On Friday the 14th of June at 6.30pm the Department of Meteorology had its 2019 summer BBQ! And what a fun, pleasant and well attended affair it was.
The weather that week had been especially awful, and the prospects of being able to have the BBQ outside were looking distinctly grim, but in a rather fluky stroke of luck, the weather took a rather unexpected turn for the better… and almost unbelievably, by Friday PM the grass was deemed dry enough – and therefore safe enough – for the event to be an outdoor, in-the-sun affair!
The event required a lot of preparation. For the most part this went smoothly, save for one or two things:
1: A sudden and panicky realisation on my part on the morning of the BBQ (thanks Michael L!) that we probably weren’t going to get very far without tongs/cooking implements of some kind! (This is my first Met BBQ, okay!)
2: The butcher delivery van going seriously AWOL (even from the butchers themselves). The van apparently departed the Reading depot at 9am and must have then gotten lost as it took them some 8 hours to find us! This caused some nerves to fray…
The event took off at 6.30pm and thanks to a small army of well-trained BBQing PhD students, both meat and plant-based sausages and burgers soon began to appear and (as we had slightly over ordered on the food front) attendees got offered seconds! No one present was to go hungry!
At around 8pm the perennial Hogs Back Band & caller began their ceilidh/barn dance. Many of us were duly terrified of this part of the evening, but such concerns quickly vanished following a few nervous giggles, a couple of bungled dance steps… and of course one or two beers. Before long, everyone, both dancers and onlookers, children and staff alike were totally caught up in the band’s buoyant jig, and all feeling of self-consciousness evaporated!
2 hours of ceilidh as it turns out, is incredibly tiring! I managed about half of the 10 dances and towards the end was beginning to seriously unravel at the seams. Perhaps a prize in future years for he or she who can manage to stick out every single dance? Surely one of the Met runners has the stamina?
As the evening drew to a close at 10pm I was impressed by the sustained, voluntary and joint effort of many to return the area to its original clean state. And, for those with energy to spare, the after-party with DJ Shonk and his new disco ball awaited!
A special thanks to Dan Shipley (one of the 2018 organisers) who despite supposedly having retired the year before, provided much help and advice at all stages of the planning and on the day! Numerous others also contributed in ways both big and small to make the event the success that it was. Thank you! Long live this particular Met Department tradition!
With thanks to all my helpers who enabled the week to go smoothly! Adam Bateson, Sally Woodhouse, Kaja Milczewska and Agnieszka Walenkiewicz
Each year PhD students in the Department of Meteorology invite a distinguished scientist to spend a week with us.This year we invited Prof. Cecilia Bitz, who visited between the 28th-31st May. Cecilia is based at the University of Washington, Seattle.
Cecilia’s research interests are the role of sea ice in the climate system, and high latitude climate and climate change. She has also done a lot of work on the predictability of Arctic sea ice, and is involved in the Sea Ice Prediction Network.
The week began with a welcome reception in the coffee area, introducing Cecilia to the department, followed by a seminar by Cecilia on ‘Polar Regions as Sentinels of Different Climate Change’. The seminar predominantly focused on Antarctic sea ice, and the possible reasons why Antarctic sea ice behaviour is so different to the Arctic. Whilst Arctic sea ice has steadily declined we have seen Antarctic sea ice expansion over the past four decades, with extreme Antarctic sea ice extent lows since 2016.
Throughout the week Cecilia visited a number of the research groups, including Mesoscale, HHH (dynamics) and Cryosphere, where PhD students from each group presented to her, giving a taste of the range of PhD research within our department.
Cecilia gave a second seminar later in the week in the Climate and Ocean Dynamics (COD) group meeting, this time focusing on the other pole, ‘Arctic Amplification: Local Versus Remote Causes and Consequences’. Cecilia discussed her work quantifying the role of feedbacks in Arctic Amplification, how they compare with meridional heat transports, and what influence Arctic warming has on the rest of the globe.
On Wednesday afternoon the normal PhD group slot consisted of a career discussion, with Cecilia. Cecilia shared some of her career highlights with us, including extra opportunities she has taken such as doing some fieldwork in Antarctica and working for the charity, Polar Bears International, her insights and advice from her own experiences, as well as about post-doctoral opportunities in the US. A few of my personal take-aways from this session were to try give yourself space to learn one new thing at a time in your career (e.g. teaching, writing proposals, supervising etc). Try to work on a range of problems, and keep your outlook broad and open to new ideas and approaches. Take opportunities when they appear, such as fieldwork or short projects/collaborations.
