According to Gallup, a minority of folks in the U.S.eh? are solidly skeptical of global warming (One in Four in U.S. Are Solidly Skeptical of Global Warming).
The skeptics in the U.S., and more so the world at large, are a minority.
Since the same goes for sea level change (SLC), which is sea level rise (SLR) and/or sea level fall (SLF), today, I want to address the SLR and SLF issues in terms of the type of skepticism stemming from ignoring the latest and/or most robust science.
In doing so, I specifically address those in the scientific community, because they are a source of the ignoring, and thus they are a source of the unknowing.
Which leads to the spreading of misinformation and disinformation.
II. Sea-Level-Fingerprint Science
The science that is being ignored has been developing for well over a century:
To our knowledge, Woodward (1888) was the first to demonstrate that the rapid melting of an ice sheet would lead to a geographically variable sea level change. Woodward (1888) assumed a rigid, non-rotating Earth, and therefore self-gravitation of the surface load was the only contributor to the predicted departure from a geographically uniform (i.e. eustatic) sea level rise. This departure was large and counter-intuitive. Specifically, sea level was predicted to fall within ∼2000 km of a melting ice sheet, and to rise with progressively higher amplitude at greater distances. The physics governing this redistribution is straightforward.(On the robustness of predictions of sea level fingerprints, emphasis added). This reminds me of the length of time between the discovery of "germs" and the acceptance of that fact by establishment medical professionals:
Semmelweis's observations conflicted with the established scientific and medical opinions of the time and his ideas were rejected by the medical community. Some doctors were offended at the suggestion that they should wash their hands and Semmelweis could offer no acceptable scientific explanation for his findings. Semmelweis's practice earned widespread acceptance only years after his death, when Louis Pasteur confirmed the germ theory. In 1865, Semmelweis was committed to an asylum, where he died of septicemia, at age 47.(What Is Pseudo Science?). Doctors and other scientific professionals emphatically rejected the reality of "germs" back then.
The science of "sea level fingerprinting" is well founded, but still not well practised or widely understood:
Rapid ice mass variations within the large polar ice sheets lead to distinct and highly non-uniform sea-level changes that have come to be known as ‘sea-level fingerprints’. We explore in detail the physics of these fingerprints by decomposing the total sea-level change into contributions from radial perturbations in the two bounding surfaces: the geoid (or sea surface) and the solid surface. In the case of a melting event, the sea-level fingerprint is characterized by a sea-level fall in the near-field of the ice complex and a gradually increasing sea-level rise (from 0.0 to 1.3 times the eustatic value) as one considers sites at progressively greater distances (up to ≈ 90° or so) from the ice sheet. The far-field redistribution is largely driven by the relaxation of the sea-surface as the gravitational pull of the ablating ice sheet weakens. The near-field sea-level fall is a consequence of both this relaxation and ocean-plus-ice unloading of the solid surface. We argue that the fingerprints provide a natural explanation for geographic variations in sea-level (e.g., tide gauge, satellite) observations. Therefore, they furnish a methodology for extending traditional analyses of these observations to estimate not only the globally averaged sea-level rate but also the individual contributions to this rate (i.e., the sources).(Fingerprinting Greenland and Antarctic Ice Sheet Flux) . The essence of the hypothesis of fingerprinting sea level is that we can discern where the melt-water (or calved ice bergs that eventually melt), came from or went to (cf. Wiley 2013, Royal Society 2006).
The science is counter-intuitive in the sense that more ice sheet melt means more SLF rather than SLR near the coast of the landmass where that melting ice sheet is located.
Nevertheless, once we get past that "mysto" reality, we have a useful tool for discerning which ice sheet is actively melting / calving, and therefore, which coasts will experience the impact of that melting and calving:
A rapidly melting ice sheet produces a distinctive geometry, or fingerprint, of sea level (SL) change. Thus, a network of SL observations may, in principle, be used to infer sources of meltwater flux. We outline a formalism, based on a modified Kalman smoother, for using tide gauge observations to estimate the individual sources of global SL change. We also report on a series of detection experiments based on synthetic SL data that explore the feasibility of extracting source information from SL records. The Kalman smoother technique iteratively calculates the maximum-likelihood estimate of Greenland ice sheet (GIS) and West Antarctic ice sheet (WAIS) melt at each time step, and it accommodates data gaps while also permitting the estimation of nonlinear trends. Our synthetic tests indicate that when all tide gauge records are used in the analysis, it should be possible to estimate GIS and WAIS melt rates greater than ∼0.3 and ∼0.4 mm of equivalent eustatic sea level rise per year, respectively.(Estimating the sources of global sea level rise, emphasis added). This is why I chose to write programs to utilize the above hypotheses, and to lose the "mean sea level" paradigm (The Gravity of Sea Level Change).
