The Greatest Storm – A Virtual Pantomime

Devon Francis d.francis@pgr.reading.ac.uk
Max Coleman m.r.coleman@pgr.reading.ac.uk

Every year the Met-PhDs put on a Christmas pantomime and perform it to the rest of the department. The autumn term always seems to drag: the mornings are dark; the evenings are darker; and no matter how hard you try, the term just feels so busy! So what better way to finish off the term than with department jokes, terrible singing and unnecessary Benny Hill chase scenes?

Met Panto 2020 virtual group photo

And despite of a global pandemic that is in full swing, this year would be no different – the show must go on! On 10th December we premiered the very first virtual Met panto: The Greatest Storm! – A spin-off of the 2017 film ‘The Greatest Showman’. The Greatest Storm follows Professor Sue Gray Barnum (or PG Barnum for short) on her journey to find the greatest storm. On her way she meets her “misfit” team: Helen Dacre, Pete Inness, Tom Frame and Javier Amezcua, and recruits her right-hand man: Philip-Craig Carlyle. Together they develop a new instrument: DOROTHY, the Data recORding unit fOr in-siTu sting jet measurements High in the skY. But with COVID lurking around every corner, will they ever be able to measure the Greatest Storm? (…although it will actually just be the greatest storm on record…)

Panto 2020 poster – designed and created by Meg Stretton

This year, Max and I were persuaded volunteered for the role of panto organisers, with the promise that running the panto would be ‘much easier’ than previous years as everything would be online. This was partly true, though there was still a lot of last-minute tweaking…

We were very fortunate that Kris Boykin brought forward the idea to recreate The Greatest Showman, with a detailed plan for the plot, which fought off the other (very good) competition for plot ideas. This made the script writing relatively pain-free as we filled in the details and decided on which of the staff should be included.

Next was the song writing: in retrospect, the songs we chose were quite difficult to get right, as it was challenging to stay in time when singing for most of them, especially when we had changed the lyrics to include meteorological puns! In a live panto this might not have been so bad, but as everything had to be recorded individually and put together by our audio editing experts Dominic Jones and Beth Saunders, we can only say, Dom, we’re very sorry…  

The next 9 weeks were filled with read throughs, character selection and filming. In a normal year, these weeks would be relatively relaxed, with rehearsals spanning the full 9 weeks, however as we were aware that the video editors Lauren James and Wilson Chan had a lot of work to do in putting all of the scenes together, we tried to film as early as possible to give them more time. Our initial plan was to meet up on a weekend to film the parts in a socially distanced setting, but as the second lockdown was announced, we had to quickly change our plan. Some scenes were filmed individually, but the majority were filmed over Zoom: although this had reduced camera quality, it was much more fun to see each other every week and laugh at everyone’s wacky costumes and improvisation!

The last week leading up to Thursday’s showing (tomorrow as we’re writing this!) was slightly busier, with reviewing footage and making final edits, in the knowledge that in these unprecedented circumstances most of the cast will not have seen a complete run through before the final showing! In the end it all came together with an entirely smooth and seamless virtual viewing experience / it all went horribly wrong and we should never have been entrusted with panto (delete as applicable), which everyone viewing hopefully enjoyed!

Screenshot of scene 2 – the misfits’ entrance.

With that, we’d like to say thank you so much to everyone involved, from script writers, band, editors, cast and everyone that helped both on and off our virtual stage! It has been so lovely to see everyone come together, and although has been a very tiring process, panto 2020 has been a very welcome distraction to the rest of 2020!

This year we did not sell tickets, but instead asked for donations to cover our (reasonably small!) running costs, plus any extra will go to the Reading Meteorology department’s charity: San Francisco Libre Association. If you didn’t donate on the night, but wanted to, here’s a link to our donations page – https://paypal.me/pools/c/8uIzsVEQwB. We were so humbled by everyone that has already donated, both small and large amounts, we really appreciate it!

Thank you to everyone that watched The Greatest Storm on Thursday, we hope you had a fun evening! And we look forward to next year’s panto; who will be next to volunteer for this incredible tradition, with panto 2021…?

