After a fairly inauspicious start to June 2017, the last few days have really boosted this months sunshine totals, particularly across southern areas. Top of the league at the moment is Jersey with 186.7 hours (average 10.3 hours per day), now there’s a surprise, closely followed by Manston in Kent and Herstmonceux in Sussex.
A good degree of consistency between the UKMO and GFS models about how saturday will look at T+120 (figs 1 & 2). How accurate it will be is another thing entirely. Pressure is still forecast to be reasonably high across the south, 1000-500 hPa thicknesses are not far from 564 dm, but there is a fresh to strong westerly flow across the British Isles, with fronts driving in from the west, so things don’t look good for this current hot spell.
If you remember ever having to change a sunshine card in a Campbell-Stokes recorder as an observer, then I’m sure that you’ll like this new way of visualising hourly sunshine data from stations across the UK that I’ve dreamed up (fig 1).
I don’t have the luxury of being able to receive minute data from the Met Office network, so the next best bet is to access hourly SYNOP data from OGIMET and put it together in some code and plot a gantt chart, which is exactly what I’ve done here (fig 1). It’s unique as far as my knowledge of visualising systems that don’t have network access to a remote AWS. There is a bit of guesswork about how you assign the hourly amount of sunshine to each hour during the day, I’ve made it so that the program defaults to the end of the hour before noon, and to the start of the hour after noon. The gantt chart format allows you to also see the approximate times of sunrise and sunset for each station. I’m pretty chuffed with the end result which only occurred to me whilst sun bathing in the garden this afternoon!
The other thing that it enables you to do is to watch sunshine total as they increase across the UK in real-time through the day (fig 2).
According to the latest GFS forecast, next Sunday might be a wet affair at Glastonbury (fig 1), as the current hot spell breaks down, and the weather turns wetter across the country, by next Sunday. Then again, all NWP models at this range are notoriously inconsistent, and with the Met Office never making public any of their NWP model data beyond T+120, it’s impossible to judge.
This really useful T+192 chart from the ECMWF (fig 2) for next Sunday is of little help. I really despair of the ECMWF, why are they so loathed to make public any of the NWP data that they supposedly generate for the people of the European countries that fund them? I ask you, of what value is a chart of MSLP overlaid with 850 hPa wind speeds to anyone? I thought my contouring had problems, have they never heard of smoothing, and please a summer chart with isobar spacing of 5 hPa is not that helpful. What about overlaying accumulated precipitation or precipitation rates, or even total cloud amount rather than 850 hPa wind speeds. Perhaps there is an option that I’ve missed on their website, but I don’t think so.
Every year when the summer starts in earnest and weather presenters start talking about how warm it is (particularly in the southeast), they start presenting charts with temperatures across the southwest of England several degrees lower than the rest of the country, and every year I can’t help writing a protest blog like this one! Today was a perfect example, take a look at yesterday’s forecast temperatures for 16 PM (15 UTC) today as presented by Jay Wynne on BBC 1 at 1.25 PM.
Now have a look at today’s actual values from across the country (fig 2).
As you can see it’s actually 20.8°C in Plymouth, 21.1°C at Culdrose and 23.0°C at Cardinham, so the forecast for Plymouth is too low, not only that, where the 19 label is drawn on the BBC graphics right on top of Exeter, where the temperature at 4 PM today was a hot 27.1°C, that’s a full 8°C higher than on the chart. The forecast temperature for Plymouth looked wrong yesterday, and it was wrong in reality today. For goodness sake, why don’t the BBC simply choose a city that’s more representative of the southwest, or perhaps display the maximum forecast temperature for the whole region.
- I did a quick search and I can see I’ve already had a go at the BBC this year back in April.
- It looks like its not only maximum temperatures that get me going.
- And here is last years effort.
The one thing you can’t accuse me of is, and that’s a lack of consistency when it comes to temperature forecasts from the BBC.
