|Fig. 1 Very Simple Algebra|
I. Some Background
We generally take 1750 as the beginning year of the Industrial Revolution (Wikipedia, cf. Prezi).
We have sea level records from less than a hundred years into that revolution, but in general they are less trusted in terms of accuracy, than recent ones.
I used a formula in a C++ routine to calculate backwards in time to develop some information (Fig. 1) ... more about that later in this post.
I found one example of very early records that were counter to conventional wisdom, but which hold up in principle (Pure Appl. Geophys., 127, 73-77, 1988). and hold up in terms of numerical patterns that regular readers and I have generated, examined, and pondered in recent times.
II. And Then ...
I downloaded those ancient values at PSMSL which were taken from a paper authored by Martin Ekman (1888), which covers sea level records from 1774-1984 in Sweden.
|Fig. 2 Old Sea Level Change Records|
I acquired them so as to compare them with my projection back into history via the formula shown in Fig. 1.
I graphed the 1774-1984 records as they were written, and lo and behold it ends up that they are accurate and modern in terms of pattern.
That becomes clear if you compare Fig. 2 with Proof of Concept - 5, which contains modern graphs based on trusted PSMSL records of that area.
III. Preparing For The Trip Back
|Fig. 3 Circa the hear 2000|
First, I acquired values on a USGS page, which indicate how much ice sheet volume there was to melt and to then cause sea level change (SLC).
I found data generated by the USGS circa the year 2000 (Fig. 3).
The SLR value is in meters (multiply by 1000 to convert meter values to millimeters).
Next, I wrote a C++ module to calculate from 2015 back to 1750 (a Wayback Machine), which generated a CSV file, from which I generated several graphs.
The program takes the variable "ivm" (ice volume max: 32,328,300 km3) and the variable "slrm" (sea level rise maximum: 80.32m) from Fig. 3.
Then, using conventional annual SLR values for the "slrc" variable in Fig. 1 (3.5mm, 3.2mm, 1.5mm and 0.5mm (Fig. 5) as values for annual SLR increases since 1750), we backtrack.
The software iterates through each year, beginning in the current year, adding or subtracting (3.5, 3.2, 1.5, or 0.5 mm) etc. from the sea level and/or ice volume for each year.
That in turn causes a decrease or increase in the ice sheet mass variable, which is in this context the inverse of the sea level value variable (in general, as ice volume decreases, sea level increases, and vice versa).
We calculate the increase in ice volume for each year going back to 1750, as well as the global mean average sea level fall (ice volume increases as sea level decreases - except near the coasts of the ice sheets).
It is the reverse of what is happening now and into the future.
It is as if we take the melt water from the ocean and put it back onto the ice sheets of Greenland, Antarctica, and glaciers elsewhere, thereby increasing the ice volume back to what it was "way back then".
IV. What I Brought Back To Show You
The inverse slope in Fig. 5 shows that as the ice sheet volume and mass was lost, the global mean sea level rose.
And, as another proof of concept, the old records graphed in Fig. 2 show that ice sheet gravity was as it is today, still mystifying some people.
That is, as Greenland began to melt as a result of global warming caused by the use of fossil fuels (mainly coal), sea level fall (SLF) began in Scandinavia.
SLF still continues unabated today (Proof of Concept - 5).
I see this technique as an opportunity to build a table in the model's database.
The table will harbor this annual ice sheet volume / mass data in it, to used in future analysis.
The more tools the better.
I intend to enhance this tool by modifying it to calculate each ice sheet's percentage of contribution.
I also plan to add the subsequent thermal expansion contribution (ocean warming induced SLR, which takes place after the cold melt-water eventually warms up).
V. So, What Does That Have To Do With Models?
Human fingerprints are indications of history, in the sense that they can show that someone was at a particular location.
Sea level fingerprints can do the same, and in this case we can "book Greenland Danno," because the fingerprints of Greenland ice sheet melt were found (SLF in Scandinavia).
A model that can run backwards and forwards in time, based upon and beginning from various segments of history which we have and know to be valid, is a more robust model (historical reality guides its future projections).
That is, models based on solid historical records are more desirable than those composed only of pure conjecture.
We press on toward knowing how to analyze what is happening around us, and why.
I must get back to the "lab," as Mark Hanson calls it.
I am anxious to make this Dredd Blog software model very robust in terms of SLC fingerprinting.
Have a robust weekend.
The previous post in this series is here.