It was the morning of 16th October when South East England got battered by the Great Storm of 1987. Extreme winds occurred, with gusts of 70 knots or more recorded continually for three or four consecutive hours and maximum gusts up to 100 knots. The damage was huge across the country with 15 million trees blown down and 18 fatalities.
The forecast issued on the evening of 15th October failed to identify the incoming hazard but forecasters were not to blame as the strongest winds were actually due to a phenomenon that had yet to be discovered at the time: the Sting Jet. A new topic of weather-related research had started: what was the cause of the exceptionally strong winds in the Great Storm?
It was in Reading at the beginning of 21st century that scientists came up with the first formal description of those winds, using observations and model simulations. Following the intuitions of Norwegian forecasters they used the term Sting Jet, the ‘sting at the end of the tail’. Using some imagination we can see the resemblance of the bent-back cloud head with a scorpion’s tail: strong winds coming out from its tip and descending towards the surface can then be seen as the poisonous sting at the end of the tail.
In the last decade sting-jet research progressed steadily with observational, modelling and climatological studies confirming that the strong winds can occur relatively often, that they form in intense extratropical cyclones with a particular shape and are caused by an additional airstream that is neither related to the Cold nor to the Warm Conveyor Belt. The key questions are currently focused on the dynamics of Sting Jets: how do they form and accelerate?
Works recently published (and others about to come out, stay tuned!) claim that although the Sting Jet occurs in an area in which fairly strong winds would already be expected given the morphology of the storm, a further mechanism of acceleration is needed to take into account its full strength. In fact, it is the onset of mesoscale instabilities and the occurrence of evaporative cooling on the airstream that enhances its descent and acceleration, generating a focused intense jet (see references for more details). It is thus necessary a synergy between the general dynamics of the storm and the local processes in the cloud head in order to produce what we call the Sting Jet .
Browning, K. A. (2004), The sting at the end of the tail: Damaging winds associated with extratropical cyclones. Q.J.R. Meteorol. Soc., 130: 375–399. doi:10.1256/qj.02.143
Clark, P. A., K. A. Browning, and C. Wang (2005), The sting at the end of the tail: Model diagnostics of fine-scale three-dimensional structure of the cloud head. Q.J.R. Meteorol. Soc., 131: 2263–2292. doi:10.1256/qj.04.36
Martínez-Alvarado, O., L.H. Baker, S.L. Gray, J. Methven, and R.S. Plant (2014), Distinguishing the Cold Conveyor Belt and Sting Jet Airstreams in an Intense Extratropical Cyclone. Mon. Wea. Rev., 142, 2571–2595, doi: 10.1175/MWR-D-13-00348.1.
Hart, N.G., S.L. Gray, and P.A. Clark, 0: Sting-jet windstorms over the North Atlantic: Climatology and contribution to extreme wind risk. J. Climate, 0, doi: 10.1175/JCLI-D-16-0791.1.
Volonté, A., P.A. Clark, S.L. Gray. The role of Mesoscale Instabilities in the Sting-Jet dynamics in Windstorm Tini. Poster presented at European Geosciences Union – General Assembly 2017, Dynamical Meteorology (General session)
When it comes to doctoral funding, the current method means project funds can come from a variety of sources, such as research councils, charities, industry partners or a mixture of these. In this blog post I will talk about my experience of being jointly funded by a research council and industrial partner.
To start with, I am not actually a PhD student like most people in the Meteorology department here at the University of Reading, but an EngD student. An EngD is a more industrial focused PhD, based on collaboration between industry and academia. There is a taught element to an EngD in the first year, during which a range of modules are covered, on everything from business analysis to sustainability. Additionally, a portion of time is dedicated to work for the industrial sponsor during the course of the project. An EngD still has the same end goal of a PhD, of an intellectual contribution to knowledge.
EngDs were started by the Engineering and Physical Sciences Research Council (EPSRC) back in 1992 and after initial success, the program was expanded in 2009. Out of this expansion came the Technologies for Sustainable Built Environments (TSBE) Centre at the University of Reading. The TSBE Centre has produced 40 EngDs over 8 years, covering a wide variety of disciplines, from modelling energy usage in the home to the effect of different roofing materials on bats. Each student is based within multiple academic departments and the industrial partner organisation with the aim of answering real world research questions.