A small group of PhDs also met with her on the Friday to have an informal discussion about climate policy. In particular about her experiences speaking to the US senate, being a part of the IPCC reports and about the role of scientists in speaking about climate change, and whether we have a responsibility to do so.
Thursday evening the PhDs took Cecilia to Zero Degrees (a very apt choice for a polar researcher!), and enjoyed a lovely evening chatting over pizza and beer.
The week ended with a farewell coffee morning on Friday, where we gave Cecilia some gifts to thank her for giving us her time this week including some tea, chocolates, a climate stripes mug and a framed picture of us…
All the PhDs had a great week. We hope Cecilia enjoyed her visit as much as we did!
From 7th-12th April, I had the exciting opportunity to attend the European Geosciences Union (EGU) General Assembly in Vienna. This was a much larger conference than any I had attended previously, with 16,273 scientists in attendance and 683 scientific sessions, which made for a whirlwind experience. I was staying with other PhD students from the department, so many evenings were spent comparing schedules and pointing out interesting courses to make sure none of us missed anything useful!
As part of the Tropical Meteorology and Tropical Cyclones session, I gave an oral presentation about my PhD work, which investigates the use of Available Potential Energy theory to study the processes involved in tropical cyclone intensification. The session included many excellent talks on different aspects of tropical meteorology, and it was great to speak with scientists whose interests are similar to mine about possible avenues for combining our work.
PhD students from the department present their research at EGU
One of the major advantages of attending such a large conference was the opportunity to learn more about areas of geoscience research that I wouldn’t normally encounter. I made a specific effort to attend a few sessions on topics that I am not familiar with, including wildfires (#FIREMIP), landslides and exoplanets. It was fascinating to see the work that goes on in different fields and I hope that being exposed to different methods and perspectives will help me to become a more creative researcher.
EGU is such a huge event that the scientific sessions are only part of the story. There were Great Debates on topics ranging from science in policy to the prioritisation of mental wellbeing for Early Career Scientists, two artists-in-residence creating pieces inspired by the science of the conference, and an extremely entertaining Poetry Slam event, which two of the Reading Meteorology PhD students were brave enough to participate in (or possibly just desperate enough for a ticket to the conveners’ party).
So now it’s the end of EGU I caught the train – and I flew We both did a talk Learnt the German for fork “Eine Gabel bitte” – thank you
– Sally Woodhouse & Kaja Milczewska
EGU was a great experience and after the conference I was able to take some time to explore Vienna, see some historic landmarks, and unwind from an enjoyably exhausting week of science. Although to begin my break from geoscience I did go straight to the Globe Museum, so perhaps I need to work on my relaxation techniques.
An important part of science is sharing our research and one of the best ways to do that is at conferences, so we can’t just stop going! But there is another way … the train (0.04 metric tonnes CO2)! And if I’m spending all that time why not have a little adventure.
After a power cut last night, a late taxi a sprint across Reading station, a delayed train and Rachael being too weak to carry anything because she didn't sleep … we've finally made it to the Eurostar for the beginning of our #EGU19 train adventure.
With the help of the man in seat 61 (check it out if you’re getting the train anywhere it’s so helpful!) we decided to go via Zurich. We had a night’s stop in Zurich, a morning there exploring and then an afternoon train through the stunning Arlberg Pass and beautiful views of Alpine Austria. Honestly the views made the 5am start the day before and sprint for the Eurostar all worth it. It was breath-taking for the whole 8 hour journey.
For the return trip we took the speedy route through Germany and Belgium – this is actually doable in a day but I decided to have an overnight in Brussels. I spent a lovely day wandering around the main sites and even managed a visit to the European Parliament!
It might take a bit longer but it was a wonderful adventure and I’d definitely recommend it to everyone traveling to EGU in future – maybe I’ll see you on the train.
