Are the warm years in the UK since 1988 caused by a high incidence of warm weather patterns or global warming?

By: Andrew Masterman  andrew@usefulinfo.co.uk   8 May 2004

An independent, voluntary and objective assessment of climate change in the UK

The rationale for AGW scepticism is to seek the truth about whether anthropogenic global warming or natural climate variability is the cause of recent global warming and to increase scientific understanding of climate change.

and

In this era of alleged "man-made" climate change where increased greenhouse gas forcing is considered to be the overriding climate factor accounting for "most global warming in the last 50 years", the following theory is heretical but it's redeeming feature is that it is devastatingly logical: warm weather is caused by warm weather patterns and cold weather is caused by cold weather patterns
 

SUMMARY

1. A high incidence of Warm Weather Patterns (WWP) is the overriding causal factor of the high temperatures in the UK since 1988.
2. High northern hemisphere temperatures are of secondary importance but undoubtedly contribute to the high UK temperatures of recent years.
3. The high incidence of WWP since 1988 is associated with the positive phase of the winter North Atlantic Oscillation (NAO) which commenced in 1988/89.
4. A review of recent research into the NAO shows that there is no consensus on which atmospheric processes drive NAO variations which means the magnitude of natural variability in winter NAO is unknown.  This means distinguishing changes in the winter NAO due to Anthropogenic Global Warming (AGW) from changes caused by natural variability is impossible but climate change scientists have nevertheless concluded that  "most authors agree that greenhouse gases are likely to be at least partly responsible for the long term trend in the boreal winter NAO index". And this is in spite of evidence from paleoclimate reconstructions of winter NAO which show that "neither the recent, highly positive NAO index values of the 1990s, nor the change from the low index values of the 1960s appear to be unique in the context of longer records".
5. A shift to a negative phase of the NAO is suggested by the weather patterns observed during winters 2003 & 2004 and the winter NAO is clearly no longer increasing but decreasing. This is likely to result in a lower incidence of WWP and a higher incidence of Cold Weather Patterns (CWP) in the UK and Europe during the next few decades.
6. CWP appear to be the causal factor of the lower UK temperatures during the 1960s, 1970s and most of the 1980s. This is at variance with the sulphate aerosol theory advocated by climate change scientists for the lower global temperatures during the 1960s & 1970s.
7. UKCIP02 which is the government report on recent climate change in the UK and future predictions does not attribute the recent run of warm years in the UK to natural variability favouring WWP and does not highlight the link between WWP and the positive phase of the NAO since 1988. This study argues that these omissions are inappropriate and surprising for a scientific report on the UK climate and that a characteristic of the IPCC and the UK Met Office (UKMO) to underrate natural climate factors and to exaggerate the importance of anthropogenic ones is the likely explanation.
8. UKCIP02 does highlight the importance of natural variability in its predictions of UK climate in the twenty first century and advises that year-on-year warming is not likely as there will be cooler periods as a result of natural variability. And this is in fact consistent with the conclusion of this study that a higher incidence of CWP in the UK and Europe is likely during the next few decades.
9. There is a conspicuous inconsistency between the IPCC/UKMO claim that "most global warming over the last 50 years is due to greenhouse gases from human activities" and the fact that the two most important natural modes of climate variability, El Nino-Southern Oscillation & the NAO,  have both favoured higher global temperatures during the last few decades. And climate change research has not conclusively shown that AGW is affecting either of these natural modes of climate variability although there has been considerable speculation in the case of the NAO.
10. The AGW sceptic argument is essentially that natural variability in climate favouring WWP probably accounts for most of the global warming of recent decades and that climate change scientists may be interpreting this natural warming as AGW. This study has shown this argument to be true for the recent warming in the UK and Europe where recent warming owes to natural variability favouring the positive phase of the winter NAO. If this argument is true for the globe as a whole, it implies that AGW is being exaggerated by IPCC/UKMO in their claims that it is the main factor causing recent global warming and therefore any future global warming in the twenty first century is probably being overemphasised.

ACKNOWLEDGEMENTS

The methodology used in this study is essentially the same as used in the two following papers: Murray & Lewis (1966) and Murray & Benwell (1970) in which PSC indices are introduced and a method of relating them to CET presented. In this era of alleged "man-made" climate change, these methods offer a powerful tool for testing for a warming of LDWTs. Tribute is also due to the late Professor G. Manley whose life time work was the construction of the CET record which gives an invaluable insight into climate change in the UK over 300 years and also to the late Professor H. Lamb who classified daily synoptic weather charts back to 1861, thereby providing a valuable synoptic history for the UK.

The datasets are maintained and made publicly available by the Hadley Centre of the Meteorological Office and the Climatic Research Unit of the University of East Anglia:

Hadley Centre:  CET              Climatic Research Unit:  LDWT.

CONTENTS

1. INTRODUCTION

It is stating the obvious that the weather on a particular day is largely determined by the weather pattern, i.e the wind direction and whether or not a depression or anticyclone is over the UK. For example in summer, anticyclones give long hours of sunshine and high temperatures during the day whereas low pressures bring cloud and rain and consequently low daytime temperatures. Furthermore in all seasons, southerly winds bring higher than average temperatures while northerly winds bring lower than average temperatures.

With respect to climate change in the UK, there have been significant changes since 1988 which include higher than average temperatures (UKCIP02) but there are at least two major factors which may account for these changes. The first potential explanatory factor is an increased incidence of weather patterns which bring higher than average temperatures: this factor is referred to as warm weather patterns (WWP). The second potential explanatory factor is warming in the atmosphere/globe caused by one or both of the following:

(i) an increased greenhouse effect within the atmosphere owing to higher concentrations of greenhouse gases – so called Anthropogenic Global Warming (AGW)
(ii) natural factors favouring higher global temperatures (i.e natural variability in global temperatures) such as increased solar activity and changes in regional atmospheric circulations.

This second factor is referred to as Global Warming (GW) which logically ought to cause a warming of weather associated with all weather patterns. Unfortunately, these two explanatory factors cannot be completely separated from each other as GW itself may cause a change in the weather patterns around the UK: this is what climate model studies of the effects of GW on the UK climate predict eg UKCIP02. This study attempts to identify both WWP & GW as causes of warming in the UK climate in recent decades and to rank them in order of importance.

To understand the AGW theory, the idea that the atmosphere moves around the Earth like a fluid in motion needs to be acknowledged. While it is true that the UK landmass is an island, this geographical isolation does not apply to the atmosphere over the UK. The atmosphere is shared by the whole surface of the Earth as it is constantly in motion. The air UK citizens breathe into their lungs today may have been over 500 miles away yesterday depending on how mobile the atmosphere is across the UK. The importing of atmosphere from other parts of the globe is shown diagrammatically on weather charts by the warm and cold fronts of Atlantic depressions. Behind a warm front (denoted by red semi-circles), the airmass is referred to as tropical maritime as it originates in the tropical Atlantic and is consistently warm high up into the atmosphere resulting in a very shallow decrease in temperature with height. Behind a cold front (denoted by blue triangles), the airmass is referred to as polar maritime as it originates in cold polar regions and temperature falls rapidly with altitude as the high sea surface temperatures significantly warm the lowest levels while the air remains very cold at higher levels. Atlantic depressions effectively bring to the UK the atmosphere from regions up to a few thousand miles away, from both the north and south Atlantic and mix them together. This high mobility in the atmosphere is why the warming from AGW is expected to be global even though the greatest warming is expected in polar regions: any warming within the atmosphere caused by higher concentrations of greenhouse gases would be transferred all around the globe by the atmosphere itself through the movement of weather systems.

This study is a continuation and development of a study the author completed 1 March 2003: UK Climate Change since 1881 and the 1989 to 2002 warm period in detail.

 

2. METHODOLOGY

The logic of this study is that it is possible to retrospectively predict a month’s mean temperature (in the UK) using data which describe the weather patterns which occurred in this month (Murray & Benwell, 1970). This permits testing for a change in the UK climate owing to GW as weather associated with specific weather patterns ought to become warmer as the temperature of the atmosphere/globe rises.

First, an introduction to the Central England Temperature record is required.

