The difficult issues for understanding global warming are the potential biases. These can arise from many technical issues, including data selection, substandard temperature station quality, urban vs rural effects, station moves, and changes in the methods and times of measurement
We have done an initial study of the station selection issue. Rather than pick stations with long records (as done by the prior groups) we picked stations randomly from the complete set. This approach eliminates station selection bias. Our results are shown in the Figure; we see a global warming trend that is very similar to that previously reported by the other groups
We have also studied station quality. Many US stations have low quality rankings according to a study led by Anthony Watts. However, we find that the warming seen in the “poor” stations is virtually indistinguishable from that seen in the “good” stations
We are developing statistical methods to address the other potential biases
I suggest that Congress consider the creation of a Climate-ARPA to facilitate the study of climate issues
Based on the preliminary work we have done, I believe that the systematic biases that are the cause for most concern can be adequately handled by data analysis techniques. The world temperature data has sufficient integrity to be used to determine global temperature trends
This is your anti climate change guy YOU trotted out as a CRU critic. Buuuuuuuut he believes in global warming, he believes in an AGW component.
Despite potential biases in the data, methods of analysis can be used to reduce bias effects well enough to enable us to measure long-term Earth temperature changes. Data integrity is adequate. Based on our initial work at Berkeley Earth, I believe that some of the most worrisome biases are less of a problem than I had previously thought.