From April 2nd-5th I attended the workshop on Predictability, dynamics and applications research using the TIGGE and S2S ensembles at ECMWF in Reading. TIGGE (The International Grand Global Ensemble, formerly THORPEX International Grand Global Ensemble) and S2S (Sub-seasonal-to-Seasonal) are datasets hosted at primarily at ECMWF as part of initiatives by the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP). TIGGE has been running since 2006 and stores operational medium-range forecasts (up to 16 days) from 10 global weather centres, whilst S2S has been operational since 2015 and houses extended-range (up to 60 days) forecasts from 11 different global weather centres (e.g. ECMWF, NCEP, UKMO, Meteo-France, CMA…etc.). The benefit of these centralised datasets is their common format, which enables straightforward data requests and multi-model analysis with minimal data manipulation allowing scientists to focus on doing science!
Attendees of the workshop came from around the world (not just Europe) although there was a particularly sizeable cohort from Reading Meteorology and NCAS.
In my PhD so far, I have been making extensive use of the S2S database – looking at both operational and re-forecast datasets to assess stratospheric predictability and biases – and it was rewarding to attend the workshop and see what a diverse range of applications the datasets have across the world. From the oceans to the stratosphere, tropics to poles, predictability mathematics to farmers and energy markets, it was immediately very clear that TIGGE and S2S are wonderfully useful tools for both the research and applications communities. A particular aim of the workshop was to discuss “user-oriented variables” – derived variables from model output which represent the meteorological conditions to which a user is sensitive (such as wind speed at a specific height for wind power applications).
The workshop mainly consisted of 15-minute conference-style talks in the main lecture theatre and poster sessions, but the final two days also featured parallel working group sessions of about 15 members each. The topics discussed in the working groups can be found here. I was part of working group 4, and we discussed dynamical processes and ensemble diagnostics. We reflected on some of the points raised by speakers over the preceding days – particular attention was given to diagnostics needed to understand dynamical effects of model biases (such as their influence on Rossby wave propagation and weather-regime transition) alongside what other variables researchers needed to make full use of the potentials S2S and TIGGE offer (I don’t think I could say “more levels in the stratosphere!” loudly enough – TIGGE does not go above 50 hPa, which is not useful when studying stratospheric warming events defined at 10 hPa).
Data analysis tools are also becoming increasingly important in atmospheric science. Several useful and perhaps less well-known tools were presented at the workshop – Mio Matsueda’s TIGGE and S2S museum websites provide a wide variety of pre-prepared plots of variables like the NAO and MJO which are excellent for exploratory data analysis without needing many gigabytes of data downloads. Figure 2 shows an example of NAO forecasts from S2S data – the systematic negative NAO bias at longer lead-times was frequently discussed during the workshop, whilst the inability to capture the transition to a positive NAO regime beginning around February 10th is worth further analysis. In addition to these, IRI’s Data Library has powerful abilities to manipulate, analyse, plot, and download data from various sources including S2S with server-side computation.
It’s inspiring and motivating to be part of the sub-seasonal forecast research community and I’m excited to present some of my work in the near future!
Some PhD projects are co-organised by an industrial CASE partner which provides supervisory support and additional funding. As part of my CASE partnership with the UK Met Office, in January I had the opportunity to spend 5 weeks at the Exeter HQ, which proved to be a fruitful experience. As three out of my four supervisors are based there, it was certainly a convenient set-up to seek their expertise on certain aspects of my PhD project!
One part of my project aims to understand how certain neighbourhood-based verification methods can affect the level of surface air quality forecast accuracy. Routine verification of a forecast model against observations is necessary to provide the most accurate forecast possible. Ensuring that this happens is crucial, as a good forecast may help keep the public aware of potential adverse health risks resulting from elevated pollutant concentrations.
The project deals with two sides of one coin: evaluating forecasts of regional surface pollutant concentrations; and evaluating those of meteorological fields such as wind speed, precipitation, relative humidity or temperature. All of the above have unique characteristics: they vary in resolution, spatial scale, homogeneity, randomness… The behaviour of the weather and pollutant variables is also tricky to compare against one another because the locations of their numerous measurement sites nearly never coincide, whereas the forecast encompasses the entirety of the domain space. This is kind of the crux of this part of my PhD: how can we use these irregularly located measurements to our advantage in verifying the skill of the forecast in the most useful way? And – zooming out still – can we determine the extent to which the surface air pollution forecast is dependent on some of those aforementioned weather variables? And can this knowledge (once acquired!) be used to further improve the pollution forecast?