 

2.1 Central England Temperature (CET)

The construction of this temperature record which extends back to 1659 was the lifetime work of Professor Gordon Manley (Manley, 1974). By searching for historical weather records in libraries and other places, Professor Manley obtained a number of temperature records from various locations  in the central England area (triangle approximately bound by London, Bristol and Manchester) of varying lengths. By comparison of overlapping records, the reliability of any individual record could be assessed and any cool or warm bias determined. Further checks involved comparison with other historical records in western Europe. The result is the longest instrumental temperature record in the world which is representative of the central England/English Midlands region. An important issue to bear in mind when viewing the full CET record is the Little Ice Age (LIA) which is well known for periods of lower temperatures, particularly colder winters in Europe . Recent studies (Jones & Briffa, 2001) have suggested that the LIA is not the several centuries long cold period which is popularly believed but was characterised by colder periods sometimes up to several decades separated by periods with more normal temperatures. Moreover, these colder periods occurred at different times in various regions around the northern hemisphere. For example, the seventeenth century was coldest in Europe while the nineteenth century was coldest in north America . In relation to the CET (Figure 1), the record up to 1850 is considered to be within the LIA and it is evident that some years were much cooler in this period compared with the twentieth century. Therefore, a presumably non anthropogenic factor which accounted for the LIA also accounts for much of but not necessarily all of the warming since 1850. An important point to note is that climate scientists do not ascribe all the warming of long temperature records like the CET to AGW but to a number of natural factors plus any anthropogenic effect. The CET is maintained by the Meteorological Office's Hadley Centre for Climate Prediction and Research.

Weather patterns around the UK can be described using the Lamb Daily Weather Types.


 

2.2 Introduction to the Lamb Daily Weather Types (LDWTs) and PSC Indices

The LDWTs (Lamb, 1972) provide a refreshing alternative and a more holistic measurement of weather variations around the UK compared with conventional weather measurements such as air temperature and rainfall. We are all familiar with synoptic weather charts for the UK area from TV and newspaper weather forecasts which show the positions of depressions (low pressure areas) and anticyclones (high pressure areas) using isobars which join areas of equal atmospheric pressure at sea level.  Lamb (1972) classified daily weather charts of the UK area back to January 1873 with one of the 27 LDWTs (Table 1).  There are eight directional types each subdivided into three categories according to the curvature of the isobars: for example, westerly is subdivided into cyclonic (low pressure) westerly, straight westerly and anticyclonic (high pressure) westerly. The remaining three types are non-directional: cyclonic when a low pressure centre is located over or close to  the UK;  anticyclonic when an anticyclone is over or close to the UK; and unclassifiable (U) when none of the preceding 26 types applies (14 U days a year on average).  Timeseries of annual and seasonal totals of Lamb types can be viewed here.



 

Table 1  The twenty seven Lamb daily weather types.

                                                                                              Curvature of   Isobars
                                                                         ______________________________________

An imperfection of Lamb's classification is that it is subjective. Jenkinson & Collinson (1977) devised a method for objectively deriving weather types from daily grid-point mean sea level pressure data of the UK region.  Jones, Hulme & Briffa (1993) used this method to generate objective Lamb types back to December 1880 and demonstrated that the objective types were highly correlated with Lamb's classification. The objective LDWTs are maintained by the Climatic Research Unit.

Working with 27 Lamb daily weather types is quite cumbersome so Murray & Lewis (1966) devised the PSC indices to measure in a succinct and meaningful way the main characteristics of the synoptic situation around the UK over long periods using the LDWTs:

P is the index of progressiveness and measures the difference in frequency of days of progressive and blocked synoptic types over the UK. It is positive when there is a bias towards progressive types. Progressive types are westerly, northwesterly and southwesterly types while blocked types are the other directional types. Click here  to see how the P index is calculated and here for data 1881 to 2003.

S is the index of southerliness and measures the difference in frequency of southerly and of northerly type days over the UK. It is positive when the bias is southerly. Click here  to see how the S index is calculated  and  here for data 1881 to 2003.

C is the index of cyclonicity and measures the difference in frequency of cyclonic and anticyclonic type days over the UK.  It is positive when cyclonic days predominate. Click here  to see how the C index is calculated  and  here for data 1881 to 2003.

For example, the indices for January 1989 were: P 62; S 11 & C -10. January 1989 was a month with an exceptionally high number of days with westerly winds and therefore the P index was very high at 62: in fact joint highest with 1916 in records going back to 1881. The S & C indices of January 1989 were not exceptional and needn’t be discussed any further. The CET in January 1989 was also high at 2.3 C above the 1961-90 average. The relationship between the P index in January and CET is shown in Table 2 together with correlation coefficients between PSC indices and CET in each month of the year.



 

Table 2 Correlation coefficients between monthly PSC indices and monthly CET 1881-2002.

^* correlation significant at 5% level;    ^*** correlation significant at 0.1% level

 

Table 2 shows that there is a highly significant positive correlation between the P index in January and January CET i.e high temperatures in January are associated with a high number of days with westerly winds. This is because westerly winds bring Atlantic warmth across the UK during winter months.

Another example is August 1976 which had the following indices: P -37; S 3; C -40. The low P index denotes westerly winds were rare and in summer months, westerly winds bring cool & unsettled weather denoted by the negative correlation coefficients in Table 2. The S index was unremarkable in August 1976 but the very low C index denotes that anticyclonic weather patterns were very persistent. And anticyclones in summer of course bring long hours of sunshine & high temperatures: August 1976 had a CET 1.8 C above the 1961-90 average.

The two examples (January 1989 & August 1976) demonstrate the relationship between anomalous values of PSC indices and anomalous monthly CET. From Table 2, the highly significant positive correlation coefficients for the S index in all months show that high values of S indices (i.e high number of days with southerly winds) occur in months with high values of CET which is unsurprising. In the case of the P & C indices, the relationship with CET changes during the year. The P index is positively correlated with CET from October to May when westerly winds bring higher than average temperatures and negatively correlated with CET from June to August when westerly winds bring lower than average temperatures. The C index is positively correlated with CET from October to February denoting that cyclonic unsettled conditions bring high temperatures in these months while from March to September, the C index is negatively correlated with CET indicating that in these months, unsettled cyclonic conditions bring low temperatures owing to low amounts of sunshine.
 

2.3 Development of models which predict monthly CET using monthly PSC indices

These strong and highly significant correlations between PSC indices and CET make it possible to predict a month’s CET if the PSC indices for the month in question are known. Moreover, to allow the testing of the hypothesis that GW is causing a warming in the UK over and above that which would be expected from a month’s weather patterns, data from recent years were excluded from the data used to construct the models which predict a month’s CET from a month’s PSC indices. These models were used to predict CET for recent years and if the atmosphere/globe is warming significantly, the models would progressively underestimate CET. This is because in a warmer world, the correlation coefficients between PSC indices and CET would be somewhat different which would result in the models becoming less accurate.

The difference between correlations as shown in Table 2 and multiple regression models as discussed below is that the latter include more than one explanatory variable: in this case two or three PSC indices.

Multiple regression models of monthly CET using monthly PSC indices (four combinations) were created using data from the period 1881-1970 and these models were used to predict monthly temperatures from 1971 to 2003.

 

3. RESULTS

For each month, the model with the PSC combination which accounted for the most variation in the CET data is presented in Figures 2 to 13. In these Figures, the red line shows observed CET from 1881 to 2003, the green line shows predicted CET for 1881 to 1970 (the period of data used to create the model) and the blue line shows predicted CET for 1971 to 2003 (the period in which signs of a warming of weather patterns are being sought). The yellow line shows the model error ie the difference between observed and predicted values of CET: observed minus predicted.

Using Figure 2 as an example, if the PSC model was 100% accurate in predicting January CET, the observed and predicted values of January CET would be identical. And such 100% accuracy would imply that variations in weather patterns measured by PSC indices can wholly explain variations in January CET. The title of Figure 2 shows the equation of the model and states that it accounts for 52% of the variation in January CET from 1881 to 1970. While 52% of variation may not sound particularly impressive it is highly significant, and it is clear from Figure 2 that the CET predictions are highly correlated with observed CET confirming that variations in weather patterns are the overriding factor in determining a month’s CET.

To judge whether or not GW is a growing factor in the UK’s climate, the predicted values of CET from 1971 to 2003 (blue line) are the key. Logically, if global/atmosphere temperatures are rising and affecting the UK climate, the PSC model should progressively underestimate CET as this is a new and increasing factor which was not present in the data from 1881 to 1970 used to construct the model.

