I recently read a paper that carefully used existing in situ data measurements at several weather stations in Southwest Greenland to extend the historical records of air temperatures in that area all the way back to 1784 (Vinther et al., 2006, PDF).
The graph at Fig. 1 shows the mean average temperature record for the areas near the fastest receding glacier in the Cryosphere (Jacobshavn near Nuuk and Ilulissat).
Today I want to continue the discussion of the Arctic region in terms of the Industrial Revolution having terminated a cooling trend.
Fig. 2 Abrupt Weather Change
The graph at Fig. 2 is the same as the graph at Fig. 1 except that I drew two red lines to illustrate the abrupt change in the weather in SW Greenland in the late 18th century.
That abrupt change melted all the fresh ice buildup that took place during the cooling epoch (Little Ice Age?) shown by the downward trending red line from circa 1784 to circa 1840.
A Little Ice Age clue from Glacier Bay:
"Ice has been a major force in the Glacier Bay region for at least the last seven million years. The glaciers seen here today are remnants of a general ice advance – the Little Ice Age – that began about 4,000 years ago. The Little Ice Age reached its maximum extent here about 1750, when general melting began."
(Glacier Bay Park). Yet another note about the time of the end of the little ice age and beginning of the industrial revolution.
The Greenland weather station records don't tell us how long the cooling period had been going on prior to the abrupt change.
But it would have been increasing the Greenland Ice Sheet's mass for all that span of time.
The big picture is that all that new ice caused by the cold spell melted abruptly, in geological terms.
The change of events was caused by the rapid increase in the use of coal and other fossil fuels in the hurried early days of the Industrial Revolution.
Those events impacted the new ice and sent ice bergs floating all the way down along the coast of Florida and around Bermuda according to U.S. Coast Guard records (Fig. 3).
Fig. 4 2014-2018 added
The graph at Fig. 4 includes the years 2014-2018 from PROMICE (NUK & QAS only) which were not included in the Vinther et al. paper.
After that "low hanging fruit" was plucked, things leveled off somewhat but the oceans began to warm up.
Most melt now is caused by a warming ocean which is engendering abrupt changes to tidewater glaciers (The Ghost Plumes - 8).
A person's country of origin, residency, or citizenship is not a factor in terms of what countries are being impacted (Countries With Sea Level Change - 2).
When I first noticed it a few days ago, only the tiny beginning of the sharp downward-to-the-right line was visible.
It was shaped like the peak of a roof at that time.
It continued for a couple of days, so I wondered if the satellite had another failure as it had twice before (once in 2009 and again a few years ago; they found a work-around both times).
I waited until there was an upward change in direction, then waited until today, thinking that maybe this is real and not an equipment failure.
I can't tell from the pictures of the ice that anything catastrophic has happened, so I stopped thinking that it might have been the radical change in the Beaufort Gyre scientists have been waiting for (Mysterious Zones of The Arctic, 2, 3).
Any ideas?
The next post in this series is here, the previous post in this series is here.
The authors of that paper sought to be innovative and discover "where da heat at" by unconventional means and unconventional methods.
Without using the plethora of available data with which to do it conventionally, they erred.
I am not going to go into it in this post except to show another way to try what they attempted to do by creating yet another example of going around the available data when it really isn't needed.
"The vast Southern Ocean, which surrounds Antarctica, plays a
Fig. 2 WOD meets GISTEMP & SOCCOM
starring role in the future of climate change. The global oceans together absorb over 90 percent of the excess heat in the climate system and roughly three-quarters of that heat uptake occurs in the Southern Ocean. Despite its critical role in our climate system, the Southern Ocean has gone almost completely unobserved."
(SOCCOM, emphasis added, originally quoted here). I had to use the Wayback Machine's historical copy because the SOCCOM folks, for some reason "lost" the original web page on their website from which I originally quoted.
Nevertheless, I think that the SOCCOM folks were correct to write what they did on their website.
"The caveats are (as usual) there are still imperfections in the ocean models being used and the systematic biases in old observations are always being looked at. The differences between the two studies are thus understandable from their study design."
I mean ample data to show that catastrophic ice sheet melt is taking place before our very eyes.
IMO, that "catastrophic ice sheet melt" is due to exactly what the SOCCOM people wrote about on their website.
II. Another Way To Make The Deniers Howl
Anyway, on to the gist of today's post.
The World Ocean Database manual contains two tables in Appendix 11, described as:
APPENDIX 11. ACCEPTABLE RANGES OF OBSERVED VARIABLES AS A FUNCTION OF DEPTH, BY BASIN
The range values provided has range values for temperature, salinity, oxygen,
Fig. 3 WOD meets only GISTEMP
phosphate, silicate, nitrate, pH, chlorophyll, and alkalinity.
The range values in the tables are used to help identify the most obvious questionable values for these variables.
For simplicity, please note that ranges are given on 33 standard levels (+ one for depths deeper than 5500 m).
(WOD Manual, p. 78, PDF). I used the in situ temperature, salinity, and depth values of two of the tables in that Appendix 11 to generate today's graphs.
I derived a median or mean average seawater temperature for all 30 of the ocean basins of the world, at 33 individual depth levels, by simply adding the maximum and minimum values for each of those 33 depth levels together.
Then, simply dividing by two.
Not only that, I also used the latest data from GISTEMP so as to conform those cast-in-concrete maximum / minimum values in Appendix 11 to current atmospheric temperature anomalies since circa 1800 CE.
In other words, for each year that the GISTEMP global average decreased, the mean average OHC decreased, and for every year that the GISTEMP value increased, the OHC mean average increased.
Thus, the graphs at Fig. 2 and Fig. 3 show the abstract results, which have the same pattern as the real data, which is the GISTEMP data.
III. The Gist of SOCCOM
The graphic at Fig. 1 shows the plethora of world wide GISTEMP stations that are used to generate the temperature anomaly trends of global warming.
The graph at Fig. 2 shows what happens when the SOCCOM statement ... "most OHC ends up in the Southern Ocean" ... is for real.
Fig. 3 shows what happens when a "bathtub model" like imaginary situation takes place, where all heat is perfectly and evenly distributed around the globe.
IV. The Real OHC
Fig. 4 The Real OHC
The graph at Fig. 4 shows the real Conservative Temperature (lower left pane) and the real OHC, a.k.a. (hO) or potential enthalpy (lower right pane).
They are compared with the abstract values that were also shown in Fig. 2 and Fig. 3.
The idealized patterns in Fig. 2 and Fig. 3 do not take into consideration that OHC is modified when the seawater's heat content is used to melt the vast ice sheets in Greenland and Antarctica.
The Resplandy paper alleged that the oceans have absorbed about 60% more heat than what has been reported over the years.
V. So, You Might Ask:
"Dredd, What Is The Value Of This Exercise?"
None, in terms of actually tracking down ocean heat content and ocean heat flux.
It does, however, show that there are any number of methods one can use to avoid the very hard work required.
I mean "very hard work required" in order to secure the WOD, OMG, SOCCOM, WHOI, and other in situ measurement sources, then load them into a favorite data server; a server that handles the vast amount of data available; an SQL or other suitable database server ready for subsequent use.
It also shows that the mathematically perfect display of abstract data is how we think sometimes, e.g. the "bathtub model" (The Bathtub Model Doesn't Hold Water, 2, 3, 4, 5).
