Thursday, April 16, 2015

The Evolution of Models - 5

Fig. 1 (click to enlarge)
I. Start Here

The notion of building a brain for a machine mystifies people who have never programmed computers, i.e., taught them to think.

That is, it mystifies people who have never developed software, which is the computer's cognitive dynamic that is a lot like the cognitive dynamic of human thinking at some level (garbage in, garbage out).

Highly opinionated people will imagine the wildest of scenarios when confronted with a machine with a software brain that can defeat them at chess.

Or defeat them in a question answer session about world geography, astronomy, or the number of atoms in various elements.

This is especially so when confronted with computers having software brains that are models which calculate future events better than they can.

I want to try to demystify this context by showing some of the world's most simple software brains for computers that can predict sea level rise.

The first one is the brain of a highly opinionated computer, which asks no questions because it already knows it all, so it just spills the beans:

#include <iostream>
int main()
{
 cout << "Hello world! SLR will reach 0 ft. in 120 years!" << endl;
 return 0;
}

That is the Senator Inhofe model.

The next example is the brain of a data driven computer, which asks a "genius" for data before it spills the beans:

#include <iostream>
#include <string>
int main()
{
cout << "Hello genius! How many feet of SLR will take place in 120 years?" << endl;
string slr;
cin >> slr;
cout << "Hello again world! The genius says that [" << slr << "] ft. of SLR will take place in 120 years!" << endl;

return 0;
}

The point is that serious software is a lot like serious people: it takes a lot of work to produce, and what they say is more reliable and less frivolous than merely opinionated people.

II. Don't Zone Out

That there are zones where ice sheet or ice cap melt takes place at a different rates
Fig. 2 (click to enlarge)
than at other zones should be as certain as the fact we live on a globe and not on a flat earth.

The zone approach to sea level rise (SLR) software, in Fig. 1, shown as four bell-curve type shapes, with X1, X2, X3, and X4 as points in each zone.

To reflect reality, "X" represents when CO2 in inordinate quantities is ejected into the atmosphere.

The upward slope is the resulting temperature rise until "Y" is reached, which is the point at which ice melt takes place (X1 = coastal, X2 = inland 1, X3 = inland 2, and X4 = no melt).

That there would be different beginning points for each zone ought not to be too much for anyone to comprehend.

Fig. 3 (click to enlarge)
The zone map of Greenland at Fig. 2 and Antarctica at Fig 3 show the four zones at each location.

It would seem to be intuitive that low lying areas at the coasts near warming oceans would be the first place where melt would take place.

As the ice weakens, one would expect some of the ice to break up into various ice chunks and slide off the land mass into the sea.

Either melt water flowing into the sea, or ice calving into ice bergs causes SLR.

In general, the ice does not have to melt to cause SLR, because when it slides off the land at the coast and into the sea, it causes displacement.

Then, depending on the circumstances of salinity, etc., it may cause a bit more SLR when it melts (SLR when floating ice melts?).

The concept in Fig. 1 shows a melt sequence, beginning with the first zone most likely to melt, then incrementally proceeding to the least likely to begin to melt.

The proof of the validity of this concept is shown by comparing the oft used WAIS and EAIS (West and East Antarctica) nomenclature, with the four zones comprised of natural contours, distance from, and elevations above the warming seas.

The WAIS and EAIS nomenclature is based on lines drawn on a paper map rather than being based on natural configurations of obvious geographical features.

The melt and destabilization of the coastal Totten Glacier @ EAIS, together with the melt of glaciers along the WAIS coast, illustrates the point that they are both in the same Dredd Blog SLR software "coastal zone."

Those familiar with erroneous historical Antarctica rhetoric will remember that the EAIS was considered to be a separate, "stable" place, compared to WAIS, and that EAIS "would not melt" for ages (The Case For A Stable EAIS).

Those familiar with real time Antarctica and with Dredd Blog SLR software will remember that coastal areas of both WAIS and EAIS are not only in the Dredd Blog SLR coastal zone, but that both WAIS, and EAIS are melting now (i.e. losing volume and/or mass).

III. Leave The Absolutes At The Bar

That the zones are geographically distinct (height above sea level, distance from ocean, etc.) does not mean that there will be no overlapping melt, it just means that, by and large, the melt will proceed like dominoes sequentially falling as the ocean and air warm up.

The Dredd Blog SLR model has database values that set dates for triggering the start of the simulation of the melt of each zone, or turn them off, by allowing the user to specify what year the melt in each zone begins.

For example, "Greenland inland 1" can be set to a different year when melt starts, from "Antarctica inland 1" (as can the other zones).