To assist in the assessment of GW as a factor, the model errors (observed minus predicted CET shown by the yellow line) show whether or not the model is becoming increasingly inaccurate with time which would occur if rising global temperatures are warming the weather associated with each Lamb weather type. However, it is necessary to distinguish between the number of years from 1971-2003 with positive model errors and a trend to increasingly anomalous positive model errors. For example in Figure 2, there were positive model errors in 22 of the 33 years since 1970 indicating that the PSC model has underestimated January CET in the majority of years. This might appear to be clear and equivocal proof that GW is warming Januaries but it is a characteristic of Figure 2 that warmer than average Januaries tend to have positive model errors whereas colder than average Januaries tend to have negative model errors.

To clarify this issue, Table 3 is presented and shows that there is a similar number of occasions from 1971-2003 for each month with positive CET anomalies (i.e above average temperatures) and positive model errors. This suggests that the high proportion of years with positive model errors in Figures 2 to 13 is associated with the high proportion of months with positive CET anomalies and may not be due to an increasing tendency of the models to underestimate CET. The only exception in Table 3 is October where there were only 13 occasions from 1971-2003 when CET was above the 1961-90 average but 26 occasions when model differences were positive. This result for October and to a lesser extent September and the clear long term trend to increasingly positive model errors in these two months (Figures 10 & 11) does suggest a warming of weather types which would be expected from GW.

Therefore, the high number of years with positive model errors from 1971 to 2003 is not a characteristic which suggests GW is warming the UK climate but a trend to positive model errors of greater magnitude would be. Returning to Figure 2 & Table 3, 20 Januaries from 1971-2003 had above average CET and 22 had positive model errors which is quite consistent. However, model errors in recent years are no more positive than in earlier periods indicating that recent years are no warmer than what would be expected from the weather patterns. It is therefore logical to conclude that the mild Januaries of recent years are the result of WWP and GW does not appear to be a factor.

Table 3   Number of occasions each month from 1971-2003 with CET above the 1961-90 average and with positive model errors.

For each Figure 2 to 13, a few comments are listed below:

Figure 2  January CET is well predicted by the model including all three PSC indices and predictions from 1971 do not suggest that Januaries are becoming warmer as a result of GW.

Figure 3  February CET was predicted with impressive accuracy by a model including both the P & S indices. Since 1970, the model underestimated CET (positive model errors) in 20 of the 33 years but model errors are no more positive than in earlier periods suggesting that GW is not causing a warming in Februaries.

Figure 4  March CET was predicted with impressive accuracy by a model including all three PSC indices. Since 1970, the model underestimated CET in 22 of the 33 years and it is noticeable that model errors from 1997 onwards are very positive. While this might suggest that GW is causing a warming in this month, a few years earlier in the record have positive model errors of the same magnitude undermining this argument.

Figure 5  April  CET was predicted with less accuracy than CET in months earlier in the year but again it is apparent that weather patterns are the overriding factor dictating a month’s temperature. Since 1970, the model underestimated CET in 25 of the 33 years but the positive model errors are no greater than in earlier periods which suggests that GW is not causing a warming in Aprils.

Figure 6  May   CET was again predicted with impressive accuracy by a model including all three PSC indices. Since 1970, the model underestimated CET in 21 of the 33 years but it is conspicuous that in a number of years recently, the models have grossly underestimated May CET to an extent not found in earlier periods which suggests that GW may have caused a warming in Mays recently.

Figure 7  CET in June was predicted with less accuracy than in some other months but the model including all three PSC indices was clearly successful in predicting CET in this month too. Since 1970, the model underestimated CET in 18 of the 33 years but the model errors are no more positive than in earlier periods and therefore do not support the theory that GW is causing a warming in Junes. 

Figure 8  July CET was fairly well predicted by a model including the S & C indices. Since 1970, the model underestimated CET in 20 of the 33 years and in a few years, namely 1976 & 1983, the model errors were higher than in any years earlier in the record which might suggest that GW is causing a warming in Julys.

Figure 9  August CET was impressively predicted by a model including all three PSC indices showing that in summer months too, a month’s temperature is largely determined by weather patterns. Since 1970, the model underestimated CET in 20 of the 33 years and there has been a trend to large positive model errors in recent years with a few exceptional values suggesting that GW may be causing a warming in Augusts.

Figure 10  September CET was well predicted by a model including all three PSC indices.  Since 1970, the model underestimated CET in 25 of the 33 years and there has been a trend to positive model errors in recent years with a few exceptional values suggesting that GW may be causing a warming in Septembers.

Figure 11 October CET was well predicted by a model including all three PSC indices. Since 1970, the model underestimated CET in 26 of the 33 years but apart from October 2002 when the model error was very large, the model errors do not suggest that Octobers are being warmed by GW.

Figure 12  November CET was well predicted by a model including all three PSC indices. Since 1970, the model underestimated CET in 23 of the 33 years and it is apparent that since 1993, the model errors have been positive with a few exceptional values suggesting that GW may be causing a warming in Novembers.

Figure 13  December CET was well predicted by a model including the P & S indices. Since 1970, the model underestimated CET in 26 of the 33 years but the model errors are no more positive than in earlier years. However, it is conspicuous that since 1996, the model has consistently underestimated December CET which perhaps suggests GW is warming December weather.

In some months (May; July; August; September; November & December), the large model errors on a small number of occasions do suggest that GW may be a factor in the warming of the UK climate in recent years but the data do not show a clear and equivocal warming of weather types. A better view is obtained if the monthly model errors are combined into one chart. Figure 14 shows the monthly model errors from January 1971 to December 2003 and compares them with monthly anomalies of CET from 1961-90 averages. It is apparent that there is no long term linear trend to increasingly positive model errors since 1970, however since 1988, there has been a change to predominantly positive model errors. What is striking about Figure 14 is that there is a very strong correlation between the monthly model errors and monthly CET anomalies (r = 0.708; P < 0.01) which is an unexpected result and which requires an explanation.

If all 12 monthly PSC models were 100% accurate in predicting monthly CET, all model errors in Figure 14 would be exactly zero. If all 12 monthly PSC models underestimated monthly CET by exactly 1 C, all model errors would be + 1 C.  And if all 12 monthly PSC models overestimated monthly CET by exactly 1 C, all model errors would be -1 C.  In practice, model errors tend to have similar values to monthly anomalies so if a month's CET is close to average, the model error is small but if a month's CET is well above or below average, the model error is much greater and with a similar sign. However, this does not mean that the models always predict average temperatures: Figures 2 to 13 clearly show that the models impressively predict CET in all 12 months albeit with errors.

The means (x) and standard deviations (sd) of the data shown in Figure 14 are: model errors x :0.43;  sd: 1.02;  temperature anomalies x: 0.32; sd: 1.34.  The higher mean of the model errors is surprising given the lower standard deviation and perhaps does suggest a trend to positive model errors of greater magnitude. But Figure 15 shows 12 month running means of monthly model errors and monthly temperature anomalies from January 1971 to December 2003 which ought to show an increasing trend to positive model errors if such a trend in the data exist. What is evident is that since 1997, temperatures have been consistently above average and as a consequence, model errors have been consistently positive confirming the relationship shown in Table 3 and discussed in preceding paragraphs but Figure 15 certainly does not show a clear trend of increasing model errors

Another method of judging the accuracy of the monthly predictions of the 12 models is to sum the 12 predictions in each calendar year and divide by 12 to give a prediction of annual CET.  These are shown in Figure 16 together with observed CET.  UK Climate Change since 1881 and the 1989 to 2002 warm period in detail presented seasonal models (winter, spring, summer & autumn) which predict CET using the same methodology as described in this study. The sum of the four seasonal predictions in each December to November year divided by 4 is also presented in Figure 16.