No more "Mr. Mean old sea level" for Dredd Blog.
III. The Zone-In Approach
(The SLR and SLF dynamics cannot be combined without creating an obscurity "e.g. mean global SLC".)
What the zone approach helps to do, however, is to group geographical locations together for an initial "zoning in."
|Fig. 1 Zone In|
At first Dawn was at an orbit that gave us a comprehensive view, noticing interesting phenomenon, from a maximum orbital distance.
Then as it moved closer and closer to Ceres, once various outstanding features were discovered, those features could be more intensely focused on at each lower orbit.
|Fig. 2 Three Dynamics|
When aspects of both SLF and SLR become attention grabbers, the software solutions can focus on them individually (or collectively by selecting multiple SLR vs SLF types).
"Hey, check out this latitude and longitude, it has SLR (or SLF) that is quite out of the 'ordinary' mean sea level."
Projection software can't give a reasonable projection by combining (deriving the average of the two) a strong SLF zone with an SLR zone.
In Fig. 2 you can see that SLF areas such as Yakutat, Alaska (Proof of Concept), compared with SLR areas, such as San Francisco, CA, are distinct even though they are in the same geographical zone "ak":
SAN FRANCISCO (Lat: 37.806667, Lon: -122.464996) (1855->2014) (6954->7143) (7107,SLR)They are both in the same geographical zone ("ak"), but they are very different because Yakutat is near Glacier Bay, which has been melting for a long time, creating SLF near it (7133 - 6442 = 700mm SLF).
YAKUTAT (Lat: 59.548332, Lon: -139.733337) (1940->2014) (7133->6460) (6442,SLF)
San Francisco, on the other hand, is not near a large ice mass, so it has SLR as the Glacier Bay ice melts (7143 - 6954 = 189mm SLR).
So, the "mean average" of the beginning years (6954 + 7133) / 2 = 7043.5, and the average of the ending years (7143 + 6460) / 2 = 6801.5 (average 242mm) hides the strong SLF of Yakutat, by blurring it with the SLR of San Francisco.
Thus, what does the mean averaging of the two do, besides hiding the stark reality?
You get my drift, but it will help to watch the video below if you haven't already.
The next phase of the software development currently ongoing is directed toward activating that approach.
Thus, I can use the same algorithms already written, however, they will not take in broad based, mixed data streams any longer.
No, they will focus on the portion of a zone that is influenced by what is taking place with particular ice sheet impacts on that particular section of the zone.
Then, those algorithms will calculate the ice sheet's expected future (e.g. rate of doubling) then go on to project the SLF and/or SLR of that one, or all of those similarly impacted tide gauge locations, within that zone.
For example, those "on the west side of zero."
Note that on the grid map of zones, "aa, ag, am, ba, bg, and bm" are on the west side of longitude zero.
Which is a lower orbit as it were, but we can get even closer, to focus on only the tide gauges separately (as subgroups) in the SLF or SLR portion of a zone.
We can better focus when we deal with subgroups that are in the fingerprint left by a particular ice sheet (note too, that some few zones are all SLR or all SLF).
That is, melt water and ice berg contribution to the sea by that ice sheet, as relocated.
Relocated by ice sheet mass / gravity loss, the overarching Earth's gravity, any axial relocation as a result of the ice sheet mass loss, the Earth's rotation, and the like.
The projection software is composed of computations that acknowledge those scientific realities.
Thus, projecting likely future SLC numbers that fit the path, which these knowing scientists have cut out of the jungle of the unknowns for us, are much more likely to be increasingly accurate (New Type of SLC Detection Model, 2).
The next post in this series is here.
Professor Jerry Mitrovica, Harvard University, comes to D.C. to 'splain: