|Fig. 1 GISS temp anomaly pattern (1880-2016)|
I. A Test Case
I have added a test-case to the thermal expansion calculation modules.
It is a multi-purpose test case with a fixed ocean temperature system based on the boundary values of the various ocean basins.
The test-case software module is used to show the difference between thermosteric volume change in the constant-mass scenario compared to the changing volume scenario (Eustatic vs. Steric).
That is, the proper way to test for and/or calculate thermal expansion / contraction is to do so in a fixed (unchanging) mass-quantity of water (On The More Robust Sea Level Computation Techniques - 2).
When the mass changes and the calculation of thermal expansion / contraction continues unabated with the new mass, the increase in sea level, etc. is likely to confuse analysts into conflating eustatic changes with thermosteric changes.
Thus invalid results are likely to ensue (ibid).
To establish a fixed environment as a context for the test-case, I used my SQL database of valid ranges built from the WOD manual @ Appendix 11.1 and 11.2 (WOD Manual, p. 132; PDF page 142).
That sets the stage for testing, but first ...
II. WOD Update
The World Ocean Database (WOD) has posted its latest update (August).
It used to be a daunting task to integrate the updates into my system, but I have modified
|Fig. 2 Home of The World Ocean Database|
I thought I would show the graph changes that resulted from the additional ~50 million ocean temperature, depth, and salinity in situ measurements, which the update added to the SQL database.
III. Hang Onto Your Hat
The import of the test-case module results can be grasped at once by looking at Fig. 3a thru Fig. 3d.
The red colored graph line on each graph is the pattern which actual measurements have recorded (actual measurements in the CTD and PFL datasets of the WOD).
As you can see, there is a radical contrast.
It doesn't mean that the measurements are wrong, or that the abstract is wrong, instead, it tells us that we need to take measurements in the same way and for the same reasons we have chosen to use the Golden 23 Zones.
That is, we seek measurements that produce a balanced representation of the oceans as a whole.
For example, if we take all of our in situ water temperature and salinity measurements only in the Arctic ocean area, we will have produced an unbalanced set of data from which to analyze the ocean temperature thermodynamics of the entire world oceans.
The same will result if we take all of our measurements in the tropics.
Also, that same result can be expected for unbalanced combinations where our mix of locations to take measurements is focused too much on one area or the other.
IV. The Abstract Graphs
They show what the software module calculations would expect global warming of the surface to produce in the oceans.
Fig. 4a is ocean mass, Fig. 4b is thermosteric volume expected when a constant water mass is analyzed, Fig. 4c is Conservative Temperature, Fig. 4d is Absolute Salinity, Fig. 4e is sea level, Fig. 4f is GISS global temperature average anomaly since 1880 compared to sea level change during that same span of time, Fig. 4g is thermal expansion and contraction when a variable mass is used in the equation, Fig. 4h is expected ocean salinity, and Fig. 4i is expected ocean temperature.
V. The Clincher Test
The oceans are hard places to work in, and can be life threatening at about any time.
I have been across some of the feisty ones on a small wooden boat in winter time with only one other person to share the "adventure."
They are all the more dangerous if you are not constantly aware of what is around, under, and over you.
Plus what is coming at you, or might be coming at you, so one can't just do measurements our there without being prepared for danger and/or trouble.
Measurements out there do not come cheap or easily (WOD-Arctic).
So, we need a way to analyze the data we have in a manner that can also tell us where and with what we need to update and to balance out our datasets.
VI. Making The Test Graphs
You will notice a similarity in the GISS surface temperature anomaly graph patterns (Fig. 1, Fig. 4f) when compared with other patterns.
That is because I use the GISS pattern to inform the others.
That is, the GISS represents warming increases caused by captured green house gases.
Some 93% of that finds its way into the oceans, so it is a sound hypothesis to consider that the oceans will warm accordingly.
Of course there are variations, exceptions, and differences, but it makes for a worthwhile pattern to look for in the abstract.
For example, Fig. 4f is composed of measurements taken from safe locations at weather stations and tide gauge stations around the world.
They have a similar pattern because one (GISS) causes the other (PSMSL), because warming melts the Cryosphere and the melt water is relocated into the oceans.
The values of sea level change match the pattern that values of atmospheric changes make.
The same is validly expected in the mass of the oceans.
The pattern of warming causes a pattern of sea level change which causes a similar pattern of ocean mass change.
There is a reasonably equal expectation with ocean water temperature (when considered as a whole) and salinity, in terms of an abstract test case.
There are a lot of things to look at, ponder, and analyze with this test case scenario.
For example, do the in situ temperature and salinity graph lines in Fig. 3a thru Fig. 3d tell us anything about our WOD dataset?
Like maybe in the 1960's (what with the red measurement line being above or below the expected location shown by the black graph line, and then dropping down below or going above that black line), that deeper (colder) measurements became more technically possible ... or did northern measurements exceed southern measurements?
Or perhaps was there a lot of cold melt-water injected into the oceans to cause cooling (see Humble Oil-Qaeda)?
There are a lot of possibilities.
It can't all be discussed in one post, so stay tuned if you like.
The next post in this series is here, the previous post in this series is here.