While at the Met Office, I began my research specifically into methods which analyse the forecast skill when a model “neighbourhood” of a particular size around a particular point-observation is evaluated. These methods are being developed as part of a toolkit for evaluation of high resolution forecasts, which can be (and usually are) more accurate than a lower resolution equivalent, but traditional metrics (e.g. root mean square error (RMSE) or mean error (ME)) often fail to demonstrate the improvement (Mittermaier, 2014). They can also fall victim to various verification errors such as the double-penalty problem. This is when an ‘event’ might have been missed at a particular time in the forecast at one gridpoint because it was actually forecast in the neighbouring grid-point one time-step out, so the RMSE counts this error both in the spatial and temporal axes. Not fair, if you ask me. So as NWP continues to increase in resolution, there is a need for robust verification methods which relax the spatial (or temporal) restriction on precise forecast-to-observation matching somewhat (Ebert, 2008).
One way to proceed forward is via a ‘neighbourhood’ approach which treats a deterministic forecast almost as an ensemble by considering all the grid-points around an observation as an individual forecast and formulating a probabilistic score. Neighbourhoods are made of varying number of model grid-points, i.e. a 3×3 or a 5×5 or even bigger. A skill score such as the ranked probability score (RPS) or Brier Score is calculated using the cumulative probability distribution across the neighbourhood of the exceedance of a sensible pollutant concentration threshold. So, for example, we can ask what proportion of a 5×5 neighbourhood around an observation has correctly forecasted an observed exceedance (i.e. ‘hit’)? What if an exceedance forecast has been made, but the observed quantity didn’t reach that magnitude (i.e. ‘false alarm’)? And how do these scores change when larger (or smaller) neighbourhoods are considered? And, if these spatial verification methods prove informative, how could they be implemented in operational air quality forecast verification? All these questions will hopefully have some answers in the near future and form a part of my PhD thesis!
Although these kind of methods have been used for meteorological variables, they haven’t yet been widely researched in the context of regional air quality forecasts. The verification framework for this is called HiRA – High Resolution Assessment, which is part of the wider verification network Model Evaluation Tools (which, considering it is being developed as a means of uniformly assessing high-resolution meteorological forecasts, has the most unhelpful acronym: MET). It is quite an exciting opportunity to be involved in the testing and evaluation of this new set of verification tools for a surface pollution forecast at a regional scale, and I am very grateful to be involved in this. Also, having the opportunity to work at the Met Office and “pretend” to be a real research scientist for a while is awesome!
Maarten Ambaum (firstname.lastname@example.org) Mark Prosser (email@example.com)
Everybody knows that the key boundary condition for a successful PhD is the provision of plenty of coffee during the day (tea, for some). Our Department has a hot water boiler with a 10 litre water tank capacity to provide an unlimited supply of hot water (it is connected to the tap to keep it topped up automatically). For historical reasons we actually call it the “urn” – I like that word so we stick to it here.
When we got a new urn recently (a “Marco Ecoboiler T10”) we were intrigued to see it had an ECO mode button, presumably promising a lower energy consumption. Indeed, when anyone in the morning saw that the urn was not in “ECO mode”, it was swiftly switched on; green credentials and all that.
One of our postdocs dug up the specs from the internet, where we learned that “ECO mode” actually makes the urn operate with 5 litres of water, which is half full. The specs suggest that when switching the urn on you then only need to heat half the amount of water. But is there more to it? Would the urn working with a half-full tank actually use less energy?
I teach atmospheric physics to our Masters and PhD students and this is precisely the kind of question I would ask them to think about. In fact I sent out an email to all members of the Department, and it turned out that there were different opinions, even amongst those who should know better, although in my view obviously only one physically correct outcome.
So, let us find out. First some theory (some basic thermodynamics), then experiment, and conclusions at the end.
One of the first things we learn in thermodynamics is conservation of energy: energy in equals energy out. The energy in is the electrical power that the urn uses, the energy out is the hot water we consume, heated up from around 15C to around 95C, as well as thermal losses, and running the internal electronics of the urn. The last bit is very marginal, just a controller and a few LEDs. We are going to ignore that. The thermal loss may well be substantial, but the water tank of the urn is actually quite well insulated with Styrofoam, so who knows.
