Main challenges for extreme heat risk communication

Chloe Brimicombe – c.r.brimicombe@pgr.reading.ac.uk, @ChloBrim

For my PhD, I research heatwaves and heat stress, with a focus on the African continent. Here I show what the main challenges are for communicating heatwave impacts inspired by a presentation given by Roop Singh of the Red Cross Climate Center at Understanding Risk Forum 2020.  

There is no universal definition of heatwaves 

Having no agreed definition of a heatwave (also known as extreme heat events) is a huge challenge in communicating risk. However, there is a guideline definition by the World Meteorological Organisation and for the UK an agreed definition as of 2019. In simple terms a heatwave is: 

“A period of above average temperatures of 3 or more days in a region’s warm season (i.e. all year in the tropics and in the summer season elsewhere)”  

We then have heat stress which is an impact of heatwaves, and is the killer aspect of heat. Heat stress is: 

“Build-up of body heat as a result of exertion or external environment”(McGregor, 2018) 

Attention Deficit 

Heatwaves receive low attention in comparison to other natural hazards I.e., Flooding, one of the easiest ways to appreciate this attention deficit is through Google search trends. If we compare ‘heat wave’ to ‘flood’ both designated as disaster search types, you can see that a larger proportion of searches over time are for ‘flood’ in comparison to ‘heat wave’.  

Figure 1: Showing ‘Heat waves’ (blue)  vs ‘Flood’ (red) Disaster Search Types interest over time taken from: https://trends.google.com/trends/explore?date=all&q=%2Fm%2F01qw8g,%2Fm%2F0dbtv 

On average flood has 28% search interest which is over 10 times the amount of interest for heat wave. And this is despite Heatwaves being named the deadliest hydro-meteorological hazard from 2015-2019 by the World Meteorological Organization. Attention is important if someone can remember an event and its impacts easily, they can associate this with the likelihood of it happening. This is known as the availability bias and plays a key role in risk perception. 

Lack of Research and Funding 

One impact of the attention deficit on extreme heat risk, is there is not ample research and funding on the topic – it’s very patchy. Let’s consider a keyword search of academic papers for ‘heatwave*’ and ‘flood*’ from Scopus an academic database.  

Figure 2: Number of ‘heatwave*’ vs number of ‘flood*’ academic papers from Scopus. 

Research on floods is over 100 times bigger in quantity than heatwaves. This is like what we find for google searches and the attention deficit, and reveals a research bias amongst these hydro-meteorological hazards. And is mirrored by what my research finds for the UK, much more research on floods in comparison to heatwaves (https://doi.org/10.1016/j.envsci.2020.10.021). Our paper is the first for the UK to assess the barriers, causes and solutions for providing adequate research and policy for heatwaves. The motivation behind the paper came from an assignment I did during my masters focusing on UK heatwave policy, where I began to realise how little we in the UK are prepared for these events, which links up nicely with my PhD. For more information you can see my article and press release on the same topic. 

Heat is an invisible risk 

Figure 3: Meme that sums up not perceiving heat as a risk, in comparison, to storms and flooding.

Heatwaves are not something we can touch and like Climate Change, they are not ‘lickable’ or visible. This makes it incredibly difficult for us to perceive them as a risk. And this is compounded by the attention deficit; in the UK most people see heatwaves as a ‘BBQ summer’ or an opportunity to go wild swimming or go to the beach.  

And that’s really nice, but someone’s granny could be experiencing hospitalising heat stress in a top floor flat as a result of overheating that could result in their death. Or for example signal failures on your railway line as a result of heat could prevent you from getting into work, meaning you lose out on pay. I even know someone who got air lifted from the Lake District in their youth as a result of heat stress.  

 A quote from a BBC one program on wild weather in 2020 sums up overheating in homes nicely:

“It is illegal to leave your dog in a car to overheat in these temperatures in the UK, why is it legal for people to overheat in homes at these temperatures

For Africa the perception amongst many is ‘Africa is hot’ so heatwaves are not a risk, because they are ‘used to exposure’ to high temperatures. First, not all of Africa is always hot, that is in the same realm of thinking as the lyrics of the 1984 Band Aid Single. Second, there is not a lot of evidence, with many global papers missing out Africa due to a lack of data. But, there is research on heatwaves and we have evidence they do raise death rates in Africa (research mostly for the West Sahel, for example Burkina Faso) amongst other impacts including decreased crop yields.  

