Modeling and assessing climatic trends
نویسندگان
چکیده
Climate studies often fit linear trends to data. In many cases simplifying assumptions such as independent errors and constant variance are used. We review a variety of approaches to estimating linear trends, and illustrate with US temperature data how oversimplified assumptions may lead to false significance. We outline a variety of methods to fit nonlinear trend models. Using the Berkeley Earth global data set we show that a bent cable fit is better than a linear fit for this series. We also review spatial and spatiotemporal trend models in mean, variance and extremes, as well as models with long term memory structure.
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تاریخ انتشار 2017