Deluge

Surely some of you noticed that the area around Houston Texas suffered extreme flooding recently. At least 8 people were killed and damages ran into the billions of dollars. It was a major disaster.


And it followed less than a year after major flooding hit the Dallas-Fort Worth area back in May of 2015. Texas was so hard hit last year, that May was the wettest month in Texas history:

TexRain

The graph doesn’t include the recent flooding, since April 2016 isn’t over yet.

One might wonder, are such deluges on the increase? Is it happening elsewhere, besides Texas? I took the precipitation data for all of the 48 states of the conterminous U.S. (the “lower 48”) and determined which were the top-10 wettest months (in terms of total precipitation) for each state. Then I counted how many top-10 months (for any state) occured each year. I got this:

StateTop10

It certainly looks like the number of extreme wet months is on the rise in the U.S. Of course, looks can be deceiving — but not in this case. The recent increase (suggested by the smooth curve in the above graph) is easily confirmed, statistically significant.

That statistical significance isn’t just because 2015 had more top-10 wettest months (for states) than any previous. If you omit 2015 from the analysis, the recent increase is still statistically significant. So: we had an increase in “deluge months” by the end of 2014 already — then we broke the record in 2015.

I was also interested in breaking it down by smaller regions than states, so I did the same analysis, not just for the 48 states, but for the 344 climate divisions of those 48 states. I got this:

DivsTop10

Once again, the recent increase (suggested by the smooth curve) is easily confirmed, statistically significant.

Once again, that statistical significance doesn’t depend on 2015 having more top-10 wettest months (for climate divisions) than any previous. Leave out 2015, the recent increase is still statistically significant. Once again: we had an increase in “deluge months” by the end of 2014 already — then we broke the record in 2015.

Deluges like that tend to bring flooding. Flooding tends to bring extreme loss, extreme cost, and death.

I wouldn’t be surprised if deniers object that the increased frequency of extreme wet months can’t be due to man-made climate change. But it is. Of course, conditions will still fluctuate and we simply can’t be sure when the next spate of deluges will hit. Unfortunately, we can expect it to get worse.

It’s not just rainfall that brings flooding. These days, sea level rise has reached the level that it can happen even without storms or rain, just from high tides. For places like Miami (for a lot of places, actually) it’s already a very costly problem. Unfortunately, we can expect it to get worse. A lot worse.

Heat waves have already gotten worse. They not only cost money, they’re deadly — like last year, when over 1,000 people died because of the heat wave in Pakistan and over 2,500 died from the heat wave in India. Temperature will continue to fluctuate, we don’t know when the next spate of killer heat waves will strike, but we can be damn sure of this: it’s going to get worse.

Global warming, man-made climate change, call it what you will, is already a problem. It already costs our economy billions upon billions of dollars. It already destroys homes, ruins crops, ends lives. It’s not a “distant future” problem, it’s not even a “near future” problem any more. It’s not a 3rd-world problem. It’s a right-here-right-now problem.

The uncertainties in climate science are tremendous. We can’t be sure how much temperature will rise, or how fast, or which regions will be hardest hit by extreme weather, or how far how fast the ocean will rise. But there is one thing we can be sure of, something we can be absolutely certain of …

It’s going to get worse.

The time to act is now.


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18 responses to “Deluge

  1. I’ve lived in Texas since 1981, and there have been some horrendous floods. The first one I experienced was the elephant flood in the 1980s. Astounding. But there is no doubt in my mind it’s on the rise. My wife was on the last airplane out before they closed the airport in Houston for tropical storm Allison. We were down there on a house hunting trip. I drove home; she barely got out the next day. Most of the houses we had looked at were damaged. We decided to lease a condo in a high rise on Hermann Park. We stayed in place for Katrina, and my wife stayed in place for Ike, which surged water into places not seen before. “Never again.” Moved back to DFW. Right now we appear to be experiencing a rash of hailstorms. I go by the clay tile roofs that were installed back in the 1920s. In Lakewood, a neighborhood in Dallas that is full of beautiful old homes, a huge hailstorm destroyed almost every clay tile and slate roof in the neighborhood – around 2013. It looked like a bull had demolished a china shop. My fort Worth neighborhood lost a bunch of roofs a few weeks ago. Mine is from 1929. Got lucky. One of our cars destroyed (I heard 340 million to FW cars from that storm); roof perfectly okay.

    • Philippe Chantreau

      JCH, Texas people joke about how extreme their weather is. I got there in 1995 and after a couple of weeks was treated to grapefruit size hailstones. You couldn’t find a windshield in Ft Worth for 3 weeks. I flew into Houston Hobby During Allison in rain so heavy that I couldn’t see anything forward through the windshield and had to look at the sides to land the plane, like one would do with a tailwheel aircraft that has bad forward vision. All the Air-Tran and Southwest guys were grounded, but us freight dogs were flying in and out, even as the TRACON facility got flooded and had to be relocated to the intl. airport :-) There is a great SVR song starting with “It’s flooded down in Texas.”
      Nonetheless, no matter how many extreme events can be recalled, the Houston area is bound to experience similar problems to those of Miami and all the Southern low lying towns. And yet, the likes of Lamar Smith can still manage to convince some that he should have access to all e-mails from Climate scientists.
      That may be the most worrisome aspect of all this. The very risks that these climate scientists have warned about what is now decades are materializing under his eyes, and he is adhering to the idea that they’re all in some sort of nefarious conspiracy. The emotional attachment to ideology on the part of conservatives boggles the mind. We need more posts like this one. Not long ago, I had an exchange at SkS with a guy who was arguing that taking drastic action against future possible problems was a faulty risk-benefit analysis. I had to point to his attention that this was not a problem coming with a probability and diluted in the future. It is happening now, and here. I had to use the same events cited here and a few more to show how clear the case is. These events are now streaming with a regularity that goes beyond natural variability, realizing climate science expectations with eerie accuracy…

      • Wow, Philipe, that’s a hairy landing.