What’s the solution? 

Talk about heatwaves and their impacts. This sounds really simple, but I’ve noticed a tendency of a proportion of climate scientists to talk about record breaking temperatures and never mention land heatwaves (For example the Royal Institute Christmas Lectures 2020). Some even make a wild leap from temperature straight to flooding, which is just painful for me as a heatwave researcher. 

Figure 4: A schematic of heatwaves researchers and other climate scientists talking about climate change. 

So let’s start by talking about heatwaves, heat stress and their impacts.  

Air-sea heat fluxes at the oceanic mesoscale: the impact of the ratio of ocean-to-atmosphere grid resolution

Sophia Moreton – s.moreton@pgr.reading.ac.uk

Sea surface temperature (SST) anomalies are vital for regulating the earth’s weather and climate.  The generation and reduction of these SST anomalies are largely determined by air-sea heat fluxes, particularly turbulent heat fluxes (latent and sensible).

The turbulent heat flux feedback (THFF) is a critical parameter, which measures the change in the net air-sea turbulent heat flux in response to a 1 K change in SST. So far in current research, this feedback is well known at large scales, i.e. over the whole ocean basin. However, a quantification of this feedback at much smaller spatial scales (10-100km) over individual mesoscale ocean eddies remains absent.

Why do we care about air-sea feedbacks at the oceanic mesoscale?

Both heat and momentum air-sea exchanges at the mesoscale impact the local and large-scale atmosphere (e.g. shifting storm tracks) and alter the strength of western boundary currents and the large-scale ocean gyre circulation. However, research into this field to date is hindered by the lack of high spatial resolution in observational data at the air-sea interface.

Therefore our study uses three high-resolution configurations from the UK Met Office coupled climate model (HadGEM3-GC3). We provide the first global estimate of turbulent heat flux feedback (α) over individually tracked and composite-averaged coherent mesoscale eddies, which ranges between 35 to 45 Wm-2K-1 depending on eddy amplitude.

Estimates of the turbulent heat flux feedback (THFF) are split, depending if the feedback is calculated using SST on the ocean grid (α0) or after regridding SST to the atmosphere (αA). An example of αA using regridded SST anomalies (SSTA) is given in Fig.1 for large-amplitude eddies in the highest ocean-atmosphere resolution available (a 25km atmosphere coupled to a 1/12° ocean, labelled ‘N512-12’).

Figure 1: A scatter plot of the relationship (THFF, αA) between regridded SST (SSTA) and THF anomalies. αA is the gradient of the linear regression line (black) +/- the 95% confidence interval (shown by the text). The data is from eddy snapshots averaged over 1 year, denoted by ‘< >’. Only large-amplitude eddies in the N512-12 configuration (25km atmosphere – 1/12° ocean) are plotted.

Why is the feedback so sensitive to the ratio of grid resolution?

In high-resolution coupled climate models, the atmospheric resolution is typically coarser than in its ocean component although, to date, a quantification of what the ocean-atmosphere ratio of grid resolution should be remains absent.

We prove increasing the ratio of atmosphere-to-ocean grid resolution in coupled climate models can lead to a large underestimation of turbulent heat flux feedback over mesoscale eddies, by as much as 75% for a 6:1 resolution ratio, as circled in Fig. 2 from a 60km atmosphere coupled to a 1/12° ocean. An underestimation of the feedback is consistent across all eddy amplitudes (A) and all three model configurations shown (Fig. 2); it suggests SST anomalies within these eddies are likely to be not reduced enough by air-sea fluxes of heat, and consequently will remain too large.

