Climate Change by the Billion

Dollars, that is.

count


The data come from NOAA, amounts are adjusted for inflation with the comsumer price index.

Billion-dollar weather disasters are getting more common. A lot more common. The reason is man-made climate change, i.e. global warming. It’s part of the cost of carbon.

NOAA classifies these disasters by type, and some are not increasing but you wouldn’t expect them to in a warming world. Like billion-dollar freezes, for instance:

nfreeze

It might look like they’re on the decline, but the change is not statistically significant (as indicated by the “p-value”) so there’s not really evidence of that. But when it comes to floods, the evidence is incontrovertible:

nflooding

We’ve already had 4 billion-dollar flood events this year (Texas/Louisiana March, Houston April, West Virginia June, Louisiana August), and the data for 2016 only go through September. As for severe storms,

nsevere_storm

It’s already clear that the Trump administration intends to eliminate the “social cost of carbon” from all accounting of the cost of energy use. They’ve already taken steps to do that, and Trump hasn’t even been sworn in yet.

That means that the economic cost of increased weather/climate disasters, a direct consequence of man-made climate change, won’t figure in the cost of fossil-fuel industries doing business. It won’t eat in to their profits. It will eat in to your personal cost of living. It might destroy your home, your car, kill your retirement fund, put an end to your job, increase your insurance bill — if you can even get insurance.

Perhaps it won’t be too long before these figures actually go down. That’s because they’re based on the amounts of insured losses. The number of disasters and their total cost may go up — but the amount of insured losses will go down because nobody can afford insurance any more.

And all of that is just the economic cost of carbon. There is also the cost in human suffering. When Donald Trump and his administration say that’s not a real cost, that it’s just a “hoax invented by the Chinese,” go to New Jersey and ask someone who lost his home in superstorm Sandy whether the cost of human suffering is real or not. Go to New Orleans and ask someone who lost a loved family member to Hurricane Katrina, to put a dollar price on human suffering.

The guiding principle of the new administration will be this:

A disregard for human suffering in the pursuit of profit.


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15 responses to “Climate Change by the Billion

  1. You forgot one way people will pay for it: in their taxes.
    When you lose your home, your car, your business, your job (because your employers lost their place of business), your health (because you lost your clean water), etc. everyone will be looking for disaster relief. And guess how that will be paid for.

  2. Yep.

    Should we count the costs of Hurricane Matthew–billions of dollars and 40-odd Americans dead, IIRC–under “Severe Storm”, or “Flooding?” Or should we attempt to apportion between the two?

    And why didn’t we hear much about it from the guys who were insisting that the “US hurricane drought” was significant?

    Sorry, feeling a bit bitter.

    • A trend toward fewer US landfalling hurricanes in no way implies zero ever occurring. Nor does a single event constitute a trend in the other direction.

  3. It is actually possible that damages due to freezing increase. Nature adapts. When it gets warmer the growing season starts earlier. Thus freezing is less related to the mean temperature and more to the temperature variability in spring. How the variability will change is hard to predict.

    Like for all damages it is also important how people protect themselves. At the Heathrow airport they were so stupid to think that with climate change weather would stop and they did not prepare themselves for snow any more. If farmers would think the same that could also lead to more freezing loses.

    For insurers it is important that they can compute the risk. Now that we take the climate system out of known territories it becomes more difficult to assess the risk. The more so if the Trump government will punish the messengers on climate change. We still need a lot of scientific work to assess local changes and changes in variability.

    • I suspect that the “freezing” data are in fact far more complicated than a straight-forward regressed p value would indicate.

      As Victor points out the earlier onset of spring leaves agricultural systems (and ecosystems…) vulnerable to subsequent cold spring events that will still occur in spite of the underlying warming trend. The literature is replete with examples, and in the short to medium term warming may actually exacerbate cold damage in some systems.

      I baulk at the fitting of a simple regression to the freezing data, because there are several phenomena that are missed in doing so. They’re at least somewhat intertwined, but basically it’s very plausible that a certain subset of objectively-defined freezing events are decreasing with time, whilst a new set of freezing events increasingly manifest as heat moving to the poles actually displaces polar temperatures to lower latitudes.

