Central England Temperature Anomalies

The Met Office reports  that 2014 was the warmest year in the 354 year series of temperature measurements in central england. Ed Hawkins also has a post on this.

So is it true and what does it really mean?

CET annual mean temperatures since 1990. The red line is a long term trend fit described below

CET annual mean temperatures since 1990 to 2014. The red line is a long term trend fit described below.

Well 2014 does indeed scrape through  above 2006 as the warmest year, but the quoted measurement error is 0.1C.  So statistically it would be more correct  to say that it is  60% probable that 2014 broke the record. However in this post I want to understand better the full time series and identify a  long term warming trend in CET.

This gives a rather different narrative than the simplistic one of just CO2 induced warming of the UK climate.

Full  354 year series of CET.  A clear warming trend is evident over the full erod. The red curve shows a linear fit to the data

Full 354 year series of CET. A clear warming trend is evident over the entire period. There is little evidence of an acceleration of this trend after the industrial revolution. The red curve shows a linear fit to the data showing a net warming of 0.03C/decode

The data shows that there has definitely been a slow but continuous warming trend since 1660 until the present time beginning well before the industrial revolution. Furthermore there is no obvious evidence of any CO2 induced acceleration in warming as emissions increased post 195o.

So let’s do something a little different and calculate temperature anomalies relative to that long term trend instead of relative to 1961-1990. The result of this procedure is shown below

Temperature anomaly relative to the linear long term trend in CET

Temperature anomaly relative to the linear long term trend in CET

Relative to the 350 year long term trend there is no real evidence for any recent anthropogenic warming. Now let’s simply put a spline through the anomaly data to see if there are  shorter time scale trends.

Spline fit to CET anomaly data

Spline fit to CET anomaly data

There is indeed an apparent upturn after 1970 but nothing that is really remarkably different to that in the 1700s. This is then  followed by a downturn back to normal.

What could be the cause of the evident  slow long term warming trend? Most likely this is due to a recovery from the ‘little Ice Age”

During the so-called “little Ice Age” the Thames was regularly frozen and ice fairs held in winter. The Great Frost of 1683–84, the worst frost recorded in England,[3][4][5] the Thames was completely frozen for two months, with the ice reaching a thickness of 11 inches (28 cm) in London.

The last Ice Fair was held in 1841 because the climate was growing milder well before CO2 levels were of any concern. Since then the climate has become milder. Once  this natural warming trend is included , then the lack of a more  rapid acceleration post 1950 becomes evident.

The distribution of these anomalies results in a normal distribution about a mean of zero. Based on this definition of anomalies against a long term trend, the next plot shows the ranked warmest years in the full series.

Ranked warmest years based on temperature anomalies to long term trends.

Ranked warmest years based on temperature anomalies to long term trends.

2014 is certainly way up there as an exceptionally warm year, but if natural climate trends are taken into account the average temperature is not exceptional. There is therefore  little hard evidence for an anthropogenic warming signal in CET.

I am convinced that enhanced CO2 levels must change the energy balance within the atmosphere so I would expect to see a first  order warming effect . However the complexities of the rest of the climate system on earth are still immense and still full of surprises.

Posted in AGW, Climate Change, climate science, GCM, Institiutions, IPCC, Meteorology, Science, UK Met Office | Tagged , , | 17 Comments

AR5 Attribution Studies

Just how reliable is the IPCC AR5 advice to policy makers?

The recent IPCC report stated that climate scientists are 95-100% certain that the observed temperature rise since 1850 is anthropogenic. The headline attribution statement in Chapter 10 was

“It is extremely likely that human activities caused more than half of the observed increase in GMST from 1951 to 2010.The best estimate of the human-induced contribution to warming is similar to the observed warming over this period.”

World political leaders are basing policy on the validity of this statement, which is entirely based on comparing CMIP5 models to global surface temperature data. These ‘fingerprinting’ studies are described in chapter 10, which I find all but impossible to comprehend. The underlying assumption in AR5  is that natural climate variability has essentially played no role in warming since 1950. However is this actually true ?

Figure 1 shows a comparison between the ensemble of CMIP5 models and observations.

CMIP5 model ensemble compared to obeservations (Hadcrut4)

Figure 1: CMIP5 model ensemble compared to obeservations (Hadcrut4). Is the pause in warming since 1998 natural ?

Agreement until 2000 would appear to be reasonably good. However we then read in Chapter 9 Box 9.1 that in reality:

Model tuning aims to match observed climate system behaviour and so is connected to judgements as to what constitutes a skilful representation of the Earth’s climate. For instance, maintaining the global mean top of the atmosphere (TOA) energy balance in a simulation of pre-industrial climate is essential to prevent the climate system from drifting to an unrealistic state. The models used in this report almost universally contain adjustments to parameters in their treatment of clouds to fulfil this important constraint of the climate system.

