Global Tropical Cyclone Landfalls, Updated 1970-2018

gtcl1The figure above courtesy Ryan Maue (@ryanmaue) updates our analysis of tropical cyclones which made landfall anywhere on Earth from 1970 to 2018. The dataset starts in 1970 because this is where Weinkle et al. (2012) judged global data to be reliable. Data for individual basins is available back in time much further than 1970 (see the paper, linked below).

Last year saw 17 total landfalls at hurricane strength (S/S Category 1+) — slightly above average, with 4 of those being major hurricanes (S/S Category 3+) — slightly below average.

This updates our 2012 analysis:

  • Weinkle, J., Maue, R., & Pielke Jr, R. 2012. Historical global tropical cyclone landfalls. Journal of Climate, 25:4729-4735. (free to read, here in PDF).

Some summary statistics for global TC landfalls, 1970 to 2018:

  • All landfalls: 15 (median), 15.3 (average), 4.4 (sd)
  • Categories 1 & 2 at landfall: 10, 10.5, 3.8
  • Category 3+ at landfall: 4, 4.8, 2.5
  • Most total landfalls in one year: 30 (1970)
  • Fewest total landfalls in one year: 7 (1978)
  • Most Category 3+ landfalls in one year: 9, (1999, 2004, 2005, 2007, 2008)
  • Fewest Category 3+ landfalls in one year: 0 (1981)
  • Most total landfalls over a 10-year period: 177 (1988-1997)
  • Fewest total landfalls over a 10-year period: 120 (1975-1984)
  • Total landfalls 2009-2018: 140
  • Most Category 3+ landfalls over a 10-year period: 65 (1999-2008)
  • Fewest Category 3+ landfalls over a 10-year period: 33 (1978-1987)
  • Total Category 3+ landfalls 2009-2018: 44
  • Total landfalls 1970-2018: 750, (516 were Categories 1 & 2, 234 were Category 3+)

Below is a graph showing Categories 1 & 2 (black) and Category 3+ (red). There are no significant trends in the data.gtcl2

 

7 Replies to “Global Tropical Cyclone Landfalls, Updated 1970-2018”

  1. Hi Roger – always enjoy your thoughts. I replied to you on Twitter but got no reply. In the spirit of a level playing field on the data here, I noticed that trend lines were put on your graphs of Global Overall Losses and Global Weather Losses as Percent of Global GDP along with “2018 contributes to the trend (1990-2018) of disaster losses decreasing as a proportion of global GDP”.

    I took a look at the Cat 3-5 data here (mainly as the frequency of more severe hurricanes increasing with climate change seems to be a talking point for future risk) and notice there is an equally noteworthy trend in the Cat 3-5 data – as much as the downward trends you’d noticed in a previous article – but you’ve said “there are no significant trends in the data”. If included a link to your 3-5 data that I’ve copied and added a trendline to:

    https://drive.google.com/file/d/1Ixduzhe6cM9qvQ4H3AW2JkImdp1ueQ1o/view?usp=sharing

    Thought that this was worth sharing here.

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    1. Richard, Thanks, and apologies I missed your Twitter comment. Yes, one can certainly draw trend lines on TC data for various periods, and it is possible to identify up, down, level trends depending on start dates, across all global basins. In our work on hurricanes, floods, extreme precipitation and tornadoes we’ve found such trends useful for an independent check on economic loss normalization results. Trends or lack of should be consistent across equal time periods in the independent datasets, for an unbiased normalization. For instance, in our US hurricane normalization we find up trends since 1970 in hurricane losses and well as normalization results (see Weinkle et al 2018). Down trends since 1940 and none since 1900. All this matches up between datasets, which gives us confidence in results. Given what we know about longer term TC landfalls in major basins around the world, we find similar variability, but no secular long term trend, on a global scale. Same as IPCC.

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      1. Thanks Roger. I just wish we had some decent climate model simulations to understand what we’re seeing and whether there’s any hint of a broad trend over and above the internal variability (especially in the Atlantic). Whenever I see a historical dataset my immediate thought is always “I wonder what 100 re-runs of this ‘history’ would produce”. I’ve been looking at this from a European Windstorm loss basis and across 100 ensembles from 1951-2011 I find a small upward trend across the data (a steady 25% increase in losses over the 60 years) but the sort of trend that a) is too small to spot an a single “history” and b) whose losses are probably swamped by shifts in population over that time.

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