Author Archives: Stephen Cusack

About Stephen Cusack

Director, Model Development

Stephen is a hazard specialist who leads the development of climate hazard models from our London office. After joining RMS in 2009, most of Stephen’s focus has been on developing the Europe Windstorm (EUWS) hazard module; working with station data to calibrate RiskLink 11 EUWS event set hazard, then various hazard improvements to the RiskLink 15 EUWS version, and the RiskLink 16 EUWS clustering model. Stephen also spent 15 months leading the recalibration of the U.S. and Canada Severe Convective Storm model, released in January 2014. Before RMS, Stephen worked in various research and development posts over a period of 13 years at the U.K. Meteorological Office, including the development of short-range weather forecasting; designing and building new seasonal and decadal climate prediction systems; and the development of radiation and cloud physics parametrizations.

The “Glasgow Hurricane”: A Fifty-year Retrospective

In the early hours of Monday, January 15, 1968, cyclone “Low Q” charged across northern U.K. and smashed the densely populated Central Belt of Scotland with urban winds which have only since been matched when storm Lothar hit southern Paris in late 1999. Glasgow suffered the most intense damage leading to the storm’s more common misnomer of the “Glasgow Hurricane”. This event has quite a low profile today, even in the U.K., and we use its fiftieth anniversary to highlight this exceptional European Windstorm.

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Seasonal Forecast of European Windstorm Activity: Will a Stormier Atlantic Deliver Increased Losses?

Known indicators point to stormier conditions in the North Atlantic this winter. However, what this means for Europe windstorm losses is much less certain.

Our ability to understand and forecast variability of North Atlantic winter storminess continues to improve year-on-year. Research highlights in 2017 include:

  • A new, and skillful, empirical forecast model for winter climate in the North Atlantic revealed that sea ice concentrations in the Kara and Barents Seas are the main source of predictable winter climate variations over the past three decades. Interestingly, a separate 2017 study supports earlier forecasts of either a slowing or reversal of the sea ice reductions in the Barents and Kara Seas between now and 2020, implying an uptick in storminess over the next few years.
  • An innovative tool to analyze sources of predictability in a numerical forecast model revealed strong links between tropical climate anomalies and winter climate in the North Atlantic in that model.

Twelve months ago, the forecasting indicators for the windstorm season broadly pointed to a 2016/17 season characterized by below average storminess — a forecast borne out by subsequent observations. We have already had a fairly active start to the 2017/18 season, with Windstorms Xavier, Herwart, and ex-Hurricane Ophelia causing local damage, but what is the outlook for the rest of the season?

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Europe’s Winter Windstorms – the Only Certainty is Uncertainty

The annual damage from European windstorms can range significantly: from years when there are clusters of severely damaging storms to other years with almost no windstorm loss. How much of this volatility can we predict, and how much remains a roll of the dice? And more specifically, what storm activity can we expect over the next few months?

Forecasting Storminess

Our understanding of the drivers of annual storminess has increased greatly in recent years, allowing us to provide more forecasting insight than ever before. However, there is a cautionary tale for the industry, one that shows the limitations of even the most sophisticated seasonal forecasts.

The Atlantic Multidecadal Oscillation (AMO) is a pattern of long-duration variability in sea surface temperature in the North Atlantic. It is known to influence the climate over much of the northern hemisphere including the level of storminess in Europe1. As north-south gradients of heat in the Atlantic act to fuel extra-tropical storms2 these longer term changes in sea surface temperature tend to alter the odds of extreme storm occurrence over timescales of 60-80 years. Today, the ongoing positive (warm) phase of the AMO favors lower than average storminess this winter.

Annual average values for the AMO Index, 1856-2015 (data from NOAA ESRL3). Positive values (red bars) indicate warmer sea surface temperatures across the North Atlantic, while negative values (blue bars) indicate cooler temperatures.

That’s the multi-decadal perspective. But it will come as no surprise for Europeans to hear that as well as these longer phases of relative activity and inactivity, the continent also experiences variability of storminess from year to year. We know that the jet stream is a main ingredient of storms, and that in turn these storms strengthen the jet itself, in a positive feedback loop that leads to the term “eddy-driven jet.”  This “storms-beget-storms” mechanism typically plays out over a few weeks, and more severe storms are likelier to occur during these periods. The positive feedback between jet and storms amplifies swings in annual damage, and explains a substantial amount of the storm clustering found in longer range historical weather records4. This coupling between storms and jet is reflected in the version 16.0 of the RMS Europe Windstorm Clustering Model.

Researchers have identified various drivers of seasonal storminess in the North Atlantic which, for the coming winter, are ambiguous. For instance: we are three years after the peak of a prolonged but subdued solar cycle and this timing suggests less forcing of storminess. But in contrast the predictions are for neutral to weak La Niña phases of the El Niño–Southern Oscillation (ENSO) which points to a chance of increased forcing of North Atlantic storminess. Whilst, to complicate things further, the anticipated values of tropical stratosphere winds, linked to the Quasi-Biennial Oscillation (QBO), are related to less storminess in the mid-latitude Atlantic – with the caveat that they are in an unusually disrupted pattern.

