Fig. 1 Extrapolation From GISS pattern |
I. Background
In this series I have been using GISS data spliced with WOD ocean temperature maximum/minimum values as well as actual in situ seawater temperatures at various depths (World Ocean Database Project - 5).
The graph at Fig. 1 is an example of the use of GISS data to estimate the future path of the well-known GISS pattern, i.e. an extrapolation beyond the present GISS anomaly data.
(But it is not a display of in situ temperature measurements at several ocean depths of several oceans as has been done in this series.)
Anyway, like Dredd Blog some notable climate scientists also use GISS data as a factor for getting at the reason or reasons for several global warming dynamics:
"Zonal-mean surface temperature ... based on the GISS temperature analysis supports the interpretation of global warming that we have presented here and elsewhere. Warming is accelerating in the past 10-15 years, especially at mid latitudes in the Northern Hemisphere. The fact that the climate physics is understandable is no reason to relax. On the contrary, we have shown that the world is approaching a point of no return in which the overturning ocean circulation may shut down as early as mid century and sea level rise of many meters will occur on a time scale of 50-150 years. Time is running short to make the public and policymakers aware of the threat posed by the delayed response of our climate system and of the actions that should replace present wishful thinking (hopium)."
Global Warming Acceleration: Hope vs Hopium). They tend to use different figure descriptions because among other things they are not splicing in situ measurements into the GISS pattern.
II. TEOS-10 Ocean Heat Calculations
Collecting in situ temperatures is not the end of the matter when it comes to "ocean heat content".
The real name for ocean heat content is "potential enthalpy" (Potential Enthalpy: A Conservative Oceanic Variable for Evaluating Heat Content and Heat Fluxes).
It can be calculated using TEOS-10 software (the C++ version is used here on Dredd Blog) as follows:
1) acquire the salinity (SP), temperature (T), and depth (D) values;
2) calculate 'Z' (aka 'height' in "the geoid" concept) using method "double gsw_z_from_depth(double depth)",
3) calculate 'P' using method "double gsw_p_from_z (double z, double lat),
4) calculare 'SA' (absolute salinity) using method "double gsw_sa_from_sp (double sp, double p, double lon, double lat)",
and 5) calculate 'CT' (Conservative Temperature) using method "double gsw_ct_from_t (double sa, double t, double p)".
Now we have a basis for calculating potential enthalpy ("heat") using those values as follows:
1) calculate 'PT' (potential temperature) using method "double gsw_pt_from_ct (double sa, double ct)"
2) calculate "ho" (Potential Enthalpy) using method "double gsw_pot_enthalpy_from_pt (double SA, double pt)".
Now the "ho" value can be spliced into the GISS pattern as was done in the previous post when "T" temperature was spliced in.
Compare the graphs in today's posts with those of the previous post and you will see that the pattern of in situ temperatures matches the pattern of potential enthalpy (even though T is in degrees C and ho is in J/kg (joules per kilogram).
When "we seek to answer the question, 'what is heat" in the ocean?":
"... it is perfectly valid to talk of potential enthalpy, h0, as the “heat content” and to regard the flux of h0 as the “heat flux.” Moreover, h0 is shown to be more conserved than is θ by more than two orders of magnitude. This paper proves that the fluxes of h0 across oceanic sections can be accurately compared with the air–sea heat flux, irrespective of whether the fluxes of mass and of salt are zero across these ocean sections. This has implications for best oceanographic practice for the analysis of ocean observations and for the interpretation of “temperature” in models."
(Potential Enthalpy: A Conservative Oceanic Variable for Evaluating Heat Content and Heat Fluxes). It is colorful and interesting to mix estimates with actual measurements taken over time (Appendices: Oceans, Coastal, Sea/Gulf).
III. Closing Comments
The "splicing-in" of in situ values is like inserting exact measurements into mere estimations.
In this anomaly application it adds dimension and contrast which are helpful in the effort to acquire and fine tune our research data.
But, using only the actual in situ ocean measurements collected over many years gives the best perspective (In Search Of Ocean Heat, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17).
The next post in this series is here, the previous post in this series is here.
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