Figure 1: The 2017 North Atlantic hurricane season. Ophelia’s location stands out from the typical tracks of North Atlantic tropical cyclones during the active 2017 season. Selected major hurricanes occurring during 2017 – Irma, Jose and Maria – are labelled. Track data are from National Hurricane Center. (Figure courtesy of Jo Camp, Met Office.)
In the early hours of the 16th October 2017, an unusual storm made landfall in Ireland and continued to track north-eastwards, causing damage across the northern United Kingdom and Scandinavia over a two-day period. That storm – Ex-hurricane Ophelia – was the easternmost major hurricane (i.e., category 3 or higher) observed in the Atlantic during the satellite era (Figure 1). Ophelia had a tropical origin and structure and transitioned to an extratropical cyclone prior to landfall. It was not the first such ‘post-tropical’ Atlantic storm to make landfall in the mid-latitudes. To give just a few examples, Hurricane Lili (1996) hit the UK and Hurricanes Vince (2005) and Leslie (2018) struck the Iberian Peninsula. ‘Superstorm’ Sandy (2012) – the 4th most costly Atlantic hurricane on record – caused widespread damage across the Northeast United States.
Figure 2: Interannual variability in North Atlantic post-tropical cyclones. (left) Annual total post-tropical cyclone count timeseries for Europe (upper panel) and the Northeast US (lower panel) and (right) non-parametric (Spearman’s rho) inter-reanalysis correlation matrices (significant correlations, where p < 0.01, are in bold type).
Post-tropical cyclones expose populous mid-latitude communities, which may lack the preparedness of regions more commonly struck by tropical storms, to hurricane-force wind speeds and extreme precipitation. The risk of such events is projected to increase in response to anthropogenic climate change because warming may induce poleward and eastward expansion of tropical cyclone genesis areas, allowing more storms to propagate to the mid-latitudes, where they may undergo extratropical transition and re-intensify (Haarsma et al., 2013). A quantitative survey of historical post-tropical cyclone variability – against which climate model fidelity may be evaluated and climate change projections put into context – is therefore required.
To understand historical post-tropical cyclone activity across the North Atlantic, we used an objective storm-tracking algorithm (Hodges, 1995) to identify post-tropical cyclones in four reanalysis datasets (ERA-Interim, JRA-55, MERRA2 and NCEP-CFSR). Here, we briefly discuss interannual variability in post-tropical cyclones, their intensity prior to and following landfall, and their associated precipitation, focussing on those systems which impact Europe and the Northeast US.
So, what have we found? Let us first consider year-to-year variability. The reanalyses show no significant trends in total annual count of post-tropical cyclones impacting Europe or the Northeast US since 1979, although pronounced interannual variability exists (Figure 2, left). Overall, Europe and the Northeast US experience around five and ten post-tropical cyclones per year, respectively, including relatively weak systems. Interestingly, highly active Atlantic hurricane seasons, such as 2005 (the most active ever recorded), do not stand out as peaks in post-tropical cyclone activity. Moreover, there is little co-variability between Europe and the US: that is to say, peaks/troughs in Northeast US activity generally do not correspond with peaks/troughs in Europe. Inter-reanalysis correlations are higher for Europe than for the US (Figure 2, right), suggesting that the different model configurations and resolutions as well as the differing observational data assimilation schemes employed by the reanalyses impact the representation of historical post-tropical cyclone activity over the Northeast US more than that over Europe.
Figure 3: Composite post-tropical cyclone lifecycles. Lifecycles of difference post-tropical cyclone types centred (i.e., where t=0) on landfall within the Northeast US. Legend entries: ‘sym’/‘asym’ = symmetrical/asymmetrical; ‘WC’/‘CC’ = warm-core/cold-core. Legend numbers give the number of cyclones in each Hart category. Shading shows one standard deviation. Example results for the Northeast US from JRA-55.
We now turn briefly to storm structure and the two primary hazards posed by storms: wind and precipitation.
Hart (2003) devised a way to describe cyclone structure and its evolution based on three parameters: cyclone symmetry and lower- and upper-level thermal winds. These parameters allow cyclones to be classified as warm- or cold-core and symmetrical or asymmetrical (frontal). Typically, tropical cyclones are symmetrical and warm-core; extratropical cyclones are asymmetrical and cold-core. Post-tropical cyclones exhibit these – as well as hybrid – structures. By classifying post-tropical cyclones in this way, we found that the majority transition to a typical extratropical structure, but an appreciable number retain structural aspects of their tropical origins (Figure 3). Crucially, warm-core post-tropical cyclones possess the highest wind speeds upon landfall.
Figure 4: Post-tropical contributions to total precipitation. Average post-tropical cyclone precipitation contributions during August for the Northeast US (left) and Europe (right). TRMM precipitation observations are available up to 50°N and the black boxes outline the cyclone landfall domains within the domain of TRMM observational coverage (although both landfall domains extend north of this latitude).
To establish the importance of post-tropical cyclones are for precipitation over Europe and the Northeast US, we sampled satellite-based precipitation estimates (from NASA Tropical Rainfall Measuring Mission) in the vicinity of each cyclone track and calculated post-tropical cyclones’ percentage contribution to the total precipitation. These contributions were mapped across our regions of interest (Figure 4). Post-tropical cyclones are responsible for up to 10% of Europe’s total summer precipitation. This is significant given that, on average, only a few such storms impact southern Europe and the Mediterranean each summer (Figure 2). Across the US East Coast, climatological contributions of up to 50% are seen in August, and contributions of up to 20% occur across New England and parts of southern Atlantic Canada. Collectively, these results highlight the contemporary importance of post-tropical cyclone precipitation.
This work is currently in preparation for publication (Baker et al., 2018). We hope these analyses stimulate further discussion of post-tropical systems, particularly their tracks, tropical-to-extratropical transition, and representation in global climate models. Future work within the PRIMAVERA project will (i) perform comparisons with multiple high-resolution, tropical-cyclone-permitting global climate model simulations and (ii) assess the spread of post-tropical storm risk across the mid-latitudes under anthropogenic climate change.
Finally, an exciting PhD opportunity in the Department of Meteorology, exploring this topic is currently open for applications, and more information is available here.
References
Baker, A. J., Hodges, K., Schiemann, S., Haarsma, R., and Vidale, P. L. Historical variability of North Atlantic post-tropical cyclones and their importance for extratropical precipitation. (in prep.)
Haarsma, R. J., Hazeleger, W., Severijns, C., Vries, H., Sterl, A., Bintanja, R., Oldenborgh, G. J., and Brink, H. W., 2013. More hurricanes to hit western Europe due to global warming. Geophysical Research Letters 40, 1783-1788. doi.org/10.1002/grl.50360
Hart, R. E., 2003. A Cyclone Phase Space Derived from Thermal Wind and Thermal Asymmetry. Monthly Weather Review 131, 585-616. doi.org/10.1175/1520-0493(2003)131<0585:ACPSDF>2.0.CO;2
Hodges, K. I., 1995. Feature Tracking on the Unit Sphere. Monthly Weather Review 123, 3458-3465. doi.org/10.1175/1520-0493(1995)123<3458:FTOTUS>2.0.CO;2
Acknowledgements
I thank the EU Horizon-2020-funded PRIMAVERA project for financial support of this research and colleagues at the Royal Netherlands Meteorological Institute (KNMI) for helpful feedback.