The underestimation stems from the calculation of the air-sea heat fluxes in the HadGEM3-GC3.1 model on the coarser atmospheric grid, instead of the finer ocean grid. Many other climate models do the same. At present, for the long spin-ups needed for climate simulations, it is unrealistic to expect the atmospheric resolution to match the very fine (10km) ocean resolution in coupled climate models, i.e. to create a one-to-one grid ratio. Therefore, to minimise this underestimation in the feedback at mesoscales, we advise air-sea heat fluxes should be computed on the finer oceanic grid.

Figure 2: Estimates of the turbulent heat flux feedback (THFF) across different eddy amplitudes (A) for α0 (lighter colours) and αA (darker colours, using regridded SST) for three model configurations: N512-12, N216-12 and N216-025. The ocean and atmosphere resolutions are added in red for each. Increasing the ratio of grid resolution, underestimates the THFF (as α0 differs from αA). The horizontal bars indicate the width of the eddy amplitude bins, and the vertical error bars indicate 95% confidence intervals.

Correctly simulating the air-sea heat flux feedback over mesoscale eddies is fundamental to realistically represent their interaction with the local and large-scale atmosphere and feedback on the ocean, to improve our predictions of the earth’s climate.

For a full analysis of the results, including a decomposition of the turbulent heat flux feedback, the reader is referred to Moreton et al., 2021, Air-Sea Turbulent Heat Flux Feedback over Mesoscale Eddies, GRL (in review).

Manuscript available: https://doi.org/10.1002/essoar.10505981.1

This work lays the foundation for my current work, evaluating how mesoscale air-sea heat fluxes feedback and alter the strength of large-scale ocean gyre circulation, using the MIT general circulation model (MITgcm).

This work is funded by a NERC CASE studentship with the Met Office, UK.

Forecasting space weather using “similar day” approach

Carl Haines – carl.haines@pgr.reading.ac.uk

Space weather is a natural threat that requires good quality forecasting with as much lead time as possible. In this post I outline the simple and understandable analogue ensemble (AnEn) or “similar day” approach to forecasting. I focus mainly on exploring the method itself and, although this work forecasts space weather through a timeseries of ground level observations, AnEn can be applied to many prediction tasks, particularly time series with strong auto-correlation. AnEn has previously been used to predict wind speed [1], temperature [1] and solar wind [2]. The code for AnEn is available at https://github.com/Carl-Haines/AnalogueEnsemble should you wish to try out the method for you own application. 

The idea behind AnEn is to take a set of recent observations, look back in a historic dataset for analogous periods, then take what happened following those analogous periods as the forecast. If multiple analogous periods are used, then an ensemble of forecasts can be created giving a distribution of possible outcomes with probabilistic information. 

Figure 1 – An example of AnEn applied to a space weather event with forecast time t0. The black line shows the observations, the grey line shows the ensemble members, the red line shows the median of the ensemble and the yellow and green lines are reference forecasts. 

Figure 1 is an example of a forecast made using the AnEn method where the forecast is made at t0. The 24-hours of observations (black) prior to tare matched to similar periods in the historic dataset (grey). Here I have chosen to give the most recent observations the most weighting as they hold the most relevant information. The grey analogue lines then flow on after t0 forming the forecast. Combined, these form an ensemble and the median of these is shown in red. The forecast can be chosen to be the median (or any percentile) of the ensemble or a probability of an event occurring can be given by counting how many of the ensemble member do/don’t experience the event.  

Figure 1 also shows two reference forecasts, namely 27-day recurrence and climatology, as benchmarks to beat. 27-day recurrence uses the observation from 27-days ago as the forecast for today. This is reasonable because the Sun rotates every 27-days as seen from earth so broadly speaking the same part of the Sun is emitting the relevant solar wind on timescales larger than 27-days. 

To quantify how well AnEn works as a forecast I ran the forecast on the entire dataset by repeatedly changing the forecast time t0 and applied two metrics, namely mean absolute error (MAE) and skill, to the median of the ensemble members. MAE is the size of the mean difference between the forecast made by AnEn and what was actually observed. The mean of the absolute errors over all the forecasts (taken as median of the ensemble) is taken and we end up with a value for each lead time. Figure 2 shows the MAE for AnEn median and the reference forecasts. We see that AnEn has the smallest (best) MAE at short lead times and outperforms the reference forecasts for all lead times up to a week. 