So the models are tuned so as to describe past observations. Furthermore periods of cooling are explained by volcanoes which are simulated by something called ‘EMICS’ – Earth System Models of Intermediate Complexity up until 2005. Please don’t ask me what EMICS are but there is also no doubt in my mind that these are also tuned so that  aerosols can then match the global temperature response to volcanic erruptions such as  Pinatubu!

Science of Doom has written a detailed analysis of AR5 attribution studies and even he is not convinced.  He writes:

Chapter 10 of the IPCC report fails to highlight the important assumptions in the attribution studies. Chapter 9 of the IPCC report has a section on centennial/millennial natural variability with a “high confidence” conclusion that comes with little evidence and appears to be based on a cursory comparison of the spectral results of the last 1,000 years proxy results with the CMIP5 modeling studies.

He proposes an alternative summary for Chapter 10 of AR5:

It is extremely likely [95–100%] that human activities caused more than half of the observed increase in GMST from 1951 to 2010, but this assessment is subject to considerable uncertainties.

The pause in warming since 1998 is clearly evident in Figure 1 above. This  pause undermines the statement that natural variability is unimportant. Whichever way you look at it, the lack of warming for the last 18 years must be natural whatever the final explanation may be. So how well do the models actually perform at simulating such natural varaibility. This from Knudson et al. ( again thanks to SoD).

The model control runs exhibit long-term drifts. The magnitudes of these drifts tend to be larger in the CMIP3 control runs than in the CMIP5 control runs, although there are exceptions. We assume that these drifts are due to the models not being in equilibrium with the control run forcing, and we remove the drifts by a linear trend analysis (depicted by the orange straight lines in Fig. 1). In some CMIP3 cases, the drift initially proceeds at one rate, but then the trend becomes smaller for the remainder of the run. We approximate the drift in these cases by two separate linear trend segments, which are identified in the figure by the short vertical orange line segments. These long-term drift trends are removed to produce the drift corrected series.

In other words, any ‘natural’ trends generated by models in the temperature data are assumed to be an artifact and simply removed.

Knutson et al. Figure 1:

Knutson et al. Figure 1:

Five of the 24 CMIP3 models, identified by “(-)” in Fig. 1, were not used, or practically not used, beyond Fig. 1 in our analysis. For instance, the IAP_fgoals1.0.g model has a strong discontinuity near year 200 of the control run. We judge this as likely an artifact due to some problem with the model simulation, and we therefore chose to exclude this model from further analysis

This certainly does not sound to me that the CMIP3(5) models are correctly simulating natural variability. Many models  have drifts which are assumed to be anomalous and need to be corrected into zero dependency. Then any resulting model structure is discarded as being an artifact. However  the observed cooling from 1940-1970 and the pause in warming post 1998 are certainly not artifacts, so why reject those models that produce something similar? The drifts and structure of these models are of the same order as observed warming. Do models correctly simulate the actual climate or do they just simulate the anthropogenic component? The AR5 attribution study depends critically on them being able to simulate both anthtopogenic forcing and natural variability. This is clearly evident from Fig 10.5 in chapter 10.

Fig 10.5 from AR5. ANT is the net anthropogenic forcing. I do not understand how the ANT errors get smaller after adding GHG and OA together !

Fig 10.5 from AR5. ANT is the net anthropogenic forcing. I do not understand how the ANT errors get smaller after adding GHG and OA together !

Now suppose there actually is a natural 60 year oceanic heat oscillation present – AMOC as described by Chen and Tung. This would necessarily imply that there has been a natural warming component of magnitude of about 0.2C since 1950. This is also  clearly visible in a simple fit to the Hadcrut4 data including such a term.

Figure 1. A Fit to HADCRUT4 temperature anomaly data

Figure 1. A Fit to HADCRUT4 temperature anomaly data

In this case the (Internal Variability) term in Figure 10.5 turns out to be  non-zero and the result now looks rather different. The models now run way too warm as shown below.

Updated Fig 10.5 This shows the attribution of warming from 1950 to 2010 where natural internal variation is measured by comparing  1940 to 2010 as the correct measure of the observed warming  because 1940 and 2010 are peaks of the  natural variation.

Updated Fig 10.5 This shows the attribution of warming from 1950 to 2010 where natural internal variation is measured by comparing 1940 to 2010 as the correct measure of the observed warming because 1940 and 2010 are peaks of the natural variation.