Demonstrating as a PhD student in unprecedented times

Brian Lo – brian.lo@pgr.reading.ac.uk 

Just over a month ago in September 2020, I started my journey as a PhD student. Since then, have I spent all of my working hours solely on research – plotting radar scans of heavy rainfall events and coding up algorithms to analyse the evolution of convective cells?  Surely not! Outside my research work, I have also taken on the role of demonstrating this academic year. 

What is demonstrating? In the department, PhD students can sign up to facilitate the running of tutorials and problems, synoptic, instrument, and computing laboratory classes. Equipped with a background in Physics and having taken modules as an MSc student at the department in the previous academic year, I signed up to run problem classes for this year’s Atmospheric Physics MSc module. 

I have observed quite a few lectures during my undergraduate education at Cambridge, MSc programme at Reading and also a few Massive Open Online Courses (MOOCs) as a student. Each had their unique mode of teaching. At Cambridge, equations were often presented on a physical blackboard in lectures, with problem sheet questions handed in 24 hours before each weekly one-hour “supervision” session as formative assessment. At Reading, there have been less students in each lecture, accompanied by problem classes that are longer and more relaxed, allowing for more informal discussion on problem sheet questions between students. These different forms of teaching were engaging to me in their own ways. I have also given a mix of good and not-as-good tutorial sessions for Year 7s to 13s. Good tutorials included interactive demonstrations, such as exploring parametric equations on an online graphing calculator, whereas the not-as-good ones had content that were pitched at too high of a level. Based on these experiences and having demonstrated for 10 hours, I hopefully can share some tips on demonstrating through describing what one would call a “typical” 9am Atmospheric Physics virtual problems class. 

PhD Demonstrating 101 

You, a PhD student, have just been allocated the role as demonstrator on Campus Jobs and are excited about the £14.83 per hour pay. With the first problems class happening in just a week’s time, you start thinking about tools you will need to give these MSc students the best learning experience. A pencil, paper, calculator and that handy Thermal Physics of the Atmosphere textbook would certainly suffice for face-to-face classes. The only difference this year: You will be running virtual classes! This means that moist-adiabatic lapse rate equation you have quickly scribbled down on paper may not show well on a pixelated video call due to a “poor (connection) experience” from Blackboard. How are you going to prevent this familiar situation from happening? 

Figure 1: Laptop with an iPad with a virtual whiteboard for illustrating diagrams and equations to be shown on Blackboard Collaborate. 

In my toolbox, I have an iPad and an Apple pencil for me to draw diagrams and write equations. The laptop’s screen is linked to the iPad with Google Jamboard running and could be shared on Blackboard Collaborate. Here I offer my first tip: 

  1. Explore tools available to design workflows for content delivery and decide on one that works well 

Days before the problems class, you wonder whether you have done enough preparation. Have you read through and completed the problem sheet; ready to answer those burning questions from the students you will be demonstrating for? It is important you… 

Figure 2: Snippet of type-written worked solutions for the Atmospheric Physics MSc module. 

  1. Have your worked solutions to refer to during class 

A good way to ensure you are able to resolve queries about problem sheet questions is to have a version of your own working. This could be as simple as some written out points, or in my case, fully type-written solutions, just so I have details of each step on hand. In some of my fully worked solutions, I added comments for steps where I found the learning curve was quite steep and annotated places where students may run into potential problems. 

Students seem to take interest in these worked solutions, but here I must recommend… 

  1. Do not send out or show your entire worked solutions 

It is arguable whether worked solutions will help students who have attempted all problems seriously, but the bigger issue lies in those who have not even given the problems a try. As a demonstrator, I often explain the importance of struggling through the multiple steps needed to solve and understand a physics problem. My worked solutions usually present what I consider to be the quick and more refined way to the numerical solution, but usually are not the most intuitive route. On that note, how then are you supposed to help someone stuck on a problem? 

It may be tempting to show snippets of your solutions to help someone stuck on a certain part of a problem. Unfortunately, I found this did not work very well. Students can end up disregarding their own attempt and copy down what they regard as the “model answer”. (A cheeky student would have taken multiple screenshots while I scrolled through my worked solutions on the shared screen…) What I found worked better in breakout groups was for the student(s) to explain how they got stuck.  

