Category Archives: Global Warming

A “winter heatwave” in a warming world

The final week of February 2019 has been characterised by anomalously warm, record-setting conditions over NW Europe. The United Kingdom broke its all-time maximum record temperature for February on several occasions and at several stations – the previous record of 19.7C from 1998 was obliterated, replaced with a new record of 21.2C (a huge difference of 1.5C, which were it to be replicated in August would see the UK experience 40C). For the first time, the UK experienced 20C during a winter month, and this moved the date of the first recorded 20C forward from March 2nd to February 26th. This was by all counts a “winter heatwave”, in magnitude and duration, and widely produced temperatures which wouldn’t be out of place in summer.

At the University of Reading, we also saw a new all-time (since 1908) record maximum for February – the previous record of 17.4C (which was first tied on Feb 25th!) was replaced with 19.5C on Feb 26th.

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A classic “heatwave” sunset on February 27 from Whitley Wood Road, Reading, after temperatures reached 17.9C. A touch down on the previous day’s 19.5C, but still 0.4C above the old record!

Why was it so warm?

This is a difficult question to answer, but there’s several components which seem to have been required in order to get the atmospheric configuration such that high temperatures were possible over the UK. Here I present a few that I’ve noticed, but there’s likely other finer components, too (these are not necessarily in any meaningful order):

  • Rossby wave train: evident in Figure 1, there is a pattern in the 200 hPa height anomalies suggesting a Rossby wave train propagating out of East Asia and the Pacific has been evident for the last week. This provides the enhanced meridional flow associated with blocking weather regimes. Figure 2 also shows anomalously weak 250 hPa zonal flow in the mid-latitudes, suggesting reduced propagation speeds of weather systems allowing for (and associated with) extended blocking regimes.
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Figure 1: 7-day (20-26 Feb) mean 200 hPa height anomalies from NCEP/NCAR Reanalysis. Apparent Rossby wave trains are shown with superimposed black arrows.

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Figure 2: 250 hPa zonal-mean zonal wind anomalies from NCEP/NCAR Reanalysis for 20-26 Feb 2019. Note the anomalously weak zonal winds in the N Hemisphere mid-latitudes.

  • Extreme eastern USA jet streak & cyclogenesis: the record-setting jet stream winds seen on Tuesday 19th preceded the development of the blocking ridge. This may be associated through the downstream impacts of such extreme winds (Figure 3) – decelerating an unusually strong jet requires a very active jet exit region, leading to strong (anti)cyclogenesis. A series of deep cyclones (Figure 4) developed in the jet exit region, and when combined with other factors aiding their meridional track, the cyclones likely acted to build the downstream ridge, with positive feedbacks, helping to amplify the pattern. HYSPLIT trajectories also suggest some of the air over the UK originated within the extreme jet streak prior to undergoing strong descent, which may have been aided by its unusually strong nature driving unusually strong descent.
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Figure 3: 250 hPa winds on Feb 19th showing a possible downstream impact of ridge amplification over NW Europe.

 

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Figure 4: MODIS view of a 938 hPa cyclone in the central North Atlantic on Feb 20, 2019.

  • Strong adiabatic descent: HYSPLIT back-trajectories shown in Figure 5 reveal the airmass over the UK originated near the tropopause a few days prior, before descending through the depth of the troposphere. This not only adiabatically warms the air (on top of its warm source region), but also dries out the entire column, allowing for strong insolation needed for the sensible heating to generate strong surface warming.
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Figure 5: Ensemble of 84 hour backwards trajectories for air at 1500 m AMSL over London at 12Z Feb 25th based on GFS 0.5 degree data.

  • Anomaly persistence: once established, the block lasted for several days. This allowed for further descent of air which also underwent diabatic warming thanks to the intense radiation under cloudless skies – recirculating around the anticyclone (a similar pattern existed during the summer 2018 European heatwave).

These are the weather components which contributed. They describe the prior and contemporary state of the atmosphere. To relate this to the climate, I’ll draw an analogy. You exeperience a car crash. Why? What I have presented so far would be equivalent to saying “You ran a stop sign”. Now we naturally ask, “what about climate change?”. In my analogy, this is asking, “Were you intoxicated?”. Being intoxicated doesn’t mean you will run a stop sign, and you certainly can do so without being drunk, but it will increase your risk of doing so.

