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January 2020: Memories of January 2007

In the UK, it’s currently mild – very mild. Provisional data through the 9th shows the mean Central England Temperature (CET) is running at 7.5°C, which is 3.9°C above the 1961-1990 average. The large-scale pattern during the month so far (Fig. 1) has been characterised by a ridge extending from the Azores to Europe, and low pressure near Greenland – creating a strong flow of mild, subtropical Atlantic air (the “tropical maritime” airmass). This is the positive phase of the ubiquitous North Atlantic Oscillation (NAO), which describes the primary mode of large-scale variability in the North Atlantic-European region. The NAO has been in a positive state since 28 December 2019, likely influenced by the strong stratospheric polar vortex.

Mean temperatures at the University of Reading have been well above the 1981-2010 average for every day of the month so far, with the 9th January a staggering 6.1°C above normal at 10.8°C!


Figure 1: 500 hPa geopotential heights and anomalies for Jan 4-10, 2020, from

The mild weather reminds me of January 2007, which was the UK’s second warmest on record (in terms of mean temperature) in the series since 1910 (5.9°C) behind only 1916 (6.3°C). January 2007 had a mean CET of 7.0°C, placing it 5th in the series since 1659, while in Reading it was the warmest January in a series since 1908 with 7.6°C (by contrast, 2020 runs at 8.0°C so far…)

As this was before the colder, snowier period of 2009-2013 (and I had yet to live through a particularly snowy winter despite being in North Yorkshire), I remember thinking that the unusual warmth must have been due to climate change (it followed hot on the heels – pun intended – of many UK heat records in 2006). Certainly, January 2007 was a hot one for most of the globe.  It was the first month in NASA’s analysis to be more than 1.0°C above the 1951-1980 average (Fig. 2), something which we only saw again in October 2015 (and which has since become “normal” with 16 subsequent months breaching that threshold).


Figure 2: Global temperature anomalies for 2007 with respect to 1951-1980. NASA GISS analysis (

You can see from the 500 hPa geopotential height anomalies for January 2007 (Fig. 3) that it was not particularly reminiscent of January 2020 thus far, with a much less zonal Atlantic. January 2007 did not have an extremely positive NAO – in fact, it turned negative from the 20th of the month, and it was relatively cold for a few days in the final third of the month. Without this colder spell, it would have almost certainly taken the crown off 1916 for the UK’s warmest.


Figure 3: 500 hPa geopotential height anomalies for January 2007 from NCEP/NCAR reanalysis (

It’s clear, therefore, just how much small circulation changes or persistence can have on these monthly-level anomalies in the heart of the winter and on the receiving end of volatile Atlantic dynamics – introducing a lot of noise into the climate signal for the month. Generating extremes always needs a “perfect storm” – in this case, a persistent, unchanging pattern bringing warm air for as much of the month as possible, superimposed on background global warmth.

Nevertheless, January has warmed in the UK (Fig. 4), though this is perhaps most noticeable in the absence of cold rather than the presence of warmth – likely in part particularly due to warming seas, but also the rapidly warming Arctic meaning cold air outbreaks are warmer than they once were.


Figure 4: UK January mean temperatures since 1910, expressed as departures from the 1910-2019 mean. Data source:

January 2020 may go on to be a record breaker. Equivalently, it may not, thanks to the sensitivity of the UK’s temperatures to fine changes in circulation patterns. But thanks to global warming, it’s increasingly likely that 1916 won’t hold the record for much longer if the right weather patterns do occur. On that note, Charlton-Perez et al. (2018) found a slight increase in persistence of the positive NAO regime under strong stratospheric vortex conditions. With the forecasts suggesting a strong stratospheric vortex for the remainder of the month, we might just be in for a record-breaker.


Figure 5: CFSv2 forecast from 10 January 2020 of 10 hPa 60°N zonal-mean zonal winds.

Thoughts upon finishing the MMet

Yesterday (May 11), at about 10:50am, I completed my Master’s Degree in Meteorology and Climate (MMet) at the University of Reading.

The exam – Oceanography (perhaps not the most typical way to end a meteorology degree, but I guess it highlights the diversity of the subject).

The way I finished it? Ending a question on the thermohaline circulation with, “And with that, I’ve finished my degree!”.

It’s a surreal feeling when it’s a moment that’s been coming for the last four years. It’s been a long slog. Like everyone who studies meteorology at university, I can confirm it’s a tough subject – full of concepts and equations that (for me at least!) have required a caffeine addiction (thanks, Taylors of Harrogate) and a lot of head scratching to understand to the required level. From linear algebra and differential equations, to fluid dynamics in the laboratory, boundary layer fieldwork… and hours of programming. The Reading degree is thorough, to say the least. But it was everything I could have wanted, and more. I finally have the understanding of the atmosphere (and, apparently, the oceans as well!) which I so craved when I first became interested in the clouds above my head.