        Years ago, my instrument instructor told me, “It’s not really raining hard until you’re afraid it will bust the windshield.” Sounds like you’ve been there.

  2. Steve Latham

    Good points regarding the here-and-now-ness of the problem. Statistically, isn’t spatial autocorrelation problematic in your analysis of the lower 48? And wouldn’t it be made worse in the analysis of climate divisions? Or does the fact that you’re only performing stats on the aggregate behavior remove that concern?

    • That would change the statistics. It would be interesting to repeat this analysis with data from the UK, where they created regions based on the leading EOF patterns in rainfall variability. See http://www.metoffice.gov.uk/hadobs/hadukp/

    • Those good points regarding the here-and-now-ness of the problem can’t be overemphasized. This was a heck of a sharply focused and in-someone’s-face statistical proof of the here-and-now-ness of the problem, no bs, exactly what is needed in today’s public forum. Kudos.

  3. David B. Benson

    Between Uruguay and adjacent Argentina a recent rain storm caused 22,000 people to be evacuated. At the same time, a different rain storm caused 4.5 million people in Chile to be without potable water for one or two days.

  4. Keith McClary

    It would be interesting to see the results for driest, hottest and coldest months.
    The “climate divisions”
    http://www.esrl.noaa.gov/psd/data/usclimdivs/data/map.html
    seem to have an eastern bias (good enough for government work).

  5. Nice post. The time to act was actually in the past, but we can still slow things down. Human nature gets in the way, unfortunately.

  6. In case you aren’t familiar with the EPA extreme rainfall graph…

    https://www3.epa.gov/climatechange/science/indicators/weather-climate/heavy-precip.html

  7. Similar story in the UK (using annual data with 5 year smooth): http://oi66.tinypic.com/2571t9d.jpg

    Big up-tick from 1970s.

    Data: http://www.metoffice.gov.uk/pub/data/weather/uk/climate/datasets/Rainfall/date/UK.txt

  8. yes, it would be interesting to do a similar analysis on the UK, we certainly seem to have had more flood events since 2000, to the point where the UK Government are introducing a government backed re-insurance scheme for flooding because it seems more and more properties are becoming uninsurable
    And uninsurable means un-mortgageable – so essentially un-saleable, which is a problem for an economy build on asset price inflation

    • Tadaaa,
      If you use HadUKP monthly data, the regional data is absent for Scotland & NI until 1931. Using the data for just the 5 regional divisions of England & Wales the analysis can run back to 1873 and yields a rather lumpy result. The most recent years do contain a higher proportion of the wettest 10 months from those 5 regions (the wettest 20 months ditto) than other periods but it is not as convincing as the US version with the lumpiness rather steals the show.
      I wouldn’t imagine a 1931-on monthly analysis (which would add the 4 regions of Scotland+NI to the analysis) making much difference to the lumps in the England+Wales result. Mind, a 1931 start means you can also use daily data which would allow wettest-30-day-periods to be analysed.

  9. Eric Swanson

    That flood event in Houston was even more amazing because it wasn’t the result of a tropical storm/ hurricane. I think it would be of interest to look at the data for non-tropical event precipitation to see whether there is evidence of a change.

    While we’re at it, the weather in Britain recently has been rather extreme as well. These stories sound rather like the anecdotal evidence presented in Fagan’s book “The Little Ice Age”, that is to say, storms moving in from the east or northeast:
    http://www.telegraph.co.uk/news/2016/04/26/snow-stops-play-at-cricket-matches-in-the-south-as-britain-suffe/

    http://www.dailymail.co.uk/news/article-3559520/Now-April-SNOW-showers-Flakes-fall-London-severe-weather-warning-issued-Scotland.html

  10. The HadUKP monthly data for 1973-to-date (England & Wales) and 1931-to-date (all UK & NI) is graphed out here (usually 2 clicks to ‘download your attachment) Unlike the US data in the post, I totted up the 20 wettest months for each region (rather than the 10 wettest) to make it more interesting looking.

  11. It does not matter where you run the analysis. Weather data has gotten weird. In Greenland, circa 1970, almost nobody had actually seen rain. Starting in 2002, I started tracking rain in Greenland. For the next 60 consecutive months, rain was reported somewhere in Greenland every month. In less than 30 years, Greenland went from rain being rare, to rain being common.

    In contrast, stronger El Ninos seem to have diminished Summer Monsoons in India. e.g., (http://www.tropmet.res.in/~kolli/mol/Monsoon/Historical/air.html) , but this is not the whole story as (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.583.2822&rep=rep1&type=pdf )

    The lesson is that AGW has emerged from the dim world of models into the bright light of adequate data.