Climate models are powerful tools that scientists use to study how the climate system works now and how it will change in the future under different scenarios of global warming. When models are updated with new scientific information, they must be evaluated to see how well they represent different climate features, including weather patterns found in particular geographical regions. 

A new study led by Graham Taylor, a Ph.D. student in Portland State's Earth, Environment, and Society program, and Paul Loikith, associate professor of geography at PSU, tested how well climate models represent large-scale weather patterns over the Pacific Northwest. Researchers from Oregon State University and the Jet Propulsion Laboratory also contributed to the study, which was published in the journal Climate Dynamics. 

“These complex computer models that simulate the Earth system can be thought of as virtual laboratories for climate science experimentation,” says Loikith. “If the models can't reproduce important features of the observed climate, they will not be very useful for studying the future climate.” 

Since all computer models have different strengths and weaknesses based on differences in physics, scientists often use the output from many different climate models to assess projections of future climate change. For this study, the researchers used data from the state-of-the-art sixth phase of the Coupled Model Intercomparison Project (CMIP6) to test how well 26 different climate models could simulate the range of large-scale patterns of atmospheric circulation (like wind and pressure) found over the Pacific Northwest. These patterns range from those associated with warm and dry weather, to cold and stormy and everything in between. 

To test the models, the team used a machine-learning technique called self-organizing maps to group daily weather patterns simulated by the climate models into a set of 12 categories. They did the same for historical observed weather data. They then compared the two sets of data to see how well they lined up. 

The researchers found that the climate models generally simulated the observed wind and pressure patterns very well and that the temperature and precipitation patterns created by the models closely matched the correct patterns found in the historical data. 

These results are important because they suggest that current climate models represent large-scale weather patterns reasonably well in the Pacific Northwest and can be used to better understand future climate change under continued global warming.

“These findings boost our confidence in the ability of these models to help us better understand how the climate will change over the region and why those changes occur,” says Loikith. 

Damage to industrial parts is expensive, results in delays, and may be unsafe to plant workers. But now, scientists from Tokyo Japan have simulated fracture initiated in materials that share a particular physical characteristic and are widely used across domestic, industrial, and scientific applications. Their work showed surprising results that may help prevent damage to industrial parts.

If you’ve ever been bored in a meeting and tried playing with a metal paperclip to pass the time, you may have noticed something surprising. Although the paperclip starts flexible and returns to its original shape several times, after enough cycles it may suddenly snap. This is an example of “fatigue,” in which cracks and defects build up as an object is subjected to cyclic loading and unloading of stress. Material fatigue is a significant concern in many industrial applications, especially for machine or airplane parts that experience many cycles of stress, but for which a sudden failure could be catastrophic. As a result, obtaining a better understanding of the underlying process of material fatigue could have significant benefits, especially for non-crystalline materials.

Now, a team of researchers at the Institute of Industrial Science, The University of Tokyo, studied the physical mechanisms of a low-cycle fatigue fracture in the case of amorphous solids, such as glass or plastics, using supercomputer simulations. For crystalline materials, it has been shown that preexisting defects and grain boundaries can initiate a fracture because of fatigue. However, the corresponding mechanism in amorphous materials is not well understood. While it seems intuitive that the stress required for a fracture to occur is much smaller for cyclic stresses compared with constant stress, this was not what the scientists found. “Contrary to the common belief, we showed that the critical strain in disorder materials that correspond with the onset of irreversible deformation is the same for both fatigue and monotonic fractures,” says co-author Yuji Kurotani.

This is because, for ordinary amorphous systems, higher density leads to more elasticity and slower dynamics. This density dependence of mechanical properties couples the shear deformation with density fluctuations. The cyclic shear can then amplify density fluctuations until the sample breaks via cavitation, in which voids are produced. “This situation is like a crowded train,” says co-author Hajime Tanaka. “Dynamic and elastic asymmetries with respect to density changes can lead to a link between shear deformation and density fluctuations.” These authors mention that these results should be confirmed with experiments, which would also help material scientists better understand the initiation of fractures.