For example, I once had a few students ask me how they should work out the boiling temperature from saturated vapour pressure using Tetens’ formula. However, my worked solutions solved this directly using the Clausius-Clapeyron equation. Instead of showing them my answer, I arrived at the point where they got stuck (red in Figure 3), essentially putting myself in their shoes. From that point, I was able to give small hints in the correct direction. Using their method, we worked together towards a solution for the problem (black in Figure 3). Here is another tip: 

  1. Work through the problem from your students’ perspective 

Figure 3: Google Jamboard slide showing how Tetens’ formula is rearranged. Red shows where some students got up to in the question, whereas black is further working to reach a solution. 

This again illustrates the point on there being no “model answer”. As in many scientific fields, there exist multiple path functions that get you from a problem to a plausible solution, and the preference for such a path is unique to us all. 

There will always be a group of diligent students who gave the problem sheet a serious attempt prior to the class. You will find they only take less than 30 minutes to check their understanding and numerical solutions with you, and they might do their own thing afterwards. This is the perfect opportunity to… 

  1. Present bonus material to stretch students further 

Some ideas include asking for a physical interpretation from their mathematical result, or looking for other (potentially more efficient) methods of deriving their result. For example, I asked students to deduce a cycle describing the Stirling engine on a TS diagram, instead of the pV diagram they had already drawn out as asked by the problem sheet.  

Figure 4: A spreadsheet showing the content coverage of each past exam question 

I also have a table of past exam questions, with traffic light colours indicating which parts of the syllabus they cover. If a student would like to familiarise themselves with the exam style, I could recommend one or two questions using this spreadsheet. 

On the other hand, there may be the occasional group who have no idea where equation (9.11) on page 168 of the notes came from, or a student who would like the extra-reassurance of more mathematical help on a certain problem. As a final tip, I try to cater to these extra requests by… 

  1. Staying a little longer to answer a final few questions 

The best demonstrators are approachable, and go the extra mile to cater to the needs of the whole range of students they teach, with an understanding of their perspectives. After all, being a demonstrator is not only about students’ learning from teaching, but also your learning by teaching! 

I would welcome your ideas about demonstrating as a PhD. Feel free to contact me at brian.lo@pgr.reading.ac.uk if you would like to discuss! 

Visiting Scientist Week Preview: Laure Zanna

Kaja Milczewska – k.m.milczewska@pgr.reading.ac.uk

As per annual tradition in the Meteorology Department, PhD students have chosen a distinguished scientist to visit the department for one week. Previous years’ visitors include Prof. Tapio Schneider (Caltech), Prof. Olivia Romppainmen-Martius (University of Bern), and Prof. Cecilia Bitz (University of Washington). This year’s winning vote was New York University’s Prof. Laure Zanna, who will be visiting the department virtually1 between 2 – 6th November. 

Laure is an oceanographer and climate scientist whose career so far has spanned three continents, won her an American Meteorological Society (AMS) Early Careers’ award for “exceptionally creative” science this year, and netted her 600 citations in the last two years.  Her research interests encompass ocean turbulence, climate dynamics, predictability, machine learning and more. Some of the many topics of her published papers include the uncertainty in projections of ocean heat uptake; ocean turbulence parametrisations; predictions of seasonal to decadal sea surface temperatures in the Atlantic using simple statistical models and machine learning to inform prediction of extreme events. Besides being an exceptional scientist, speaker and educator, Laure is a down-to-Earth and friendly person, described by the Climate Scientists podcast’s Dan Jones as ‘a really great person who helps to tie the whole community together’.

As someone who had received their PhD only just over a decade ago, we thought Laure would be the perfect candidate to inspire us and our science through sharing some of her academic experiences with us. Before her visit next week, Laure kindly answered some interview-style questions for this week’s Social Metwork blog post.

Q: What inspired you to research oceanography and climate in the first place?

A: I always enjoyed math and physics. The possibility of using these disciplines to study scientific problems that I could “see” was very appealing.

Q: Why were you drawn to machine learning?

A: The power of machine learning (ML) to advance fields such as natural processing language or computer science is indisputable. I was excited by the premise of ML for climate science. In particular, can ML help deepen our understanding of certain aspects of the climate systems (e.g. interactions between scales or interactions between the ocean and atmosphere)? Can ML improve the representation of small-scale processes in climate models? ML, by itself, is not enough but combined with our physical understanding of the climate system could push the field forward.

Q: Can you give us an idea of what’s the most exciting research you are working on right now?