What’s worth more, though, is the understanding of the sheer scale of the atmospheric science discipline, and just how much I don’t know. The most challenging class I took was Advanced Synoptic at the University of Oklahoma (taught by Howie Bluestein, all-round meteorology legend and someone who can plaster the whiteboard with the semi-geostrophic equations and make the whole thing less daunting than it should be!). I’d probably show the notes I made in this class to anyone who thinks that meteorology is just about standing in front of a weather map saying it might rain tomorrow. Here’s a brief look at them:

Deciding to study the MMet degree at Reading was the best decision I ever made, and it’s opened up a world of opportunities for me – both here and in Oklahoma, where I spent my third year. I’ll be studying for a PhD in Meteorology from September, sharing my time between Reading and Oklahoma yet again (which I’m super excited about).

Thank you to all the staff at Reading and OU for making it all worth it, and for sharing your knowledge in a consistently entertaining and passionate way. Thank you to all my fellow students and friends, who sufferred and celebrated through the degree with me. And, thanks to everyone on #WxTwitter – I’ve learnt a great deal from all of you!

I couldn’t recommend the MMet strongly enough to anyone with an interest in the atmosphere. You won’t regret it!

“How did you get into weather?”

Something often unique to meteorologists is our ability to pinpoint the moment in our lives when we were captivated by the weather.

I’ve been interested in weather since 2002, when I was 6 years old. My hometown of Harrogate, North Yorkshire is a few miles east of the Washburn Valley reservoirs (Lindley Wood, Swinsty, Fewston and Thruscross). When I was growing up, they were a place my family often visited on a weekend, and one day my Mum noticed that Thruscross Reservoir was to be featured in an episode of Wild Weather, a BBC series presented by Donal McIntyre about weather extremes. Given how much I loved the reservoirs, we tuned in to watch Donal get pummelled by water from Thruscross in order to demonstrate the sheer power of water in the context of flash-flooding.

I was hooked, and watched the rest of the series multiple times, discovering more and more about the atmosphere. I was particularly inspired by the global scale…jet streams guiding weather systems for thousands of miles, something which has stayed with me ever since. I always remember that this series was where I first learned of the oceanic ‘thermohaline conveyor’. The fact that weather and reservoirs combined to spike my interest is no coincidence, as I always wanted to see the reservoirs overflowing or at very low levels…so rainfall surplus or deficits had always been on my mind. Perhaps the only other thing aside from weather in which I’m known to have an excitable interest is dams!

That was the first aspect of my life which pushed me towards meteorology.

But the other aspect is that I grew up into a world of weather extremes, particularly in the UK but also on a global scale, thanks (in part) to climate change. I remember the headlines in the summer of 2003 as the UK and Europe baked in a record-breaking heatwave (the one and only time the UK has surpassed 100°F). 2004 was memorable for the Boscastle flash flood in August, but I also remember being captivated by the frequent (at the time, record-breaking) tropical cyclone landfalls on the US.

I spent the summer (and autumn) of 2005 tracking the Atlantic tropical cyclones, which turned out to be memorable for many record-breaking reasons. I remember having no Internet access on the day Katrina made landfall and being heart-broken I wasn’t able to follow what was clearly an unfolding disaster. I remember the moment the NHC issued the advisory showing Wilma as the most intense on record. I have the list of names for that season committed to memory. I just fell in love with it.

By this point I’d become known amongst friends as a weather obsessive, but still the inspiration from the meteorological world around me kept coming. In July 2006, Britain experienced its hottest month on record, and then in September a weak tornado struck Harrogate and nearby Leeds which was a tremendous experience that I reported to TORRO with observations from my sister, who at the time worked in the tallest building in Harrogate and watched the event unfold.

Then followed the 2007 wet summer in the UK (which lead to the partial failure of the Ulley Reservoir in South Yorkshire…very exciting!), the failed “BBQ summer” of 2009, the 2009-10 cold winter, the record-breaking cold of December 2010, the record-breaking wet summer of 2012…and so on. These extremes and others helped commit my interest and also spurred my interest in the jet stream, which will be the focus of my final year research project at the University of Reading.

I can’t imagine my life without an interest in the atmosphere; I often find it hard to think how one couldn’t be interested in trying to understand the chaos above our heads. With climate change a serious issue for everyone, it’s my hope that everyone will gain a little more understanding about the power and beauty of the skies.