Figure 16 is very interesting and the main points to note are summarised below:

1. as mentioned above, the 12 PSC models have the characteristic of underestimating CET in months with above average temperatures and to overestimate CET in months with below average temperatures: this means the model predictions (both monthly & seasonal) show less variability than observed CET.
2. there is little difference between the annual CET values predicted by the monthly and seasonal models.
3. in 1989, both model predictions and observed CET rose sharply and most years since then have high observed and predicted temperature values. This indicates that a shift to a higher incidence of WWP in 1989 was the cause of the rise in UK temperatures and WWP are the cause of subsequent warm years
4. there are seven previous years with annual CET predictions as high as those of 1989 & 1990 but in only two of these cases (1920 & 1949) was observed CET well over 10 C compared with ten of the fifteen years since 1988 with annual CET greater than 10 C.
5. it is apparent that previous to 1989, there are three years (1921; 1949 & 1959) with similarly high observed CET as in recent years which suggests that it is the run of very warm years since 1988 which is perhaps more noteworthy than the high values of CET themselves.
6. finally, the CET predictions have been trending downwards since 1989/90 although most years had high values compared with predictions for earlier years but observed CET has remained very high. And it is evident that 2001 was predicted to be an unusually cold year on the basis of the weather patterns but observed annual CET was well above average at almost 10 C.

Judging from point 6) and Figure 16, another factor in addition to WWP is required to explain the persistently high annual CET since 1988.  As discussed in the Introduction, the atmosphere is highly mobile and will bring any global warming to the UK if it is occurring. This theory is supported by Figure 17 which shows the highly significant relationship between northern hemisphere surface temperatures and CET (r = 0.535; P<0.01).

To test the hypothesis that higher global temperature is the missing factor which accounts for the persistently high annual CET since 1988, the development of the 12 monthly PSC models shown in Figures 2 to 13 was repeated with monthly northern hemisphere temperature anomaly included as an additional predictor. In 11 cases (not May), the percentage of variation in monthly CET accounted for by the model was increased by including northern hemisphere temperature anomaly: in the range 1.5 to 7% except in June when the increase was 11%. Figure 18 compares the annual CET predictions from 1881 to 2003 obtained by summing the 12 monthly predictions in each calendar year and dividing by 12 for the two groups of models: those including only PSC indices and those including monthly northern hemisphere temperature anomaly as well. Evidently, the models including northern hemisphere temperature anomalies can account for the run of warm years since 1988 when ten of the 15 years had observed annual CET above 10 C and in general gave more accurate predictions than models including only PSC indices. The equations of these models which include monthly northern hemisphere temperature anomaly (NH) are shown in Table 4. All the coefficients for NH are positive which is expected and confirms the theory expressed in the Introduction that Atlantic depressions bring any GW to the UK. What is interesting is the seasonal change in the size of the NH coefficient: less than 1 in winter months but around 1.5 in summer months. This is consistent with Figures 2 to 13 (models including PSC indices only) which identified that PSC indices (i.e weather patterns) accounted for more variation in CET during winter months. However the coefficients much greater than one in summer months suggests that some positive feedback process enhances the warming effect of higher global temperatures in summer months. This positive feedback process is probably a higher incidence of WWP in summer months in the UK when global temperatures are higher: this is certainly the case since 1988.

Table 4   Equations of models which predict monthly CET which include PSC indices and monthly
 northern hemisphere temperature anomaly (NH).

4. DISCUSSION

Having presented the results, it is now appropriate to focus on the main subjects of this study:

1) to identify both WWP & GW as causes of warming in the UK climate since 1988 and to rank them in order of importance.

2) to test the hypothesis that GW is causing a warming in the UK climate over and above that which would be expected from the weather patterns.

 

4.1 Evidence of WWP contributing to the warming in the UK since 1988

It is obvious that in all months (Figures 2 to 13), the higher than average temperatures since 1988 mainly owes to a high incidence of WWP because the 12 PSC models quite accurately predict CET both before and since 1988. However, there were differences between months in the extent to which year to year temperature variations were predictable on the basis of PSC indices.

The best PSC models were those of February (Figure 3) and March (Figure 4) which accounted for 58 & 65% respectively of the variation in CET 1881-1970 indicating that weather patterns in late winter/early spring have a greater influence on temperature than at other times of the year. This is probably related to the large contrast in temperature between warm airstreams from the tropical Atlantic and very cold airstreams from the continent/Scandinavia at this time of year.

The worst PSC models were those of  April (Figure 5) and June (Figure 7) which accounted for only 27 & 18% respectively of the variation in CET 1881-1970 indicating that temperature in these months was less influenced by weather patterns than in other months of the year. Quite why temperatures in these two months are least affected by weather patterns is not obvious but it is certainly true that the temperature of months in the summer half of the year are less variable than in winter months because insolation is much stronger and this severely limits how low temperatures can fall when weather patterns favour cold airstreams.

 

4.2 Evidence of GW contributing to the warming in the UK since 1988

A feature of some months (March; May; August; September; October & November) was large positive model errors in one or a few years since 1988 which were greater than in any earlier years which is indicative of GW having an influence on UK climate. However, Figure 14 which shows the timeseries of the model errors from January 1971 to December 2003 does not show a tendency for the models to increasingly underestimate CET in recent years. This does not suggest that weather patterns are increasingly unable to account for variations in monthly CET since 1988 which implies that higher global temperature is not a factor in the warming in the UK since 1988. Yet Figure 16 suggests the opposite by showing that according to the weather patterns, annual CET should have slowly fallen since the peak in 1989 & 1990 whereas observed CET has remained at high levels. And Figure 18 shows that GW represented by northern hemisphere temperature anomaly is an important factor in the high annual CET values since 1988. Taking into account these various results, it is reasonable to conclude that although WWP certainly explain much of the higher than average temperatures in the UK since 1988, WWP alone are insufficient to account for the fact that eight out of the last ten years had an annual CET well above 10 C. In conclusion, GW is certainly a significant factor in the high temperatures in the UK since 1988.

 

4.3 Which factor is more important to the UK warming since 1988: WWP or GW?

The overriding importance of weather patterns to monthly CET variations from 1881 to 2003 has been convincingly shown in the various Figures presented above and these results support the opening statement of the Introduction which began “It is stating the obvious that the weather on a particular day is largely determined by the weather pattern”.  While higher global temperature since 1988 is definitely a contributory factor in the high annual CET in recent years (Figure 18), the improvement in the models engendered by including northern hemisphere temperature anomaly was relatively modest: a 1.5 to 7% increase in the percentage variation of monthly CET from 1881 to 1970 explained by ten of the 12 models. And the model errors did not show a clear and equivocal tendency to increasingly underestimate CET in recent years which would be the case if rising global temperature was the overriding factor in recent warm years.  It is therefore correct to conclude that WWP is more important than GW.

Brown (2002) & Brown (2003) analysed the LDWTs and daily values of CET from 1881 to 2000 and tried to assess whether the long term warming in the CET was due to (a) “warm” LDWTs  becoming more frequent (i.e an increased incidence of WWP) or (b) a warming of LDWTs. Brown concluded that “the recent warmth undoubtedly owes something to more favourable weather patterns eg W & SW types have become more frequent in February & March, there has been more of the A type in July and August while northerlies have declined in many months. These fluctuations in weather types appear to contribute between -0.5 and +1.0 C to recent monthly averages. Although the weather types themselves undergo variations in their frequencies, these are insufficient to explain all of the temperature trends”. In brief, Brown concluded both (a) and (b) contributed to both the long term warming in the CET and the very warm years since 1988. Brown (2002) found that spring and autumn months showed the most consistent warming across all weather types and this is in agreement with Figures 2 to 13 which show the most anomalous positive model errors in spring and autumn months.

And UK Climate Change since 1881 and the 1989 to 2002 warm period in detail. concluded that WWP alone accounted for most of the 1989 to 2002 warming and that there was little evidence of a warming of weather types. The results of this study for the UK suggest that the significance of rising global temperatures is being overemphasised and that natural variability which is of a large magnitude over years and decades is being "rebranded" as AGW.

 

4.4 Is GW causing a warming in the UK climate over and above that which would be expected from the weather patterns? 

Figure 18 answers this question very clearly by showing that WWP alone do not account for the high annual CET since 1988 but the models including northern hemisphere temperature anomaly predict very accurately the exceptional high annual CET of recent years.

The fact that both WWP & GW are required to explain the UK warming since 1988 confirms the arguments presented in the Introduction about the overriding importance of weather patterns and about the mobility of the atmosphere and Atlantic depressions  bringing any GW to the UK.

 

4.5 Regional atmospheric circulations, UK weather patterns and global temperatures  

This section attempts to determine whether this strong bias to WWP in the UK since 1988 can be attributed to natural climate factors or to Anthropogenic Global Warming (AGW).

