Rainfall statistics, stationarity, and climate change
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%...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the National Academy of Sciences of the United States of America|
|Sun_Roderick_Farquhar_2018_PNAS.pdf||1.55 MB||Adobe PDF|
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