Given that we drink the same amount of coffee, whether the urn is in ECO mode or not, the energy cost for producing the hot water does not depend on whether we run at half tank capacity or full tank capacity. We still need to heat up the same amount of water for our coffee consumption.
What is left is the energy loss. But the energy loss is proportional to the temperature difference between the inside of the tank and the outside. The inside of the tank remains close to 95C all the time, so it looks like the energy loss also cannot depend on whether we are in ECO mode or not.
Energy in equals energy out, energy out remains the same, so energy in should remain the same, ECO mode or not.
Did we miss something? Surely, a feature that is advertised as ECO mode should consume less energy?
We should give the manufacturer some credit. They claim: “This mode saves energy by minimising the energy wasted during machine down-time. The ECO mode is most effective in installations where the machine has a regular ‘off’ period.” Perhaps; perhaps not.
Unfortunately they also claim: “During the ‘off’ period as there is less water in the tank there will be less energy lost to the surrounding environment resulting in an energy saving.” This latter claim is a tricky one: Energy loss is proportional to the temperature difference between the tank and the exterior irrespective of how much water is in the tank. As the heat capacity of the full tank is higher, it will reduce its temperature more slowly, possibly leading to a higher total energy loss, as the temperature differential is kept higher on average for a full tank. So after switching on the urn again, this increased energy loss needs to be topped up. Is that then the way ECO mode helps us being green?
We did what any scientist would do, faced with such a question: do the experiment; this is where Mark comes in. Easy enough: these days you can buy power adaptors that plug in the wall socket and accumulate the total amount of electrical energy used over some period.
We did four experiments: two midweek ones running for three consecutive 24 hour periods from Tuesday to Thursday, two weekend ones running from 6pm on Friday to 9am on Monday. In half of the experiments we left the ECO mode button on, and in the other half, the ECO mode button was left switched off.
Straight to the results:
Midweek (3 days)
Lo and behold: it does not make much difference at all and, if anything, ECO mode uses more energy!
Of course the experiment is not carefully controlled: perhaps we drank more coffee during the ECO mode periods, but both weeks were pretty similar in coffee room usage, there were no big events, and the two weekends were pretty much completely quiet. In fact the weekend usage is probably dominated by the usage before 9am on a Monday. We have cleaners that come in very early, and there are quite a few members of staff that come in before nine in the morning, and perhaps even some PhD students!
Let’s do some more analysis of the data: daily normal usage is about 7KWh per day, as in the midweek data. That means that from the 4.1KWh weekend usage less than about 1KWh (about one seventh of a normal day’s usage to account for the Monday am usage – I know it is a rough estimate) corresponds to normal usage, and the rest is energy loss when the urn is switched on but not used. I estimate the loss to be 1.7KWh per day, so that a weekend, including the Monday early rush hour, corresponds to about 3.4KWh losses and about 0.7KWh normal usage.
So, from the 7KWh daily energy usage, about 1.7KWh is thermal energy loss (and other bits and bobs, such as the lovely LEDs at the front of the urn), with an error bar, I guess, of possibly 30%. Is this a lot of energy loss? 1.7KWh per day corresponds to 70W loss, about the same as the lighting of a single-person office. Not bad. The Marco Ecoboiler is probably pretty “eco”, but not because of its ECO mode.
We are then left with 5.3KWh each day to make coffee. A coffee cup is about 200ml, and assuming the water for the coffee needs heating from 15C to 95C, each cup of coffee requires 0.2kg x 80K x 4200 J/kg/K = 67KJ of energy, or 0.019KWh. That means that 5.3KWh corresponds to about 280 cups of coffee per day. Probably quite realistic, given the size of our Department.
Should we switch off the urn overnight? Well, an overnight period (all losses, as there is no usage of the urn, perhaps for about 11 hours) would use about 0.8KWh. But, of course, the tank will have cooled down, perhaps to 30C, and needs reheating to 95C. This costs for a 10 litre tank about 0.8KWh. Funny that is: probably better to just leave the tank on overnight to prevent people from using highly inefficient kitchen kettles, and prevent people from having to wait for the urn to heat up in the morning.
Actually, this is not as much coincidence as it may seem: the thermal loss during the night switch off period must of course equal the loss in thermal energy of the water, which then needs to be replenished when we reheat the water back to 95C.
