Some rulers say there is a nitrogen “crisis”, and others say there is a climate “crisis”. There is no nitrogen “crisis”, and there is no climate “crisis”, neither. But since those who rule over us think these crises exists, it is worth investigating why they think so.
One reason (well known to regular readers) is models: too much unjustified trust in Expert models.
The AERIUS/OPS model (OPS for short) is a model which, among other things, measures certain forms of nitrogen (and other chemicals) deposition. It’s used extensively in the Netherlands by rulers to make consequential decisions. Such as ordering the closing of farms.
An open question, for which I have no answer, is where these rulers think their food will come from after they save us all from cow farts? China? Albert Heijn? You tell me.
Anyway, my friends Geesje Rotgers and Jaap Hanekamp and I have a new paper: Criticizing AERIUS/OPS Model Performance. Download and read at your leisure. If you’re in a hurry and don’t have spare toeslag in your ogenblikkelijk, go to Hanekamp’s place to read a summary in Dutch. Or read this post.
The paper is long and detailed, but not especially complicated. I’ll focus here on one or two aspects of model validation—also called forecast verification—which are more unfamiliar, but which are crucial to grasp.
Now model validation isn’t easy. It requires time and money: at least as much, and usually more, time than it took to create the model, and is therefore expensive. Facts which tend to discourage thorough vetting.
One way, and the worst way, is to test the model on already known data (a.k.a. observations). This is because (a) it’s always possible to build a model which predicts perfectly old observations, and (b) the easiest person to fool is yourself, and (c) the second easiest person to fool is the model user.
This makes the only true way to test a model is on observations never before seen or used in any way in building that model.
Those who built OPS, or some of them, knew this. Some true validations were attempted. But not many, and certainly not thoroughly. The verification measures used were inferior, and there was no accounting for skill. Skill as it is defined formally.
I have attempted to explain skill many times, on the blog, in papers, and in a book. I can’t make it stick. Maybe you have better ideas how to describe it. Skill is a commonplace in meteorological modeling, far less so (for obvious reasons) in climatological, and almost unknown elsewhere. But it should be everywhere.
This is skill: if you have two models, A and B, and B is better than A, then you should not use A, but should use B. B has skill over A.
Now I ask you: is that complicated? True, we have to define “better”. But that’s easy. It means what it says: better as defined by whatever performance measure you picked. B having skill over A doesn’t mean, or imply, B is any good or should be used, of course. Just that if you were forced to pick, and such things as cost or availability weren’t important, you’d pick B.
OPS does not have skill with respect to a simple “mean” model.
That is, if we’re predicting NH3 (or SO2 or whatever) deposition at some location, and we knew the mean over the time of prediction and used that mean as a prediction, that model (for it is indeed a model) would often beat the vastly more sophisticated OPS—using the performance measures selected by those who rely on the model.
Our paper describes these measures. One is “fractional basis.”
where Y is the observations and X the model prediction.
This is best when FB=0, which happens when the mean of the predictions equals the mean of the observations. Matching means is, of course, a desirable trait, but it is the weakest of verification measures, because, experience shows and as we show in the paper, even poor models may have equal means with observations.
Such as the mean model. Which will always nail, absolutely kill, the FB. How can it not?
That doesn’t mean you should use the mean model. That is the Do Something Fallacy, so beloved by many. It means you should fix OPS. Read the paper for details, and for times where OPS might sometimes (not often) have skill over the mean, using FB and other measures.
A prime way to fool yourself is aggregations, or averaging. Formal OPS validations played this trick on themselves. Here’s a picture to show how easy this is:
For whatever reason, OPS validation papers always invert the axes, putting the observations on the x-axis and predictions on the y-axis. We followed suit. The left panel is a bunch of made up numbers, no correlation between observation and prediction, except that both sets have the same mean. The red is a one-to-one line on which all dots would lie if the model here were perfect (notice, though, how that red line can fool the eye: it seems to draw the points closer to it).