Record-Warm Global Temperatures

Over the past 18 months, global temperatures have been regularly breaking records, on both the surface-based (NASA, NOAA, Met Office) and the remote sensing records (UAH, RSS). Yes, this has been occurring now due to the 2nd strongest (by 3-monthly Nino 3.4 anomalies) El Nino on record. But I would argue, in many news broadcasts or articles, that the role of El Nino is regularly overstated – as though the reason for record-setting global temperatures is entirely ‘natural’ and should not be cause for alarm. This is not the case. Merely having an El Nino doesn’t guarantee a new record, without the background GHG forcing. It would be harder to argue that point if the current El Nino was by far and away the strongest, but it isn’t – 1982/3 (+2.1) and 1997/8 (+2.3) were similar to 2015/16 (+2.3).

The El Nino-Southern Oscillation (ENSO) is a big, noisy oscillator on global temperatures. There are other, slower factors (like the PDO and AMO), but ENSO is the biggest contributor year-on-year. Warming due to increased GHG forcing continues in the background, whilst ENSO causes these short-term fluctuations and will ‘make-or-break’ a year when it comes to setting records. It’s therefore natural that El Nino years set the records, as they spike temperatures upwards – it wouldn’t be the case that a La Nina year would result in a record. Notable is 2005, which was, at the time, a record-warm year, but ENSO neutral (a weak El Nino occurred in boreal winter 2004/5). Fig.1 shows this most clearly.


Figure 1: NOAA monthly global temperature anomalies coloured by ENSO conditions.

2015 was the warmest calendar year on record according to NASA’s GISTEMP record and NOAA’s NCDC record. However, it was not very strongly affected by El Nino – perhaps only around 10% of the warmth was due to ENSO – as the event was only developing during the year. With a lag effect of the warming Pacific on raising atmospheric temperatures, without increased GHGs it would not have beaten the 1998 value as much as it did (a 1951-1980 GISS anomaly of 0.87°C in 2015, compared with 0.63°C in 1998). It’s a tad ‘brute force’ (and not perfect) to do, but taking all other things to be equal, the difference of 0.24°C between those values is a trend of 0.14°C/decade.

This trend is of note due to the overhyped ‘global warming pause’ that seemed evident in the early part of the 21st century. Often exaggerated by skeptics who picked 1998 as a year to start a linear trend, it is something which seems to be evident in all datasets to differring extents – whether or not it is worth considering is still argued by different scientists. Many potential reasons exist – a change to a cool PDO and persistent La Nina conditions in 2007-2014 is something I always return to as a reason, particularly because since the PDO turned positive in 2014, temperatures have spiked, significantly. Fig. 1 strikingly shows the magnitude of recent warming, suggesting any pause/hiatus/slowdown is over – we will see the picture clearly in the next La Nina year.


Figure 2: NASA GISTEMP monthly data from Jan 1997 to June 2016. Credit

2016 is now looking very likely to beat 2015 (the first 6 months were the warmest half-year on record), which would make the top 3 record-warm years on the surface datasets 2014, 2015 and 2016 – rather remarkable. 7 consecutive months from October 2015 – April 2016 saw GISTEMP anomalies above 1°C relative to 1951-1980, which had never been observed before. The magnitude of the final 2016 anomaly depends on the strength of the developing La Nina, which is currently expected by most models to be rather weak. Fig. 3 shows a plume of various model forecasts. It’s worth noting 2010 set a new record at the time despite a strong La Nina developing in the 2nd half of the year.


Figure 3: ENSO model plume. Credit IRI.

Now for a brief comparison of the GISS and UAH records. NASA’s record is often accused of being the warmest (using a 1200km smoother to cover regions of sparse data, something which doesn’t actually alter the end result as much as some argue) whilst the UAH is a skeptic-friendly dataset, mainly because the 1998 El Nino spike was rather more severe. Fig. 4 shows a comparison of their records for June (the warmest in the GISTEMP record, and the 2nd warmest in the UAH record behind 1998).


Figure 4: Comparison of UAH and GISTEMP records for June 1979-2016 w.r.t. 1981-2010.

There are slight differences, and indeed the trends are slightly different. But the broad picture is the same. They differ on exact monthly rankings, as one would expect, but it’s not as though the UAH record shows global cooling, is it? (I’d argue satellite temperatures exaggerrate the ENSO influence – note how the 1998 El Nino spike and the 2008 La Nina dip are bigger).

A final note is inspired by a Twitter discussion I had and considers climatic averages. NOAA use the entire 20th century, NASA use 1951-1980 whilst UAH use 1981-2010. In the case of the latter, it’s enforced due to the data beginning in 1979. But is 1951-1980 or the full 20th century appropriate?

Local climate statistics are updated to reflect the new averaging periods and the ‘changing climate’, which is meaningful for the public (I don’t particularly care about knowing whether England was warmer than the 1961-1990 average, as I didn’t ever experience that, whereas 1981-2010 has meaning to me). However, when it comes to the globe as a whole, updating averaging periods would only confuse the message – suddenly these massive anomalies would become smaller, whilst you can’t actually ‘feel’ the anomaly, unlike for local regions. Moreover, as the 1981-2010 period exhibited such strong warming (whereas 1951-1980 was almost neutral) the average never truly existed. To best communicate the data, the anomalies should reflect the amount of warming that has taken place. For that reason, the full 20th century average (which is very similar to 1951-1980) would be my preference when it comes to the surface based temperature datasets.