A: This is impossible. I work on 2 main areas of research right now: understanding and parameterizing ocean mesoscale eddies and understanding the role of the oceans in climate. I am passionate and excited about both topics. Hopefully, you will hear about both of them during the week.

Q: When did you realise/decide you were going to remain in academia?

A: I decided that I wanted to try and stay in academia in the last year of my PhD.  I was lucky enough to be able to.

Q: What is your favourite part of your job?

A: Working with my group!  The students and postdocs in the group have different expertise but all are passionate about their research. They make the work and the research more fun, more challenging, and more inspiring.

We are honoured to have our invitation accepted by Laure and are eagerly anticipating answers to more of these kind of questions throughout next week’s conversations.  Laure will be presenting a seminar titled, “Machine learning for physics-discovery and climate modelling” during the Monday Departmental Seminar series, as well as another seminar in the Climate and Ocean Dynamics research group, titled “Understanding past and future ocean warming”. She will also give a career-focused session at PhD group and, of course, engage with both the PhD students and staff on an individual basis during one-to-one meetings. We are grateful and delighted to be able to welcome Laure to the Meteorology department despite the various difficulties the year 2020 has posed on everyone, so come along to next week’s events!


1In true 2020 curve-ball style, of course.

Explaining complicated things with simple words: Simple writer challenge

Email: l.toca@pgr.reading.ac.uk & m.r.coleman@pgr.reading.ac.uk

A challenge most researchers will be familiar with is how do you explain your research to friends and family in a way that’s readily understandable to non-experts? The web comic xkcd decided to try describing the Saturn-V moon rocket (‘Up Goer Five’) using only the ten-hundred most commonly used words.

Feeling that we needed something a bit different during the Covid-19 lockdown, and inspired by our predecessors in a previous blog post, we decided to have a go at explaining our own research using the xkcd ‘simplewriter’ tool in our weekly PhD group meeting. While restricting yourself to only the ten-hundred most commonly used words seemed to make things more confusing at times, it certainly gets one thinking about what complicated words don’t need to be used… and results in some amusing explanations!

A screenshot of the xkcd “Simple Writer” tool

Devon FrancisAdvanced methods for assimilating satellite data in numerical weather prediction

When we find out how hot or cold it is outside, sometimes it is not right as sometimes it can be too hot and sometimes it can be too cold. If over lots of time it is more often hot than it is cold, or the other way around, then we have to move how much warmer we have found it to be so that we can write down how warm it actually is. We can also imagine how hot or cold it will be by thinking about how hot or cold it has been before, or how hot or cold it is on a day that is like today. But if it was hotter before but we did not notice, then we may think it is also hotter today, so we may need to change what we thought about before as well as what we think about today. Sometimes it is hard to work out why we are wrong about how warm it is today. It could be because we can not decide how warm it is or it could be because it has been too hot or cold in the past. My job is to decide why we think it is too hot or cold, so that tomorrow we can know how warm it will be!

Linda van GarderenClimate change detection and attribution of extreme events

I look at the warming of the sky, and see if that is different from what the sky was like before it was warming. The cool thing is, that we only look at those moments where the sky was attacking us. With us we are talking about humans on the ground. Any form of attack such as warm, cold, strong wind and rain is a thing. I do this by telling a story. The story helps in finding what made the attack happen, if it was the warming of the sky or maybe something else.

Max ColemanClimate response to short-lived pollutants

In the air are very small things that can hurt us if we breathe them in. However, these things can also change how warm the Earth is by catching light or sending it back to space, and also change how much it rains by changing how much cloud there is in the sky. If humans make more of these things then we will change how warm the Earth is. I study how these small things change how much cloud there is and other things, which in turn change how much light is caught or sent back to space. I do this using a computer which can pretend to be the Earth and works out how much light is caught or sent back to space by changing these things.

Mark ProsserUsing aviation meteorology to improve aircraft safety

My finish-big-school work piece is about crazy wind and sky high-lighting causing problems for flying buses. Crazy wind is already a problem for flying buses which we think will get worse with the Earth hotter than it is now (it is already hotter than before). Didn’t-see-it-coming crazy wind is especially a problem for flying buses because you can’t see into the future. So we brain people use things that big brain animals use on computer brain best guesses, but these aren’t perfect. My work piece is saying good or bad about these things by putting them on real flying buses meeting didn’t-see-coming crazy wind (things really go wrong when these two meet). Day to day I pull down guesses from big computer brain and use not friend long toothy animal to eat these guesses. Right now I am writing up a paper using over leaf and hope it will be put on many bits of paper and seen by some other brain people and liked and talked about.