The model isn’t perfect. It can’t be. It’s made up. It stinks. On purpose. But suppose the left picture was days in a month. What if we took the average of those days, then the average of each month over a year. Then plotted those averages over the course of several years.
They’d look like the right panel—which is what we did with more made-up numbers. All of a sudden, the model looks fantastic! Wow! Look at how close those lines are to one another!
These are still all numbers completely made up, with zero correlation between them, except they agree in the average. The correlation after averaging suddenly appears.
This proves that you can easily fool yourself in validations using averages. (Somewhat hilariously, even this made-up model would not have skill next to the observed mean model, with the FB as a score. Old time readers will recall we have seen this trick used many, many times in climate model validations.)
We also asked: even if the OPS is perfect, is it important? One of the concerns rulers have is how nitrogen from dairy farms affects so-called natural areas. So we ran the model using typical conditions, and looked at deposition at a nature area from a simulated farm. Here’s the results:
One of the schemes rulers have is forcing farmers to give up half their cattle. To “solve” the nitrogen “crisis.” At least for this run, halving from 400 to 200 cows leads to a reduction of about 3 moles of nitrogen per hectare per year at the nature area (the hexagon with the largest deposition).
Eliminating all cows leads to a non-whopping 5 moles of Nitrogen per hectare per year.
We go into details in the paper, but it must be obvious that even measuring that trivial difference is difficult, or impossible. Plus the atmospheric measures the Netherlands now uses (the MAN data) are estimates themselves. Meaning they have uncertainty in them.
Of course, we do not pretend these runs are a complete review of OPS. But they are not unusual. Add to that the weak and unskillful performance of OPS, and we can’t be certain what is going on.
“Okay, Briggs. You convinced me. OPS needs fixing. But we have to do something, so we have no choice but to use it until something better comes along. We need to alleviate the nitrogen crisis.”
No you don’t. You don’t have to do anything. That’s the Do Something Fallacy again.
Even worse, the reason you believe there is a crisis is because of the model. You’re arguing in a circle. You can’t say with any certainty there is a crisis. Even if you believe there is, and you believe OPS, you won’t be able to measure with any reasonable degree of certainty whether your “solutions” had any effect.
Besides all that, if you do implement your “solutions” and close down the farms where are you going to get your food?
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Briggs wrote: “No you don’t. You don’t have to do anything. That’s the Do Something Fallacy again.”
I can think of a reply by someone who shall not be named (but it begins with a T and ends with a B hint hint): “But by it’s unknown nature it could have a FAT TAIL! We could be facing a multiplicative risk and an existential threat to humanity! Ban Nitrogen! Ban all agriculture!” LOL.
You’d almost think we were all in a state of Mass Hypnosis aka Mass Psychosis. You’d almost think it, if that weren’t an unapproved thought.
What is most needful, for them, is Obedience to the Current Narrative. Exercises in obedience are always a feature of forced collectivism; that, and magical hypnosis: while you’re trying to figure out under which cup they’ve hidden the peanut, they’re busy stealing the farm.
You’d think we’d be CRAZY to fall for it. Yet here we are. Pretty crazy.
Hypnotized by models…..or not even that. Hypnotized by experts. We sometimes call them magicians, but the ones in Las Vegas don’t hold a candle to these experts w/ their graphs; these ones can shut down whole societies over a virus, declare CO2 a “pollutant”, and close farms because “nitrogen”.
Part of their pleasure with models, is choosing what to model, and more importantly, what NOT to model. In this case, you will not see them model the reduction in food supply and resulting worldwide famines. They’re all stocked up for years to come, and in their view, prepared to ride this out.
Maybe we don’t KNOW we are at war, or we don’t care. We’ve become lazy and indifferent, and our enemies (the enemies of liberty, the forced collectivists) have already taken over most of our institutions from within, without firing a shot.
Now, all that’s left in this war action, is the mopping up, as our energy infrastructure is destroyed, as our farms are taken out of production, and as thousands upon thousands of foreign nationals, most of them young, gang and military-age males, pour across our southern border.