The first issue to note is that there is a large amount of natural variability in UK weather patterns which is depicted in Figure 19 which shows ten year running means of annual PSC indices. It is apparent that recent changes are no greater than in earlier periods: on the contrary, both the P and C indices show rather more variation from 1881 to 1950 than from 1950 to 2003. Clearly, weather patterns have constantly changed since 1881 with each year having a unique sequence of Lamb daily weather types and this confirms the author’s own experience of the large year to year variability in UK climate. It is therefore incorrect for anyone to argue that currently changing weather patterns around the UK are clear proof of AGW. Such statements are simply climate change spin used to support the hypothesis that Man is changing the climate via increasing greenhouse gas emissions. The continuous variability of annual CET (Figure 1) and monthly CET (Figures 2 to 13) is associated with the constantly changing UK weather patterns shown in Figure 19.

Now it is necessary to introduce the subject of regional atmospheric circulations or regional weather patterns. The most famous regional weather pattern in the world is the El Nino-Southern Oscillation Index (ENSO or SOI) which is a measure of the sea level pressure difference between Tahiti in the middle of Pacific and Darwin in northern Australia and is related to Sea Surface Temperature (SST) anomalies in the tropical Pacific (El Nino & La Nina).  The SOI is known to influence the weather in large swathes of the globe including North & South America, Indonesia and Australia (El  Nino Theme Page). Indeed, so widespread are the effects of SOI that global temperatures are correlated with it (Figure 20;  r =  -0.237, P<0.05): high global temperatures occur with negative SOI (El Nino) and low global temperatures with positive SOI (La Nina). While it is apparent that SOI does not account for most variation in global temperatures, SOI was most negative in some years in the first and last quarters of the twentieth century when global temperatures rose sharply in contrast to mid-century when SOI was near neutral and global temperatures were relatively stable. The last paragraph of this article mentions this theory about global temperatures and SOI being correlated and states that the warmest year on record 1998 was associated with an intense El Nino.  Climate Change 2001: the scientific basis confirms the importance of SOI to global climate by describing it as “the strongest natural fluctuation of climate on interannual time-scales” and states “ENSO is generated by ocean-atmosphere interactions internal to the tropical Pacific and overlying atmosphere”.  With respect to the effects of AGW on SOI,   Climate Change 2001: the scientific basis states (in Box 7.2), “ENSO is not simulated well enough in global climate models to have confidence in projected changes with global warming. It is likely that changes in ENSO will occur, but their nature, how large and rapid they will be, and their implications for regional climate change around the world are quite uncertain and vary from model to model”. This means that although the IPCC acknowledges that SOI is a natural factor which does account for some of the GW since 1975, they are unsure whether or not the strong El Ninos of the last 25 years are caused by AGW and are unsure how AGW will affect SOI in the future.

SOI is not considered to have consistent effects on UK weather and climate. However, the fact that SOI affects global temperatures (Figure 20) and that northern hemisphere temperature anomalies affect CET (Figure 18) means El Nino years are likely to be warm years in the UK.

The regional weather pattern which has large effects on the climate of the UK and Europe is the North Atlantic Oscillation (NAO) which is related to the Arctic Oscillation. A brief definition of the NAO is presented in this article while The North Atlantic Oscillation: Climate Significance & Environmental Impact is a recent and detailed study of the subject (preface & Overview/Chapter 1 can be downloaded free). The Overview/Chapter 1 is a PDF file which is 35 pages long so it is quite a carry-on to download and print it out but well worth a read if you want to understand the NAO and its effects. This article is subsequently referred to as the “NAO Study”.  In brief, the NAO can be summarised as two alternative sea-level pressure patterns in the North Atlantic as seen in Figure 9 of  the NAO study:  positive NAO patterns occur when pressure is lower than average in the Icelandic region and higher than average in the Azores region resulting in strong westerly winds across Europe and negative NAO patterns occur when pressure is higher than average in the Icelandic region and lower than average in the Azores region resulting in weaker westerly winds and more variable weather patterns across Europe. Using monthly averaged data for winters from 1900-2001, the 306 months (102 years x 3 months) were allocated to four different patterns of sea level pressure in the North Atlantic: positive NAO in 17% of months; negative NAO in 29% of months; ridge (defined as anticyclone centred over or close to the UK) in 32% of months; and trough (defined as low pressure centred over or close to the UK) in 22% of months. Using these data, 47% of winter months from 1900 to 2001 were characterised by NAO type weather patterns and negative NAO patterns were more common than positive NAO patterns.

Figure 21 shows the highly significant positive correlation (r = 0.662; P<0.01) between the NAO and European temperatures in winters 1900 to 2004. European rather than UK temperatures are shown because there is a stronger correlation for Europe. The more positive NAO in the first 24 and last 11 winters of the twentieth century is apparent whereas negative NAO winters were more common from the 1930s to the early 1980s. The average winter NAO 1900 to 2003 is +0.48 which confirms that the first 24 and last 11 winters had a high proportion of years with above average NAO. This is consistent with Figure 9 of the NAO study which found positive NAO patterns to be less common than negative NAO patterns during winters 1900 to 2001. It is apparent from Figure 21 that although there is considerable year to year variability in the winter NAO, so-called negative and positive phases which persist for several decades are discernible: hence the NAO is referred to as a multi-decadal oscillation. Figure 19 shows ten year running means of winter (Dec-Feb) NAO 1881 to 2003 alongside ten year running means of PSC indices and the positive phase from around 1905 to 1930, negative phase from 1940 to around 1985 and the recent positive phase are obvious.

To demonstrate that the NAO is related to UK weather patterns, Figure 22 shows the highly significant relationship between the P index and the NAO in winters 1881 to 2003 (r = 0.805, P<0.01). Clearly, winters with high numbers of days with westerly winds are associated with positive NAO winters and vice versa which is consistent with the definition of the NAO discussed earlier. In fact years with high P indices tend to follow winters with high P indices (Figure 19) which implies that winter NAO has a knock-on effect on the weather patterns for the rest of the year. This is indicated by Figure 23 which shows the highly significant relationship between mean Europe annual temperature anomaly and the NAO index in the preceding winter 1900 to 2003 (r = 0.538, P< 0.01). This paragraph of the study UK Climate Change since 1881 and the 1989-2002 warm period in detail shows an association between winter and summer weather in the UK which contributes to the relationship shown in Figure 23: warm anticyclonic summers tend to follow warm winters with a high P index (positive NAO winters) and cool unsettled cyclonic summers tend to follow colder winters with a low P index (negative NAO winters).

While the winter NAO is clearly a major factor determining European annual temperatures, it is a characteristic of Figure 23 that annual temperatures in Europe have been very high in recent years and 2003 was another very warm year despite winter 2002/2003 being a negative NAO winter. As was the case with annual CET (Figure 18), high northern hemisphere temperatures are probably a significant factor contributing to the high European temperatures of recent years. This is supported by the improvement in the relationship between Europe annual temperature anomaly and the NAO index in the preceding winter when annual northern hemisphere annual temperature anomaly is included as a second predictor: percentage of variation in mean Europe annual temperature anomaly which is explained was increased to 55% from 25%. 

Having established that variations in the winter NAO largely dictate UK weather patterns, it is now relevant to discuss the causes of  NAO variations. This subject is addressed in detail in the NAO study and the conclusions of several chapters of this study are presented in the next few paragraphs.

Atmospheric processes governing the Northern Hemisphere Annular Mode/North Atlantic Oscillation (Thompson, Lee & Baldwin, 2003) emphatically states that the NAO "owes its existence entirely to atmospheric processes" but go on to conclude that "the absence of a unique theory for the existence of the NAO constitutes a key shortcoming in our understanding of extratropical climate variability". Various possible theories are presented to explain NAO variations based on climate model simulations of the atmosphere and it has been demonstrated that atmospheric processes alone are sufficient to generate NAO-like patterns of variability. One theory which has a lot of support is that there is a coupling between NAO variability in the trophosphere and the circulation in the stratosphere: a colder and stronger stratospheric polar vortex is associated with anomalously strong trophospheric westerlies along ~55^o N (i.e positive NAO) and vice versa. However this coupling is not well understood.  Another theory emphasises the importance of the circulation in the tropics as there is an association between positive NAO phases and stronger than normal trade winds over both the Atlantic and Pacific sectors. And a wide range of possible forcing mechanisms have been identified in published papers including increasing greenhouse gases, ozone depletion, increases in tropical SSTs and variations in solar forcing. But the final remarks were: "Nevertheless, it is unlikely that the source(s) of the observed trends in the NAO can be unequivocally isolated in the absence of a consensus regarding the atmospheric processes that give rise to NAO variability in the first place. In our view, establishing a theory for the existence of NAO variability is of paramount importance for future research".

