This is where the understanding of
climate modeling uncertainty is lost in the scientific communications to the public by the politicians and vocal advocates that drive climate change discussions.
Tim Palmer's presentation was superb and very relevant to our discussions of
climate model uncertainty.
Some discussion is provided on how to practically estimate
the climate modelling uncertainty based on an ensemble of opportunity.
Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly.
The primary consequence of considering this alternative paradigm is to narrow
the climate modelling uncertainty.
More complete exploration of
climate model uncertainty, including unknowns and model structural uncertainty
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.
Using Multiple Diagnostics in Climate Change Detection to Assess
Climate Model Uncertainty.
Not exact matches
Reducing
uncertainties in the
models could lead to better long - term assessments of
climate, Esposito says.
Some of the largest
uncertainties in current
climate models stem from their wide - ranging estimates of the size and number of dust particles in the atmosphere.
Modeling future
climate scenarios is a notoriously tricky science, involving wide margins of
uncertainty, myriad variables and a profusion of data.
By improving the understanding of how much radiation CO2 absorbs,
uncertainties in
modelling climate change will be reduced and more accurate predictions can be made about how much Earth is likely to warm over the next few decades.
Therefore, Caldeira said, the more important question - and one of the largest sources of
uncertainty in
climate models - is «will the end of oil usher in a century of coal, or will it usher in a transition toward low - carbon - emitting technologies?»
Three approaches were used to evaluate the outstanding «carbon budget» (the total amount of CO2 emissions compatible with a given global average warming) for 1.5 °C: re-assessing the evidence provided by complex Earth System
Models, new experiments with an intermediate - complexity
model, and evaluating the implications of current ranges of
uncertainty in
climate system properties using a simple
model.
Mission leaders were relieved and eager to begin their studies of cloud and haze effects, which «constitute the largest
uncertainties in our
models of future
climate — that's no exaggeration,» says Jens Redemann, an atmospheric scientist at NASA's Ames Research Center in Mountain View, California, and the principal investigator for ObseRvations of Aerosols above CLouds and their IntEractionS (ORACLES).
Any detailed, careful reading of the
climate models includes a great deal of
uncertainty.
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.
Using a hierarchical
model, the authors combine information from these various sources to obtain an ensemble estimate of current and future
climate along with an associated measure of
uncertainty.
Its behaviour looks like what happens in the real world, but Erickson stresses that «the
uncertainties remain large», and that much more work needs to be done before such
models can be used to predict future
climate trends.
It's a well - known fact that clouds are the major
uncertainty in any
climate model.
Clouds also are the largest source of
uncertainty in present
climate models, according to the latest report of the Intergovernmental Panel on Climate
climate models, according to the latest report of the Intergovernmental Panel on
Climate Climate Change.
Uncertainty about rain, little uncertainty about sea level rise Climate change could also affect precipitation in California, though the two models USGS used in its research produced differe
Uncertainty about rain, little
uncertainty about sea level rise Climate change could also affect precipitation in California, though the two models USGS used in its research produced differe
uncertainty about sea level rise
Climate change could also affect precipitation in California, though the two
models USGS used in its research produced different results.
A recent study in the Journal of Environmental Management carried out by researchers at the European Forest Institute and their partners in the FP7 funded MOTIVE project (
Models for Adaptive Forest Management) discusses how forest managers and decision makers can cope with
climate uncertainties.
«A cloud system - resolved
model can reduce one of the greatest
uncertainties in
climate models, by improving the way we treat clouds,» Wehner said.
In fact, cloud and mesoscale, or medium - scale, processes in the atmosphere are among the biggest
uncertainties in today's
climate models, Rasmussen said.
For example, when examining hurricanes and typhoons, the lack of a high - quality, long - term historical record,
uncertainty regarding the impact of
climate change on storm frequency and inability to accurately simulate these storms in most global
climate models raises significant challenges when attributing assessing the impact of
climate change on any single storm.
But calculating the fraction of warming is a far more contentious task, points out climatologist Stephen H. Schneider of Stanford University, because of the inherent
uncertainty and variability of
climate models.
However, he says, «Aerosol effects on
climate are one of the main
uncertainties in
climate models.
