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What to do When the Data Doesn't Agree
About a month and a half ago, I wrote about the lack of temperature increases in our oceans and the problems that was causing for the global warming community. Yesterday, I saw this New York Times story about a new climate model which is predicting global cooling for the next decade.
One of the first attempts to look ahead a decade, using computer simulations and measurements of ocean temperatures, predicts a slight cooling of Europe and North America, probably related to shifting currents and patterns in the oceans.
The team that generated the forecast, whose members come from two German ocean and climate research centers, acknowledged that it was a preliminary effort. But in a short paper published in the May 1 issue of the journal Nature, they said their modeling method was able to reasonably replicate climate patterns in those regions in recent decades, providing some confidence in their prediction for the next one.
The authors stressed that the pause in warming represented only a temporary blunting of the centuries of rising temperatures that scientists have projected if carbon dioxide and other heat-trapping gases continue accumulating in the atmosphere.
I find it somewhat amusing that once again, global warming advocates have to backpedal when the data doesn't match their predictions. For something where the "science is settled", I find it rather amusing that new data keeps coming up which contradicts the settled science. As I've said before, I do believe that in general temperatures have increased, but I don't believe that the global warming advocates really have as clear an understanding of the causes and the effects that they suggest. I don't believe we should be taking radical steps to reduce climate change when the data doesn't match our original hypothesis. How can we know what we're doing is going to have the desired result? It just doesn't make sense to me.


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