user comments

• Ronald Morreson

  A smattering of philosophy of science is enough to clear this one up. Popper put the contention that science may only disprove hypotheses, not prove the reality of one over another. To state baldly that all NATURAL causes may be excluded because we cannot fit a phenomenon into our current models of natural phenomena therefore it must be UNNATURAL falls into the same error as those of the creationists who demand a complete fossil record, or those whose believe in the loch ness monster waving a blurry photo. On balance it is possible to say that the 0.74 C rise in temperature in the twentieth century appears to be significant, but wwhat it signifies we don't yet know.

• Ronald Morreson

  The hockey stick is undoubtedly a kludge, and quite a cynical one at that. However, the real damage it has done is to obscure the very real 0.7 C increase in average global temperatures observed in the 20th century. In trying to emphasise the scale of the issue of possible climate change the Hockey Stick imposed a monolithic statistical approach to a fluctuating, cyclical and subtle system- of course it was going to be wrong. If we could stop the shouty politicised methods, and get back to examining the global climate system and keep asking basic questions about the relationship between human activity and environmental change we may be able to get to the bottom of the role of anthropogenic CO2 in global climate. to give up or discredit because of dodgy "research" would be throw the baby out with the bath water.

• Ronald Morreson

  This is a classic problem in Management Information Systems. A new system is brought in that reveals how inaccurate historic data is, however after some "cleaning" and some "adjusting" there appears to be a trend that requires a management response. The boss then asks "how reliable is the data?" and is told how useless it is and responds "I ain't going to stick my neck out for corrupt data". Is he right? In my opinion no. Data is never going to be perfectly clean. Wishing for perfect information in making a decision is a species of cowardice. If all you have is rough data or nothing, you have to make the decision based on rough data, like crossing a dance floor under a strobe light. Having said that the authors who "adjusted" the data and then "lost" the raw set should now be teaching high school statistics in outer Mongolia.