The link between extreme weather events, climate change, and national security is discussed in Extreme Realities, a new episode in PBS’ series Journey To Planet Earth hosted by Matt Damon.
The video features a number of extreme weather phenomena: hurricanes, tornadoes, floods, wild fires, and flooding. The discussion is about climate change and the consequences on the ground – or, how climate change may affect you.
It is important to ask what is the story behind the assertions made in the video. What scientific support is there for the link between such extremes and climate change?
Linking global warming to some of these extreme weather and climate phenomena has been tricky in the past. In some cases the record of past events may not be sufficiently complete to identify whether there is a dependency to the global state, mainly because many extremes are both rare and take place at irregular intervals. However, there has been substantial progress over the recent years.
Global climate models may provide a tool for studying such links, but they are designed to provide a picture of general large-scale features such as the greenhouse effect and how the air moves around, rather than local extreme phenomena. For some types of extremes such as heat waves, they can nevertheless provide valuable insight (Hansen et al., 2012).
Heat waves and droughts often extend over space and time, and the global climate models may provide a good representation of droughts and heat waves if they manage to predict the frequency and duration of high-pressure systems and the soil moisture associated with these events.
The way the air flows is in some circumstances difficult to predict, for instance where the storms move (storm tracks) and changes in the large-scale atmospheric circulation. The reason for this is described in earlier posts on chaos and climate, and was first discussed by Lorenz.
The climate models manage to reproduce the Hadley cell, El Nino Southern Oscillation, the Jet streams, the Trades, and the westerlies, but not tornadoes, derechoes, and thunderstorms. They do not provide the details needed to describe the local climate and many extreme phenomena affecting society and ecosystems.
Our knowledge about extremes and climate is based on more evidence than just climate model results. One elegant example is the recent paper in PNAS by Petoukhov et al., (2013) based on mathematics, physics, and measured air flow.
From physics, we know that different conditions such as soil moisture and cloud micro-physics both affect weather extremes, although different types and on different scales. Convective storms and tornadoes, as opposed to heat waves, have in the past gone undetected and tend to pass below the radar of the global climate models.
New studies, such as Petoukhov et al., (2013), are emerging in the scientific literature that provide additional support for a link between climate change and a wider range of extreme phenomena. These are based on our physical understanding, observational data, new ways of analysing data, and attribution studies (Coumou and Rahmstorf, 2012).
We are also learning more about local convective storms, and a recent example is provided by the Swedish Rossby Centre, reporting that showery convective rainfall type intensifies faster than the more spatially extensive stratiform type in response to warmer temperatures (Berg et al., 2013).
The analysis of the past observations has not always given a clear picture. So far, no clear connection has been found between the global warming and mid-latitude storms (or wind speed), and efforts comparing different ways to analyse past storm observations have only recently been published (Neu et al. (2012). If we understand why some analytical methods give different results for past storms, then we will be in a better position to detect potential dependencies to the state of the global climate.
Extreme events are a natural part of the climate system, and a climate change means that their frequencies and intensities may change. Detecting the changes in probabilities in rare events is statistically challenging. However, counting the recurrence of record-breaking extremes can provide an indication of whether the extreme values are changing (Benestad, 2008).
The consequences of a climate change involves some known aspects as well as some which we cannot predict. Extreme phenomena take place in certain environmental conditions, favourable for forming e.g. tornadoes, storms, or droughts. We also know that our models have their limitations, and that the range of possible outcomes can be fairly wide.
The incomplete knowledge is no different to any other field, as the future always seems to involve some surprises. Societies have traditionally tackled the absence of complete certainties by adopting various forms for risk analyses, e.g. fire brigades, police, defence, hospitals, and so on.
Better safe than sorry. Here, there are some known connections of concern. The bottom line is that we need pragmatic ways of dealing with issues that may have devastating effects for people or societies – and this is the red thread in ‘Extreme Realities‘.
- J. Hansen, M. Sato, and R. Ruedy, "From the Cover: PNAS Plus: Perception of climate change", Proceedings of the National Academy of Sciences, vol. 109, pp. E2415-E2423, 2012. http://dx.doi.org/10.1073/pnas.1205276109
- D. Coumou, and S. Rahmstorf, "A decade of weather extremes", Nature Climate Change, 2012. http://dx.doi.org/10.1038/nclimate1452
- P. Berg, C. Moseley, and J.O. Haerter, "Strong increase in convective precipitation in response to higher temperatures", Nature Geoscience, vol. 6, pp. 181-185, 2013. http://dx.doi.org/10.1038/ngeo1731
- U. Neu, M.G. Akperov, N. Bellenbaum, R. Benestad, R. Blender, R. Caballero, A. Cocozza, H.F. Dacre, Y. Feng, K. Fraedrich, J. Grieger, S. Gulev, J. Hanley, T. Hewson, M. Inatsu, K. Keay, S.F. Kew, I. Kindem, G.C. Leckebusch, M.L.R. Liberato, P. Lionello, I.I. Mokhov, J.G. Pinto, C.C. Raible, M. Reale, I. Rudeva, M. Schuster, I. Simmonds, M. Sinclair, M. Sprenger, N.D. Tilinina, I.F. Trigo, S. Ulbrich, U. Ulbrich, X.L. Wang, and H. Wernli, "IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms", Bulletin of the American Meteorological Society, vol. 94, pp. 529-547, 2013. http://dx.doi.org/10.1175/BAMS-D-11-00154.1
- R.E. Benestad, "A Simple Test for Changes in Statistical Distributions", Eos, Transactions American Geophysical Union, vol. 89, pp. 389, 2008. http://dx.doi.org/10.1029/2008EO410002