Monday, September 12, 2016

The article "Scientists See Push From Climate Change in Louisiana Flooding", published in the New York Times on September 7th, describes the use of attribution studies in climate modeling. Climate attribution studies are a scientific way of discovering the physical explanations for climatic events. The article takes the position that attribution studies provide sufficient information to deduce whether an event is linked to climate change or not. In regard to the recent flooding in Louisiana, attribution modeling was used to determine a connection to climate change. The warming of the atmosphere and oceans, as stated in the article, contribute to the intensity and length of storms. The scientists who ran this study believe this to be true and their information to be accurate although there are opponents to the idea. The author, as well as the New York Times, takes a liberal view on climate change issues which is reflected in the article's push that climate change was in fact a factor in the flooding. Though I agree with the idea that climate change offers a push in climatic events like the Louisiana Flooding, I do not necessarily agree with the speed at which these attribution studies have been accepted among some in the scientific community. Like most science, there needs to be a period of trial and error before a conclusion can be reached or a method to be proven effective.

3 comments:

  1. I like the basic explanation of the article and how you included both the author's opinion an yours. Additionally you keep that entire blog short and concise.

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  2. I appreciate the in depth detail and analysis of the article. I share your position that these studies have been accepted too quickly but I also don't believe that they're necessarily wrong.

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  3. I like that you address the role of different perspectives here - both the NYT and the scientists promoting their methodology. Even without changing climatic conditions, Louisiana has long been subject to flooding. The relative role of climate may be tricky to distinguish from imagining a world with no human intervention.

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