New research will advance understanding of how wildfires may evolve in the future, and how we can most effectively respond to them.

In a new study, researchers show that machine learning algorithms can pick out different types of earthquakes from three years of data at Geysers in California. The repeating patterns of earthquakes appear to match the seasonal rise and fall of water-injection flows into the hot rocks below.

The better climate models become, the harder it is to use them. One team of researchers is working to fix that.

The Interdisciplinary Earth Data Alliance is fueling groundbreaking multi-disciplinary discoveries worldwide. “This is a new era of data mining,” says IEDA Director Kerstin Lehnert, a geochemist at Lamont-Doherty Earth Observatory.

The sheer number of observations now streaming from land, sea, air and space has outpaced the ability of most computers to process it. The Data Science Institute’s newest working group —Frontiers in Computing Systems—will try to address some of the bottlenecks facing scientists working with these and other massive data sets.

Journalist Cheryl Philips described using publicly accessible records of infrastructure assessments done by the Department of Transportation in Washington State to map the most vulnerable bridges and to tell the story behind a bridge that collapsed, killing several people. John Bohannon of Science Magazine used iPython coding to send a fake journal article to close to 200 open access journals in a sting operation to uncover the lack of peer review of a clearly flawed article.

The scientific publisher Elsevier and a data archiving facility at Columbia University’s Lamont-Doherty Earth Observatory are offering $5,000 and a trophy to the person with the best example of how data-preservation techniques are being used to advance new discoveries in the earth sciences.