My project is in collaboration with the BT Group and looks at weather impacts on the UK telecommunications network. I have found that being in an industrial sponsored project is of great benefit. It has been useful to get experience of how industry works, as it can be very different to the academic life in which most doctoral students find themselves. There have also been a lot of opportunities for training in specialist subjects including industrial project management and help to get chartership from professional bodies for those who want it. Being linked with an industrial partner can also offer strong networking and knowledge transfer opportunities, as was the case when I attended a recent interdisciplinary conference of the newly formed Tommy Flowers Institute. This institute has been formed by BT, along with other partner organisations, to further support collaboration between industry and academia.
It can be a challenge at times to balance the approaches of academia and industry. They do not always pull you in the same direction but this is often the same with any lengthy piece of work produced under the guidance of different advisors from different disciplines. The strength with the EngD partnership comes from the different perspectives offered from those different fields to ultimately solve the problem in question.
For me working on a heavily applied problem in the setting of a real organisation has been of greater benefit to me than working on a purely theoretical problem would have been. I have enjoyed seeing my preliminary output being tested within the organisation and look forward to being able to test a more advanced version in the final stages of my project.
Alan Halford is funded by the EPSRC and BT and supported by the TSBE centre.
When an El Niño is declared, or even forecast, we think back to memorable past El Niños (such as 1997/98), and begin to ask whether we will see the same impacts. Will California receive a lot of rainfall? Will we see droughts in tropical Asia and Australia? Will Peru experience the same devastating floods as in 1997/98, and 1982/83?
El Niño and La Niña, which see changes in the ocean temperatures in the tropical Pacific, are well known to affect weather, and indeed river flow and flooding, around the globe. But how well can we estimate the potential impacts of El Niño and La Niña, and how likely flooding is to occur?
This question is what some of us in the Water@Reading research group at the University of Reading have been looking to answer in our recent publication in Nature Communications. As part of our multi- and inter-disciplinary research, we work closely with the Red Cross / Red Crescent Climate Centre (RCCC), who are working on an initiative called Forecast-based Financing (FbF, Coughlan de Perez et al.). FbF aims to distribute aid (for example providing water purification tablets to prevent spread of disease, or digging trenches to divert flood water) ahead of a flood, based on forecasts. This approach helps to reduce the impact of the flood in the first place, rather than working to undo the damage once the flood has already occurred.
Photo credit: Red Cross / Red Crescent Climate Centre
In Peru, previous strong El Niños in 1982/83 and 1997/98 had resulted in devastating floods in several regions. As such, when forecasts in early 2015 began to indicate a very strong El Niño was developing, the RCCC and forecasters at the Peruvian national hydrological and meteorology agency (SENAMHI) began to look into the likelihood of flooding, and what FbF actions might need to be taken.
Typically, statistical products indicating the historical probability (likelihood [%] based on what happened during past El Niños) of extreme precipitation are used as a proxy for whether a region will experience flooding during an El Niño (or La Niña), such as these maps produced by the IRI (International Research Institute for Climate and Society). You may also have seen maps which circle regions of the globe that will be drier / warmer / wetter / cooler – we’ll come back to these shortly.
These rainfall maps show that Peru, alongside several other regions of the world, is likely to see more rainfall than usual during an El Niño. But does this necessarily mean there will be floods? And what products are out there indicating the effect of El Niño on rivers across the globe?
For organisations working at the global scale, such as the RCCC and other humanitarian aid agencies, global overviews of potential impacts are key in taking decisions on where to focus resources during an El Niño or La Niña. While these maps are useful for looking at the likely changes in precipitation, it has been shown that the link between precipitation and flood magnitude is nonlinear (Stephens et al.), – more rain does not necessarily equal floods – so how does this transfer to the potential for flooding?
