PLEA Network

14 January 2016, Yale Connections, Experts Fault Reliance on Satellite Data Alone. Over-reliance on satellite data to the exclusion of other data can amount to ‘confirmation bias,’ say scientists urging analysis of numerous different data sets. This month’s “This is Not Cool” video focuses on an ongoing, and again festering, climate science controversy, the value and reliability of satellite-derived global temperatures. And of that data at the exclusion of – or as a surrogate for – other data. Independent videographer Peter Sinclair sought reactions of leading climate scientists to points made in a recent hearing of the Senate Commerce, Science and Transportation Committee, chaired by Texas Republican Senator and presidential nominee hopeful Ted Cruz. “According to the satellite data, there has been no significant global warming for the past 18 years,” the senator said.In the hearing, Senator Cruz emphasized that “The satellite data are the best data we have,” an often-echoed point made by those generally scornful of much of the so-called consensus climate science. Climate scientists Michael Mann, Kevin Trenberth, Andrew Dessler, Carl Mears, and Ben Santer, David Titley, and others voice what they see as limitations or shortcomings of the satellite data. They point to a history of documented errors and mistakes that have often caused satellites to underestimate climate warming.Among these errors are a failure to account for “orbital decay,” changes measuring in the diurnal cycle, and faulty calibration of satellite sensors. Most of all, they discourage over-reliance on any single set of data and instead urge consideration of numerous authoritative data sets. Remote Sensing Systems scientist Carl Mears points to inherent problems in reviewing data only from a particular point in time, especially the often-chosen 1998 starting point, which was characterized by a strong El Niño. “If you start driving at the top of a hill, you’re going to go down, at least at the beginning,” says Mears. Andrew Dessler of Texas A&M says he sees in all this an example of “confirmation bias,” with climate contrarians often looking only at data that “tells them what they want to hear.” Read More here