As I said before, the full tank could well lose more energy as it keeps relatively warmer during the cooling off period compared to the half full tank of ECO mode. But a quick calculation, assuming a well-insulated tank, shows that the temperature reduction is proportional to (T0-Te) / k with T0 the initial tank temperature (95C), Te the external temperature, and k the heat capacity of the tank. So, indeed, a full tank, with larger k, has a smaller temperature reduction with time, and remains warmer on average. But the energy cost of this reduction of course equals the heat capacity k times the change in temperature: k x (T0-Te) / k = (T0-Te), so we get an energy loss proportional to (T0-Te), but independent of the heat capacity k of the tank. It looks like the engineers at the manufacturers overlooked some basic physics.
By the way: how long would it take to reheat the tank in the morning if it had cooled down to 30C overnight? Well, at full pelt the urn uses 2.8KW, so a required energy of 0.8KWh takes about 15 minutes to produce. Pretty long wait. Probably not worth the frustration.
So, to conclude: our Ecoboiler is quite “eco”: it wastes only about 70W in thermal losses, not so bad for a Department that uses big computing resources (not so “eco”).
The thermal energy losses from the urn are pretty modest in the grand scheme of things, and it turns out to be better to just leave the urn on overnight, as the cost of reheating the cold urn in the morning is nearly the same as the energy cost of leaving it on. Leaving the urn on over the weekend is probably also better than switching off, because the occasional weekend user will end up using a highly inefficient kitchen kettle.
The “ECO mode” button makes the urn operate at half tank capacity, but the thermodynamical arguments as well as the measurements show that it actually uses at least the same amount of energy in ECO mode. In fact, at half capacity the tank has more steam in it, and the steam is possibly slightly hotter, on average, than the liquid, and thus more energy may be lost through conduction. Just leave the ECO mode button switched off; it doesn’t do any good.
**Scroll to the bottom for picture of a bearded dragon.**
A full-time PhD is not always what you see yourself doing. Perhaps you don’t like the idea of being an academic, going through the realities of post-doc life, and battling for the few research roles out there. Maybe you want to get a job in industry, but keep your hand in the research pool. Maybe you have other commitments, meaning that your time is limited but you want to still learn and build your research skills. Whatever the reason, there is always an option to go part-time.
After doing a year and a bit full-time, I knew I wanted to work outside of academia in something more practical than an office-based PhD. Wanting to make use of the work I’d already started, myself, my supervisors and my funders agreed that a part-time MPhil gave the outcomes that all parties wanted. It means I can finish my studies sooner and have something tangible for the years of study, but it also provides new research into my topic that can be used by subsequent researchers.
But how to broach the subject in the first place? You need to take a bit of time to look at the reasons why you want to change, but not so long that you end up regretting never actually saying how you’re feeling at least. It’s really important at this stage that you assess your options, and think about the practicalities, like how it will affect your funding.
It is important to work out how your new schedule will fit together. Part-time doesn’t mean a few hours a week, it means half of what a full-time PhD student would do. With my hours, it means I do 12 hours a week and then work during school holidays. Realistically I won’t get much time off, but it is workable into a roughly 8-6 schedule. It’s important to keep your weekends as free as possible, because social time will help keen you sane!
And in terms of touching base with your supervisor, for me that means coming in once a fortnight, and keeping a record of everything I’ve been up to each day, so I know exactly where I am on my project objectives. You and your supervisor need to be realistic about how much you can complete in a given time, and that your work won’t happen as quickly, so regulating expectations is important. And if things aren’t working, then it’s important to look at them again, perhaps with the help of your Monitoring Committee, to keep you on top of your work.
It’s also important to learn to say no – anyone who knows me knows I struggle with this! People might be under the impression that you have more time to take on other stuff now that you’re part-time, but you have to know what you can make time for in your schedule (like writing a short blog), what might bring other benefits (little bit of open day volunteering), and what really isn’t your problem to worry about!
Having gone part-time, a lot of the stresses seem to have relaxed; it’s nice to not feel like the PhD is all-consuming, and I’m finding it easier to manage my targets each fortnight. If anything, knowing I only have a limited window for work seems to increase productivity! And my job as a lab technician now means I’m gaining a whole other range of skills, can leave that work at work, and make friends with a whole host of school reptiles!