I realise it’s not the same thing as UV, but the hourly solar radiation figures in the SYNOP reports do give you a very good idea of the sun’s strength at the moment, which is extremely strong across most areas. I know that down here in Devon, I’m starting to burn in less than 5 minutes sat out in it. It’s a funny thing, you wait patiently for the first hot sunny summers day to arrive, but then when it does, you have to hide from the sun.
The fair weather cumulus across East Anglia, has pegged solar radiation values down there a touch (fig 2), but in many other places it’s well in excess of 3000 kJ/m² (fig 1) this lunchtime.
The usual culprits are at the top of warmest places from the SYNOPs, but Exeter is doing quite well with 25.9°C at 13 UTC. It’s almost 4 degrees warmer than that here, about 8 km to the north of the airport, but my Vantage Pro is far too well sheltered, and at the moment is covered in splashes of Ambre Solaire.
A little unfair of me perhaps, but this is a comparison of the last weeks sunshine from Kinloss on the Moray Firth in the north (fig 1), and Exeter in deepest darkest Devon in the south (fig 2). I’ll let the graphics do the talking. I’m sure that the balance will be redressed as the summer goes as they usually do. The GFS forecast still looks good, but thundery showers might be a problem for some areas next week.
One of the very first articles that I read in the Weather Magazine as a young outstation assistant was entitled “A simple summer index with an illustration for summer 1971” by R. Murray which was published in April 1972. Now over forty years later as a retired programmer with the Met Office, I have decided to revisit the summer index and update his record.
I have a number of advantages that Murray could only dream of, and they are a powerful personal computer, up to date freely accessible climate data, and of course the Internet to access that data from. The Met Office provide the data in the form of monthly regional and national gridded climate data back to 1910. This provides you with all the temperature, rainfall and sunshine that you require to calculate a summer index, and the advantage of this data is that you can generate a summer index not only for the UK, but for England, Wales, Scotland, Northern Ireland as well as any of the other twelve other regional areas.
All that was required to access the latest climate data from the Met Office website was internet access. The program converted the text files I downloaded into a data structure to hold each month’s mean temperature, total rainfall and sunshine values necessary to compute each year’s summer index. The slightly tricky bit was to calculate the quintiles of each month’s mean maximum temperature, and the terciles of the total sunshine and rainfall that the formula requires.
The summer index [SI]
SI = 3T + 5S – 5R – 9m
- m = number of months
- T = sum over m months of quintiles of monthly mean temperature
- S = sum over m months of terciles of monthly sunshine
- R = sum over m months of terciles of monthly rainfall
Quintiles and terciles are statistical terms used with any series of data arranged in order of magnitude. Rainfall is conventionally divided into three equal classes; the driest third being tercile 1, and the wettest tercile 3. With temperature the data is divided into five equal classes; quintile 1 refers to the coldest and quintile 5 to the warmest. There is a drawback in using the climate data series from the Met Office, although the temperature and rainfall series extend back to 1910, the sunshine series is only available from 1929, so I was unable to reach back quite to 1881 as Murray did originally. Using Murray’s formula the absolute best ‘meteorological’ summer can score a maximum SI of 48, and the absolute worst a SI of -48.
A simple summer index
The summer index was first proposed by Davis in 1968, its beauty lies in its simplicity, but a good summer can be ruined by a wet last week in Autumn, so the index is far from perfect. You could dream up a summer index that looked more closely at daily values of temperature, rainfall and sunshine, but at the moment the Met Office do not make daily regional climate data available, so for now monthly data will have to suffice.
How do you define what constitutes a ‘good’ summer? It is very subjective, and as we grow older, it may have less to do with weather, and more to do with other things that are going on in our lives. Keeping it strictly meteorological, and if you’re older than 70, you probably look back at the summer of 1959 as being the best, older than 50 and it’s highly likely that 1976 will be your perfect summer, younger still and it may well be the summer of 1995 or 2003. The worst summer in contrast is not so easy to quantify, and many people if asked will struggle to name the worst summer that they have experienced in their lifetime.
The ‘best’ summers
As you can see from the table of best summers (fig 1), 1976 tops the Summer index back to 1929 for the UK which probably comes as no great to surprise to many. In fact its score is the perfect maximum of 48.