The motivation behind this work was to provide similar information, but taking into account the hydrology as well as the meteorology. We wanted to answer the question “what is the probability of flooding during El Niño?” not only for Peru, but for the global river network.
To do this, we have taken the new ECMWF ERA-20CM ensemble model reconstruction of the atmosphere, and run this through a hydrological model to produce the first 20th century global hydrological reconstruction of river flow. Using this new dataset, we have for the first time estimated the historical probability of increased or decreased flood hazard (defined as abnormally high or low river flow) during an El Niño (or La Niña), for the global river network.
The question – “what is the probability of flooding during El Niño?”, however, remains difficult to answer. We now have maps of the probability of abnormally high or low river flow (see Figure 1), and we see clear differences between the hydrological analysis and precipitation. It is also evident that the probabilities themselves are often lower, and much more uncertain, than might be useful – how do you make a decision on whether to provide aid to an area worried about flooding, when the probability of that flooding is 50%?
The likely impacts are much more complex than is often perceived and reported – going back to the afore-mentioned maps that circle regions of the globe and what their impact will be (warmer, drier, wetter?) – these maps portray these impacts as a certainty, not a probability, with the same impacts occurring across huge areas. For example, in Figure 2, we take one of the maps from our results, which indicates the probability of increased or decreased flood hazard in one month during an El Niño, and draw over this these oft-seen circles of potential impacts. In doing this, we remove all information on how likely (or unlikely) the impacts are, smaller scale changes within these circles (in some cases our flood hazard map even indicates a different impact), and a lot of the potential impacts outside of these circles – not to mention the likely impacts can change dramatically from one month to the next. For those organisations that take actions based on such information, it is important to be aware of the uncertainties surrounding the likely impacts of El Niño and La Niña.
“We conclude that while it may seem possible to use historical probabilities to evaluate regions across the globe that are more likely to be at risk of flooding during an El Niño / La Niña, and indeed circle large areas of the globe under one banner of wetter or drier, the reality is much more complex.”
PS. During the winter of 2015/16, our results estimated an ~80% likelihood of increased flood hazard in northern coastal Peru, with only ~10% uncertainty surrounding this. The RCCC took FbF actions to protect thousands of families from potentially devastating floods driven by one of the strongest El Niños on records. While flooding did occur, this was not as severe as expected based on the strength of the El Niño. More recently, during the past few months (January – March 2017), anomalously high sea surface temperatures (SSTs) in the far eastern Pacific (known as a “coastal El Niño” in Peru but not widely acknowledged as an El Niño because central Pacific SSTs are not anomalously warm) have led to devastating flooding in several regions and significant loss of life. And Peru wasn’t the only place that didn’t see the impacts it expected in 2015/16; other regions of the world, such as the US, also saw more rainfall than normal in places that were expected to be drier, and California didn’t receive the deluge they were perhaps hoping for. It’s important to remember that no two El Niños are the same, and El Niño will not be the only influence on the weather around the globe. While El Niño and La Niña can provide some added predictability to the atmosphere, the impacts are far from certain.
As well as being a meteorologist, I am a bird watcher. This means I often combine meteorology and bird watching to see the impact of the weather on birds. Now that we are well into March my focus in bird watching turns to one thing – the migration.
March generally marks the time when the first summer migrants start arriving into the UK. Already this year we have had reports of Sand Martin, Wheatear, Garganey, Little Ringed Plover, White Wagtail, Osprey, Swallow, House Martin, Ring Ouzel and Whitethroat (up to 9 March), some of which are depicted below.
There are many people that consider the arrival dates of certain migratory species of birds and how this arrival date changes over many years. I do keep extensive records of the birds that I see (and thus arrival dates), but what interests me more are the odd days in the record, and the sightings of unusual birds and working out how they arrived at their destinations.
A good example of this can be found by looking at my first Swallow sighting of the year in Kent and East Sussex. Since I started bird watching in 2001 my first Swallow of the year has moved from around 10 April to between 26-March and 1 April. However in 2013 my first record was 15 April. Then in 2015 and 2016 I saw my first Swallow on 1 April and 27 March respectively (I was in Cheshire in 2014 in late March/early April).
