I have been working with NOAA data to see if, by statistical extrapolation alone, I can derive reasonable values of how much Greenland might lose by the end during the 21'st century.
First, the data I obtained from the website (in the caption of the above chart):
I interpolated the points from this chart and reversed the y axis, setting the 2002 point at 300 gigatons so that all points would increase from zero. I also performed a straightforward calculation to determine that 3000 gigatons if loss (from land) of ice would cause a one cm rise in sea level.
I then attempted two methods of extrapolation. The first, represented by the blue line, is simply a quadratic least-squares trend line (using LibreOffice 4.3), yielding about 100,000 gigatons of loss, amounting to 33 cm (13 inches).
The red extrapolated line required several steps. First, I split the data into two sets, took the first derivative of each, and divided the second by the first to obtain a ratio of about 1.6. I then calculated each successive sixth year from the last point by this ratio. Then, realizing that the lost ice was partly a function of how much ice was left, I multiplied these points by a descending exponential with ultimately reduced the last by a factor of about two.
What is the purpose of this (somewhat) complicated procedure? The reason has to to with positive feedback and the exponential changes they can lead to. In this case, disappearing Greenland ice increasingly exposes the land beneath it. As this land absorbs much more sunlight as the ice, it grows progressively warmer, thus increasing the melt rate of the remaining ice. But of course, the amount of ice that can melt is also is a function of how much remains.
The big question then is, which is correct (if either)? As I only had 13 data points to work with, describing a modest curve, I won't pretend certainty either way. My best guess is that it will be somewhere between these "extremes" (one can derive even higher and lower levels), and so the meter or so of sea level rise, fairly consistent with IPCC predictions, may very well be right. And very well might not, because there are other factors that complicate global temperatures.