Figure 2 – The mean absolute error of the AnEn median and reference forecasts.

An error metric such as MAE cannot take into account that certain conditions are inherently more difficult to forecast such as storm times. For this we can use a skill metric defined by  

{\text{Skill} = 1 - \frac{\text{Forecast error}}{\text{Reference error}}}

where in this case we use climatology as the reference forecast. Skill can take any value between -\infty and 1 where a perfect forecast would receive a value of 1 and an unskilful forecast would receive a value of 0. A negative value of skill signifies that the forecast is worse than the reference forecast. 

Figure 3 shows the skill of AnEn and 27-day recurrence with respect to climatology. We see that AnEn is most skilful for short lead times and outperforms 27-day recurrence for all lead times considered.  

Figure 3 – The skill of the AnEn median and 27-day recurrence with respect to climatology.

In summary, the analogue ensemble forecast method matches current conditions with historical events and lifts the previously seen timeseries as the prediction. AnEn seems to perform well for this application and outperforms the reference forecasts of climatology and 27-day recurrence. The code for AnEn is available at https://github.com/Carl-Haines/AnalogueEnsemble

The work presented here makes up a part of a paper that is under review in the journal of Space Weather. 

Here, AnEn has been applied to a dataset from the space weather domain. If you would like to find out more about space weather then take a look at these previous blog posts from Shannon Jones (https://socialmetwork.blog/2018/04/13/the-solar-stormwatch-citizen-science-project/) and I (https://socialmetwork.blog/2019/11/15/the-variation-of-geomagnetic-storm-duration-with-intensity/). 

[1] Delle Monache, L., Eckel, F. A., Rife, D. L., Nagarajan, B., & Searight, K.(2013) Probabilistic Weather Prediction with an Analog Ensemble. doi: 10.1175/mwr-d-12-00281.1 

[2] Owens, M. J., Riley, P., & Horbury, T. S. (2017a). Probabilistic Solar Wind and Ge-704omagnetic Forecasting Using an Analogue Ensemble or “Similar Day” Approach. doi: 10.1007/s11207-017-1090-7 

Why renewables are difficult

Adriaan Hilbers – PhD researcher at Imperial and Reading a.hilbers17@imperial.ac.uk

Adapted from a 2018 blog post: see the original here

Renewable energy represents one of the most promising solutions to climate change since it emits no greenhouse gases. However, it poses some difficulties for power systems. Source: U. Leone

The public have been aware of the importance of reducing carbon emissions since around the 1980’s. Furthermore, renewable technologies such as solar and wind have been around for decades. Under these conditions, it’s surprising that most countries still generate the majority of their electricity from carbon-emitting fossil fuels. Why, after decades of both the problem and a possible solution being known, haven’t renewables taken off yet? This article describes why renewables are “difficult”, and how the world can keep the lights on into the future in a cheap, secure, and sustainable way. 

Until recently, the primary reason was economics. It was impossible to build wind turbines and solar panels cheaply enough to compete with fossil fuel technologies, which have become highly cost effective after more than 100 years of use. Governments were not willing to spend billions to subsidise renewables when electricity could be generated cheaply by other means. Recently, however, improved manufacturing methods, economies of scale and increased competition sent prices plummeting. The price of solar panels has decreased by a factor of 200 in the last 45 years, and wind farms (even offshore) are now cost-effective without subsidy.  

So, is it just a matter of time before fossil fuel electricity disappears? Why are societies still so hesitant to go 100% renewable? To understand why, one needs a quick introduction to power systems: the industries, infrastructures and markets based around electricity. 

At their core, power systems are supply & demand problems. Industries and consumers use electricity provided by generators. One key feature distinguishes power systems from other economic markets: there is very limited means of storing it at large scale (with the notable exception of hydropower, discussed below). For this reason, supply must match demand on a second-by-second basis. 