The Ocean's Response to North Atlantic Oscillation Variability (Visbeck, Chassignet, Curry, Delworth, Dickson & Krahmann, 2003) discusses the extent to which the Atlantic Ocean influences the atmosphere and therefore the NAO via feedbacks. Early investigators of the NAO believed that it was changes in SSTs and the associated exchange of heat between sea and air which had a significant impact on the atmosphere and this may have reinforced or controlled the state of the NAO. However, in recent years, large numbers of ocean-atmosphere climate model studies have shown that the NAO is largely driven by atmospheric processes as discussed in the paragraph above and that the consensus is that there is only a modest feedback from the ocean back to the atmosphere. However, it is argued that the ocean's role is more important on longer timescales of  years and decades as changes in ocean circulation which are influenced by NAO variability take a long time to adjust. Thus the multi-decadal phases of the NAO may owe to the ocean's feedback on the NAO but there is no clear consensus on the mechanisms involved. However, there is consensus on the short term seasonal and year to year fluctuations in Atlantic SST anomalies induced by changes in the NAO: the Atlantic tripole of SST anomalies.

The Role of Atlantic Ocean-Atmosphere Coupling in Affecting North Atlantic Oscillation Variability (Czaja, Robertson & Huck, 2003) challenges the claim that the NAO is entirely driven by processes internal to the atmosphere by arguing that "The atmospheric cap north of the equator is, however, not an isolated system. It exchanges heat, moisture and momentum with the ocean, the land, the biosphere and the cryosphere below, as well as with the tropics at its southern boundary. All these interactions could possibly influence NAO variability." This argument is supported by atmosphere climate model experiments forced by the observed global SST and sea ice anomalies from 1947-97 which reproduced annual NAO variations over this period very well and in particular faithfully replicated the strong rise in the NAO in recent decades. A key part of the argument that the feedback of the Atlantic ocean is significant is that the Atlantic tripole of SST anomalies induced by NAO variability change the SST gradient in middle latitudes which could affect storm tracks and subsequently large scale atmospheric flow. And the southern lobe of the Atlantic tripole affects the cross-equatorial SST gradient  which could affect monsoons associated with the movement of the Intertropical Convergence Zone and have a knock-on effect on the large scale atmospheric circulations. So the conclusion of this chapter is that modelling is underrating the importance of interactions between the ocean and atmosphere in the Atlantic and that the feedbacks of the ocean on the NAO are greater than what earlier chapters suggest.

On the Predictability of North Atlantic Climate (Rodwell, 2003) gives support to the argument that feedback from the ocean is significant to NAO variability by showing that for winter, there is useful predictive skill (correlation of around 0.45) from a knowledge of the previous May SSTs. However, it is relevant to point out that predictions of positive NAO winters in 2003 and 2004 based on this technique were wrong (see Met Office article;  Figure 21). One finding of relevance to the anticyclonic summers which have occurred in the UK since 1988 is an association between summer anticyclonicity over the UK and warm SST anomalies off Newfoundland.

Climate Change and the North Atlantic Oscillation (Gillett, Graf & Osborn, 2003) examines whether the dramatic rise in the winter NAO in recent decades is connected to increasing concentrations of greenhouse gases or whether natural variability is the cause. But before discussing the findings of this chapter, it is relevant to review the conclusions of the earlier chapters about the causes of NAO variations. In brief, processes within the atmosphere were considered to be of overriding importance with the strength of the polar vortex in the stratosphere also being critical. The feedback of the Atlantic Ocean on the NAO was considered to be of lesser importance than atmospheric processes. Yet there was no consensus about which atmospheric processes control NAO variations because a whole spectrum of possible theories exist. This is significant in relation to the alleged effects of climate change on the NAO because if you don't have an agreed theory to explain natural variations in the winter NAO and define the limits of natural variability, you cannot distinguish natural variations from those allegedly caused by increasing concentrations of greenhouse gases. Returning to this chapter on the effects of climate change on the NAO, while climate proxy reconstructions of past variations of NAO suggest that "neither the recent, highly positive NAO index values of the 1990s, nor the change from the low index values of the 1960s appear to be unique in the context of longer records", climate model simulations indicate recent high values of the winter NAO are outside natural variability. Most climate model studies which have examined the effects of increasing greenhouse concentrations show an increase in the winter NAO index and several different mechanisms have been suggested. One theory is that the strength of the stratospheric circulation has been enhanced because of a greater temperature contrast between the tropics and the poles in the upper trophosphere/lower stratosphere induced by more greenhouse gases. And anthropogenic ozone depletion has also been suggested as an explanation for the upward trend in the NAO by again enhancing the stratospheric circulation. Research has shown that some non-anthropogenic factors may also affect the NAO: volcanic aerosols in the stratosphere in the 2 to 3 years after a major volcanic eruption may enhance the winter NAO as might the peaks in the 11 year sunspot cycle, again through effects on the polar vortex in the stratosphere, and strong forcing from tropical SST anomalies was also found. An interesting observation was that "the observed NAO trend in recent decades is somewhat larger than one might expect based on models forced with greenhouse gas increases. Thus it may be that the NAO index in the real atmosphere is more sensitive to greenhouse gas changes than in models or it may be that the anthropogenically enhanced trend in the observations has been enhanced by natural variability over the past forty years". This is an example of what in all probability is frequently happening in the AGW debate: natural variability in climate is being underrated and natural climate fluctuations are being interpreted by climate change scientists as symptoms of AGW. To close this paragraph on climate change and the NAO, "most authors agree that greenhouse gases are likely to be at least partly responsible for the long term trend in the boreal winter NAO index". So in conclusion, natural variability certainly has played a major role in the trend to increased winter NAO in recent decades with increased greenhouse gases probably making a contribution. At this point, it is appropriate to point out that in both winters 2003 and 2004, the NAO has been negative and European winters have cooled relative to the high values of many winters from 1989 to 2002 (Figure 21) which arguably is evidence that it is natural variability and not increasing greenhouse gases which is dictating NAO variability.

It is now relevant to read again the contents of Box 7.2 from  Climate Change 2001: the scientific basis which discussed the SOI as it also refers to the NAO.

"In particular, are the observed changes in ENSO and the NAO (and other modes) perhaps a consequence of global warming itself?

There is no simple answer to this question at present. Because the natural response of the atmosphere to warming (or indeed to any forcing) is to change large-scale waves, some regions will warm while others cool more than the hemispheric average, and counterintuitive changes can be experienced locally. Indeed, there are preferred modes of behaviour of the atmospheric circulation, sometimes manifested as preferred teleconnection patterns (see this chapter) that arise from the planetary waves in the atmosphere and the distribution of land, high topography, and ocean. Often these modes are demonstrably natural modes of either the atmosphere alone or the coupled atmosphere-ocean system. As such, it is also natural for modest changes in atmospheric forcing to project onto changes in these modes, through changes in their frequency and preferred sign, and the evidence suggests that changes can occur fairly abruptly. This is consistent with known behaviour of non-linear systems, where a slow change in forcing or internal mechanisms may not evoke much change in behaviour until some threshold is crossed at which time an abrupt switch occurs. The best known example is the evidence for a series of abrupt climate changes in the palaeoclimate record apparently partly in response to slow changes in sea level and the orbit of the Earth around the Sun. There is increasing evidence that the observed changes in the NAO may well be, at least in part, a response of the system to observed changes in sea surface temperatures, and there are some indications that the warming of tropical oceans is a key part of this.

Therefore, climate change may manifest itself both as shifting means as well as changing preference of specific regimes, as evidenced by the observed trend toward positive values for the last 30 years in the NAO index and the climate “shift” in the tropical Pacific about 1976. While coupled models simulate features of observed natural climate variability such as the NAO and ENSO, suggesting that many of the relevant processes are included in the models, further progress is needed to depict these natural modes accurately. Moreover, because ENSO and NAO are key determinants of regional climate change, and they can possibly result in abrupt changes, there has been an increase in uncertainty in those aspects of climate change that critically depend on regional changes."

