In recent articles we have looked at rainfall and there is still more to discuss. This article changes tack to look at tropical cyclones, prompted by the recent US landfall of Harvey and Irma along with questions from readers about attribution and the future.
It might be surprising to find the following statement from leading climate scientists (Kevin Walsh and many co-authors in 2015):
At present, there is no climate theory that can predict the formation rate of tropical cyclones from the mean climate state.
The subject gets a little involved so let’s dig into a few papers. First from Gabriel Vecchi and some co-authors in 2008 in the journal Science. The paper is very brief and essentially raises one question – has the recent rise in total Atlantic cyclone intensity been a result of increases in absolute sea surface temperature (SST) or relative sea surface temperature:
Figure 1
The top graph (above) shows a correlation of 0.79 between SST and PDI (power dissipation index). The bottom graph shows a correlation of 0.79 between relative SST (local sea surface temperature minus the average tropical sea surface temperature) and PDI.
With more CO2 in the atmosphere from burning fossil fuels we expect a warmer SST in the tropical Atlantic in 2100 than today. But we don’t expect the tropical Atlantic to warm faster than the tropics in general.
If cyclone intensity is dependent on local SST we expect more cyclones, or more powerful cyclones. If cyclone intensity is dependent on relative SST we expect no increase in cyclones. This is because climate models predict warmer SSTs in the future but not warmer Atlantic SSTs than the tropics. The paper also shows a few high resolution models – green symbols – sitting close to the zero change line.
Now predicting tropical cyclones with GCMs has a fundamental issue – the scale of a modern high resolution GCM is around 100km. But cyclone prediction requires a higher resolution due to their relatively small size.
Thomas Knutson and co-authors (including the great Isaac Held) produced a 2007 paper with an interesting method (of course, the idea is not at all new). They input actual meteorological data (i.e. real history from NCEP reanalysis) into a high resolution model which covered just the Atlantic region. Their aim was to see how well this model could reproduce tropical storms. There are some technicalities to the model – the output is constantly “nudged” back towards the actual climatology and out at the boundaries of the model we can’t expect good simulation results. The model resolution is 18km.
The main question addressed here is the following: Assuming one has essentially perfect knowledge of large-scale atmospheric conditions in the Atlantic over time, how well can one then simulate past variations in Atlantic hurricane activity using a dynamical model?
They comment that the cause of the recent (at that time) upswing in hurricane activity “remains unresolved”. (Of course, fast forward to 2016, prior to the recent two large landfall hurricanes, and the overall activity is at a 1970 low. In early 2018, this may be revised again..).
Two interesting graphs emerge. First an excellent match between model and observations for overall frequency year on year:
Figure 2
Second, an inability to predict the most intense hurricanes. The black dots are observations, the red dots are simulations from the model. The vertical axis, a little difficult to read, is SLP, or sea level pressure:
Figure 3
These results are a common theme of many papers – inputting the historical climatological data into a model we can get some decent results on year to year variation in tropical cyclones. But models under-predict the most intense cyclones (hurricanes).
Here is Morris Bender and co-authors (including Thomas Knutson, Gabriel Vecchi – a frequent author or co-author in this genre, and of course Isaac Held) from 2010:
Some statistical analyses suggest a link between warmer Atlantic SSTs and increased hurricane activity, although other studies contend that the spatial structure of the SST change may be a more important control on tropical cyclone frequency and intensity. A few studies suggest that greenhouse warming has already produced a substantial rise in Atlantic tropical cyclone activity, but others question that conclusion.
This is a very typical introduction in papers on this topic. I note in passing this is a huge blow to the idea that climate scientists only ever introduce more certainty and alarm on the harm from future CO2 emissions. They don’t. However, it is also true that some climate scientists believe that recent events have been accentuated due to the last century of fossil fuel burning and these perspectives might be reported in the media. I try to ignore the media and that is my recommendation to readers on just about all subjects except essential ones like the weather and celebrity news.
