Archives For climate change


How can there possibly be a link between a modestly cool month in Reigate and the earliest start to the melt-season in Greenland, the devastating wild fires in Canada and the seventh hottest-ever global month in succession?

April summary weather statistics for Reigate

  • Average Temp 8.2C
  • Tmax 17.7C
  • Tmin 0.1C
  • precipitation 43.4mm (local Reigate) SE PPT 55mm
  • sunshine 140.4 hours
  • Max wind gust 30mph
  • average wind bearing 199 degrees

Reigate, like the UK as a whole, had a cooler than average April at 8.2C. The town even experienced some unusual snow showers on 26 April in a cool northerly air flow.


The cool month for the UK is in stark contrast to the bulk of the planet which experienced a much much warmer month than average, at over 1.1C warmer than any previously measured April.


Astonishingly, this is the seventh month straight that has brought record breaking global temperature anomalies.  This continuing succession of warm months globally should be of concern to everyone.  More on this below.

Back to the UK… The Central England Temperature came out at 7.5C,  0.4C below average, and the UK mean was even lower at 6.5C, 0.9C below the long term average.

Rainfall was about average in Reigate with around 40mm of rainfall.  The MetOffice SE figure came out at 55mm.

April was sunnier than usual with a total of 140 hours of sunshine.


This continues the trend of drier and sunnier Aprils in the UK in recent years.

The first half of April was unsettled with most of the rain falling associated with low pressure systems and fronts. The second half of April saw an unusual cool period as northern blocking over the Arctic sent cool northerly winds south with attendant sunshine and showers.


Globally April was the warmest ever April on record.  An anomaly of 1.1C sent the Paris target of keeping global temperatures below 1.5C into grave doubt as this is the 7th month in succession to yield much higher temperatures than ever. This is now being dubbed a “Climate Emergency” because of the sudden and rapid increase in global temperature to levels not expected to occur so soon.


The UK / NW Europe was about the only part of the planet, with NE Canada, to record below average temperatures.


The cool spot over the UK  was due to northern blocking (high pressure) over the Arctic. As pressure rose over the Arctic, cold air pushed out into mid-latitudes.


It is a matter of chance where high pressure and low pressure set up that determines where cold polar air penetrates in these northern blocking scenarios.  This time the pattern sent the cold air to the UK and N Europe.  The Northern Hemisphere as a whole saw anomalously low snow cover as a result of incredibly high temperatures elsewhere.


Arctic Amplification, where the northern latitudes experience highest rates of warming, is well documented and of increasing concern to climate change.  It is acting as both a response and a further driving force behind rapid climate change.

Temperatures rocketed over the Arctic this cold season with temperature departures over 3C widely across the Polar regions.  The Greenland ice sheet experienced one of the earliest starts to the ice melt season on record.


Arctic Sea cover also recorded another record low maximum winter extent.

“On March 24, Arctic sea ice extent peaked at 5.607 million square miles (14.52 million square kilometers), a new record low winter maximum extent in the satellite record that started in 1979. It is slightly smaller than the previous record low maximum extent of 5.612 million square miles (14.54 million square kilometers) that occurred last year. The 13 smallest maximum extents on the satellite record have happened in the last 13 years.” NASA 

This is both a response and a further catastrophe for climate change.  As snow and ice melt in the Polar regions there are connections with further warming as darker sea and land surfaces heat up more readily.


This Polar warming itself is connected with a weaker jetstream as latitudinal temperature gradients in the atmosphere decline.  It is temperature gradient, especially in Mid-Latitudes, that generates the driving force behind the jetstream.  A weaker jetstream is said to cause more blocked atmospheric conditions as it meanders with greater amplitude in a meridional pattern that locks in swoops of northerly and southerly winds. More extreme weather is caused as these pressure patterns persist for longer.  Sweeps of warmer air penetrate into the Arctic, melting more ice over Greenland and, for mid-latitudes, cooler dry Polar air leaks out causing damaging late frosts and wild fires.

So, whilst it seems tenuous to connect these far-off events to our own rather benignly cool April, it is still important to think globally when considering how our own weather links to increasingly extreme weather elsewhere.


