October 27, 2010 — andyextance

Do you trust the measurements your bathroom scales provide? If not, you share a classic dilemma faced by scientists, which is whether or not their data gives an accurate picture of what they are trying to study. This is an especially sore point in the debate between climate scientists and their critics who differ, for example, over whether it’s OK to exclude temperature measurements from certain weather stations. One accusation is that scientists are just choosing the figures that support their arguments, a practice referred to as “cherry picking”.

Such disputes made me especially interested to see that Max Planck Institute for Developmental Biology scientist George Wang and his colleagues had specifically chosen a set of temperature measurements for their research. Together with Michael Dillon at the University of Wyoming and Raymond Huey at the University of Washington, Wang looked at how temperatures since 1960 would have affected metabolism of ectotherms – better known as “cold-blooded creatures”. They surprisingly found that, despite temperatures changing more slowly where they live, tropical species would be worse affected than those living in cold areas. Could choice of weather stations have influenced this research improperly? Not according to Wang.

“Scientists will exclude data for many reasons, but fundamentally we do it because blindly leaving data in an analysis can bias results,” he told Simple Climate. “In general, scientists in every field have to use judgement based on experience to detect and remove outliers. It is something scientists take very seriously, and it is an integral part of analysing data.”

Furthermore, whether a scientist knows exactly which data to exclude is the best way to tell if he’s an expert in his field, Wang thinks. “The knowledge and judgement needed to determine which data should be excluded to remove bias or outliers is, along with experimental design, in my opinion, very underappreciated. I would hope that anyone with a healthy scepticism of any research would not simply accuse a researcher of cherry-picking, but would instead strive to first understand and evaluate why the researcher made the decision to exclude some data.”

“We used the data from the US National Climatic Data Center (NCDC) Integrated Surface Database,” Wang continued. “We needed temperature measurements every few hours and global coverage in order to accurately determine metabolism. When we started the project, this was the only dataset that offered high enough resolution.”

“We excluded data from stations that did not sample at least every 6 hours,” Wang explained. “We do this because if a weather station only records temperatures once per day in the morning, it does not adequately represent the range of temperatures, and thus metabolic rates, an organism would experience through the day. Similarly, we excluded stations that did not sample in all seasons. But, the decisions about criteria used to exclude stations based on these criteria were made before we analyzed, or even assembled, any data.”

This is the third blog entry that I’ve written about Wang and his colleagues, so it’s about time we got around to tackling the question that is the purpose of this blog: just how would he explain climate change? In this case the answer is especially brief: “Global average temperatures are increasing due to man-made changes in the composition of our atmosphere,” Wang said.

While this explanation doesn’t say much about how warming has happened, Wang is keen to point out that scientists both have the proof and understanding to back up this statement. “There is a lot of evidence, but we also know a lot of the process by which human activities change the atmosphere and thus the climate,” he said. “Too many people who deny the existence of man-made climate change do not seem to acknowledge our understanding of the processes of climate change. There are many sources of evidence, too many for me to do justice here. I would point people to the IPCC and NCDC ‘State of the Climate‘ reports.”