If this doesn’t describe what happens during “war” I don’t know what does. I guess “War” can be added to those other words with fuzzy definitions, like “Recession” and “Woman”.
I wonder how they’ll re-define “Famine”?
“…where are you going to get your food?”
Get with the program, Dr Briggs! This has all been worked out for us. Just relax and eat the bug, denier!
“Cricket Farming: 7 Effortless Steps to Raise Crickets for Profit/Food
If you can get past the idea of eating a cricket, you might be surprised to learn just how good they actually are for your health. Crickets contain a ton of protein without a lot of fat or calories.
Actually, they contain more protein per bite (per density) than beef or chicken can provide per bite. For example, in a 100-gram cricket there is 16-21 grams of protein.
Also, there is only 5 grams of fat and 121 calories per 100 grams of crickets. Beef can contain up to 300 calories per 100 grams. Not to mention, the fat that crickets have is actually the good kind that will not raise your cholesterol.”
Nitrogen deposition or fixation is required for plant growth. That’s all you really need to know about all this. The beings in charge wish to reduce or eliminate food production in order to “reduce the excess population,” as Scrooge would say.
As for the total amount, Nitrogen has an atomic weight of 14. The 5.87 moles per hecatre (a square 100 meters on a side) allegedly produced by cow amounts to less than 84 grams per 10,000 square meters per year. That’s a trifle over one ounce per acre.
It amuses me that a study that claims nitrogen kills plants also says it results in rapid weed growth – in the same paragraph. Oh, and by the way, nitrogen is 78% of the atmosphere. That same paper claimed that pure rain water was hazardous because it moved a tiny amount of nitrogen from the atmosphere to the ground. Which, again, is absolutely essential for plant growth.
”Even worse, the reason you believe there is a crisis is because of the model. You’re arguing in a circle. You can’t say with any certainty there is a crisis. Even if you believe there is, and you believe OPS, you won’t be able to measure with any reasonable degree of certainty whether your “solutions” had any effect.”
Watching you dissect sketchy models is as interesting as watching someone reveal just how magicians do their tricks. In both cases deception produces an illusion, and in both cases self-deception is a powerful factor. The Sketchy Model trick is like the Sawing a Girl in Half trick — it looks real, but it’s just an illusion. These sorts of tricks are practiced on a grand scale by the Magic Masters who seek to rule by deception. They practice a craft as old as Eden. Presenting illusions, casting spells, and hypnotizing an audience gives them power. Their magic spellcraft is passed down through the generations, just as the tricks a magician employs are passed down.
One of the secrets of magicians, and the Magic Masters is that people like to be deceived. Illusions can be exciting and satisfying. And we are good at deceiving ourselves, as Briggs notes. So much so that it can be difficult disabusing a dupe. Especially so when the illusion justifies some sin and makes the dupe feel good.
I’m reading Tim Reiterman’s excellent book on the Jim Jones cult. It’s fascinating to see how freelance magician Jones was able to spellbind a following through deception and canny psychological manipulation. Many of the techniques he used are currently being used by the Magic Masters who have turned half of Western Civilization into a scaled-up Jim Jones cult. Next up in my queue is a new book by Mattias Desmet — the “mass formation psychosis” guy — The Psychology of Totalitarianism.
Interesting nugget on Desmet:
”With his background in statistics, Desmet studied the statistics that were presented by government and media outlets. When he noticed that most of the people uncritically accepted these numbers, even though they were often “blatantly wrong”, he started to study this phenomenon from a mass psychology perspective.”
It’s hard to trick a good statistician.
The tried and true EU method called destroy everyone’s dairy sector so the French can sell their shitty milk. This is literally the only reason for the existence of the Nitrogen Directive.
Ask former dairy farmers in any new member state. I don’t understand why the Dutch are so confused about what is going on and why they fall for the WEF and refugee agitprop. Just call up your partners in Czechia or Romania and ask. You can’t fight a battle if you don’t know who your enemies are.