Forecasting confidence decreases over time

If we are not certain about the weather next week, how can we be confident about climate change predictions 50 or 100 years into the future? The charts below show two predictions about the temperature in Europe.. one was forecast for a day in June 2015, some 198 hours ahead, the other is a prediction for European July temperature by 2100, some 876,000 hours ahead.  If computer model forecasts beyond 120 hours are known to become significantly more unreliable pushed further into the near future, how confident can we be in similar computer models predicting atmospheric conditions some 876,000 hours into the distant future?


Two temperature anomaly predictions for 198 hours and 876,000 hours ahead.

Of course, weather and climate are different things: weather is short term atmospheric conditions over days and weeks and is usually forecast at high resolution over small areas, while climate describes long term weather over decades or more for larger regions or the whole planet.  Nevertheless, much like the computer models that broadcast meteorologists use to issue short range weather forecasts, climate models use equations of fluid motion and thermodynamics to determine the behaviour of the atmosphere and ocean and to project predictions of Earth’s climate into the future. Both short range and long range predictions require powerful super-computers to run similar complex models that ingest millions of real time observations and perform trillions of calculations to produce predictions of atmospheric conditions on a huge three dimensional grid across different surfaces and altitudes, including the oceans.

The atmospheric system is essentially unpredictable.   Even the most powerful super-computer short range weather predictions can become quite unreliable beyond about 120 hours.  This is perhaps why the MetOffice still only widely publish short term forecasts out to 5 days.  It’s also why charts beyond 300hours are sometimes called “Fantasy Island”… they are so unreliable and not to be taken seriously as a forecasting tool on their own.

In the medium range, accurate ten day forecasts are still something of a holy grail and longer range seasonal forecasts arguably remain largely experimental as they are based on the unreliable time-frame of most numerical model output and the application of complex teleconnections and /or the extrapolation of observations from historic analogue patterns. The MetOffice have even put their seasonal long range predictions into obscure parts of their website after notable public failures in past seasonal forecasts, where they still languish today despite huge investment in computer power.  The charts below show examples of MetOffice contingency planner long range forecast information.

Even with a “perfect model”, weather and climate prediction will always suffer from uncertainties due to the immense complexity of the climate system, the chaotic nature of the atmosphere and the simplifications and approximations necessarily built into models themselves.  The ensemble charts below illustrate this growing uncertainty over just a short time scale of a few weeks.  Note the increasingly wide range of possible outcomes from the individual members showing the growing uncertainty as time progresses, and this is in a relatively settled period of weather.

So, if we really cannot be not certain about the weather next week, how can we be confident about related computer model predictions of climate for 50 or 100 years ahead?  To answer this we need to outline the three different types of uncertainty over climate change prediction:

There are three main types of uncertainty over climate change predictions:

  1. Model uncertainty: climate models have to approximate and estimate feedbacks and processes, they do this slightly differently.
  2. Internal variability: weather is chaotic partly due to uncertain internal forcings, like volcanic eruptions.
  3. Scenario uncertainty: future estimates of human behaviour and emissions of greenhouse gases in particular are uncertain

So, do these uncertainties increase over longer time scales thus rendering computer model predictions of climate in 100 years completely unreliable?  The answer is “No”!  Or more precisely, most of these uncertainties actually decrease over time making model predictions of climate in 100 years possibly more reliable than a seasonal forecast for next summer! Time scale and geographic scale are two reasons that can explain why this happens:

  1. Time scale: climate models deal with longer timescales better than short. The chart below shows lines indicating different model output for temperature change between 1850 and 2010. Note the various models (shown as different lines) all reaching a similar overall temperature increase of +0.8C by 2010.

temperature change more certain over longer time scale

Over the long timescale shown above, the model runs all agree on an overall temperature rise of +0.8C due to initial changes in radiative forcing linked to combinations of, for example, increases in emissions of greenhouse gases, changes in solar radiation and frequency of volcanic eruptions etc.  Models confidently handle these changes over long time scales because climate system and model uncertainty both decrease over time..