      I suspect that cryptic factors are missed in a simple “freezing” regression, as old and new phenomena are binned in the same category.

  4. But you forgot the really important question. It doesn’t matter if the cost has gone up, whether more people are impacted, whether there has been an increase in inequality in who feels the impact.

    What matters is how much the costs have changed relative to GDP.

    :-)

  5. Is there an estimate for the costs of drought? AGW will dramatically affect that as well.

  6. “A disregard for human suffering in the pursuit of profit.”
    Unlike before.

  7. We broke the arctic, which broke the jet stream. Polar blobs can park over Russia or Canada longer and age/damage infrastructure and kill off already stress wildlife. So, yes, climate change can produce “freeze” waves.

    • We can also get such events without climate change. Climate change is real, but your cause won’t benefit if you hype every event as if climate change is THE explanation. Weather variability remains larger than the trend in the middle latitudes. Honesty is more important than fear mongering, just like it should have been for the Iraq war.

  8. Not that I can ask you to do more work, given all the good stuff you’re already working on… but it would be great to see the comparison of “damages from events plausibly altered by climate” v. “events unlikely to be influenced by climate” (e.g., earthquakes). I vaguely recall that SwissRe had a chart that showed the two diverging nicely, as one would expect.

    (which is much better than the RP Jr. “damages/GDP” which completely ignores all the flaws of GDP, along with the possibility that better building codes and other adaptive efforts would very much skew trends in that measure)

  9. Of interest, maybe:

    +———————————————————————————————-+
    | Sometimes the Noise is Signals, Too |
    | from the come-on-feel-the-noize dept. |
    | posted by Fnord666 on Tuesday December 13, @07:46 (Science) |
    | https://soylentnews.org/article.pl?sid=16/12/12/220233 |
    +———————————————————————————————-+

    [0]charon writes:

    This insight into the information which can be gleaned from data is
    [1]cool and worrisome by equal measures.

    Early in his talk, computer scientist John Hopcroft noted a funny
    fact about clustering algorithms: they work better on synthetic data
    than real data. But this is more than an odd tidbit about software.

    […] When we invent our own synthetic data, we try to mimic real
    data by mixing true information with random distraction–combining
    “signal” with “noise.” But in real data, the divide isn’t so clear.
    What often looks like noise turns out to be the deep structure we
    haven’t grasped yet.

    Hopcroft’s insight: data doesn’t just have one structure. It has
    many. If I scanned notebooks from a hundred people, and made a
    database of all the individual letters, I could sort them lots of
    ways. Alphabetically. Capital/lowercase. Size. Darkness. Handwriting.
    Each of these is a different layer of structure.

    And to understand data–and the world–you’ve got to reckon with all
    those layers.

    The part of the [2]video which discusses the above starts around 5:45.

    [3]Original Submission

    Discuss this story at:
    https://soylentnews.org/comments.pl?sid=16/12/12/220233

    Links:
    0. mailto:charon@soylentnews.org
    1. https://mathwithbaddrawings.com/2016/09/22/sometimes-the-noise-is-signals-too/
    2. http://hitsmediaweb.h-its.org/Mediasite/Play/c0b458983019417eb928271a90b422491d
    3. https://soylentnews.org/submit.pl?op=viewsub&subid=17407

    ————————————————————————

  10. This article reflects a point for potential concern, but it is dishonest because it sets the bar so high for events that the sample size is too small to yield real statistical significance. Although the p-values seem high for some, disasters drawn randomly from an even distribution in time could easily produce the appearance of trends.

    [Response: First: the statistics speak for themselves. Hand-waving about small sample size doesn’t alter a p-value. Either dispute the p-values themselves, or accept them, but to reject them without cause is foolish.

    Second: describing this as “dishonest” is disgraceful. If you think it’s mistaken, that’s one thing. When you bandy about accusatory words, you discredit yourself.]