So, the IPCC describe both the SOI & NAO as preferred natural modes of variability in global climate and argue that it is likely that AGW would cause changes in both these natural regional circulations. However, the IPCC have not shown how changes induced by AGW can be separated from natural changes in SOI and the NAO.  For SOI, the consensus is “ENSO is not simulated well enough in global climate models to have confidence in projected changes with global warming” (Climate Change 2001: the scientific basis). In the case of the NAO,  the paragraphs above summarising the results of some chapters of the NAO study suggest that AGW has probably contributed to the recent positive NAO winters but natural variability is the overriding factor.

Global Cooling about to kick-in? argues that variations in SOI & NAO may both be controlled by variations in the global ocean conveyor belt known as the Thermo-Haline Circulation (THC). The theory is that changes in the speed of the THC result in characteristic SSTs in various parts of the globe and changes in SOI & NAO are the result. The co-incidence of negative SOI and positive NAO for multi-year periods at the beginning and end of the twentieth century supports this idea that both these natural cycles in climate are controlled by a single underlying factor, the THC. If this theory is correct, then the GW observed since the early 1970s could owe to entirely natural changes in the THC dictating SOI & NAO and not to AGW.

Variability and trends of air temperature and pressure in the maritime Arctic 1875-2000 is a recent study with the aim of assessing long-term (century plus) arctic air temperature and pressure trends and their low-frequency variability using available observational data from around the entire Arctic. It was found that Arctic air temperature and pressure display substantial variability on time scales of 50-80 years and that the likely cause is slow changes in the THC in the North Atlantic. A finding which has relevance to the recent positive phase of the NAO was that maximum warming in the Arctic occurred 5 to 15 years after the period with lowest pressure.  Pressure is lowest in the Arctic during positive NAO/AO phases and the peak of this recent positive phase was during 1989 & 1990 (Figure 23) which means the high temperatures across the Arctic and other high latitudes of the northern hemisphere over the last decade (RSS MSU data) may be associated with the unusually low pressure in the Arctic in 1989 & 1990. But 2004 is the 14th year since 1990, so a marked cooling in the Arctic ought to commence around now according to this 5 to 15 year lag theory.  The record low Arctic sea ice extent in summers 2002 & 2003 measured by satellites since 1979 could also be linked to this 5 to 15 year lag in maximum Arctic warming.

Hurrell (2003) states that “The NAO accounts for much of the interannual and longer-term variability evident in northern hemisphere surface temperature”. So there is a strong case for arguing that the notably high temperatures in the northern hemisphere (Figure 17) including the UK (Figure 1) and Europe (Figure 23)  since 1988  are largely a response to the recent positive phase of the NAO and not to any alleged enhanced greenhouse effect ie. AGW. 

What is certainly true is that time and time again, changes caused by the recent positive phase of the NAO are quoted by climate change scientists as evidence of AGW but in nearly every case, there is a clause stating that the recent positive phase of the NAO may be entirely natural:

Changing intensity of rainfall over Britain concluded “It is not yet possible to say whether these observed changes in UK rainfall characteristics can be attributed to man-made climate change, because (although they can have very significant impacts) the changes may not be outside the range of variation that could occur naturally.”

Osborne & Hulme (2002) acknowledged that the positive phase of the NAO could account for the increase in winter rainfall they found in their study of UK daily rainfall from 1961-2001.

Climate change doubles Britain’s stormy weather showed a linear trend of increasing storminess since 1950 but the Hadley Centre in their own presentation of the results (see page 5 of Climate Change Observations & Predictions) state “It is also important to place these new results in context. Evidence of storm frequency from daily indices and measurements of wave heights suggest that although it has increased in recent times, the magnitude of storminess at the end of the twentieth century was similar to that at the start. This could mean that natural variations in the magnitude of storminess on timescales of several decades or more are responsible for all or part of the trends seen in these new results and that data covering a longer period is needed to distinguish a climate change trend from the natural variability.”

Climate Change & Changing Snowfall Patterns in Scotland which shows a decrease in Scottish snowfall during the 1990s and predicts further decreases in the decades to come has a health warning in Chapter 4 , paragraph 4.24 stating “The North Atlantic Index provides an indication of the strength of the mid-latitude westerly circulation, which dominates Scotland's weather. The last two decades have seen relatively high index values, which has brought a moist and relatively warmer maritime climatic influence to Scotland. The index does, however, fluctuate (North Atlantic Oscillation) and, on the basis of past experience, it is unlikely that the NAI will remain at its current high level for ever. Any decrease in the influence which the westerlies exert on the Scottish climate is likely to see some measure of a return to cooler winters."

From the above review of recent climate research, scientists do not claim that AGW is the main cause of the increase in the winter NAO in recent decades although they think that it probably has made a contribution. So the recent strong bias towards WWP in the UK which this study argues is linked to the positive phase of the NAO cannot be wholly attributed to AGW (perhaps partly) but natural variability in weather patterns is the likely explanation.
 

4.6 Will the high incidence of WWP and the run of very warm years in the UK since 1988 continue?

The annual CET predictions of the models including PSC indices only (Figure 18) clearly show the flip to WWP in 1989 and that WWP have persisted in most years since then but with a slight decline. Moreover, although there is considerable year to year variability in predicted CET since 1881 indicating large variations in weather patterns from year to year, several periods with predominantly WWP and several periods with predominantly Cold Weather Patterns (CWP) can be identified. The 1940s & 1950s generally had WWP and consequently high annual temperatures, the 1960s, 1970s & most of the 1980s generally had CWP and consequently low annual temperatures, and post 1988, WWP and high annual temperatures have prevailed. This shows that the UK climate sometimes flips between periods of predominantly WWP and periods of predominantly CWP and this is related to the constantly changing climate (Figure 19) in which the NAO plays an important part. This reality of a constantly changing UK climate is evident in the CET (Figure 1) which shows periods of higher and lower temperature throughout the period commencing 1659. Across Europe too (Figure 21), changing weather patterns associated with the NAO have led to warm and cold periods during the twentieth century. So climate change is not a new phenomenon which previous generations didn’t experience although climate change spin is being used to imply that this is the case.

Given the large variability in historical UK weather patterns and temperatures, it is very unlikely that the current strong bias to WWP will continue indefinitely and at some point, CWP are likely to become more prevalent than WWP, or at least occur with a more similar frequency. Such changes are likely to be associated with changes in the winter NAO with CWP becoming more frequent all year round as negative NAO winters become more common. If global temperatures continue to rise, Figure 18 suggests that any cooling induced by CWP would be somewhat counteracted but if the theory about the THC controlling both the SOI and NAO is correct, a change to CWP in the UK associated with a change to more negative NAO would be accompanied by more positive SOI which together would lower global temperatures. This theory is supported by the co-incidence of lower global temperatures during the 1960s & 1970s (Figure 24) at the same time as CWP were causing lower temperatures in the UK. These lower global temperatures during the 1960s & 1970s may owe to the cumulative effect of CWP in various regions of the world caused by positive SOI & negative NAO

This theory is at variance with the argument advocated by climate change scientists that the global cooling in the 1960s & 1970s was caused by increasing sulphate aerosols in the atmosphere (from coal burning) associated with rapid industrialisation after the Second World War which scattered incoming solar radiation, thereby cooling the surface. This argument goes on to explain the resumption of global warming during the 1970s by the introduction of legislation in developing countries to control sulphate emissions. For scientists who argue that an enhanced greenhouse effect owing to anthropogenic greenhouse gas emissions is the overriding factor dictating the rise in global temperature during the twentieth century, this global cooling in the 1960s & 1970s is problematic. The sulphate aerosol argument is their explanation for this global cooling but appears a weak argument relative to the CWP theory articulated in the paragraph above. Moreover, it has numerous flaws including the fact that sulphates usually get washed out of the atmosphere within a few days by rainfall (acid rain) limiting their lifetime in the atmosphere and logically the northern hemisphere would be cooled much more by sulphate aerosols (much more land and therefore industry in the northern hemisphere) whereas the surface temperature record and the satellite MSU data of lower atmosphere temperatures clearly show that the northern hemisphere has warmed more than the southern hemisphere in recent decades. In fact the South Pole and much of the Southern Ocean which are undoubtedly least affected by anthropogenic sulphate aerosols have cooled since 1979 (graph) which suggests that both the sulphate theory and the AGW theory may be wrong.

