Will Satellite Mean Sea Levels Continue to Rise? Mean sea level changes have become another hallmark of the Anthropogenic Global Warming (AGW) hypothesis. Recently attention has turned away from the traditional sea level gauges to satellite altimeter measurements. These show a much greater increase in mean sea level than terrestrial gauges. This brief study take s a look at the new and developing global record from satellites. Is global mean sea level change following a predictable trend and will it continue upward? The University of Colorado at Boulder provides four datasets for Jason/Topex (J/T) satellite mean sea level variations which differ in the degree of correction applied. All four, including pre plotted charts, are available here:http://sealevel.colorado.edu/results.phpIn this analysis, just one dataset will be used. It is the fully corrected record, with inverse barometer applied and seasonal influences removed ( http://sealevel.colorado.edu/current/sl_ib_ns_global.txt ). First a plot of the da ta is essential: A local polynomial regression smoothing fit (Gaussian kernel) has been applied to reveal the trend. This smoothing is used throughout this document.
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8/2/2019 Will Satellite Mean Sea Levels Continue to Rise?
Mean sea level changes have become another hallmark of the Anthropogenic Global Warming
(AGW) hypothesis. Recently attention has turned away from the traditional sea level gauges tosatellite altimeter measurements. These show a much greater increase in mean sea level than
terrestrial gauges.
This brief study takes a look at the new and developing global record from satellites. Is global mean
sea level change following a predictable trend and will it continue upward?
The University of Colorado at Boulder provides four datasets for Jason/Topex (J/T) satellite mean sea
level variations which differ in the degree of correction applied. All four, including pre plotted
charts, are available here: http://sealevel.colorado.edu/results.php
In this analysis, just one dataset will be used. It is the fully corrected record, with inverse barometerapplied and seasonal influences removed (http://sealevel.colorado.edu/current/sl_ib_ns_global.txt).
First a plot of the data is essential:
A local polynomial regression smoothing fit (Gaussian kernel) has been applied to reveal the trend.This smoothing is used throughout this document.
A sine fit to the data yields a slightly better value for R2
= 0.9435 and it is described by the equation:
Y = 26.11*SIN((X*0.1393)-259.6)+4.453
The period of the sine is about 45 years.
R2
does not always reveal the fit accuracy particularly well so plots of the residual errors betweenmeasured values and the models were created, as below:
Looking at this graph, it is clear that the sine model describes the data significantly better than the
linear version most of the time.
Could it be that mean sea level rise is at least partially cyclic? If it was then that might help explain
the apparent difference between the significantly lower linear trends of long records from tide
gauges and the short satellite dataset. This divergence is clearly shown in an interestingpresentation from Laury Miller et al of NOAA, on page 2 (see below):