So what happened; why were the Swallows late in Kent in 2013? Well, it all comes down to wind direction. The spring of 2013 was very chilly and along the east coast there were plenty of N/NE winds – this would have provided a head wind so the Swallows would preferentially not migrate up the east coast in those conditions but instead migrate up the west coast where there were southerlies.
So, the wind direction plays a key part in the migration of birds. If conditions are for a tailwind or very light winds the birds will migrate; otherwise they will stay put. However, headwinds can lead to some interesting phenomena associated with bird migration – ‘falls’.
A ‘fall’ occurs when there are a large number of migrants building up along the coastline at a departure point (so for the interest of UK bird watchers Northern France), as they cannot get to their destination. When the wind direction changes the birds will then migrate en masse and quite literally fall out of the sky.
It’s not all about the wind direction though; rain is also a key factor that bird watchers consider when looking at weather forecasts. Essentially, fronts and showers are great for bird watchers. On migration birds will often fly higher than they normally would. This means on a clear sunny day you could easily miss birds passing overhead as they are so high up. However, with the rain the birds will often fly lower, avoiding the in-cloud turbulence. For many of the summer migrants their food sources (insects) also fly lower in these conditions.
This means that a forecast of showers with a southerly wind is generally what I look for from mid-April onwards (particularly as an inland birder), as it means there is a good chance of migratory species turning up – also because then I can head out after work as the evenings are brighter. This is something that I did last year and ended up recording the first Sandwich Tern (photo below (not of the bird I saw)) of the year in Berkshire.
So in summary, it’s not as simple as just keeping an eye on the wind direction – there are other factors that can influence the birds’ migration and where they will end up. For more information about the impact of weather on bird sightings (considering both rare and common birds) check out my blog.
From 12th to 16th December 2016, the annual American Geophysical Union (AGU) Fall Meeting took place at the Moscone Centre in San Francisco. AGU remains the largest Earth and Space Science conference in the world with more than 25,000 scientists.
At the 2016 Fall Meeting, I was one of around 8000 students who arrived in San Francisco to present one of the 15,000 posters that would be displayed over the course of the week. While I knew that AGU is one of the largest Earth science conferences, and had indeed spent hours on the plane fine-tuning my schedule to choose which of the ~200 hydrology sessions (let alone the meteorology sessions also related to my work) I would attend, the scope and diversity of the research presented throughout the week really sunk in when I stood on the mezzanine overlooking the poster hall on the first day of the conference.
I was lucky enough to be awarded an AGU student travel grant in order to present my latest PhD research that I’ve been working on at the University of Reading, in collaboration with the European Centre for Medium-Range Weather Forecasts (ECMWF), and funded by NERC as part of the SCENARIO Doctoral Training Partnership. My work maps the historical probability of increased (or decreased) flood hazard across the globe during ENSO (El Niño and La Niña) events, using the first 20th Century ensemble river flow reanalysis, created at ECMWF as part of this work. But more on that another time!
Unlike other conferences I’d presented at, the poster sessions at AGU span half a day – while you are only expected to be there to discuss the work for two hours, it’s inevitable that you get caught up in discussion and I saw many presenters (myself included) who stuck by their poster for the full 4.5 hours! I thoroughly enjoyed my poster session, where several familiar faces dropped by for an update on my work, and others stopped to pose new questions and make a few suggestions for improvements to my maps (wait, why didn’t I think of that?!). As a student presenter, I could also register for the Outstanding Student Poster Award – which means that my poster was anonymously judged, and I will soon be receiving feedback on my poster and presentation – an opportunity I was excited about to make sure I continue to improve the way I communicate my research.