Jake BlandThe control of cloud and moisture on extratropical cyclone evolution

People use computers to tell them if there will be rain, sun, clouds, or storms in the future, and if it will be hot or cold. To be right about these things the computers need to know about how hot the sky is and how much water is in it, among other things. We get this information by looking with machines on earth, putting machines into the sky, or putting machines in space and telling them to look down at the sky.

You can think of the sky as being in layers, where we are in the lowest layer, and that is where most of our clouds are too. The layer above that is drier, changes less and changes more slowly, but the water in there is still important for being right about the future. It is harder to look at the water in the higher layer than it is to look at how hot it is, or the water in the lower layer, so computers often think there is too much water there. They also think it will be colder up there in the future than it really will be.

I have worked out how wrong computers are about how wet it is and how cold it will be using guesses made four years ago, and machines that were thrown into the sky to look at the same times that were guessed about. (I’m now finishing off writing about this so other people can know about it too!) I have also looked at how the computer being wrong about water and wrong about how cold it is in the future are tied together.

Now I have made a lot of future guesses about those days four years ago, some where the computers have the wrong information like they did before, and some where they have the better information. I am also getting the computer to tell me how it is making the guesses, so I can try to find out what it is wrong with the computer to make it think the higher sky layer is too wet. Using these two sets of guesses I can also find out exactly how important getting how wet it is right for telling the future well.

Linda  TocaAnalysis of peatland carbon dynamics using combined optical and microwave satellite data

I study very important wet places and the tiny parts they breath in and out. Most of the time I use space pictures and computer to come up with something to show, but later I plan to go outside to the wet places and see in person how much tiny parts they breath out, and check if it is the same as computer says. I also want to use small flying thing that can make more pictures of wet places from above to see if they can help computer work better. It is very important as the wet places hold huge numbers of tiny parts and we need to know what could happen in the further times with air getting hotter and dry times longer. Do the wet places give much more tiny parts with hotter air and is it enough with space pictures to tell how much, that is what we want to find out.

Wilfred Calder-PottsQuantifying the impact of increased atmospheric CO2 and climate change on photosynthesis using Solar Induced Fluorescence

When trees accept light they make food. They also make their own light. If you see this light you can guess how much food they are making. Some people have built machines to see this light from space. But we are not sure exactly how much food they are making. I am trying to understand exactly how much food is made, using the light. I am doing this by seeing this light from trees which are hot or cold or have more or less bits of food.

Tips for working from home as a PhD student

As PhD students, working from home is an option for many of us on a “normal” day – as indeed is increasingly the case with jobs which primarily need just an Internet connection. But, thanks to COVID-19, working from home (WFH) is our new collective reality. So how can we make this work well, when for many, our offices may only now be a few steps away from our beds? We asked around for advice on this matter from current PhD students.

Remember to take a break every half an hour or so. Go away from the desk!

It can be easy to forget to take a break when you’re “at home”, even if you’re also “at work”, and especially when you’re likely closer to the kettle/food/toilet than you would be otherwise. Get up, move around!

Stick to a regular schedule: when you wake up, go to sleep, work, relax, etc.

This is great advice for doing a PhD in general, but even more pertinent now that our routines have been turned upside down.

Pretend that you “go to and from work”, i.e take a morning and afternoon walk/cycle to mark the start and end of your work day.

A commute can be a great time to wake up in the morning and wind down in the evening. Get creative with what you can (safely, and in accordance with government guidance) do to replace your commute during this time.

Pretend that you go to work by dressing accordingly, it makes the brain active and makes you stronger against the ‘do something else’  or ‘ relax’ mode activated by the comfy at home clothes.

It’s tempting to work wearing pyjamas, but will this help your productivity and mindset? Getting dressed for work can also help to maintain your work-life balance.

Look after your posture. If possible, sit at a desk with a screen at the right height. 