A still from Drax Electric Insights, where electricity demand and generation levels can be browsed through, both in real time and historically. Source: Drax Electric Insights

(As an aside, in the UK, there is a fantastic website, called Drax Electric Insights, in which the total UK electricity demand, and exactly from which sources it is being generated, can be browsed through in real time as well as historically. Looking through it for a few minutes will give a better feel for how power systems work than any blog post can). 

Before renewables, most electricity came from fossil fuel plants. Fuel (mostly coal or gas) was burnt at different rates and level of electricity supply was directly adjusted to meet demand. This isn’t always easy; for example, the UK’s system operator had to deal with a massive demand spike just after the royal wedding, as millions turned on their kettles at the same time.  

A famous graph showing total UK electricity demand during the 1990 World Cup semi-final against Germany, with spikes at times that viewers turned on their kettles en masse. System operators had to rapidly adjust supply to ensure the lights stayed on. Source: National Grid

With renewables, the single biggest difficulty is that their production levels can’t be controlled. It’s not always windy or sunny, and times of high renewable output do not always align with times of high demand. How does one ensure the lights stay on on a cloudy day or when the wind tails off? 

In most countries, this is not yet a problem since renewable capacity is still small and there’s ample conventional backup capacity. Renewables produce whatever electricity they can, and the rest is picked up by the conventional plants.  

A problem occurs when countries start generating most of their electricity from renewables as this drastically changes the economic outlook of power markets. In a nutshell, building renewable capacity displaces fossil fuel generation, but not generation capacity; all power plants must be kept open for the rare days when there isn’t any wind or sun. Keeping these plants open but using them infrequently is very expensive, and closing them is impossible, unless you want to accept significant risks of blackouts on calm, cloudy days. It’s a perilous choice: higher electricity prices or reduced security of supply, and this problem defines the difficulties of renewable electricity systems. 

Thankfully, there are a few ways that society can generate most of their electricity from renewables while keeping prices low and supply secure. They fall broadly into two categories. 

The first is electricity storage. With grid-scale storage, excess electricity production on windy or sunny days can be stored and used in times when renewable output is low. Besides adding to supply security, this would enhance the economic picture since storage owners buy up electricity when price is low and sell it when price is high, evening out price jumps and allowing a smaller number of conventional plants to run more often. Almost all grid-scale storage currently in existence is hydropower, which countries like Norway use to generate almost all their electricity but requires a mountainous terrain and access to water. The reason other grid-scale storage is rare is economics. Most storage technology (e.g. battery) prices still have to drop significantly before they can be used at large scale. 

Hydropower provides an economical option to store electricity, but requires mountainous terrain. Source: skeeze

A second solution is interconnecting different countries and allowing them to share electricity. When it is wind-free in London, it usually is in Scotland as well, bit it may be windy in Germany or Spain. Transporting electricity around could help alleviate supply insecurity. Many countries are doing just this; the UK, for example, currently has interconnections with France, the Netherlands, Belgium and Ireland, and more are in the pipeline. They may eventually from part of the European Supergrid, where electricity can be transported across Europe to balance out regional renewable supply peaks and troughs. 

The prospect of combining hydropower and interconnections between countries is tempting, since it means countries with lots of wind but little storage capacity, like Germany or Denmark, could “use Norway as a battery” by exporting their excess wind power to Norway in windy periods, which allows dams to accumulate water. In calm spells, hydropower generation levels are increased and excess electricity exported back the other way. Making this work will require significant increases in Norwegian hydropower infrastructure, interconnection lines and international cooperation. 

The batteries in electric cars can be used for grid management provided that owners agree to this. Source: Marilyn Murphy

Another creative solution to the storage problem is to use the batteries in electric cars. Electric car uptake will lead to demand spikes when people return from work and plug them in. An electric car owner can get the option of cheaper electricity if it means her car’s battery is not charged (smart charging), or even emptied (known as vehicle-to-grid), during demand spikes and recharged when demand is lower. Such approaches are currently being trialled in the UK

Current power systems are not yet ready to use renewables for the majority of their electricity supply. However, the immediacy of the climate change danger means business-as-usual is not an option, and a total energy revolution is required. Presently, the most realistic solution is the use of renewables (see a separate blog post on nuclear power here). Nobody knows exactly how the power system of the future will look. But everyone agrees it will be very different. 