For me, some of the sessions that were highlights of the conference included ‘Global Floods: Forecasting, Monitoring, Risk Assessment and Socioeconomic Response‘, ‘Large-scale Climate Variability and its Impact on Hydrological Systems, Water Resources and Population‘, ‘Forecasting Hydrology at Continental Scale‘, ‘Transforming Hydrologic Prediction and Decision Making: Uncertainty’ and ‘ENSO Dynamics, Observations and Predictability in light of the 2015-2016 El Niño Event‘. With such a range of science being presented, there’s also plenty of opportunity (well, so long as you haven’t double- or triple-booked sessions in your schedule already!) to listen to talks outside of your own field – which is how I ended up in an 8am talk on operational earthquake forecasting and early warning. It was brilliant to learn about forecasting natural hazards outside of hydrology and meteorology!
There was also the social aspect that’s a big part of any conference – networking, networking and more networking! While it can be daunting, particularly at a conference of this size, to find and introduce yourself to scientists in your field whose work you’ve read but you’ve never met, I was pleased to first bump into some friendly faces who in turn introduced me to the new faces. Plus, it’s an AGU tradition that ‘AGU beer’ is served at 3.30pm sharp and the conference centre fills with groups of friends and colleagues in heated debates and discussions about anything from volcanoes to Jupiter’s magnetosphere.
It was impossible not to notice, however, the many more politically-themed conversations than would normally be overheard at such an event, as a result of uncertainty about the future of science in light of the recent US presidential election. While I was in the middle of research discussions at my poster, a ‘Stand up for Science‘ rally took place a few blocks away from the conference centre, where scientists donned lab coats and held signs – “stand up for science”, “ice has no agenda – it just melts” – protesting to raise awareness of the challenges, and to support science. You can read the Guardian article here.
All in all, AGU was a brilliant chance to present and discuss part of my research that I had just finished – it was certainly overwhelming and tough to choose which sessions to stop by (which meant I missed one or two presentations that sounded great), but I would recommend it for showcasing your work (and receiving feedback via the OSPA) and meeting scientists in your field that you wouldn’t normally bump into at conferences in Europe, especially if you can apply for one of AGU’s travel grants to help cover the costs of getting there.
P.S. You can watch presentations from the AGU Fall Meeting 2016 on the website.
Of course, I couldn’t fly all the way out to California and not find time to explore San Francisco a little.
The interaction between atmospheric flow and topography is at the origin of various important weather phenomena, as we have already seen in Carly Wright’s blog post. When a mountain range is particularly high and extended it can even block or deflect weather systems, as it happens with the Alps. For example, in Figure 1 we can see the main Alpine range with its over-4000m-high peaks blocking a cold front coming from the north. The main ridge acts as a wall, enhancing condensation and precipitation processes on the upstream side (stau condition) and leaving clear skies on the downstream lee side, where dry and mild katabatic foehn winds flow. The contrast is striking between sunny weather on Lake Maggiore and snowy conditions over Monte Rosa, just a few miles apart. The same phenomenon is shown in Figure 2 with a satellite image that highlights how a cold front coming from northwest gets blocked by the Alpine barrier. A person enjoying the sunny day in the southern side of the Alps, if unaware of this mechanism, would be very surprised to know that the current weather is so different on the other side of the range.
A comparison with Figure 3 helps to notice that in Figure 2 the shape of the cloud band closely mirrors the mountain range. As an additional remark, this comparison shows that foehn bring clear skies even in the Po Valley, having blown away the typical mist/fog occurring in the region in Autumn and Winter months in high pressure regimes. The stau/foehn dynamics is actually very fascinating, and you can read more about it in Elvidge and Renfrew (2015 ) and in Miltenberger et al. (2016), among others. Unfortunately, the interaction of weather systems with the Alps can often trigger very damaging phenomena, like heavy and long-lasting precipitation on one side of the slope, and this is what the rest of this post will be focused on. In fact, the most recent event of this kind just happened at the end of November, with intense and long-lasting rain affecting the southern slope of the Alps and causing floods particularly in the Piedmont region, in northwestern Italy ( Figure 4).
