The Gleissberg (~85 year) and other periodicities in the flood cycles of the Brahmaputra River past present and future; implications for possible global mechanisms
Authors: Asten Michael , McCracken Ken 
Published: March 2022

&lt;p&gt;Asten and McCracken (AGU 2021, paper H45Z-12) note strong ~85 and ~50 year periodicities in flood data and lake level data in NSW, south-east Australia.&amp;#160; We now compare data sets for the Brahmaputra River (latitude 25&amp;#8304;N) 1800-2000CE with Lake George (latitude 35&amp;#8304;S)&amp;#160; levels 1820-2020CE.&amp;#160; Both data sets show a pair of dominant spectral maxima at 80 and 50 year periods.&lt;/p&gt;&lt;p&gt;A study by Rao et al (2020) of observed and reconstructed discharge of the Brahmaputra shows only limited correlation of discharge rates with recorded floods.&amp;#160; We use a record of Oceanic Nino Index 1870-2021CE (McNoldy, 2021) to compare with floods and find that for time 1875-2010, 14 of 17 observed floods associate with La Nina events. However there were 27 La Nina events in this interval hence as a working hypothesis LaNina events are close to being a necessary condition (~82%) for floods but not a sole determinant. We use spectral analysis to locate multi-decadal natural cycles which also influence discharge levels and flood frequency.&lt;/p&gt;&lt;p&gt;The Brahmaputra discharge rate data extends back to year 1309CE (Rao et al, 2020).&amp;#160; The power spectrum &amp;#160;&amp;#160;shows a series of strong maxima, especially at 242, 132, 90, &amp;75year periods similar to those in &lt;sup&gt;14&lt;/sup&gt;C and &lt;sup&gt;10&lt;/sup&gt;Be records for the Holocene.&amp;#160; The entire record can be fitted using a model of 8 sinusoids, leaving only a 20% residual variance.&amp;#160; The model allows extrapolation of the discharge rate into the future and predicts an above-average discharge for years 1995-2040CE, peaking ~2020.&amp;#160; This predicted time-span of above-average discharge is based on natural frequencies embedded in the record and does not include any possible influences from 21&lt;sup&gt;st&lt;/sup&gt;-century global warming.&amp;#160; The prediction appears closer to the observed increase post-2000, than does a prediction based on CMIP5 models as provided in the Rao etal (2020) paper.&lt;/p&gt;&lt;p&gt;A further test of the efficacy of the discharge curve fitting method is provided by limiting the observed data to years 1309-1900CE, then projecting the model to 2200.&amp;#160; The projected curve from 1900 replicates the observed dry period 1950-1995 and validates the hypothesis that the dry period was not an unusual event but was part of the natural cycles as reconstructed since 1309.&amp;#160; The projected curve from 1900 also closely follows the model based on all data to 2010 in predicting the above-average discharge rates 1995-2040.&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;As noted above both data sets show a pair of dominant spectral maxima at 80 and 50year periods. The similarity between the spectra invites a hypothesis that the long-period natural cycles at both locations have a common origin, possibly solar-related rather than being of local atmospheric/oceanic origin.&amp;#160; A key difference is that the phases of the spectral maxima are reversed for the two sites.&amp;#160; Physical mechanisms producing these dominant periods for the 19&lt;sup&gt;th&lt;/sup&gt; and 20&lt;sup&gt;th&lt;/sup&gt; centuries, and the phase difference between the northern and southern hemisphere sites are not yet known. They could be related to variations in solar insolation, cosmic-ray ionization of cloud cover, or mode changes in global ocean current systems driven by unknown external forcing.&lt;/p&gt;