A still from an online tutorial on power system models, showing generation from different sources.

Want to know more? For a similar discussion on the merits of nuclear power, see this blog post. To get a feel for how a power system works, see this page. It allows users, inside a cloud (no downloads or installs necessary), to create their own power system for the United Kingdom, and see how electricity is generated from renewable and conventional sources. 

Note: this article was adapted from a 2018 blog post: see the original here

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…?

The Social Metwork in 2020

James Fallon – j.fallon@pgr.reading.ac.uk
Brian Lo – brian.lo@pgr.reading.ac.uk 

Hello dear readers! Reviewing submissions and discovering the fascinating research that takes place in Reading Meteorology has been an amazing experience, and a personal highlight of the year!

Thank you to everyone who has contributed to the social metwork this year, and especially to those who have been patient whilst myself and Brian have been getting used to our new roles as co-editors. The quality of submissions has been very high, but don’t let that deter you if you haven’t written for the blog before! Writing for the social metwork is not as tricky as you might think – we promise!

At the time of writing, the blog has had over 5550 visitors, and is on track for an all time high by the end of the year. We hope that the social metwork has contributed to lifting spirits and continuing the met department social atmosphere throughout the year. In case you missed any posts, or want a second look at some, here is a list of all the posts from this year:

January
North American weather regimes and the stratospheric polar vortex – Simon Lee
Evaluating ocean eddies in coupled climate simulations on a global scale – Sophia Moreton
The (real) butterfly effect: the impact of resolving the mesoscale range – Tsz Yan Leung

February
Life on Industrial Placement – Holly Turner
An inter-comparison of Arctic synoptic scale storms between four global reanalysis datasets – Alec Vessey
A new, explicit thunderstorm electrification scheme for the Met Office Unified Model – Ben Courtier

March
Relationships in errors between meteorological forecasts and air quality forecasts – Kaja Milczewska
Tips for working from home as a PhD student – Simon Lee

May
Air pollution and COVID-19: is ozone an undercover criminal? – Kaja Milczewska
The philosophy of climate science – Mark Prosser
Explaining complicated things with simple words: Simple writer challenge – Linda Toča

June
Methane’s Shortwave Radiative Forcing – Rachael Byrom

July
How do ocean and atmospheric heat transports affect sea-ice extent? – Jake Aylmer

August
A Journey through Hot British Summers – Simon Lee
Exploring the impact of variable floe size on the Arctic sea ice – Adam Bateson

September
How Important are Post-Tropical Cyclones to European Windstorm Risk? – Elliott Sainsbury
The Scandinavia-Greenland Pattern: something to look out for this winter – Simon Lee

October
My journey to Reading: Going from application to newly minted SCENARIO PhD student – George Gunn
The visual complexity of coronal mass ejections follows the solar cycle – Shannon Jones
Organising a virtual conference – Gwyneth Matthews
Visiting Scientist Week Preview: Laure Zanna – Kaja Milczewska

November
Demonstrating as a PhD student in unprecedented times – Brian Lo
ECMWF/EUMETSAT NWP SAF Workshop on the treatment of random and systematic errors in satellite data assimilation for NWP – Devon Francis
Extra conference funding: how to apply and where to look – Shannon Jones
Youth voices pick up the slack: MOCK COP 26 – James Fallon

Enjoy the panto, have a very merry Christmas, and here’s to 2021!
From your metwork co-editors James & Brian!

Youth voices pick up the slack: MOCK COP 26

James Fallon – j.fallon@pgr.reading.ac.uk

This year’s Conference of the Parties (COP) should have taken place earlier in November, hosted by the UK in Glasgow and in partnership with Italy. Despite many global events successfully moving online this year, from film festivals to large conferences such as the EGU general assembly, the international climate talks were postponed until November 2021.

