The true
test of climate models, hence of the CO2 hypothesis, will be in how well they predict data not yet seen.
We'll likely revisit this topic, as it is a long - standing critique from climate skeptics and an important
test of climate models.
In fact, the true
test of climate models is paleoclimate reconstruction, in which they have been rather successful.
Have there been any «classic»
tests of climate models that would falsify the hypothesis of large warming over the long term?
There are limited observational data to start with, insufficient
testing of climate model simulations of extremes, and (so far) limited assessment of model projections.
A realistic
test of a climate model would be to initialize it to conditions around 1850 - 1880 (which would mean making multiple runs with random starting data) and see if the average model outputs follow the measured trend from 1900 onwards.
Now I want just to point out that this paper is an example of, how difficult it is to have good empirical
tests of climate models.
Not exact matches
CA Department
of Food and Agriculture awards CSWA a $ 450,000 grant for a four - year project to drive
climate protection and innovation through field
testing a carbon offset and greenhouse gas emissions
model for California wine grape growers (2010)
The researchers were able to
test their hypothesis that stronger winds were driving the ocean heat uptake by putting the observations
of wind behavior into
climate models.
Instead, this effect could be used to
test climate models, he said, to check if their physics is good enough to reproduce how the pull
of the moon eventually leads to less rain.
«They are using this information to
test state -
of - the - art
climate models under conditions
of high atmospheric carbon dioxide concentrations, similar to those expected by the end
of this century.»
«These experiments will enable us to further
test and refine the underlying processes in the CORPSE
model and should lead to improved predictions
of the role
of plant - soil interactions in global
climate change,» Sulman said.
«Using data mining to make sense
of climate change: New methodology puts emphasis on data to
test climate models.»
At the Environmental Change Institute in Oxford, researchers Nathalie Schaller and Friederike Otto analysed results from almost 40,000
climate model calculations to
test the impact
of climate change on Britain's winter rains.
To
test his idea, Salzmann used a computer
model of the Earth system to find out how the
climate would react to a doubling
of the atmospheric carbon - dioxide concentration.
Bringing together observed and simulated measurements on ocean temperatures, atmospheric pressure, water soil and wildfire occurrences, the researchers have a powerful tool in their hands, which they are willing to
test in other regions
of the world: «Using the same
climate model configuration, we will also study the soil water and fire risk predictability in other parts
of our world, such as the Mediterranean, Australia or parts
of Asia,» concludes Timmermann.
A team
of scientists from Vanderbilt and Stanford universities have created the first comprehensive map
of the topsy - turvy
climate of the period and are using it to
test and improve the global
climate models that have been developed to predict how precipitation patterns will change in the future.
Instrumental measurements are also too short to
test the ability
of state -
of - the - art
climate models to predict which regions
of the hemisphere will get drier, or wetter, with global warming,» says Charpentier Ljungqvist.
«The new work improves our understanding
of history, allowing better
model tests and allowing better assessment
of how the ice responded to
climate changes in the past,» Alley said, «and this will help in making better and more - reliable projections for the future.»
The
models used for
testing the impact
of climate change combine the risks
of avalanche with local
climate data.
The challenge is to use this evidence to
test and improve the predictive skill
of climate models.»
Instead, Collins says that AI algorithms are best suited to help
test the next generation
of climate models.
These
tests can be conducted with the help
of computer
models that depict future demographic and economic development and that examine the interplay between industry and the
climate and other essential natural systems.
In order to understand how El Niño responds to various
climate forces, researchers
test model predictions
of past El Niño changes against actual records
of past ENSO activity.
Researchers at Chalmers University
of Technology have studied new ways
of measuring sea level that could become important tools for
testing climate models and for investigating how the sea level along the world's coasts is affected by
climate change.
No
climate model has ever been properly
tested, which is what «validation» means, and their «projections» are nothing more than the opinions
of «experts» with a conflict
of interest, because they are paid to produce the
models.
Does this mean that the hypothesis
of nuclear winter does not survive
testing by modern
climate models?
Tom appears challenged by the idea
of building global
climate models based on atmospheric physics and doing years
of testing those
models against actual data.
So, the key thing in evaluating
climate sensitivity is to use the LGM as a
test of how well the
models are doing clouds, using the LGM, and then see what happens in the same
model when you project to the future.
Climate models are being subjected to more comprehensive
tests, including, for example, evaluations
of forecasts on time scales from days to a year.
Indeed, Gore could have used the ice core data to make an additional and stronger point, which is that these data provide a nice independent
test of climate sensitivity, which gives a result in excellent agreement with results from
models.
One critical limitation is a paucity
of historical
tests of modeled human responses to
climate variability and
climate change.
The drug and alcohol
testing industry depends on this favorable legislative and regulatory
climate, because the industry was effectively created in 1986 by the Drug Free Workplace Act, and the Dept.
of Transportation rules serve as a
model for most
testing programs.
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All
of that stuff I listed off above does come at a price, but we have to keep in mind that our particular
test car is a Vsport Premium
model that packs a bunch
of other features like 20 - way adjustable front seats, a reconfigurable gauge cluster, your choice
of either real carbon fiber or wood cabin accents, color configurable head - up display, aluminum pedals, adaptive cruise control, front and rear automatic braking with collision preparation, a giant sunroof, tri-zone
climate controls, heated rear seats and fancier wheels.
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Toyota equips the Camry with a well - appointed interior from which to control this array
of tech; our
test model had heated leather seats, dual - zone
climate control, and a snazzy, digital instrument panel.
This
model has many valuable options - Leather seats - Backup Camera - Satellite Radio - Heated Front Seats - Auto
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Then there are the
tests of climate changes themselves: how does a
model respond to the addition
of aerosols in the stratosphere such as was seen in the Mt Pinatubo «natural experiment»?
While the various methods can be
tested with
climate model simulations, it would arguably be more satisfying if inferences could be obtained in a manner which bypasses the difficult issue
of calibration entirely, and also eliminates any need to establish the precise seasonality
of information reflected by the various available proxy records.
Climate models have passed a broad range
of validation
tests — e.g. a 30 - year warming trend, response to perturbations like ENSO and volcanic eruptions... On the other hand, in a statistical
model, parameters
of the
model are determined by a fit to the
model.
For
climate models, there is a much larger range
of tests available and there isn't necessarily an analogue for «persistence» in all cases.
Eventually, we will get a better idea
of how wide the spread
of climate model parameterisations can be while still passing the stringent valdiation
tests that state -
of - the - art
models must pass.
Understanding past
climate changes are
of course also very interesting — they provide
test cases for
climate models and can have profound implications for the history
of human society.
Climate modelers are very thankful for the existence
of the seasonal cycle, for providing such a beautiful data set with which we can
test a
models quantitative response to a well - defined change in external forcing.
We used it heavily as part
of a Global
Climate Processes course at UW - Madison for later undergrad and grad students, so it has a good deal
of flexibility in what you can
test (though the
model blows up for extreme forcings like snowball Earth, I used CO2 at about 140 ppm and couldn't get much lower than that).
A yet more stringent
test for realistic
climate sensitivity is the application
of a
model to a
climate with different CO2 levels.
We use the global cooling and drying
of the atmosphere that was observed after the eruption
of Mount Pinatubo to
test model predictions
of the
climate feedback from water vapor.
As a physics student very much used to operating on the «make prediction;
test prediction»
model of determining the reliability
of a theory, I appreciate thorough discussion
of realistic expectations for these
climate models.
Let's look at something a little later, something done in preperation for AR4 — plans
testing the incorporation
of the carbon cycle into
climate models.