Try to follow standard health and safety advice when it comes to working long hours at a desk. If possible, invest time and money in making your home working environment a comfortable and non-straining place to be.

If you can at all help it, don’t work in the room where you sleep. It can cause difficulties sleeping.

This also helps add some breaks and changes in your day, which can help to maintain focus and motivation.

Enjoy the benefits of working from home: take a break to actually cook lunch, get things done around the house. Let yourself appreciate the things that are handy about it as well as the negatives. 

Being able to get away from your work and do something like ironing, cooking, baking or cleaning might actually help your productivity and concentration by providing a better break than you might otherwise get in an office. Embrace it!

Schedule social e-contact. Don’t let yourself go more than a day without at least hearing someone’s voice on the phone. Use the opportunity to reconnect with old friends. 

In Reading, we’re making extensive use of Microsoft Teams to remain in contact with each other and try to mimic our vibrant work atmosphere.

Do (as long as it’s safe to do so) go for walks, head outside, make sure you do some exercise twice a week. 

Luckily, we’ve got some very nice weather this week in most of the UK. But do please adhere to social distancing guidelines when you do go outside.

It can be easy for the lines between work and life outside of work to be blurred during a PhD at the best of times, and WFH can make this more problematic. Set your hours, and stick to it.

If you work 8-4, work 8-4! At 4pm, switch your computer off and do something different. Without an evening commute, it can be trickier to bring an end to your working day, but this is probably one of the most important things to maintain.

Most operating systems, including Windows 10, support multiple virtual desktops. Try using one of those for your virtual “work” PC, and another as your virtual “home” PC. Then you can keep the two segregated. 

At the end of the day you can switch to your “home” desktop, and then return to “work” the following day.

This Twitter thread has some great advice: https://twitter.com/ProfAishaAhmad/status/1240284544667996163?s=19

Twitter is of course full of great (and not so great) advice. It can keep people connected but also increase anxiety. Be cautious with it, along with all social media during this time.

Allow yourself ample time to adjust, get the important things in order first (friends/family/food/fitness), and build a regular schedule.

This is a huge change. It’s not just a huge change to work, it’s a huge change to our entire lives. Go easy on yourself as you get into the swing of things.

Fill the space around you with plants – it’ll make you feel like you’re outside if you don’t have that luxury – and open your windows every morning (you’ll appreciate the fresh air!) 

Nature is very calming. Open the window, listen to the birds (you might hear them more than you used to nowadays).

Extending our best wishes to all from everyone in Reading Meteorology during this challenging time.

2019 on The Social Metwork

It’s been quite a busy and successful year here on The Social Metwork, and my first full calendar year as Editor after taking over in October 2018. We’ve had some great contributions on all sorts of topics, from published research to summer schools, conferences, and PhD tips. I’d like to extend my thanks and praise to everyone who has contributed a post or reviewed a submission this year – thank you for taking the time out from your busy PhD life! To those of you who have since finished your PhD, congratulations and all the best for the future. I’d also like to thank everyone who visited the site from around the world (over 5000 of you) and read our blog posts – you’re the reason we do this! – Simon, Editor.

To wrap up 2019, here is a list of all this year’s 32 posts, in case you missed any.

AMS Annual Meeting 2019 – Lewis Blunn

My tips, strategies and hacks as a PhD student – Mark Prosser

Going Part-time… – Rebecca Couchman-Crook

Quantifying the skill of convection-permitting ensemble forecasts for the sea-breeze occurrence – Carlo Cafaro

Is our “ECO mode” hot water boiler eco-friendly? – Mark Prosser

Evaluating aerosol forecasts in London – Elliott Warren

APPLICATE General Assembly and Early Career Science event – Sally Woodhouse

The Circumglobal Teleconnection and its Links to Seasonal Forecast Skill for the European Summer – Jonathan Beverley

Extending the predictability of flood hazard at the global scale – Rebecca Emerton

On relocating to the Met Office for five weeks of my PhD – Kaja Milczewska

Workshop on Predictability, dynamics and applications research using the TIGGE and S2S ensembles – Simon Lee

Representing the organization of convection in climate models – Mark Muetzelfeldt

EGU 2019 – Bethan Harris and Sally Woodhouse

Investigating the use of early satellite data to test historical reconstructions of sea surface temperature – Thomas Hall