IV. Irrelevant Difficult Parts

A. Why Simplify?

The reason for focusing only on SLR software in a simplified way is underscored by 1 study in 1 city in 1 country, out of 196 countries with more than 4,764 ports (World Port Source):
2.4 Resources Threatened by Sea Level Rise

In any given area, rising seas pose a threat to many different types of resources. Among the vulnerable coastal systems are transportation facilities such as roadways, airports, bridges, and mass transit systems; electric utility systems and power plants; stormwater systems and wastewater treatment plants and outfalls; groundwater aquifers; wetlands and fisheries; and many other human and natural systems from homes to schools, hospitals, and industry. Any impacts on resources within the affected area may lead to secondary impacts elsewhere.
...
3,2 ... Facilities At Risk [@ 1 m/3 ft. SLR]

Schools ... 60 ... Healthcare facilities ... 29 ... Fire stations ... 10 ... Police stations ... 8 ... hazardous material sites ... 208 ... buildings ... 49,000 ... lives ... 220,000

3.4.2 Ports
...
Our assessment of future flood risk with sea level rise shows significant flooding is possible at the Port of Oakland. The San Francisco and Oakland airports are also vulnerable to flooding with sea level rise. In addition to directly affecting port operations, sea level rise may cause other interruptions to goods movement at ports. Sea level rise can reduce bridge clearance, thereby reducing the size of ships able to pass or restricting their movements to times of low tide. Higher seas may cause ships to sit higher in the water, possibly resulting in less efficient port operations (National Research Council 1987). These impacts are highly site specific, and somewhat speculative, requiring detailed local study. We also note the connection between possible direct impacts of sea level rise on the ports themselves and possible flooding of transportation (rail and road) corridors to and from the ports.
...
4.1 Conclusions

Rising sea levels will be among the most significant impacts of climate change ...

We estimate that sea level rise will put 220,000 [people at risk] ... with a 1.0 m ... rise in sea levels ... A wide range of critical infrastructure, such as roads, hospitals, schools, emergency facilities, wastewater treatment plants, power plants, and wetlands is also vulnerable. In addition ... property is at risk ... with a 1.0 ... m rise in sea levels ...
(Impact of SLR - San Francisco Bay, emphasis added; PDF). The real difficulty is not "being able to see" what is coming (it is easy to see what is coming).

(TEST: multiply the individuals in that 1 area who must move, by the number of ports ... 220,000 × 4,764 = 1,048,080,000 ... if moving over a billion people does not convince us, then multiply each of those figures, for each item, schools, healthcare facilities, fire stations, police stations, hazardous material sites, and buildings, etc., by 4,764).

The real difficulty is being able to do something about the impact of SLR.

B. How To Simplify

It should be clear that the progression through X1,2,3,4, Y1,2,3,4, and Z1,2,3,4, is also a progression of difficulty, in terms of determining when each Zone1,2,3,4 activity will begin to take place.

I have not concerned myself with that too much, because just the coastal zones of Greenland and Antarctica themselves can generate SLR above the 3 ft. catastrophe level.

The model sets SLR potential in each coastal zone of the three locations as: (Antarctica) 10.0265 + (Greenland) 4.298 + (non-polar) 0.27, which totals 14.5945 feet (see Section V for those figures as they appear in the data).

Focusing on stopping the catastrophe by leaving fossil fuels in the ground, and switching to non-suicidal fuels, is the target logic and target sanity.

V.  Example Data File

The following is an SQL related file structure which the mySQL client program processes to create a simple SQL table, from which the SLR software loads its values:

CREATE DATABASE IF NOT EXISTS [sql database name];
USE [sql database name];
CREATE TABLE [sql table name] (
[index variable] INT NOT NULL AUTO_INCREMENT,
[key variable] VARCHAR(255) NOT NULL,
[data variable] VARCHAR(32) NOT NULL,
PRIMARY KEY ([index name]) );
insert into slr_projection VALUES (0, "[key variable] = ", "[data value]");

I include this sample for the simple purpose of showing that changing the data can seriously change the outcome of what the software generates.

Some values have more impact on the outcome than others do.

For example, changing the year the melt begins in each zone, the number of feet of potential SLR in each zone, the degrees Celsius the globe will be warmed to by the year 2100, and the like, can significantly change the outcome.

That is why I choose to use, as the backbone, IPCC projections from years ago that turned out to be correct projections when reviewed for accuracy.

And, it is why I try to improve upon the IPCC SLR projections, which have not been accurate (The IPCC Record on Global Warming Temperature Projections, The Evolution of Models - 4).

VI. The Way It Works Now

I use the "curve", the "footprint", and/or the "pattern" shown by the IPCC temperature and CO2 ppm projections, which have been shown to be reasonably accurate.

I apply that mold to the SLR potential in each zone of each location in a manner that follows the upward slope of the IPCC temperature and the CO2 ppm patterns, after fusing the two into one trend-slope.

Since that slope is upward, and the recent satellite measurements have shown a significant upward slope, we know not only that there is acceleration in SLR going on, but we also know that the rate of acceleration of SLR is going to be catastrophic to ports around the globe (Will This Float Your Boat - 8).

VII. Conclusion

It is much easier to focus on SLR, leaving out the rest of climate change, instead of trying to construct a software program which tries to project all aspects of the damaged global climate system.

What I mean is that the specific purpose is to alert those who want to hear and know that SLR is a real and present danger.

I am most definitely an unapologetic alarmist who sounds an alarm when it is time not to err on the side of disaster:
A blogger, commenting on the prudence of having insurance, wrote: "[as] far as frequency you could figure that 0.317% of households ... 0.276% of housing units had a fire in the year."

Nevertheless, fire insurance is not only required for mortgages, it is also a custom of our culture to have fire insurance, and in fact even with those very low odds (less than 1%) that our own fire insurance protection will be used in the context of catastrophic circumstances, as a society we still practice "better safe than sorry" insurance ideology.
(New Climate Catastrophe Policy: Triage - 12). Not sounding the alarm is toying with the lives of billions of people.

If we must err, it is orders of magnitude better to err on the safe side.

The next post in this series is here, the previous post in this series is here.

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