Figure 5 shows that the accumulated rainfall in the event goes over 300 mm in a large band that follows the shape of the southern Alpine slope in the region (see map of Piedmont, from Google Maps), reaching even 600 mm in a few places. This situation is the result of moist southerly flow being blocked by the Alps and thus causing ascent and consequent precipitation to persist on the same areas for up to five days. It is quite common to see quasi-stationary troughs enter the Mediterranean region during Autumn months causing strong and long-lasting moist flows to move towards the Alps. Hence, it is crucial to understand where the heaviest precipitation will occur. In other words, will it rain the most on top of the ridge or on the upstream plain? What processes are controlling the location of heavy precipitation with respect to the slope?
The study published by Davolio et al. (2016), available here and originated from my master degree’s thesis, tackles this issue focusing on northeastern Italy. In fact, the analysis includes three case studies in which heavy and long-lasting rain affected the eastern Alps and other three case studies in which intense rainfall was mainly located on the upstream plain. Although all the events showed common large-scale patterns and similar mesoscale settings, characterised by moist southerly low-level flow interacting with the Alps, the rainfall distribution turned out to be very dissimilar. The study highlights that the two precipitation regimes strongly differ in terms of interaction of the flow with the mountain barrier. When the flow is able to go over the Alps the heaviest rain occurs on top of the ridge. When the flow is instead blocked and deflected by the ridge (flow around), creating a so-called barrier wind,intense convection is triggered on the upstream plain (Figure 6) .
The key mechanism that explains this different evolution is connected to the thermodynamic state of the impinging flow. In fact, when the southerly moist and warm air gets close to the Alpine barrier it is lifted above the colder air already present at the base of the orography. It can be said that the colder air behaves as a first effective mountain for the incoming flow. If this lifting process triggers convection, then the persistence of a blocked-flow condition is highly favoured (see Figure 7). On the contrary, if this initial lifting process does not trigger convection the intense moist flow will eventually be able to go over the ridge, where a more substantial ascent will take place, causing heavy rain on the ridge top. This study also looks at numerical parameters used in more idealised analyses (like in Miglietta and Rotunno (2009)), finding a good agreement with the theory.
To summarise, we can say that the Alpine range is able to significantly modify weather systems when interacting with them. Thus, an in-depth understanding of the processes taking place during the interaction, along with a coherent model is necessary to capture correctly the effects on the local weather, being either a rainfall enhancement, the occurrence of foehn winds or various other phenomena.
Davolio, S., Volonté A., Manzato A., Pucillo A., Cicogna A. and Ferrario M.E. (2016), Mechanisms producing different precipitation patterns over north-eastern Italy: insights from HyMeX-SOP1 and previous events. Q.J.R. Meteorol. Soc., 142 (Suppl 1): 188-205. doi:10.1002/qj.2731
Elvidge A. D., Renfrew, I. A. (2015). The causes of foehn warming in the lee of mountains. Bull. Am. Meteorol. Soc.97: 455–466, doi:10.1175/BAMS-D-14-00194.1.
Miglietta M. and Rotunno R., (2009)Numerical Simulations of Conditionally Unstable Flows over a Mountain Ridge.J. Atmos. Sci.,66, 1865–1885, doi: 10.1175/2009JAS2902.1.
Miltenberger, A. K., Reynolds, S. and Sprenger, M. (2016), Revisiting the latent heating contribution to foehn warming: Lagrangian analysis of two foehn events over the Swiss Alps. Q.J.R. Meteorol. Soc., 142: 2194–2204. doi:10.1002/qj.2816
Under the United Nations Framework Convention on Climate Change (UNFCCC), countries negotiate how to address the impacts of anthropogenic climate change through mitigation and adaptation. Despite these efforts, climate-related events still cause huge impacts across the globe every year. Impacts can be particularly devastating in developing countries and this is what the relatively new area of ‘loss and damage’ in the negotiations aims to address.
In 2013, the UNFCCC established the Warsaw International Mechanism (WIM) to “address loss and damage associated with impacts of climate change, including extremes events and slow onset events, in developing countries that are particularly vulnerable to the adverse effects of climate change” (UNFCCC, 2013). Two decades of negotiating went into forming this mechanism, since the first calls from small island developing states in the early 1990s to address the effects of sea level rise.
