HADCRUT4.6 for June 2018

The CRUTEM4.6 weather station data for June 2018 has just been published, which when combined with the HadSST3 sea surface temperature data forms the global average – HadCRUT4.6. The traditional method for calculating this is by binning all the station data onto a 5 degree (lat, lon) grid and then forming the area weighted average over all populated bins. HadSST3 is already published on a 5×5 grid.

The MetOffice/CRU  result for June is a temperature anomaly of 0.57C, down by 0.03C from May.

I calculate the global average differently, by forming a 3D triangular mesh of all measurements over a spherical surface. The vertices of each triangle is one individual station or one individual SST value. The temperature of every triangle is taken as the average temperature of its 3 vertices. The global average is the sum of all triangular temperatures weighted by their area.The area of each triangle depends on the density of temperature measurements. The main difference to using a 2D (lat,lon) grid is that all the earth’s 3D surface is sampled, including the poles.  Cowtan and Way cover the full 2D surface by using a 2D kriging interpolation to extend HADCRUT4 data into polar regions . I think my method is neater because the only assumption made is that the earth is a sphere and has a well behaved temperature distribution. Both methods agree almost exactly, as we shall see.

My result for June 2018 is 0.66C, which is up 0.05C from May.

Comparison of 3 different methods of calculating the HADCRUT4 global monthly average temperature anomaly.

There is an almost perfect agreement between the spherical triangulation method and Cowtan & Way, (they have yet to publish their results for June). Shown below are the 3D  spatial temperature distributions from the spherical triangulation.

Northern and Southern hemispheres

Antarctica (in winter) was warmer than normal, but the rest of the southern hemisphere is about average or cooler that the ( 1961-1990) normal. The most noticeable feature globally is the strong hotspot over northern Siberia with warmth passing across the US, the Atlantic and Europe, while Northern Scandinavia, Greenland and Labrador are much cooler than normal.

East – West

Temperatures across Northern Siberia stretching south as far as China are up to 10C warmer than normal.  The heat waves over Europe, the Middle East and North Africa look almost minor in comparison!  The Pacific is shows a weak la Nina pattern, while South America is much cooler than normal.

The large scale picture of a gradual warming trend of course remains the same.

Last 140 years of Hadcrut4

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UK Heatwaves and Climate Change

The UK is experiencing a prolonged heatwave which could exceed that of the exceptional 1976 summer. It is an “Endless Summer” – like that surf movie. So is climate change to blame?

Climate Change is happening but what that really means is that whenever a heat wave occurs it will likely be 1C warmer than it would have been 100y ago. It does not imply that heatwaves will occur more often. In other words a record temperature of 35C in 1930 might now become 36C now and perhaps even  37C by 2100. Having said that, most of the observed warming occurs a night (minimum temperatures are rising faster than maximum temperatures)

Of course all this depends on exactly how you define a heatwave. This is much easier for the UK because normally we have cool summers with lots of rain. Those who can afford to escape the misery by taking a package holiday to Spain instead. Last year (2017) was a classic example with loads of rain and average temperatures just over 17C.  I would define a UK heatwave as a period of at least six weeks with hardly any rain, with daily sunshine and high ( > 26C) maximum temperatures.  There have been 3 such summer heatwaves in the last 50 years. Here they are:

June Temperature anomalies 1976

1976 was an exceptional summer. The first rain was the day I got married 28th August just as we were leaving the church, although it cleared up later! The heat was restricted to Western Europe though.

August 2003. There were extreme temperatures in France.

2003 saw record high temperatures especially in France.

June 2018

2018 is shaping up to be an exceptional summer for the UK. At the time of writing we only have data for June this year, but it seems likely that July will be warmer still. This is also why I show comparisons with 1976 also for June. August 2003 was the hottest month for Europe.

AR5 chapter 2 claims there is evidence of an increase in heatwaves in Europe, but they don’t define what a heatwave is. It seems to be the number of days temperatures exceed some threshold which I would indeed expect to increase, but that is not what I call a heatwave. It is true that Europe has been warming. This is what I calculated by using my triangulation method for Europe’s temperature anomaly (same as used for the plots above).

Global (red) and Europe (blue) temperature anomalies

Europe seems to have warmed slightly faster than the global average since 2000. Therefore you would expect the number of days above a certain threshold to increase, but these are still not heatwaves. Heatwaves are the result of a particular weather pattern with high pressure extending over the UK caused by a weak Jet stream  lying north of mainland UK. The heat which would normally migrate to the north gets trapped below it. In fact Greenland and Labrador are far cooler than normal as a result. It is actually snowing in Labrador!

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Has Gaia really been explained?

I was interested in a new paper which claims to be able to explain the Gaia hypothesis, first proposed by James lovelock, that life stabilises the earth’s climate.  The paper is described in an article in the Conversation. The paper itself is here.

Life has existed on Earth for the last 3.7 billion years during which time the sun’s output has increased 30% while the atmospheric content has changed dramatically, determined by life and geology. Lovelock proposed a simple ‘Daisy World’ model of white and black daisies to illustrate how life could regulate temperature by changing surface albedo. This new paper takes this idea much further by generalising to an ensemble of species and environments. Each species is best adapted to a particular set of environmental parameters where they flourish and struggles far outside this optimum. Their interaction with the environment is such as to maintain these ideal set of conditions.  The model assumes a Gaussian like distribution about these optimum conditions. There is then a competition between species, and external astronomy and geology which selects who survives and which species preferred environment wins out over time. They call this model “sequential selection”. It  is illustrated in their Figure 1. below.

The figure shows a hypothetical interaction between 4 species as the environment changes (eg. Solar increases). Life acts to dampen change as 4 species flourish and then die off. Environmental variable E could simply be temperature.

This mechanism can only work if each species interacts with its environment so as to dampen changes from its preferred value, i.e. it has a negative feedback.  If any Species evolves which globally has a positive feedback on an environmental variable, then it will quickly drive itself to extinction. This is where we find a bit of politics creeping into the article, because what is implied is that humans, despite our success, are nevertheless driving temperatures beyond the optimum value for our species.

What is true is that we are releasing a fraction of buried organic carbon back into the atmosphere over a relatively short time span, after which the atmosphere will slowly recover.  The effect on climate and on other species will be negative in some places and perhaps even positive in others. As a result these other species will begin to react to these changes so as to counterbalance this increase in CO2. Plants are an obvious example.

I don’t think “sequential selection” is really a fundamental breakthrough in understanding Gaia. Instead it is more like an ensemble of ‘Daisy’ like species each with a Gaussian value for its optimum ‘environment’, whose populations acts to stabilises each successive optimum. If one fails (goes extinct) another then takes over, until (hopefully never) none are left and the planet dies.

Posted in Climate Change, climate science, Gaia | Tagged | 5 Comments