Credit: Pixabay/CC0 Public Domain Researchers at Stanford and Colorado State University have developed a rapid, low-cost approach for studying how individual extreme weather events have been affected by global warming. Their method , detailed on Aug. 21 in Science Advances , uses machine learning to determine how much global warming has contributed to heat waves in the U.S. and elsewhere in recent years. The approach proved highly accurate and could change how scientists study and predict the impact of climate change on a range of extreme weather events. The results can also help to guide climate adaptation strategies and are relevant for lawsuits that seek to collect compensation for damages caused by climate change. "We’ve seen the impacts that extreme weather events can have on human health , infrastructure, […]
Original web page at phys.org