Saturday, February 17, 2024

Because it is not climate

That's why.  

So yesterday we were supposed to have a dusting of snow.  The temperatures would drop, some mix of rain and snow, perhaps a little dusting.  And that was that.  As late as yesterday morning's weather forecasts on the morning news.  Yet this is what it looked like this morning: 

Not exactly a dusting.  And because we weren't ready, much of the prep work hadn't been done.  My sons noted that they didn't issue any type of travel advisory until after the evening news, when the majority of the snow had passed.   

This morning, however, the weather forecaster did address the staggering fail when it came to the forecast.  Which is only one of many  in recent months.  We've noticed that it does seem they have been missing the forecasts more than usual over the last year or so. 

The meteorologist said, at the end of the day, it's weather.  Weather is complicated and not always easy to predict. Plus it's based on models.  Models provide many things, but it isn't some magical spell.  In this case, only one model showed anything close to what happened.  All other models showed what all of the local stations predicted.  A light snowfall if anything at all. 

I had to chuckle.  After all, much of the climate change narrative is based on models.  But apparently those models predicting what the entire global climate will be in a hundred years are just spot on perfect in their accuracy.  As opposed to models that predict the daily weather in a given location.  How can we predict what will happen outside our windows later today?  It isn't like predicting the entire planet's climate a hundred years from now!  Apparently that's as easy as pie. 

Always remember: A forecast of 79 degrees means excessive heat watch.  Modern meteorology in a nutshell


  1. It's all about distribution of wealth and controlling what people do in their lives. As far as I'm concerned climate change is another word for communism.

    "In a Nov. 14, 2010 interview with the Swiss newspaper Neue Z├╝rcher Zeitung, Edenhofer, co-chair of the U.N. IPCC's Working Group III, made this shocking admission:
    One must free oneself from the illusion that international climate policy is environmental policy. [What we're doing] has almost nothing to do with the climate. We must state clearly that we use climate policy to redistribute de facto the world's wealth.

    In the same interview, Edenhofer added this:
    Climate policy has almost nothing to do anymore with protecting the environment. The next world climate summit in Cancun is actually an economy summit during which distribution of the world's resources will be negotiated."

    Read the whole article here.

    1. I don't think it takes a tremendous amount of effort to imagine that protecting the environment or combating climate change is likely outside of the top ten in terms of priorities.

  2. There are basically two schools of thought when it comes to uncertainty in models:

    The first says that you should carry through all uncertainty, such that each new stage of the model or new measurement magnifies existing uncertainties. For example, suppose you could be off by half and inch every time you measure. If you measure a hundred times, then you could be off by 50 inches, assuming the worst case scenario where you have the maximum error each time. If you use this data in a model you have to start by assuming that it could be off by 50 inches, and this will cause additional uncertainty because the model itself isn't going to be certain even with perfectly accurate data.

    The second school of thought says that we can suppose that errors "average out" over time. So in the above example sure each individual measurement could have been off by half an inch, but probably the times we were over by a half an inch cancel out with the times we were under by half an inch so we'll suppose that our combined 50 measurements are very accurate; in fact even more accurate than a single measurement. You can use similar arguments for repeated use of models.

    The second perspective only works with very particular assumptions. We very well could have a consistent bias which pushes our errors in one direction, in which case they will get worse the more we combine. If we do not know that this isn't the case, the only honest thing to do is to do a worst case scenario analysis and use that as our margin of error. Of course, people end up preferring the second method because it convinces them that their results are more significant. And once they start using it they get even more sloppy: in effect they start assuming that with enough measurements there is NO measurement error, and they start viewing the output of models as if they were more accurate than reality.

    And thus they can square the circle that you present. The weatherman is only talking about one day with a limited set of measurements. But if we combine inaccurate measurements over the whole world and then make predictions for years in the future, somehow that is going to be more accurate. It's absurd of course, but many academics think this way. I wonder if Isaac Asimov's Foundation series is to blame (his short story "Franchise" also contains this view.)

    1. Well, numbers aren't my game. My wife is the science/math person of the family. But I get the gist of what you're saying. As I've said, it isn't that I deny our approach to STEM has had potentially negative impacts on our environment. I simply reject the political narrative of Global Warming. And it's the little tricks like this, that smack more of snake oil sales than science, that make me even more skeptical. The idea that I'm supposed to blindly accept that despite everything, trust us it will all fit the narrative, is just a little beyond what I'm capable of believing.

  3. Of course it’s not about The Climate (TM). All the talk from Davos tells us as much. A couple summers ago our county had a planning meeting and the guest speaker was a lady from the WEF who spoke for 2 hours on literally NOTHING. Except she extolled vague concepts like being “fluxy” and sharing your car with others. The tentacles of The Climate (TM) are about long and deep as The Science (TM).

    1. The narrative has become dogma, like so many things the media promotes, and that makes it tough. Not that there is anything wrong with dogma per se. But I don't think science and dogma should be in the same room. The fact that advocates preach it like it is some God truth and don't even entertain the possibility of dissenting views shows why it's such a tough nut to crack now.


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