| Abstract: | Hydroclimatological time series often exhibit trends. While trend magnitude can be determined with little ambiguity, the corresponding statistical significance, sometimes cited to bolster scientific and political argument, is less certain because significance depends critically on the null hypothesis which in turn reflects subjective notions about what one expects to see. We consider statistical trend tests of hydroclimatological data in the presence of long-term persistence (LTP). Monte Carlo experiments employing FARIMA models indicate that trend tests which fail to consider LTP greatly overstate the statistical significance of observed trends when LTP is present. A new test is presented that avoids this problem. From a practical standpoint, however, it may be preferable to acknowledge that the concept of statistical significance is meaningless when discussing poorly understood systems. |
| Genre: | Article |
| ProdID: | 70027303 |
| Citation Author: | Cohn, T. A.; Lins, H. F. |
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| Citation End Page: | 5 |
| Citation Issue: | 23 |
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| Citation Language: | English |
| Citation Larger Work Title: | Geophysical Research Letters |
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| Citation Number Of Pages: | 5 |
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| Citation Search Results Text: | Nature‘s style: Naturally trendy; 2005; Article; Journal; Geophysical Research Letters; Cohn, T. A.; Lins, H. F. |
| Citation Start Page: | 1 |
| Citation Volume: | 32 |
| Citation Year: | 2005 |
| Type: | citation/reference |
| Text: | Nature‘s style: Naturally trendy; 2005; Article; Journal; Geophysical Research Letters; Cohn, T. A.; Lins, H. F. |
| URL (THUMBNAIL): | http://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg |
| URL (DIGITAL OBJECT IDENTIFIER): | http://dx.doi.org/10.1029/2005GL024476 |
| Date Other: | Sat, 1 Jan 2005 00:00 -0600 |
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