaches.
A key problem for reducing
the uncertainty in climate projections is historical records of change are often too short to test the skill of climate models, raising concerns over our ability to successfully plan for the future.
The uncertainties in climate projections originate in the representation of processes such as clouds and turbulence that are not resolvable on the computational grid of global models.
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.»
«We used the MIT Integrated Global System Model (IGSM), which quantifies various sources of
uncertainty in climate projections,» Gao told environmentalresearchweb.
By the statistical evaluation of the different climate developments simulated,
the uncertainties in climate projections can be better estimated and reduced, for example, for rainfall trends.