Author:
Sun Fubao,Roderick Michael L.,Farquhar Graham D.
Abstract
There is a growing research interest in the detection of changes in hydrologic and climatic time series. Stationarity can be assessed using the autocorrelation function, but this is not yet common practice in hydrology and climate. Here, we use a global land-based gridded annual precipitation (hereafter P) database (1940–2009) and find that the lag 1 autocorrelation coefficient is statistically significant at around 14% of the global land surface, implying nonstationary behavior (90% confidence). In contrast, around 76% of the global land surface shows little or no change, implying stationary behavior. We use these results to assess change in the observed P over the most recent decade of the database. We find that the changes for most (84%) grid boxes are within the plausible bounds of no significant change at the 90% CI. The results emphasize the importance of adequately accounting for natural variability when assessing change.
Funder
National Key Research and Development Program of China
The Australian Research Council
Publisher
Proceedings of the National Academy of Sciences
Reference41 articles.
1. Smith JA (1993) Precipitation. Handbook of Hydrology, ed Maidment DR (McGraw-Hill, New York), Chap 3.
2. Mosley MP McKerchar AI (1993) Streamflow. Handbook of Hydrology, ed Maidment DR (McGraw-Hill, New York), Chap 8.
3. Bras RL Rodriguez-Iturbe I (1985) Random Functions in Hydrology (Addison-Wesley, Reading, MA), p 559.
4. Stationary is dead: Whither water management;Milly;Science,2008
5. Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water;Wood;Water Resour Res,2011
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