There is no doubt that the configuration of the atmosphere during the last week has been extreme, and primed for producing these warm temperatures. However, in a stationary climate we do not expect to break records with the frequency that we are doing, especially given a lengthening record (e.g. Kendon 2014). Now that we have warmed the mean temperatures, an extreme dynamical perturbation to the mean state (e.g. a monster blocking ridge) will produce an even more extreme temperatures than we would have seen beforehand.

This mechanism is supported by looking more closely at the University of Reading’s weather data record (Figure 6 & Table 1). Similar events, even with similar sunshine, have historically produced cooler temperatures. The recent frequency of extremely warm February temperatures is also evident, and you can also see recent cases of very warm temperatures with much less sunshine than older cases that matched the temperatures but only with strong solar forcing – suggesting, as I mentioned earlier, that it doesn’t take as much of a ‘push’ to equal temperatures which were once close to a “theoretical maximum”, such that now we can obliterate those records with sufficiently unusual large-scale anomalies.

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Figure 6: Data from Reading University Atmospheric Observatory 1957-2019 showing daily maximum temperatures above the monthly 95th percentile and associated sunshine hours. Red indicates February 2019, grey indicates pre-2000, black post-2000. The 2019 record is shown with a red star. Tmax exceeding 16C is selected for further analysis in Table 1.

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Table 1: Data corresponding to the points within the box in Figure 6 plus the 2019 record value.

But sunny, warm weather in February is nice!

Indeed it is – it was my birthday on February 24th, and I never expected to be celebrating it sitting outside! This event didn’t have the same severe impacts as a summer heatwave, but to me it almost felt more disturbing – the knowledge of what this might mean should a similar extreme be generated in the summer months, and that climate change was “eating away” at winter’s very existence. Unusual late winter/spring temperatures mainly impact the natural world which is highly sensitive to temperature and sunshine at this time of year (e.g. Figure 7), and this is why we should care – this could have many wide-ranging impacts on the ecology which supports our existence.

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Figure 7: Blackthorn blossom, complete with Honey Bee (if you look closely), on Feb 23rd in Reading. This blossom is more likely in March and April.

NCEP/NCAR anomaly plots credit https://www.esrl.noaa.gov/psd/map/.

Why deny climate science?

Imagine you are an astronaut who has just returned from the International Space Station and you meet a Flat-Earther… how would you even go about that argument? 

Climate science and evolution are two sciences denied by many. In the case of evolution-denial, a creationist view is faith-based. Those who believe that God made the Universe 6,000 years ago (or equivalent) at least get a religious ‘kick’ out of it. I’m not saying that belief is a good thing (far from it – I think evolutionary science is an incredible human achievement and filled with beauty), but at least I can somewhat understand the mindset that leads to it (or the root of the belief – a religious text).

I cannot say the same for climate science denial. I just don’t understand what motivates it. What is the benefit to the individual? Does it make you feel good to think that all the experts are wrong?

Now, I do what I can to help the environment. I could do much more – I’m aware of the scale of the problem. But I don’t refuel a diesel car or use a petrol lawn-mower and feel riddled with guilt. My scientific opinion on climate change doesn’t follow me around like a dark cloud. I don’t overuse fuel in order to save money, primarily.

When the World Health Organization listed bacon (and other processed meats – of which you probably consume more than you think!) as definitely carcinogenic, I didn’t deny it – I’m not a medical scientist, and I’m sure good science was done in order to reach that conclusion. Equally, when we meteorologists and climate scientists announce that greenhouse gases are causing global warming, I don’t expect non-experts to take issue with that. Whether you act on it is something else, but don’t turn around and say, “Ha! Have you even considered the urban heat island?“. An every-day equivalent would be responding to an F1-trained mechanic informing you that your car needed a new engine by saying “Really? Did you check the oil?”. 

Of course they checked the oil.

