 |
| Fig. 1 |
I. A Major Problem Arose
This series is about one question: "So, how does one go about finding the Golden World Ocean Database (WOD) measurements the same way that scientist Bruce C. Douglas did with PSMSL tide gauge station records?"
Bruce C. Douglas (hereinafter 'Douglas') carefully and professionally boiled it down to what Dredd Blog has called "the Golden 23 tide gauge stations" (Golden 23 Zones Meet TEOS-10).
Douglas had to do that, pick the golden 23, from over a thousand tide gauge stations spread all around the globe.
II. A Larger Problem Has Arisen
As the link to the WOD page shows, there are 648 individual WOD Zones in 18 ten-degree latitude bands around the globe.
 |
| Fig. 2 |
So, it would seem at first blush that the current problem is easier to solve because 648 is less than over a thousand.
What makes the current problem more difficult is that Douglas only had to deal with one depth, which is zero, because sea level at tide gauge stations is measured at the surface.
To solve the WOD measurement selection problem that is now confronting us, we have to also consider measurements of temperature and salinity at 33 different depths in each of those hundreds of WOD Zones.
 |
| Fig. 3 ARGO float distribution |
The location is just one issue in this multi-issue problem.
So, there are two main issues: "what latitude and longitude locations make a balanced measurement dataset," and "at what depths should the measurements be taken".
The depth issue is a particularly difficult problem because even the ARGO automated measuring drones (Fig. 3) only go down to about 2,000 meters, which is over a thousand meters short of the median ocean depth of about 3,682.2 meters.
The ARGO data is in the WOD PFL dataset which I use consistently, along with the CTD dataset (the CTD and PFL datasets have quite a few measurements at depths greater than 3,000 meters).
III. Tools To Help
Solve The Problem
 |
| Fig. 4a |
 |
| Fig. 4b |
 |
| Fig. 4c |
 |
| Fig. 4d |
Version 1.4 of that module generated the graphs shown in today's post.
The first problem was to have an abstract gauge which we could compare to measurements in the WOD datasets.
That initial tool was described in the first post of this series (Oceans: Abstract Values vs. Measured Values).
That tool: 1) uses all measurements recorded in the WOD (all 18 layers of zones), 2) uses six specially selected layers I am calling "the Golden Six Layers" for comparisons, and 3) uses the abstract mathematical median calculated from the WOD manual values of minimum / maximum salinity and temperature.
The comparisons allow an analysis of the results of using those eighteen layers vs. an analysis of the results of using only the six layers, and then comparing those two results with the results generated by the abstract mathematical projection (Oceans: Abstract Values vs. Measured Values - 2).
The abstract version generates a mathematical temperature & salinity matrix based on those WOD maximum / minimum values for each of the 30 ocean basins around the world (i.e. both salinity and temperature at 33 depths in 30 ocean areas).
This backdrop will expose datasets of measurements as being too concentrated in terms of latitude & longitude, as well as exposing those being too concentrated at habitual depth levels.
But more than that, it can also reveal a balanced selection of layers, each layer containing up to 36 WOD zones (most layers have some zone over land, so they are of course excluded).
IV. Conclusion
I am using the software module (version 1.4) in an effort to choose the best layers ("cherry picking" is a process of picking the best cherries after all ... except in alt-cherry picking which is a process of picking the rotten cherries).
So far, as I said in previous posts, six layers (5,7,8,9,10, and 12) are being used (see the map here).
Check out the graphs in today's post for an idea as to how the effort is progressing.
Dr. Mitrovica reveals some previously unused science to clear the air of some common ignorance concerning sea level changes that plagued scientists until Douglas cleared the air (video below).
The next post in this series is here, the previous post in this series is here.