So is it possible to get off the meteorological fence and make a call? Yes: overall, the multi-decadal and seasonal drivers indicate slightly below average storminess.

Severe Events Can Occur During Any Season

But this does not mean that we as an industry should be entirely relaxed about the new storm season, as the outlook for annual storm damage is blurred by the vagaries of local weather. This is exemplified by storm Kyrill in January 2007.

Then, ahead of the 2006/07 winter, the seasonal and multi-decadal drivers indicated below average storminess, just as they do today. But Kyrill occurred and turned an otherwise innocuous season into a bad one for many. The gusts and damage during this storm were much more extreme than its general circulation, because convection cells embedded in the cold front contributed to extreme damage intensity in some areas5. Storm Kyrill showed how processes on small space and time scales can dominate annual storm damage. These drivers have seriously short predictability windows of just a few hours.

More generally, some of the past variations in annual storminess have no known driver. We are not quite sure how much, but a reasonable ball-park figure is one half. This random part is found in climate models, where the tiniest possible changes at the start of a forecast often grow into large changes in seasonal average storminess.

Although our understanding of the drivers of storminess has greatly increased over the past few years and the odds do favor less storm damage this winter, we should not be complacent. As its tenth anniversary approaches, Storm Kyrill reminds us that major losses can happen in any season, regardless of the forecast.

Web links to references above

1Peings and Magnusdottir (2014)  [ ]

2Shaffrey and Sutton (2006)  [ ]

3NOAA ESRL AMO data [ ]

4Cusack (2016)  [ ]

5Fink et al. (2009)  [ ]

This post was co-authored by Peter Holland and Stephen Cusack.

What Is In Store For Europe Windstorm Activity This Winter

From tropical volcanoes to Arctic sea-ice, recent research has discovered a variety of sources of predictability for European winter wind climate. Based on this research, what are the indicators for winter storm damage this season?

The most notable forcings of winds this winter – the solar cycle and the Arctic sea-ice extents – are forcing in opposite directions. We are unsure which forcing will dominate, and the varying amplitude of these drivers over time confuses the situation further: the current solar cycle is much weaker than the past few, and big reductions in sea-ice extent have occurred over the past 20 or so years, as shown in the graph below.

Figure: Standardized anomalies of Arctic sea-ice extent over the past 50 years. (Source: NSIDC)

There are two additional sources of uncertainty, which further undermine predictive skill. First, researchers examine strength of time-mean westerly winds over 3-4 months, whereas storm damage is usually caused by a few, rare days of very strong wind. Second, storms are a chaotic weather process – a chance clash of very cold and warm air – which may happen even when climate drivers of storm activity suggest otherwise.

RMS has performed some preliminary research using storm damages, rather than time-mean westerlies, and we obtain a different picture for East Pacific El Niños. Most of them have elevated storm damage in the earlier half of the storm season (before mid-January) and less later on. Of special note are the two storms Lower Saxony in November 1972 and 87J in October 1987: the biggest autumn storms in the past few decades happened during East Pacific El Niños. The possibility that East Pacific El Niños alter the seasonality of storms, and perhaps raise the chances of very severe autumn storms, highlights potential gaps in our knowledge that compromise predictions.

We have progressed to the stage that reliable, informative forecasts could be issued on some occasions. For instance, large parts of Europe would be advised to prepare for more storm claims in the second winter after an explosive, sulphur-rich, tropical volcano. Especially if a Central Pacific La Niña is occurring [vi] and we are near the solar cycle peak.

However, the storm drivers this coming winter have mixed signals and we dare not issue a forecast. It will be interesting to see if there is more damage before rather than after mid-January, and whatever the outcome, we will have one more data point to improve forecasts of winter storm damage in the future.

Given the uncertainty in windstorm activity levels, any sophisticated catastrophe model should give the user the possibility of exploring different views around storm variability, such as the updated RMS Europe Windstorm Model, released in April this year.

[i] Fischer, E. et al. “European Climate Response to Tropical Volcanic Eruptions over the Last Half Millennium.” Geophys. Res. Lett. Geophysical Research Letters, 2007, .
[ii] Brugnara, Y., et al. “Influence of the Sunspot Cycle on the Northern Hemisphere Wintertime Circulation from Long Upper-air Data Sets.” Atmospheric Chemistry and Physics Atmos. Chem. Phys., 2013.
[iii] Graf, Hans-F., and Davide Zanchettin. “Central Pacific El Niño, the “subtropical Bridge,” and Eurasian Climate.” J. Geophys. Res. Journal of Geophysical Research, 2013.
[iv] Baldwin, M. P., et al. “The Quasi-Biennial Oscillation.” Reviews of Geophysics, 2001.
[v] Budikova, Dagmar. “Role of Arctic Sea Ice in Global Atmospheric Circulation: A Review.” Global and Planetary Change, 2009.
[vi] Zhang, Wenjun, et al. “Impacts of Two Types of La Niña on the NAO during Boreal Winter.” Climate Dynamics, 2014.