Paper Reviewed
McAneney, J., van den Honert, R. and Yeo, S. 2017. Stationarity of major flood frequencies and heights on the Ba River, Fiji, over a 122-year record. International Journal of Climatology 37 (Suppl. 1): 171-178.

Flooding is an extreme climatological event. Climate models project that CO2-induced global warming will increase both the frequency and severity of such events in the future. What is more, climate alarmists suggest that such events should already be discernible, as nary a major flood event goes by these days without their attempting to attribute it to anthropogenic global warming.

Fortunately, real scientists engaged in real research have used sound statistical methods to investigate this topic; and what they typically find does not bode well for climate alarmists (see, for example, the many reviews of papers we have posted in our Subject Index under the heading of Floods on this page). And in this current review, we add yet another study to show that there is nothing unusual, unnatural or unprecedented about current flood trends -- this time from Fiji.

On the southwestern Pacific Ocean Fiji island of Viti Levu (18°S 178°E), citizens have recorded flood occurrence and height data at the Rarawai Sugar Mill on the Ba River since 1892. In their recent analysis, McAneney et al. (2017) performed a series of statistical analyses on these data, seeking to determine "whether the data set can reveal the degree to which islands in the Pacific are already seeing the impact of global climate change on the risk of severe flooding."

Results of the analysis revealed that despite a persistent warming trend of ~0.18°C per decade over the past seven decades, there has been no consistent trend in flooding. Consequently, McAneney et al. matter-of-factly attest that they were "unable to detect any influence of global warming at this tropical location on either the frequency or the height of major flooding." What is more, they add that their study demonstrates "the difficulty of achieving statistical significance in terms of attribution of extreme weather even with relatively long data sets." And that means that climate alarmists will have to continue looking elsewhere to find support of their claims -- claims that have been disproven by real world observations multiple times over!