This paper used a weather prediction model starting a few days before each storm to predict the outcome. If you understand the idea behind Knutson 2007 then this is just one step further – a few days prior to the emergence of an intense storm, input the actual climate data into a high resolution model and see how well the high res model predicts the observations. They also used projected future climates from CMIP3 models (note 1).
In the set of graphs below there are three points I want to highlight – and you probably need to click on the graph to enlarge it.
First, in graph B, “Zetac” is the model used by Knutson et al 2007, whereas GFDL is the weather prediction model getting better results in this paper – you can see that observations and the GFDL are pretty close in the maximum wind speed distribution. Second, the climate change predictions in E show that predictions of the future show an overall reduction in frequency of tropical storms, but an increase in the frequency of storms with the highest wind speeds – this is a common theme in papers from this genre. Third, in graph F, the results (from the weather prediction model) fed by different GCMs for future climate show quite different distributions. For example, the UKMO model produces a distribution of future wind speeds that is lower than current values.
Figure 4 – Click to enlarge
In this graph (S3 from the Supplementary data) we see graphs of the difference between future projected climatologies and current climatologies for three relevant parameters for each of the four different models shown in graph F in the figure above:
Figure 5 – Click to enlarge
This illustrates that different projected future climatologies, which all show increased SST in the Atlantic region, generate quite different hurricane intensities. The paper suggests that the reduction in wind shear in the UKMO model produces a lower frequency of higher intensity hurricanes.
Conclusion
This article illustrates that feeding higher resolution models with current data can generate realistic cyclone data in some aspects, but less so in other aspects. As we increase the model resolution we can get even better results – but this is dependent on inputting the correct climate data. As we look towards 2100 the questions are – How realistic is the future climate data? How does that affect projections of hurricane frequencies and intensities?
Articles in this Series
Impacts – II – GHG Emissions Projections: SRES and RCP
Impacts – III – Population in 2100
Impacts – IV – Temperature Projections and Probabilities
Impacts – V – Climate change is already causing worsening storms, floods and droughts
Impacts – VI – Sea Level Rise 1
Impacts – VII – Sea Level 2 – Uncertainty
Impacts – VIII – Sea level 3 – USA
Impacts – IX – Sea Level 4 – Sinking Megacities
Impacts – X – Sea Level Rise 5 – Bangladesh
References
Hurricanes and climate: the US CLIVAR working group on hurricanes, American Meteorological Society, Kevin Walsh et al (2015) – free paper
Whither Hurricane Activity? Gabriel A Vecchi, Kyle L Swanson & Brian J. Soden, Science (2008) – free paper
Simulation of the Recent Multidecadal Increase of Atlantic Hurricane Activity Using an 18-km-Grid Regional Model, Thomas Knutson et al, American Meteorological Society, (2007) – free paper
Modeled Impact of Anthropogenic Warming on the Frequency of Intense Atlantic Hurricanes, Morris A Bender et al, Science (2010) – free paper
Notes
Note 1: The scenario is A1B, which is similar to RCP6 – that is, an approximate doubling of CO2 by the end of the century. The simulations came from the CMIP3 suite of model results.
Impacts – VIII – Sea level 3 – USA
Posted in Commentary, Impacts on February 19, 2017| 101 Comments »
In Parts VI and VII we looked at past and projected sea level rise. It is clear that the sea level has risen over the last hundred years, and it’s clear that with more warming sea level will rise some more. The uncertainties (given a specific global temperature increase) are more around how much more ice will melt than how much the ocean will expand (warmer water expands). Future sea level rise will clearly affect some people in the future, but very differently in different countries and regions. This article considers the US.
A month or two ago, via a link from a blog, I found a paper which revised upwards a current calculation (or average of such calculations) of damage due to sea level rise in 2100 in the US. Unfortunately I can’t find the paper, but essentially the idea was people would continue moving to the ocean in ever increasing numbers, and combined with possible 1m+ sea level rise (see Part VI & VII) the cost in the US would be around $1TR (I can’t remember the details but my memory tells me this paper concluded costs were 3x previous calculations due to this ever increasing population move to coastal areas – in any case, the exact numbers aren’t important).