But young people around the world are more engaged than ever before with the urgent need for international cooperation in the face of the climate emergency. The Fridays for Future (FFF) movement has recorded participation since late 2018 of more than 13,000,000 young people, in 7500 cities from all continents. FFF has adapted to the covid-19 crisis, and on 25th September this year participants from over 150 countries took part both online and in the streets, highlighting the Most Affected People and Areas (MAPA).

Unimpressed by the delay of important climate talks and negotiations, students and youth activists from FFF and a multitude of groups and movements have initiated the MOCK COP26, a 2-week online global conference on climate change that mirrors the real COP.

“My country, the Philippines, is struggling. We don’t want more floods that rise up to 15 feet, winds that peel off roofs in seconds, the rain that drowns our pets and livestock, and storm surges that ravage coastal communities. We don’t want more people to die. We’re still a developing country that contributes so little to global carbon emissions yet we face the worst of its consequences. This is absurd! 

Angelo, Philippines
https://www.mockcop.org/why

Programme

Organisers have chosen five themes to focus on:

  1. Climate education
  2. Climate justice
  3. Climate resilient livelihoods
  4. Health and wellbeing
  5. Nationally Determined Contributions

Full programme here: https://www.mockcop.org/programme

Over a dozen academic support videos break down complicated topics such as “The Kyoto Protocol”, “Agriculture and Agribusiness”, and the “History of Climate Negotiation”. These videos are helping youth delegates and all participants to understand what happens at a COP summit.

Panel sessions have featured United Nations Youth Envoy Jayathma Wickramanayake, 9 year old Climate & Environmental Activist Licypriya Kangujam, and (actual) COP26 president Alok Sharma.

High Level Country Statements

A unique aspect of MOCK COP that I have been excitedly anticipating is the high level country statements; each a 3 minute speech given by youth climate activists representing their nation.

Mock COP26 is not dominated by big polluters as COP26 is. We believe that we need to amplify the people on the frontlines of climate change, which is why we will be aiming to, throughout Mock COP, uplift the voices of those from MAPA (Most Affected People and Areas) countries above those from the Global North. This is why Mock COP26 is special.

Jamie Burrell, UK
https://www.mockcop.org/today

Youth delegates have been encouraged to give speeches in whichever language they are most comfortable talking. At the time of writing, subtitles don’t appear to be fully functioning. However a large number of talks are given in English, and transcripts of all talks have been made available here: https://drive.google.com/drive/folders/1wnQUMt-rcD9XoKtg8YPWba_LZSf16qTD

I highly recommend setting some time aside to give these speeches a listen. Although the total number might put you off, it is very easy to jump in and out of talks. You can find videos embedded below, or on the official youtube channel.

Africa

Pick: Two youth delegates represent Morocco. Whilst Morocco has been ranked a role model for climate action, the reality of the country’s future is alarming. Globally the most affected are the least protected. It’s time for world leaders to protect everyone.

Americas

Pick: The delegate for Suriname explains risks faced as a Small Island Developing State (SIDS) with infrastructure near the coast. Suriname must implement climate adaptation whilst enhancing its legislation in forestry, mining, and agriculture.

Asia

Pick: Indonesia’s delegate opens with the stark warning that the country will lose 1500 of its islands due to rising sea levels by 2050. The high level statement includes calls to incorporate climate education into the national curriculum, and find ways to protect natural habitat. Indonesia has the 2nd biggest rainforest in the world, but currently has no agreed emissions reductions pathway.

Europe

Pick: Ireland’s youth delegates present a necessarily progressive 5 year plan to stick to the EU target of reducing emissions by at least 65% by 2030. The need for much stronger climate education, and providing access to affordable and sustainable energy, are among many other commitments.

Oceania

Pick: The year started with forest fires devastating large swathes of Australia’s natural habitats. Youth delegates want their nation to lead the world as a renewable energy exporter, and an overhaul of media rules to foster new diverse media outlets and prevent monopolies that currently stall climate action.

What is the hoped outcome?

With so many connected issues relating to the climate and ecological emergency, previous COPs have often seen negotiations stall and agreements postponed. The complexity of tackling this crisis is compounded by the vested interests of powerful governments and coal, oil, and gas profiteers.