In truth, what deniers say to climate scientists is often hurtful, and sometimes very difficult to respond to, purely because of the extent of the misunderstanding – not because we can’t support our science. It’s also plain baffling what some deniers say. When you’re just an excited or concerned scientist doing your thing, experiencing people thowing wild accusations at you is just…bizarre.

So, to all climate scientists – from those currently braving the harsh Antarctic winter, to those dealing with difficult questions from the media, to those who have been sitting coding for two days straight (or more!) – I salute all of you, for everything you deal with.

Going Viral: Some thoughts one week later

Sunday, July 22, 2018, 9:31 PM BST. I put out a relatively simple tweet comprising of two NASA GISS global temperature anomaly graphics – one for June 1976, and one for June 2018. After listening to the media and meteorologists alike comparing and contrasting the current UK heatwave with that of 1976 (something which I had earlier written about here), I felt it necessary to put it into some global context: the planet as a whole is far warmer than it was in 1976 – meaning that regardless of the final ranking of the 2018 heatwave in the UK, it occurred with a different climate background. The heatwave, alongside record-breaking heatwaves across the Northern Hemisphere, is symptomatic of climate change. It has a different meaning in today’s world.

I did not in any way expect the response the tweet gained – with close to 14,000 likes a week later. Initially, I thought it might rile up a few ‘climate change deniers’ (I had a genuine interest in what might get said in response…) but after it surpassed by previous highest like/retweet count within a few hours, I knew something special was happening! I have no real idea of how far and wide the comparison went, as some didn’t relay any credit back to me for the original idea (e.g. a BBC News special “Feeling the Heat” which aired on July 26, and Met Office blog post using their HadCRUT data). Not that it bothers me – they are NASA’s graphics, after all, and I’m just happy to get a conversation going. Special thanks to Leo Hickman of Carbon Brief for helping me keep track of the various media appearances!

I’ve been looking at NASA’s GISS maps for years – the plotting tool on their website is a fantastic way to play around with climate data. Seeing a comparison like 1976 vs 2018 wasn’t surprising to me, but it occurred to me that the public don’t regularly see imagery like that – especially in such a relevant and meaningful way. It told a story. Telling the general public that the globe is X degrees warmer than it was 100 years ago, or showing them a line graph doesn’t really work – hence the success of my tweet and other novel visualisation ideas, such as the ‘climate spiral’ and ‘warming stripes’ by Professor Ed Hawkins – the original climate science viral sensation from the University of Reading! As I stated in the tweet thread, graphics like those I posted shouldn’t be surprising – global warming isn’t new, and the planet has been much warmer (relative to normal) than it is currently (try plotting February 2016 for a real shock).

Perhaps initiated by my tweet, or perhaps a coincidentally, the media – and scientists – quickly began widely discussing the relationship between climate change and the heatwaves across the Northern Hemisphere. The tweet seems to be the reason why the phrase ‘global heatwave’ gained so much use – I have seen it used before my tweet, but my use of that as a hashtag seems to have made it mainstream. It is not meant to suggest everywhere is under heatwave conditions – just that this heatwave is part of something bigger; that the planet itself is warmer than normal (i.e., a ‘heatwave’). It’s perhaps a bit of flippant phrasing which I can understand disagreement with.

However, whilst this has been the best-reported and most clear-cut example of linking climate change to ongoing weather, it did strike me that in some cases it was reported as though this was, in some way, new. A BBC News article from August 2003 (“Heatwave part of global trend”) could have been extracted word-for-word and used in 2018. The story then: a heatwave in the UK, but also deadly heatwaves around the world as global temperatures rose. 15 years later, and the story is the same. Yes, we have come a long way in 15 years in terms of our understanding of the climate, but the story is the same and the expectations are (broadly) the same. How long until it is accepted that the future we predicted is now happening? How long until we stop speaking of ‘heatwaves are expected to become more common due to climate change’? Climate change isn’t something we should continuously speak of in the future tense – it has happened and it is happening.

If you’ve read this far and are still with me, I added some of my ‘in the moment’ thoughts on July 24 to my first post on Reading’s Meteorology PhD blog site, “The Social Metwork”.

Right. What do I tweet next?

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.

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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.

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

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.

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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).

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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.