The anthropogenic term ANT is now no longer in agreement with the observations and the attribtion statement should be modified to account for the non-zero natural component. As a consequence it becomes clear that CMIP5 models are running about 50% too hot. Therefore the attributrion statement should  now probably read instead.

“It is very likely that human activities caused about half  of the observed increase in GMST from 1951 to 2010. The best estimate of the human-induced contribution to warming is 55% of the observed warming over this period.”

This could also explain discrepancies in the spatial distribution of warming. In general models and data agree fairly well  that most warming occurs over land and arctic regions. However van Oldenborgh et al.  show there is significant disagreement mostly over the oceans, overestimating warming in the northern Pacific and underestimating warming in the southern tropical oceans. Figures 4 and 5 show simple CMIP5 modle comparisons for the two hemispheres.

CMIP-NH

Comparison of CMIP5 models for Northern Hemsiphere temperature anomalies with Hadcrut4

CMIP-SH

Comparison of CMIP5 models for Southern Hemisphere with Hadcrut4

The southern hemisphere is dominated by oceans and warms slower. Overall the spatial agreement on a grid spacing level is fairly good except for the last 15 years. However there are discrepencies both in overestimating warming in about one quarter of the world and underestimating it in  about one third.

WG1 Box 9.2 AR5 admits that “Hiatus periods of 10/15 years can arise as a manifestation of internal decadel climate variability, which sometimes enhances and sometimes counteracts the long term forcing trend” followed by a long explanation as to why this does not affect ever increasing confidence in climate models.

I am not convinced – nor do I suspect are some of the authors of AR5. One can only imagine the intense pressure that has been placed on them to increase the certainty of human warming, thereby maintaining  the various green/governmental interests and funding lobbies for another 4 years.

I wonder who will eventually jump first  ?

 

 

Posted in AGW, Climate Change, climate science, IPCC, Science | Tagged , , | 10 Comments

CO2 Thermagedon ?

What is the worst damage that increased Carbon Dioxide could possibly cause on earth?The  answer is  surprisingly little  (ignoring hypothetical ‘feedbacks’) !

CO2 greenhouse effect for concentrations up to 0.1 C. Shown are the direct surface temperature responses under business as usual.

CO2 greenhouse effect for concentrations up to 0.1 %. Shown are the direct surface temperature responses under ‘business as usual’ policies  untileventually  fossil fuels are exhauted.

So now let’s imagine the most extreme case possible. What   if CO2 levels were somehow to rise 300 times higher than current levels reaching crazy levels like 10%? Just how hot would the earth then get ?

Saturation of the narrow CO2 15 micron lines into the Stratosphere ensures that total greenhouse warming is limited to 13C.

Saturation of the narrow CO2 15 micron lines into the Stratosphere ensures that total greenhouse warming is limited to 13C.

 

So really not so bad after all! The maximum possible CO2 greenhouse effect on earth is about 13 deg. C.

These calculations are based on a line by line ‘radiative transfer’ code covering the  dominant 15 micron absorption band described here.

So what is the problem of anthropogenic global warming – if any?

For 99.9% of earth’s 4 billion year climate history CO2  never has been a problem. On the contrary CO2 has helped to keep the earth’s temperature just right for life to flourish. In reality CO2 is a wonderful stabilising feedback that counteracts  external  ‘dangerous’ forcings on climate, and will allways to do so as long as life continues to flourish.

CO2 levels in the earth’s atmosphere normally react to changes in climate. They naturally regulate atmospheric CO2 by  responding to changes in ocean temperature. It is basically only now  that CO2 levels have increased before temperature, with the possible exception of the Paleocene–Eocene Thermal Maximum (PETM) event 50 million years ago. Anthropogenic CO2 ‘climate change’ is less than a blink in the eye.

Geological  evidence shows that during the PETM, CO2 levels rose by about 3 times more than the most pessimistic levels imaginable today, even  if humans were to burn all available fossil fuels on earth. Yet during PETM  temperatures only rose by just 5C. Furthermore it is entirely possible that the PETM excursion in CO2 levels was not due to some volcanic belch of CO2,  but instead was also the result of some external astronomical forcing such as a supernova, which CO2 levels then reacted to as a response.

So we need to keep things in perspective regarding (catastrophic) anthropogenic climate change. Yes human activity will most likely result in some small warming but its effect will naturally be  rather limited.

It may even turn out to be a blessing in disguise because increased CO2 levels now may likely delay the onset of the next ice age which otherwise is due to start around now. Another ice age would be orders of magnitude more catastrophic.

 

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