Island convection and its many shapes and forms: a closer look at cloud trails – Michael Johnston

PhD Visiting Scientist 2019: Prof. Cecilia Blitz – Rebecca Frew

Met Department Summer BBQ 2019 – Mark Prosser

Simulating measurements from the ISMAR radiometer using a new light scattering approximation – Karina McCusker

RMetS Student and Early Career Scientists Conference 2019 – Dom Jones

The 2nd ICTP Summer School in Hierarchical Modelling of Climate Dynamics – Kieran Pope

The 27th General Assembly of the International Union of Geodesy and Geophysics (IUGG) in Montreal, Canada – Tsz Yan (Adrian) Leung

The Colour of Climate – Jake Gristey

Fluid Dynamics of Sustainability and the Environment Summer School – Mark Prosser

SWIFT and YESS International Summer School, Kumasi, Ghana – Alex Doyle

Wisdom from experience: advice for new PhD students – Simon Lee and Sally Woodhouse

On relocating to Oklahoma for 3.5 months – Simon Lee

Characterising the seasonal and geographical variability in tropospheric ozone, stratospheric influence and recent changes – Ryan Williams

Combining multiple streams of environmental data into a soil moisture dataset – Amsale Ejigu

How much energy is available in a moist atmosphere? – Bethan Harris

The Variation of Geomagnetic Storm Duration with Intensity – Carl Haines

The impact of atmospheric model resolution on the Arctic – Sally Woodhouse

Sudden Stratospheric Warming does not always equal Sudden Snow Shoveling – Simon Lee

On relocating to Oklahoma for 3.5 months

Email: s.h.lee@pgr.reading.ac.uk

From May 4th through August 10th 2019, I relocated to Norman, Oklahoma, where I worked in the School of Meteorology in the National Weather Center (NWC) at the University of Oklahoma (OU). I’m co-supervised by Jason Furtado at OU, and part of my SCENARIO-funded project plan involves visiting OU each summer to work with Dr. Furtado’s research group, while using my time in the U.S. to visit relavant academics and conferences. Prior to my PhD, I studied Reading’s MMet Meteorology and Climate with a Year in Oklahoma degree, and spent 9 months at OU as part of that – so it’s a very familiar place! The two departments have a long-standing link, but this is the first time there has been PhD-supervision collaboration.

The National Weather Center in Norman, Oklahoma – home to the School of Meteorology.

The National Weather Center (NWC) [first conceived publicly in a 1999 speech by President Bill Clinton in the aftermath of the Bridge Creek-Moore tornado] opened in 2006 and is a vastly bigger building than Reading Meteorology! Alongside the School of Meteorology (SoM), it houses the Oklahoma Mesonet, the NOAA Storm Prediction Center (SPC) (who are responsible for operational severe weather and fire forecasting in the U.S.) and the NOAA National Severe Storms Laboratory (NSSL). SPC and NSSL will be familiar to any of you who have seen the 1996 film Twister. You could think of it as somewhat like a smaller version of the Reading Meteorology department being housed in the Met Office HQ in Exeter.

Inside the NWC.

The research done at SoM is mostly focussed on mesoscale dynamics, including tornadogenesis, thanks to its location right at the heart of ‘tornado alley’. It’s by no means a typical haunt of someone who researches stratosphere dynamics like I do, but SoM has broadened its focus in recent years with the inception of the Applied Climate Dynamics research group of which I’m a part. Aside from the numerous benefits of being able to speak face-to-face with a supervisor who is otherwise stuck on a TV screen on Skype, I also learnt new skills and new ways of thinking – purely from being at a different institution in a different country. I also used this time to work on the impact of the stratosphere on North America (a paper from this work is currently in review).

I also visited the NOAA Earth System Research Laboratory (ESRL) in Boulder, Colorado to present some of my work, and collaborate on some papers with scientists there. Boulder is an amazing place, and I highly recommend going and hiking up into the mountains if you can (see also this 2018 blog post from Jon Beverley on his visit to Boulder).

As for leisure… I chose to take 2 weeks holiday in late May to, let’s say, do “outdoor atmospheric exploration“. This happened to coincide with the peak of one of the most active tornado seasons in recent years, and I just so happened to see plenty of them. I’m still working on whether or not the stratosphere played a role in the weather patterns responsible for the outbreak!