Two examples that I could find (on global movement of people rather than just in the US), Nicholls 2011:
And Anthoff et al 2010
I was struck by the “trillion dollar problem” paper and the general issues highlighted in other papers. The future cost of sea level rise in the US is not just bad, it’s extremely expensive because people will keep moving to the ocean.
So here is an obvious take on the subject that doesn’t need an IAM (integrated assessment model).. Perhaps lots of people missed the IPCC TAR (third assessment report) in 2001. Perhaps anthropogenic global warming fears had not reached a lot of the population. Maybe it didn’t get a lot of media coverage. But surely no could have missed Al Gore’s movie. I mean, I missed it from choice, but how could anyone in rich countries not know about the discussion?
So anyone since 2006 (arbitrary line in the sand) who bought a house that is susceptible to sea level rise is responsible for their own loss that they incur around 2100. That is, if the worst fears about sea level rise play out, combined with more extreme storms (subject of a future article) which create larger ocean storm surges, their house won’t be worth much in 2100.
Now, barring large increases in life expectancy, anyone who bought a house in 2005 will almost certainly be dead in 2100. There will be a few unlucky centenarians.
Think of it as an estate tax. People who have expensive ocean-front houses will pass on their now worthless house to their children or grandchildren. Some people love the idea of estate taxes – in that case you have a positive. Some people hate the idea of estate taxes – in that case strike it up as a negative. And, drawing a long bow here, I suspect a positive correlation between concern about climate change and belief in the positive nature of estate taxes, so possibly it’s a win-win for many people.
Now onto infrastructure.
From time to time I’ve had to look at depreciation and official asset life for different kinds of infrastructure and I can’t remember seeing one for 100 years. 50 years maybe for civil structures. I’m definitely not an expert. That said, even if the “official depreciation” gives something a life of 50 years, much is still being used 150 years later – buildings, railways, and so on.
So some infrastructure very close to the ocean might have to be abandoned. But it will have had 100 years of useful life and that is pretty good in public accounting terms.
Why is anyone building housing, roads, power stations, public buildings, railways and airports in the US in locations that will possibly be affected by sea level rise in 2100? Maybe no one is.
So the cost of sea level rise for 2100 in the US seems to be a close to zero cost problem.
These days, if a particular area is recognized as a flood plain people are discouraged from building on it and no public infrastructure gets built there. It’s just common sense.
Some parts of New Orleans were already below sea level when Hurricane Katrina hit. Following that disaster, lots of people moved out of New Orleans to a safer suburb. Lots of people stayed. Their problems will surely get worse with a warmer climate and a higher sea level (and also if storms gets stronger – subject of a future article). But they already had a problem. Infrastructure was at or below sea level and sufficient care was not taken of their coastal defences.
A major problem that happens overnight, or over a year, is difficult to deal with. A problem 100 years from now that affects a tiny percentage of the land area of a country, even with a large percentage (relatively speaking) of population living there today, is a minor problem.
Perhaps the costs of recreating current threatened infrastructure a small distance inland are very high, and the existing infrastructure would in fact have lasted more than 100 years. In that case, people who believe Keynesian economics might find the economic stimulus to be a positive. People who don’t think Keynesian economics does anything (no multiplier effect) except increase taxes, or divert productive resources into less productive resources will find it be a negative. Once again, drawing a long bow, I see a correlation between people more concerned about climate change also being more likely to find Keynesian economics a positive. Perhaps again, there is a win-win.
In summary, given the huge length of time to prepare for it, US sea level rise seems like a minor planning inconvenience combined with an estate tax.
Articles in this Series
Impacts – I – Introduction
Impacts – II – GHG Emissions Projections: SRES and RCP
Impacts – III – Population in 2100
Impacts – IV – Temperature Projections and Probabilities
Impacts – V – Climate change is already causing worsening storms, floods and droughts
Impacts – VI – Sea Level Rise 1
Impacts – VII – Sea Level 2 – Uncertainty
References
Planning for the impacts of sea level rise, RJ Nicholls, Oceanography (2011)
The economic impact of substantial sea-level rise, David Anthoff et al, Mitig Adapt Strateg Glob Change (2010)
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