The WIM states it will address the impacts of both extreme events (such as floods and heatwaves) and slow onset events (such as sea level rise). However, as yet, there is no official definition of what loss and damage will actually encompass. In our commentary in Nature Climate Change (James et al., 2014), we considered one aspect of defining loss and damage: whether loss and damage would need to be attributed to anthropogenic climate change. As the text of the WIM describes “loss and damage associated with the impacts of climate change” and the UNFCCC’s definition of climate change is that which is “attributed directly or indirectly to human activity” (UNFCCC, 1992), this could imply that there would need to be proof that impacts from events were caused by anthropogenic climate change.
If this were the case, impacts would first need to be attributed to particular events (e.g. the infrastructure damaged by a particular flood), and then the event would need to be attributed to anthropogenic climate change. For slow-onset events like sea level rise, the science attributing these to anthropogenic climate change is well-established. However for individual events it is much more challenging to say how climate change had an influence. Extreme event attribution can, for some types of events, estimate how anthropogenic climate change affected the probability of the particular event occurring. This generally relies on large ensembles of climate model simulations, which are necessary to estimate the probabilities of such rare events, and studies therefore rely on the ability of the models to represent the processes that produce the extreme event in question. Observations are also necessary to both to validate the model simulations and define the extreme event to be studied, which are not always available, particularly in developing countries. Up to now, studies attributing specific events have been carried out on an ad hoc basis in the aftermath of particularly extreme events, rather than more systematically. They have also mainly focussed on events in developed countries, rather than the developing countries the WIM aims to assist.
While the attribution of events to anthropogenic climate change could be relevant to addressing loss and damage, it is controversial in negotiations. This is in part due to its perceived association with compensation claims. However we suggest that, somewhere along the line, the question of causality is likely to come up, to establish just what the loss and damage being addressed is. Attribution may or may not have a role to play here. What is key is that as event attribution science is continuing to develop, scientists and policymakers need to have opportunities for conversations about what information the science can provide and how this could be applied if it was deemed necessary for policy.
Since writing our commentary we have continued to research this science-policy interface. We have investigated what is understood about event attribution science by stakeholders associated with loss and damage negotiations and how they think it could be relevant (Parker et al., 2016). We have also investigated how policymakers and practitioners are defining ‘loss and damage’, as this still has no official definition and there are differing perspectives among those looking to address loss and damage. Our aim is that by better understanding this policy context, the science will be able to develop in ways that are most relevant to the needs of decision makers and, if deemed relevant, ultimately help to address loss and damage in vulnerable regions.
This work forms part of the ACE-Africa project, for more information see http://www.walker.ac.uk/projects/ace-africa-attributing-impacts-of-external-climate-drivers-on-extreme-weather-in-africa/
James, R., Otto, F., Parker, H., Boyd, E., Cornforth, R., Mitchell, D., & Allen, M. (2014). Characterizing loss and damage from climate change. Nature Climate Change, 4, 938-939, doi: 10.1038/nclimate2411.
Parker, H. R. , Boyd, E., Cornforth, R. J., James, R., Otto, F. E. L., & Allen, M. R. (2016). Stakeholder perceptions of event attribution in the loss and damage debate. Climate Policy, doi: 10.1080/14693062.2015.1124750.
UNFCCC (1992). Article 1: Definitions
UNFCCC (2013). Decision 2/CP.19: Warsaw International Mechanism for Loss and Damage Associated with Climate Change Impacts FCCC/CP/2013/10/Add.1
Showers are one of the many examples of convective events experienced in the UK, other such events include thunderstorms, supercells and squall lines. These type of events form most often in the summer but can also form over the sea in the winter. They form because the atmosphere is unstable, i.e. warm air over a cooler surface, this results in the creation of thermals. If there is enough water vapour in the air and the thermal reaches high enough the water vapour will condense and eventually form a convective cloud. Convective events produce intense, often very localised, rainfall, which can result in flash floods, e.g. Boscastle 2004.