Is the weather in June getting worse?

June 2016 was the 11th wettest on record for the UK as a whole (records from 1910) and the third in the last decade to see >100mm of rain (2007 and 2012 being the other two, notably the top 2 wettest in the record). There hasn’t been an ‘outstanding’ June in this period either, the warmest being 2010 at around 1°C warmer than average.

British summers are on average, not fantastic – the long term average England and Wales summer rainfall (228.7mm) isn’t significantly different (95%) to what is seen in winter (235.5mm), with the much drier (184.0mm) spring season probably quite confusing for public perception.

Table 1: Some statistical analyses of the EWP record (MAM 1766 onwards). Values in mm.


Therefore, it’s not as though we’re expecting something amazing given the historical precedent. But, the following question arises:

  • Given the 3 very wet Junes in the last decade, is the month getting ‘worse’?

I’ve been asked this rather often. It’s of particular interest this year, because it’s 40 years since the record-breaking “long, hot summer” of 1976 which is heavily ingrained in the public perception of British summers. It was the warmest summer on record for the UK and is the only record-holder for a UK season from outside the current climate “normal” of 1981-2010 (DJF 1988-89 being the oldest), whilst June 1976 was the warmest on record for the UK (mean temperature) and also holds the record for highest average maximum temperature on the CET running from 1878.

Let’s look at some temperature statistics. I’ve chosen maximum temperatures as they are probably what most people pay attention to in summer, as opposed to overnight minima in winter.

June UK Max T

Figure 1: UK average maximum temperature time series for June, 1910-2016.

Fig.1 shows no statistically significant long-term trend, and there’s not much visible by eye either suggesting not much has changed. However, by closer inspection it appears the ‘volatility’ of recent Junes has decreased – in the earlier part of the record there seem to be wild swings from warm to cold extremes from one year to the next, something apparently absent since the 1990s. A quick statistical measure is standard deviation – from 1910 through 1994, this was 1.22°C, whilst since then it has been 0.95°C. It’s a little unfair to pick different length time periods, but I chose 1995 as the divider as it marked the change of the AMO to a warm phase, which has been shown to impact UK summer weather (Sutton and Dong, 2012).

June SD Variation

Figure 2: Variation in decadal running standard deviation for UK June avg. max temp.

Fig. 2 does the standard deviation analysis a bit better, and it’s apparent that the current variation is at a low point for the dataset, and follows a highly volatile period in the mid 20th century. There is no significant trend through the full period (though it’s obvious we’d have one if we went from peak to trough!).

Recap: June’s maximum temperatures haven’t done anything special in the last few decades, but have been rather clustered year-on-year, without extremes.

Performing the same analysis for rainfall, we see that there’s a large number of wet Junes recently (Fig. 3) and an increase in the decadal running standard deviation (Fig. 4) reaching the maximum value in the entire record.

June Rainfall

Figure 3: UK June rainfall time series, 1910-2016.

June Rainfall SD

Figure 4: As for Figure 2 but for the data from Figure 3.

Therefore, it seems June has moved into a period of high rainfall variability but low temperature variability, with a marked reduction in cooler months. These two can be obviously linked – the wetter Junes are warmer due to excessive cloud cover (and often mT/cT air).

We can wrap this up with a look at sunshine statistics (which began a little later in 1929) to give a full picture. Figure 5 shows this, and it turns out to be the most exciting!

June sunshineFigure 5: UK June sunshine hours time series. Linear trend added (p-value 0.03).

Satisfyingly, I’ve got something statistically significant to say! The slope on the line is -0.28 ± 0.13 hrs/year, and passes at the 95% confidence level. This ties in nicely with the reduced temperature volatility, which would be expected in cloudier, wetter conditions.

Thus, I have an answer: June has become a less sunny month, with extremes of rainfall becoming more frequent. Though the month has seen a reduction in the coolest extremes, it hasn’t seen an increase in the opposite extreme, so yes – it’s got a little ‘poorer’.

As for the why? Well, this could turn into an entire research project at this point – and there are papers exploring it – but the AMO link (and global warming exaggeration…and then don’t forget the Arctic dipole anomaly…) can’t be ignored!

I don’t have an equivalent to the grosswetterlagen record, but the lack of extremes, reduction in sunshine and increase in rainfall suggests a reduction in dominating anticyclones – but that’s for another day.

Long term climate records from the Met Office. Charts and analyses produced using RStudio.