An EF2-rated wedge tornado on 23 May near Canadian, Texas.

Wisdom from experience: advice for new PhD students

The new academic year is now underway, and a new bunch of eager first year PhD students are dipping their toes into a three-to-four year journey to their doctorate. So, we’ve collated some advice from the more experienced among us! The idea behind the following tidbits of advice is that they are things we would tell our younger selves if we could go back to day 1…

Work

“Make sure you and your supervisor set out expectations and at least a vague timeline at the start, that way you will know you’re on track.”

“Write code as if you’re giving it to someone else – one day you might have to.”

Even if you don’t give your code to another use, in a year’s time you’ll have forgotten what it does! Related to this, it’s useful to keep good “readme” documents to note where all your code is, how to run things, etcetera. Also, if you think you’re going to present a plot at some point – in a talk, paper, or even your thesis, make a final version at the time (using appropriately accessible colour maps and big enough labels), plus note down where you’ve stored the code you used to make it.

“Learn and use git/github (or at least get familiar with the 3 basic commands of: git add, commit, push) ASAP! This means that if you take a wrong turn in your code (you will), you can painlessly ‘revert’ to a stage before you made a mess.”

“Read papers with your literature review in mind. If you can’t see where the paper will fit in your literature review, either reconsider your literature review… or find a more relevant paper.”

“Write down everything you learn, or facts you are told – you never know when you’ll need a piece of information again.”

But also be prepared to have not really followed any of this advice properly until you regurgitate it to new students in your fourth year and wonder why you haven’t been doing any of it up until now.

“Try to keep up a good routine – it’s much easier to get out of bed when you’re having a slow work week if that’s what your body is used to.”

“You’ll be amazed at how much you’ll learn and master without even realising.”

“Don’t compare yourself to others.”

Every PhD project is unique, as is every student. During a PhD, you’re looking into the unknown. Maybe you’ll get lucky (with some hard work) and have some really interesting results, or it might be a bit of a battle. Some projects are more suited to regular publications, others less so – this doesn’t necessarily reflect your individual abilities. In addition, everyone has different background knowledge and motivation for doing a PhD.

“Not every day has to be maximum productivity, that’s okay!”

“Some days are great, others are rubbish. Like life, really.”

Life

“Make friends with other PhD students. It’s nice to have someone who might make you cake when you feel sad, or happy.”

This is so true. A PhD is quite a unique experience and lots of people don’t really get it, thinking it’s just like another undergrad. Sometimes it’s really useful to have someone who understands the stress of some code just not working, or the dread of a blank page where your monitoring committee report should be. It’s also helpful to get to know people in the years above, or even post-docs, since they’ve probably already gone through what you’re experiencing.

“Make friends and join clubs and societies with people that aren’t doing PhDs.”

Sometimes it’s important to get out of the PhD “bubble” and put things in perspective. Keeping in touch with friends that have “real” jobs (for want of a better word) can be a nice reminder of some of the benefits of PhD life – such as flexible hours (you don’t have to be in before 9 every day) or not having to wear formal business attire.

Wellbeing

“Try to keep your weekends free – it’s great for your sanity!”

“Take holiday! You are expected to.”

“Don’t feel guilty for not cheering up when people tell you everything’s okay. It almost invariably is, but sometimes it all gets a bit much and you’ll feel bad for a while, that’s totally normal!”

Yes, it’s totally okay to have a couple of bad days. Remember, this can often be true of people with ‘real’ jobs, it isn’t just unique to the PhD experience! However, if you’re feeling bad for a long period of time, it’s important to acknowledge that this isn’t okay and you don’t have to feel like that. It might be helpful to let your supervisor know that you’re having a bit of a hard time, for whatever reason, and work might be slow for a while. There are also lots of support systems available. For students at Reading, you can find out more about the Counselling and Wellbeing Service here (http://www.reading.ac.uk/cou/counselling-services-landing.aspx). A PhD is hard work, but it should be a fundamentally enjoyable experience!

Finally:

“No poking your supervisor with a stick. They don’t appreciate it.”

(…no, we don’t get it either)


Co-written by Simon Lee and Sally Woodhouse, with anonymous pieces of advice collected from various PhD students in the Department of Meteorology.