What "100 year flood" really means

How likely is a "Hundred Year Flood" this year? Does the likelihood change when you've just had one?

I have a subscription to an online new source. Many of the stories it publishes are open for comment. One of the reports was about a Turkish geologist, Naci Gorur, who was trying to raise earthquake awareness. I saved the following comment because it makes a crucial point about what the probabilities of "rare" events actually mean. The highlighted sentence sums up the math. Percentage odds are not intuitive. I've added the calculation below Repetto's comment. I used my computer's calculator to do the arithmetic.

[ by R.C. Repetto, Amherst, MA]

People can't deal with probabilities, such as "a hundred-year flood". If there was one ten years ago, they think they're safe for another 90 years. No, they face a one percent probability there will be one next year and more than a ten percent chance* there will be one in the next decade. That misunderstanding and shortsightedness is why people still move into disastrous locales, such as Florida or Phoenix or the mountainous regions of the West. It makes a mockery of the claim that "we" can adapt to climate change. We haven't and won't, until it's too late.

* If the odds of some event is 1 percent (one per hundred) per year, then the odds that it will happen within the next 10 years are (1.01^10*100)-100, or 10.4%

Footnote: If you knew there was a one percent chance of having an accident every time you drove your car, would you drive it?

The cost of externals: An accumulating debt

Steel, concrete, and climate change: the cost of zero-priced externals

New Scientist (November 16-22, 2019) has published an article showing the high carbon cost of making steel and cement, the two raw materials that make our techno-civilisation possible.

The article reports several projects to reduce the carbon cost. One is to use hydrogen instead of coal in blast furnaces. “If the economics work out”, that is. All these projects are priced at the actual costs of development and deployment. This makes them look expensive compared to traditional methods of making steel and cement. (1)

Steel and concrete are a prime example of how traditional economics has misstated the costs of our life style. Neo-liberal (Chicago school) economics prices externals at zero. Thus steel and cement have seemed to be cheap materials for making the things we want. In fact externals do have a price. We just haven’t bothered to work out good methods for pricing them, still less for paying them. (2)

As a species, we have evolved to use our environment as a freely available resource for making what we want, eg, spears. The cost of making these tools was the labour of making them. The cost to the ecosystems was ignored. Our ancestors didn’t notice or care that the tree they destroyed to make sticks for poking game animals to death meant that the ecosystem had to make another tree. As long as humans were a small component of the ecosystems, the long-term effects of our use of natural resources were minimal. (3)

However, the costs of externals accumulate. If we don’t pay them, they become a debt. Mother Nature always collects her debts. We either spend our resources now to mitigate and if possible reverse climate change, or we will pay with the loss of property and life.

(1) Concrete is made by using cement to bind the sand and gravel particles together. This process requires CO2, so some of the CO2 used to make cement is recovered from the air.

(2) Zero-priced externals mean that the goods are under-priced. The market works efficiently if and only if prices express costs accurately relative to each other. Mispriced goods distort the market, which leads to market failure.

(3) Human effects were actually not balanced by ecosystem recovery: archeologists have found evidence that agriculture began the climate warming cycle at least 7,000 years ago. Also, many local or regional extinctions of animals were caused by humans.

Climate is a chaotic system

     Climate is a chaotic system. It consists of a web of interconnected feedback loops. This makes it difficult to model precisely, since some feedback loops cancel the effects of other loops, and some feedback loops enhance the effects of other loops, and all of them are entangled with two or more other feedback loops. Chaotic system are characterised by non-linear relations between causes and effects. Small (sometimes very small) changes in some factor can become magnified into huge effects.

Some chaotic systems cycle through a series of states ("the seasons") that vary within some range but average out over time (number of cycles). This average is called the attractor. "Regression to the mean" is a common effect: Think of a baseball pitcher's performance over time. Pitching is the influenced by many factors, most of which affect each other. The pitcher's performance is a chaotic system: sometimes he's hot, sometimes he's not, most of the time he performs near his average level.

However, if some factor or factors exceed some limit (too much or too little) the whole system will shift into a new series of states, some or all of which are radically different from the previous ones.

There is no question that burning fossil fuels has increased CO2 concentration in the atmosphere, now approaching double the concentration of pre-Industrial Revolution levels. This is having an effect on climate (ie, on annual weather cycles). The important questions IMO are:
a) How fast is this happening?
b) Is it happening faster in some climate zones than others?
c) How far will it go?

Answer to a) Unknown, but climate models so far have understated the expected changes. This is shown in:

Answer to b) Yes. For example the Arctic: Predictions of the extent of summer seas ice (the extent of summer sea ice melting) have underestimated the melting. The general trend is faster melting than predicted by the models available at the time.

Answer to c) Nobody knows for sure how far climate change will go. Models are continually updated and tested with new data (both historical and current). Reserach uncovers new feedback loops. As these models get better they imply several (from my POV) important conclusions:

1) Climate can change very rapidly from one normal limit to the other (look up Little Ice Age).

2) Seasonal weather patterns can change in opposite directions;

3) Seasonal weather patterns can go from one extreme to the other within a year or two.

3) There's a lag between the warming effects of CO2 and climate change because of heat-sinks (chief of which is the ocean: over half of the recent rise in ocean levels is caused by the expansion of water as the oceans warmed up).

It's true that climate models aren't good enough to satisfy the popular yearning for "near certainty" in their predictions. But the certainty is higher than required in a civil law case ("balance of probabilities"), and IMO close to that required in a criminal case ("beyond reasonable doubt, emphasis on "reasonable").