Now… if we zoom into one part of the chart above the predictive capability of the model is shown to be much more questionable as the lines wiggle about much more over shorter timescales and sometimes go in completely opposing directions.  This shows uncertainty increasing over shorter timescales.


less accurate predictions over a short time scale

On the shorter timescale of decades or less, model uncertainty increases as climate variability over short time scales is naturally large from one year to the next i.e. one year can be colder or warmer than the previous due to internal variability of the climate system (i.e.chaos).  Models don’t handle this small scale short term climate chaos very well!  One model run predicts cooling in a particular decade, while another predicts warming for the same decade.  It turns out that predicting climate change over smaller timescales is more unpredictable than predicting changes over broad sweeps of time! This is because of the internal chaotic nature of the climate system and model uncertainty being greater at this higher resolution. For example, models will handle these short term variables differently: How will ocean heat uptake respond?  What will happen to ocean currents and regional climates? How will snow cover respond?  Will volcanoes erupt? How will cloud cover and type change? … and many more besides.


climate model variables

Despite these transient climatic uncertainties over short time scales the overall direction of change towards a new climatic equilibrium in the long term is confidently predicted by all the models. So… longer timescales are better handled by models than short.


Scenario uncertainties increase over time in long range climate prediction models

The exception to this reduction in uncertainty over time is scenario uncertainty.  Most long range climate model charts include a wide range of predictions.  This wide range is not due to model uncertainty or uncertainties over internal climate variability. Scenario uncertainty is the uncertainty over predicting future emissions of greenhouse gases.  In other words, uncertainty over our own human behaviour in the future, which is historically difficult to predict!  This is the reason why the IPCC charts show several “RCP trends”.  Representative concentration pathways (or emissions scenarios) show a range of human response to the climate crisis… ranging from drastic curbs to emissions and lower growth, through business as usual, to increased emission pathways presumably due to high growth with no curbs to greenhouse gas emissions. These all yield obviously different outcomes.  The uncertainty over human response, known as the scenario uncertainty, increases over time.  Despite scenario uncertainty, each RCP is an accurately modelled temperature change based on changes in radiative forcing, the wide range of results is due to our own unpredictable behaviour more than climate chaos or uncertainties in the models.

2. Geographic coverage

On a long term global scale, climate system uncertainties are reduced while uncertainties increase over how climate change will occur over small geographic regions.  Predicted global mean annual temperature change is therefore more certain than, for example, regional European or UK temperature change in 100 years.  Future climate change on regional scales is more uncertain than on a global scale due to small scale variabilities.


So… prediction of climate change over short time scales and regional scales is more uncertain than predicting longer range changes on a global scale.  Models struggle to resolve climate change at small time scales and small geographic scales. Overall however, longer term climate outcomes are more certain than short term small scale weather action.  Even with the immense complexity of the climate system, computer models can provide confident predictions of future climate within a range of scenarios.  The IPCC quote levels of confidence and certainty for their climate predictions and, even for the end of the century, they claim high confidence in their predictions ranging from “likely” to “more likely than not” for various scenarios.


IPCC AR5 report on confidence in computer model temperature predictions


the range of climate predictions will hit the probable climatological outcome

In conclusion, maybe this analogy might help: Perhaps climate prediction is a bit like a football match: complex uncertainties about precisely where the ball will go during the game are perhaps completely impossible to forecast beyond the first few seconds of the game.  Any detailed minute-by-minute action on the field thereafter becomes increasingly uncertain over time as countless variables come into play, including some chaos.  For example, individual player performance on the day, how the players and teams interact, the chaotic nature of the ball, the nature of the pitch… these are internal variables that make it almost impossible to model accurate step by step action of a game perhaps beyond the first few kicks after the whistle blows.  This is why small scale high resolution weather forecasts are still limited to less than a week ahead.  Nevertheless, despite such short term uncertainty the overall score and outcome of the game is still possible to predict with confidence, particularly within a certain range. The same can be said for long range climate models.

This post has only scratched the surface of climate and weather uncertainty. Please let me know of any errors you spot in this post. Further reading available here:

further reading

Click to access WG1AR5_SPM_FINAL.pdf

Here’s a copy (below) of the IPCC AR5 report that has the juicy bits highlighted for ease of reading!

In essence the IPCC have toned down some of their projections because they recognise that there has been no global warming since 1997, something their models did not expect.  The IPCC believe the 1997 – present day heat is “hidden” in the oceans and will emerge at some point.  They also point out that warming will not be regular and that some of their previous models had “forcing inadequacies” (i.e. modelled temperature rise incorrectly?) and that in some models there was an “overestimate of the response to increasing greenhouse gases and other anthropogenic forcing”.