Given that both the UK and many countries in Europe are large industrialised economies which were burning large quantities of sulphur-emitting coal in the 1960s & 1970s, if CWP alone can explain the colder temperatures during this period in these countries without any reference to sulphates, it raises serious doubts about the argument that sulphates account for the colder period globally in the 1960s & 1970s (Figure 24).

Returning to the issue of whether or not WWP will persist in the UK in the next few decades, the effects of a shift to a higher frequency of CWP on SSTs around the UK also need to be considered. Just as WWP warm SSTs around the UK, CWP cool SSTs around the UK and because the UK is an island, SSTs do have a significant effect on temperatures on the UK landmass. This phenomenon which currently favours the high UK temperatures will favour lower temperatures when CWP are more frequent.

In fact, there is some evidence already of a shift to a higher incidence of CWP in Europe. The following links present graphs of daily temperature anomalies from 1961-90 averages for various places in Europe and show that since the persistent and amazing warmth of summer 2003, temperatures in southern Europe have on average been closer to normal and have been fluctuating both below and above average for significant periods which is a sign that both CWP and WWP have been occurring: Western Europe; Alpine and South East Europe. Both winters 2002/03 and 2003/04 in Europe have not been dominated by persistent westerly winds which characterised the 1990s but both had negative NAO weather patterns and consequently lower temperatures than most 1990s winters. And Figure 21 clearly shows that the winter NAO is no longer increasing but decreasing. Only time will tell if CWP will continue to increase in frequency across Europe and whether the argument advocated by this study that the UK and Europe are likely to cool somewhat in the next few decades is correct.

 

4.7 Discussion of results in relation to UKCIP02

UKCIP02 are predictions of the UK climate in the twenty first century which were launched by the Department for Environment, Food & Rural Affairs (DEFRA) in April 2002. They describe four different scenarios of how the world may develop in the decades to come, being based on four different emission scenarios from the IPCC. These predictions are dramatic. For example, in the High Emissions scenario by the 2020s (2011-2030), the average temperature rise in annual temperatures of  England are predicted to be 0.5 to 1.5 C relative to the 1961-90 average rising to 3.0 to 4.5 C by the 2080s (2071-2100). The comparative figures for the Low Emissions scenario are 0.5 to 1.0 C and 1.5 to 2.5 C. From 1989 to 2003, the average monthly anomaly from the 1961-90 average is +0.7 C which is more than consistent with these warming. This observed warming is already of a magnitude predicted for the 2020s which arguably supports the findings of this study that the run of warm years in the UK since 1988 owes to natural variability favouring WWP and is not wholly attributable to AGW.

UKCIP02 also discusses observed trends in UK climate in Chapter 2: Recent Trends in Global and UK Climate. In section 2.1, global warming and its causes is discussed and a case based on climate model simulations is presented arguing that most of the global warming over the last 50 years is attributed to greenhouse gases from human activities. As this modelling technique specifically applied to global and not UK temperatures, section 2.1 ended with: “Although this analysis has been carried out on a global scale, it is not unreasonable to suppose that at least part of the climate warming observed over the UK can also be attributed to human activities”. So the view of scientists is that recent warmth in the UK is not all due to AGW but owes to a combination of both natural and human factors.

However, UKCIP02 does not explicitly attribute recent warm years in the UK to a strong bias to WWP and does not remark on the rise in UK temperatures in 1989 associated with the commencement of the positive phase of the NAO. However, it does mention the NAO in section 2.4, Long-term trends in circulation patterns and gales: “Many aspects of UK winter climate are strongly influenced by the NAO…” and identifies the NAO as the key factor in a higher incidence of gales at the beginning and end of the twentieth century but comments “The evidence for the recent increase in gale frequencies over the British Isles being related to human-induced warming remains unconvincing”. This is yet another example of scientists stating that the NAO has caused recent changes in UK climate but admitting that they cannot claim that AGW is causing the changes in the NAO!

This study highlights the NAO as the key factor in recent climate change in the UK and Europe and this focus on the NAO is supported by published scientific works like the NAO study. UKCIP02 does not give prominence to the NAO which is surprising as the positive phase of the NAO is the overriding factor in the run of warm years in the UK since 1988. What could the explanation for this underrating of the NAO in UKCIP02 be? One possible explanation is that attributing recent high annual temperatures in the UK to the NAO identifies natural variability in weather patterns as the major cause which is at variance with the IPCC/UKMO message that greenhouse gases linked to human activities are the cause of most global warming over the last 50 years.

Natural variability is included in the UKCIP02 predictions (see Figure 43 on p 43) and substantial year-to-year and decade-to-decade variability is expected to be superimposed on a long term warming of the UK climate during the twenty first century. Fluctuations in the incidence of WWP and CWP are the major part of this natural variability. Figure 43 may be compared with the model which includes PSC indices plus northern hemisphere temperature anomaly in Figure 18: the year-to-year and decade-to-decade variability is represented by variations in PSC indices and the long term upward trend represented by rising northern hemisphere temperatures. So UKCIP02 is in fact consistent with the main conclusion of this study that some cooling is likely in the next few decades as the long run of mainly WWP which has prevailed since 1988 (1991, 1993, 1996 & 2001 being the exceptions to this trend) cannot be expected to continue indefinitely and a higher incidence of CWP must occur at some point in the future.

4.8 Discussion of results in relation to global temperatures

This study identifies natural variability in climate favouring WWP as the overriding causal factor in the high UK temperatures since 1988. Might it not be the case that this same factor in a number of regions of the world accounts for the high global temperatures since 1988 (Figure 24)?  This is a very reasonable theory as evidence that variations in the weather pattern, ENSO/SOI are correlated with global temperatures  (Figure 20) has been presented earlier in this Discussion. And it is known that the winter NAO accounts for much of the temperature variability in the northern hemisphere (Hurrell (2003)) and the recent positive phase of the NAO is certainly a major cause of the high temperatures in this hemisphere post 1988. Yet despite this weight of published scientific evidence, the IPCC/UKMO view is that "most global warming over the last fifty years is due to greenhouse gases from human activities" which implies natural factors have only played a minor role. This is a conspicuous inconsistency within climate change science and suggests that the IPCC/UKMO may be biased in favour of AGW and tend to underrate the importance of natural variability in climate. Greenhouse gas forcing in reality is just one of a number of  factors affecting global temperatures and certainly does not account for the year-to-year variability in the global temperature records in Figure 24 or for the year-to-year or decade-to-decade variability in the CET (Figure 1). Increased greenhouse gas forcing may possibly account for some of the long term warming trends in global temperature and the CET but a sudden warming in these two records like the one post 1988 are more likely caused by other factors as argued in this paragraph.

The IPCC/UKMO are presenting AGW as almost certain and indisputable when they don't have any robust data (climate model simulations are not robust evidence of AGW) which conclusively show that recent global warming is connected to rising carbon dioxide concentrations in the atmosphere. This study is not arguing that AGW is definitely not occurring or that further increases in greenhouse gases won't result in higher global temperatures. Scientists might unfortunately be proved right in due course about increasing atomospheric concentrations of carbon dioxide causing significant global warming but their emphatic claims that AGW accounts for most of recent global warming and that natural factors are minor players are surely erroneous given the published scientific evidence about SOI and the NAO discussed above.

In recent weeks, there have been press releases about impending climate catastrophe that appear more like science fiction than sober science: Science Meets Hollywood; Melting Greenland ice threatens global rise in sea level; Why Antarctica will soon be the only place to live - literally; Climate risk to 'million species'. Looking at the global temperature records in Figure 24 or regional temperature records like the CET (Figure 1), is it logical to conclude that temperatures are rising out of control and that the world is heading for a climate catastrophe? What Figure 24 shows is that global temperatures rose during the first half of the twentieth century as much as they have since 1950 and climate change scientists attribute the former rise to an increase in solar activity. And a recent study reports that the Sun is more active than for a millennium which is yet another natural factor which favours recent global warming but climate change scientists believe that natural factors only play a minor role in recent global warming! This study argues that the IPCC/UKMO are underrating natural variability in climate and interpreting natural variability which has favoured WWP on a global scale for the last few decades, as a symptom of AGW and as a consequence, future global warming is probably being overhyped and overemphasised.

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