Flash floods are very difficult to predict, unlike flood events that happen from the autumnal and winter storms e.g. floods from Storms Desmond and Frank last winter, and the current floods (20-22 November). So often there is limited lead time for emergency services to react to flash flood events. One of the main reasons why flash floods are difficult to predict is the association with convective events because these events only last for a few hours (6 hours at the longest) and only affect a very small area.
One of the aspects of forecasting the weather that researchers look into is the predictability of certain events. My PhD considers the predictability of convective events within different situations in the UK.
The different situations I am considering are generally split into two regimes: convective quasi-equilibrium and non-equilibrium convection.
In convective quasi-equilibrium any production of instability in the atmosphere is balanced by its release (Arakawa and Schubert, 1974). This results in scattered showers, which could turn up anywhere in a region where there is large-scale ascent. This is typical of areas behind fronts and to the left of jet stream exit regions. Because there are no obvious triggers (like flow over mountains or cliffs) you can’t pin-point the exact location of a shower. We often find ourselves in this sort of situation in April, hence April showers.
On the other hand in non-equilibrium convection the instability is blocked from being released so energy in the system builds-up over time. If this inhibiting factor is overcome all the instability can be released at once and will result in ‘explosive’ convection (Emanuel, 1994). Overcoming the inhibiting factor usually takes place locally, such as a sea breeze or flow up mountains, etc. so these give distinct triggers and help tie the location of these events down. These are the type of situations that occur frequently over continents in the spring and often result in severe weather.
It’s useful having these regimes to categorise events to help determine what happens in the forecasts of different situations but only if we understand a little bit about their characteristics. For the initial part of my work I considered the regimes over the British Isles and found that we mainly have convective events in convective quasi-equilibrium (showers) – on average roughly 85% of convective events in the summer are in this regime (Flack et al., 2016). Therefore it is pertinent to ask how well can we predict showers?
To see how well we can predict showers, and other types of convection, the forecast itself is examined. This is done by adding small-scale variability into the model, throughout the forecast, to determine what would happen if the starting conditions (or any other time in the model) changed. This is run a number of times to create an ensemble.
Using ensembles we can determine the uncertainty in the weather forecast, this can either be in terms of spatial positioning, timing or intensity of the event. My work has mainly considered the spatial positioning and intensity of the convection, and is to be submitted shortly to Monthly Weather Review. The intensity in my ensemble shows similar variation in both regimes, suggesting that there are times when the amount of rainfall predicted can be spot on. Most of the interesting results appear to be linked to the location of the events. The ensembles for the non-equilibrium cases generally show agreement between location of the events, so we can be fairly confident about their location (so here your weather app would be very good). On the other hand, when it comes to showers there is no consistency between the different forecasts so they could occur anywhere (so when your app suggests showers be careful – you may or may not get one).
So I’ll answer my question that I originally posed with another question: What do you want from a forecast? If the answer to this question is “I want to know if there is a chance of rain at my location” then yes we can predict that you might get caught by a shower. If on the other hand your answer is “I want exact details, for my exact location, e.g. is there going to be a shower at 15:01 on Saturday at Stonehenge yes or no?” Then the answer is, although we are improving forecasts, we can’t give that accurate a forecast when it comes to scattered showers, simply because of their very nature.
With forecasts improving all the time and the fact that they are looking more realistic it does not mean that every detail of a forecast is perfect. As with forecasting in all areas (from politics to economy) things can take an unexpected turn so caution is advised. When it comes to the original question of showers then it’s always best to be prepared.
This work has been funded by the Natural Environmental Research Council under the project Flooding From Intense Rainfall, for more project details and project specific blogs visit: www.met.reading.ac.uk/flooding
Arakawa, A. and W. H. Schubert, 1974: Interaction of a Cumulus Cloud Ensemble with the Large-Scale Environment, Part I. J. Atmos. Sci., 31, 674-701.
Emanuel, K. A., 1994: Atmospheric convection, Oxford University Press, 580 pp.
Flack, D. L. A., R. S. Plant, S.L. Gray, H. W. Lean, C. Keil and G. C. Craig, 2016: Characterisation of Convective Regimes over the British Isles. Quart. J. Roy. Meteorol. Soc., 142, 1541-1553.