Read Simon Keeling’s @weatherschool musing on this. here

Read the summary report here…


Climate change is the natural state of the planet. The Earth’s climate has changed dramatically throughout all timescales: the longest geological timescale measured in thousands of millions of years shows frequent dramatic swings between extremely cold ice-house phases and much warmer-than-present greenhouse phases. Over the 4.5 billion years of Earth history there have been five big ice-house epochs where cold conditions have dominated.

Snowball Earth

BIG cold snap

The most extreme example was around 700-800 million years ago when the Earth was totally covered by ice, the so-called “snowball earth”.  Volcanic eruptions probably released the planet from this particular predicament by ejecting vast quantities of CO2 which warmed the atmosphere.  Despite these dramatic deep freeze episodes, for 85% of geological time the Earth has been warmer than it is right now and with much higher levels of carbon dioxide.  For example, 70 million years ago CO2 was eight times higher than now and shortly before that it was twelve times higher.  Only 15% of Earth history has seen cold ice-house conditions.  So the last 2 – 3 million years has been much colder than “average” for planet Earth.  During this time there have been several fluctuations into and out of cold conditions called glacials that have typically lasted 100,000 years.  The interspersing warmer periods are called interglacials and these have usually lasted about 10,000 years.  The cold period of the last 2 million years is popularly known as the Ice Age and more technically termed the Pleistocene.

Dinosaurs: mean but warm

Dinosaurs: mean but warm

The Ice Age itself has been subject to warmer and colder times.  The last really cold snap ended about 10,000 years ago.  Modern human existence has developed entirely in this warmer interglacial period over the last 10,000 years but technically we are still living in an “Ice Age” period, merely a warm bit of it, called the Holocene interglacial.  Until the 1970’s this warm period was expected to be nearing its end, being about 10,000 years since the last glacial ended, and global cooling was the concern in many climate books of the time e.g. Nigel Calder: “The Weather Machine and the Threat of Ice” BBC 1974.
Orbital cycles are one of the possible causes of regular long-term swings in global climate. The orbit of the Earth wobbles and stretches which affects seasons and energy receipt from the sun. These wobbles occur regularly over 100,000 years. Orbital cycles are the “pace-makers” for temperature change and could be argued to trigger change when other factors coincide with it (like location of continents over polar regions, volcanic eruptions, etc).

Pinning one cold Spring on such large scale cycles would be stretching the evidence somewhat: one cold snap certainly doesn’t prove the climate is changing. Nevertheless, when the Earth’s climate decides to change to another phase, the rate of change is often rapid (called step functions). Spot the steep lines in all of the climate charts: these show how temperature change, once underway, can accelerate and “change gear” quite rapidly.   It is the RATE of change happening now that seems to show the Earth’s climate is possibly moving towards a new phase and scientific monitoring seems to suggest this. Moving into a new climate phase could herald a time of more frequent extreme weather like the unusually cold Spring 2013.  Whilst blaming “climate change” for “changing weather” is arguably a tautology and not especially useful, climate change, regardless of the cause, must surely be another prime suspect in the death of Spring 2013!  At least, there is enough uncertainty not set this prime suspect free just yet!

Climate Cluedo!

The cool pattern of winter weather we have experienced in Reigate during February has not been reflected everywhere across the Northern Hemisphere.  Greenland, in particular, has been warmer than usual. Whilst Reigate has experienced Polar air incursions pushing temperatures 2ºC colder than average, Greenland has experienced more frequent warm southerly air masses than usual and it’s HIGH pressure has not developed so strongly this month to keep out the warm air, until recently. The Greenland ice sheet doesn’t usually start melting until April or May (average 1980-2010). In 2013 surface melting has started already in SE Greenland. So, the 2013 Northern Hemisphere winter climate appears to be acting strangely with extreme storms in the USA (Sandy and Nemo), heavy snow in Russia, severe storms in the Atlantic and now the early onset of melting on the Greenland ice sheet being startling reminders that weather patterns have been far from “average”.  Reigate is fortunate to have  escaped any severe weather on this scale!