Speakers in a March Meeting session devoted to climate change described how physics methods can be applied to study this important issue.
One usually doesn’t find climate science at a physics meeting, session chair John Wettlaufer of Yale University said in a press conference on the topic. Physicists have a unique perspective that is relevant to the study of climate, he said. Several scientists reported their latest results and described how physics methods can be used to study climate.
For instance, Annalisa Bracco of Georgia Tech has used simulations to study turbulence. Ocean and atmospheric flows have large Reynolds numbers and low viscosity, but most climate models, which have limited resolution, use viscosity higher than is found in nature, she pointed out. Bracco used simulations to explore how large-scale circulation depends on Reynolds number. The simulations, which required three years of computation, could result in better climate modeling, she reported.
A statistical physics approach can give insight into climate change while avoiding time-consuming numerical simulations, according to Brad Marston of Brown University. Weather is the moment to moment fluctuations; climate is the big picture we’re trying to understand, he said. While we can’t predict the weather more than a few days in the future, a statistical approach can provide better understanding of climate, Marston said. His approach is similar to describing the behavior of a gas by looking at statistical properties such as temperature rather than tracking the individual molecules that make up the gas. “Statistical physics teaches us to focus on important variables and not get caught up in details,” he said. Marston believes his approach can lead to a better understanding of processes relevant to climate change without the need for complicated numerical simulations that require years of supercomputing time. Numerical simulations may reproduce known effects, but may not give real insight into why things happen, he said.
Daniel Rothman of MIT reported on his model of the rates at which microbes consume organic matter in soil and sediment, converting organic carbon to carbon dioxide. Many processes are involved, and these processes happen at rates that are “disordered”–some are fast, most are slower. Overall, Rothman’s model predicts that the rate of decay of organic matter and production of CO2 decreases with age. His results compare well with measurements, he said. Similar considerations could be applied to other aspects of the carbon cycle, such as the decay of leaves to carbon dioxide. The work could lead to better understanding of the carbon cycle and predictions of atmospheric carbon dioxide levels, he said.
Soil moisture and vegetation are also significant factors in climate. Antonello Provenzale (ISAC-CNR, Torino, Italy) reported on a simple box model used to study the relationship between vegetation and summer droughts. Soil moisture and vegetation cover at the end of spring and beginning of summer are important in determining the probability of a severe dry season, the researchers found. Droughts are more likely if there is less than a minimal vegetation cover. Also, a fixed vegetation cover, such as in cultivated areas, is more likely to lead to drought than a dynamic natural vegetation cover that can respond to prevailing soil moisture conditions.
Stephen Griffies of NOAA discussed the physical process and numerical issues involved in ocean modeling, but said that there are many processes that may be relevant to ocean flows and the larger climate issues, and scientists still need to figure out what factors matter most. “A lot of the tools are at the art stage rather than the science stage,” he said.