World-renowned local weather scientist J. Shukla calls the new paper by College of Maryland scientists ‘a very important paper in the history of predictability research.’
College of Maryland (UMD) scientists have carried out a novel statistical evaluation to find out for the first time a worldwide image of how the ocean helps predict the low-level environment and vice versa. They noticed ubiquitous affect of the ocean on the environment in the extratropics, which has been tough to exhibit with dynamic fashions of atmospheric and oceanic circulation. The outcomes are revealed in the Journal of Local weather, “Local atmosphere–ocean predictability: dynamical origins, lead times, and seasonality.”
The analysis attracts on a traditional assertion typically heard in introductory statistics courses that “correlation is not causation.” Clive Granger was a Nobel-laureate mathematician who got here up with a novel technique to deal with this situation by distinguishing correlation from causation.
“The Granger method relies upon a simple but important notion that a cause precedes its effect, and should improve the prediction of reffect in the future. We realized that this could be a powerful method to study the interactions between atmosphere and ocean, and to provide a global picture of how well they predict each other,” mentioned utilized mathematician Safa Motesharrei, an Environmental Techniques Scientist at UMD. “This method sheds light on both the potential to better predict regional climate as well as the nature of the interactions.”
“There are many physical processes that govern the interaction between the atmosphere and ocean,” mentioned lead creator Eviatar Bach, PhD scholar in the Division of Atmospheric and Oceanic Science (AOSC) at UMD. “For example, wind blowing on the ocean surface creates currents, and the sea surface heats up the lower atmosphere. These interactions between the atmosphere and ocean play a major role in climate and our ability to predict it, so understanding their geographical structure is important.”
“It has been known that in the tropical oceans, the ocean is predominantly driving the atmospheric changes, while in the extratropics the atmosphere generally drives the ocean,” mentioned co-author Eugenia Kalnay, Distinguished College Professor of AOSC at UMD. “I developed a dynamical rule to determine the direction of the forcing in 1986, and others have addressed this question using climate models. This study provides a definitive answer.”
The fundamental Granger technique was launched in 1969, however the authors “cleverly applied it for the first time to atmosphere and ocean data,” mentioned Juergen Kurths, Head of Complexity Science Division at Potsdam Institute for Local weather Influence Analysis in Germany, who was not a co-author. Kurths is a outstanding physicist who has developed many novel mathematical strategies for learning local weather and different nonlinear techniques.
“The most novel finding of this research is that the method of Granger causality found the ocean to influence the atmosphere almost everywhere in the extratropics,” mentioned Samantha Wills, a postdoctoral researcher at NOAA’s Pacific Marine Environmental Laboratory, who was not a co-author. “This can be a challenging task given that the atmosphere dominates air–sea interaction in the extratropics, and the influence of the ocean on the atmosphere is not much larger than internal variability.”
“This had not been demonstrated by previous General Circulation Model experiments. Although there have been a few special cases where it has been shown that mid-latitude sea-surface temperatures have a significant impact on the atmosphere, this relationship was not known to be as ubiquitous as this paper has shown,” mentioned J. Shukla, College Professor at George Mason College, who was not a co-author. Shukla is a world famend local weather scientist who pioneered research of predictability.
Furthermore, the examine’s estimates of the spatial construction of predictability may assist to additional advance the science of coupled knowledge assimilation, the nascent area that makes an attempt to leverage the interactions between environment and ocean to enhance local weather prediction.
“The ability to anticipate changes to the ocean or atmosphere based on information from the other system provides society with the opportunity to prepare for future impacts, such as to agriculture and fisheries,” mentioned Wills.
“This is a very important paper in the history of predictability research,” mentioned Shukla, “It will surely inspire further research by the predictability research community. In particular, this paper identifies geographical regions on the globe over which there exists potential predictability which can be harvested for improving operational predictions.”
Reference: “Local Atmosphere–Ocean Predictability: Dynamical Origins, Lead Times, and Seasonality ” by Eviatar Bach, Safa Motesharrei, Eugenia Kalnay, and Alfredo Ruiz-Barradas, 7 October 2019, Journal of Local weather.