But youth messages can be heard loud and clear at MOCK COP 26, reflecting the 5 themes of the conference.

We demand concrete action, not mere promises. It’s time for our leaders to wake up, prioritize the realization of the Green Deal, and cut carbon emissions. 

We won’t have more time to alter the effects of the climate crisis if we let this opportunity pass. The clock is ticking. The time for action is NOW. 

In the wake of covid-19 induced economic shocks, policy makers must ensure genuine green recovery that engages with ideas of global climate justice.

Youth delegate panels will continue over the weekend, working towards the creation of a final statement outlining their demands for world leaders. This will be presented to High Level Climate Action Champion for COP26 Nigel Topping, at the closing ceremony (12:00 GMT Tuesday 1st December)

Extra conference funding: how to apply and where to look

Shannon Jones – s.jones2@pgr.reading.ac.uk

The current PhD travel budget of £2000 doesn’t go far, especially if you have your eye on attending the AGU Fall Meeting in San Francisco. If the world ever goes back to normal (and fingers crossed it will – though hopefully with more greener travel options, and remote participation in shorter conferences?) you might wonder how you are ever going to afford the conferences your supervisors suggest. Luckily, there are many ways you can supplement your budget. Receiving travel grants not only means more conferences (and more travel!), but it also looks great on your CV. In this blog post I share what I have learnt about applying for conference grants and list the main places to apply.

Sources of funding include…

Graduate School Travel Support Scheme

  • Open to 2nd and 3rd year PhD students at the university (or equivalent year if part-time) 
  • 1 payment per student of up to £200 
  • Usually 3 deadlines throughout the year 

There are two schemes open to all PhD students who are members of the IOP (any PhD student who has a degree in physics or a related subject can apply to become a member)

Research Student Conference Fund

  • Unlimited payments until you have received £300 in total
  • 4 deadlines throughout the year: 1st March, 1st June, 1st September and 1st December 
  • Note: you apply for funding from an IOP group, and the conference must be relevant to the group. For example, most meteorology PhD students would apply for conference funding from the Environmental Physics group. You get to choose which groups to join when you become an IOP member. 

CR Barber Trust

  • 1 payment per student of £100-£300 for an international conference depending on the conference location 
  • Apply anytime as long as there is more than a month before the proposed conference 

Legacies Fund

Conference/Meeting Travel Subsistence

From the conference organiser

  • Finally, many conferences offer their own student support, so it’s always worth checking the conference website to see 
  • Both EGU and AGU offer grants to attend their meetings each year 

Application Tips

Apply early!!!

Many of these schemes take months to let you know whether you have been successful. Becoming a member can also take a while, especially when societies only approve new members at certain times of the year. So, it’s good to talk to your supervisor and make a conference plan early on in your PhD, so you know when to apply. 

Writing your application

Generally, these organisations are keen to give away their funds, you just have to write a good enough application. Keep it simple and short: remember the person reading the application is very unlikely to be an expert in your research. It can be helpful to ask someone who isn’t a scientist (or doesn’t know your work well) to read it and highlight anything that doesn’t make sense to them. 

Estimating your conference expenses

You are usually expected to provide a breakdown of the conference costs with every application. The main costs to account for are: 

  • Accommodation: for non-UK stays must apply for a quote through the university travel agent 
  • Travel: UK train tickets over £100 and all international travel must be booked by university too 
  • Subsistence: i.e. food! University rules used to say this could be a maximum of £30 per day – check current guidelines 
  • Conference Fees: the conference website will usually list this 

The total cost will depend on where the conference is. You are generally expected to choose cheaper options, but there is some flexibility. As a rough guide: a 4-day conference within the UK cost me around £400 (in 2019) and a 5-night stay in San Francisco to attend AGU cost me around £2200 (in 2019).  

Reading PhD students at Union Square, San Francisco for AGU! 

Good luck! Feel free to drop me an email at s.jones2@pgr.reading.ac.uk if you have any questions 😊