Gary Geernaert, director of DOE's
Climate and Environmental Sciences Division, states that «it is critical that federal investments to advance climate science for use by both public and private stakeholders must place significant priority on incorporating uncertainty quantification methodologies into modeling fram
Climate and Environmental Sciences Division, states that «it is critical that federal investments to advance
climate science for use by both public and private stakeholders must place significant priority on incorporating uncertainty quantification methodologies into modeling fram
climate science for use by both public and private stakeholders must place significant priority on incorporating
uncertainty quantification methodologies into
modeling frameworks.
By 2100, the choice of driving
climate model conditions dominates the
uncertainty, but by 2200, the
uncertainty in the ice sheet
model and the elevation scheme are larger.
That
uncertainty is represented in the latest crop of global
climate models, which assume a
climate sensitivity of anywhere from about 3 to 8 degrees F.
Those data, to be collected this year and next, could improve
climate models, which account poorly for these atmospheric interactions and contain «horrific»
uncertainties about the levels and behaviour of water vapour at stratospheric altitudes, Austin says.
A new integrated
climate model developed by Oak Ridge National Laboratory and other institutions is designed to reduce
uncertainties in future
climate predictions as it bridges Earth systems with energy and economic
models and large - scale human impact data.
«The
model we developed and applied couples biospheric feedbacks from oceans, atmosphere, and land with human activities, such as fossil fuel emissions, agriculture, and land use, which eliminates important sources of
uncertainty from projected
climate outcomes,» said Thornton, leader of the Terrestrial Systems Modeling group in ORNL's Environmental Sciences Division and deputy director of ORNL's Climate Change Science Ins
climate outcomes,» said Thornton, leader of the Terrestrial Systems
Modeling group in ORNL's Environmental Sciences Division and deputy director of ORNL's
Climate Change Science Ins
Climate Change Science Institute.
A new integrated computational
climate model developed to reduce
uncertainties in future
climate predictions marks the first successful attempt to bridge Earth systems with energy and economic
models and large - scale human impact data.
As can be seen your graph, our
climate models make a wide range of predictions (perhaps 0.5 - 5 degC, a 10-fold
uncertainty) about how much «committed warming» will occur in the future under any stabilization scenario, so we don't seem to have a decent understanding of these processes.
Oppenheimer and his co-authors use a technique known as «structured expert judgment» to put an actual value on the
uncertainty that scientists studying
climate change have about a particular
model's prediction of future events such as sea - level rise.
«New tool puts a consistent value on experts»
uncertainty on
climate change
models.»
By providing new data on how CO2 cycles through land and ocean plants, HIPPO will allow researchers to improve the accuracy of their
climate models and reduce that
uncertainty, Stephens said.
In order to evaluate this
uncertainty, Lauer et al. (2010) used 16 GCMs and the International Pacific Research Center (IPRC) Regional Atmospheric
Model (iRAM) described in Lauer et al. (2009) to simulate clouds and cloud —
climate feedbacks in the tropical and subtropical eastern Pacific region.
I would agree that unforeseen changes in ocean circulation could throw off
model predictions, there are surely other wildcards too, but
uncertainty like that is not your friend if you want to argue against avoiding
climate change.
Leung and Qian also participate in the North American
Climate Change Assessment Program to use multiple global and regional climate models to better quantify uncertainties in projecting climate
Climate Change Assessment Program to use multiple global and regional
climate models to better quantify uncertainties in projecting climate
climate models to better quantify
uncertainties in projecting
climate climate change.
PNNL researchers play a key role in reducing
uncertainty through improved process understanding and
modeling of
climate processes such as clouds and aerosols.
Click here for Part II, an accounting of Exxon's early
climate research; Part III, a review of Exxon's
climate modeling efforts; Part IV, a dive into Exxon's Natuna gas field project; Part V, a look at Exxon's push for synfuels; Part VI, an accounting of Exxon's emphasis on
climate science
uncertainty.
After the field campaign, Fast will perform computer simulations to help evaluate all of the field campaign data and quantify the
uncertainties associated with using coarse grid global
climate models to study megacity emissions and to determine the radiative impact of the Mexico City particulates on the local and regional
climate.
Throughout its
climate modeling phase, Exxon researchers, like outside scientists, grappled with the
uncertainties inherent in
climate model projections.
But while Lewis argues that the
uncertainty in E is large and
climate models do not give the value as accurately as we'd like, that does not justify ignoring that
uncertainty entirely.
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.
One of the largest
uncertainties in global
climate models (GCMs) is the response of clouds in a warming world.
These current
uncertainties are also reflected in future
climate projections by these
models.