The extended summer index
The beauty of the algorithm is that you can also calculate an extended Summer index (May through to September), which gives an entirely different slant on what was the best summer. The table below (fig 2) shows that 1959 has the highest extended summer index of 62 (out of a possible 80), and that 1976 is only eleventh in the rankings, with an index of 28. So why was the extended summer of 1976 so much worse? If you compare the various quintiles and terciles for 1976 and 1959, you will see that 1976 was in fact duller and wetter than 1959 in May and September so the extended index score was reduced.
Because the data is also split into regional as well as national values, it’s easy to compare what kind of summer other parts of the UK experienced. As you can see in the breakdown of the extended summer of 1959 (fig 3), the northeast of England and the Midlands score a very high 72, whilst somewhat lower down the rankings came the north and west of Scotland.
The ‘worst’ summer
The summer of 1954 has the lowest summer index -48 of all summers in the UK since 1929 (fig 4), you just can’t get a summer index lower than -48. 1954 was the very antithesis of 1976, it was not only wet, it was cold and dull. Even if you compare 1954 using the extended summer index, it’s still has the lowest index of -64 for the UK. Just to show you how poor that summer was, here are the headlines for each month of the extended summer of 1954 that I’ve copied from the Monthly Weather Report.
- May 1954 mainly dull and wet, with frequent thunderstorms; large variations of temperature.
- June 1954 mainly dull and cool; periods of rain, heavy at times.
- July 1954 notably cool and dull; wet in some areas.
- August 1954 cool and dull, mainly wet in England, Wales and southern Scotland.
- September 1954 cool and unsettled; wet in most areas; sunny on the whole.
What about summer 2016?
To a lot of people, especially those in the south and east, summer 2016 was very good, and the eagle-eyed amongst you will have noticed that it ranked joint 19th in the table of meteorological summers, and joint 11th in the table of extended summers, just behind 1976 and on a par with 1947. But how did the extended summer of 2016 look nationally and regionally? According to the extended summer index East Anglia fared best in 2016 with a summer index of 42 (fig 5), closely followed by southern England and the Midlands.
Finally, here is a graphical way of looking at the summer’s since 1929 as a whole by means of two scatter graphs. The first graph plots temperature against rainfall (fig 6), whilst the second graph plots temperature against sunshine (fig 7). They show at a glance just how each summer compares with each other, for instance although 1995 was very slightly drier than 1976, it was slightly less sunny and not as warm.
Are summers getting any better?
The one remaining question is – are summers getting better? Well with the help of another chart (fig 8) I’ve plotted the summer index and overlaid it with a five-year centred moving average (dashed line with a yellow outline). I’ve also added a simple linear trend (dashed black line), although climatologically this may be frowned upon (because any trend certainly wouldn’t be linear), it does help to highlight the increase in summer index that there has been since 1929. So the short answer to that question is yes, the summer index has increased over the last 87 years, whether that equates to better summers, I will leave that for you to decide.
Davis, N. E.1968. An optimum summer index. Weather 23: 305-317.
Murray, R.1972.A simple summer index with an illustration for summer 1971.Weather 45:161-169.
Many of my regular readers may remember that I wrote an article about the ‘Summer Index’ last July. I fully intended to get a fuller version of it published in the Weather Magazine of the Royal Met Society. I lost heart in the end, I don’t think I write in the way that they like, and I’m not good at writing in any other way. I went to a bit of trouble in putting the article together, so instead of it just languishing in a folder named ‘Weather Magazine’ in my Google drive account, I thought that I’d publish it in my blog just for posterity. The other thing that I like about a blog is that you can always fix typo’s or mistakes which you can’t do in a printed magazine, hopefully there are not too many of those.
The warmest place may have been Heathrow with a high of 24.3°C (anomaly +3.0°C) today, but in the alternative ‘anomaly’ top ten they only finished in joint 10th place, and it was Ballypatrick in County Antrim, that topped the list with an anomaly of +5.7°C anomaly (fig 1).