141: United Kingdom - temperature trends WARMING

In this post I will consider the temperature data of the United Kingdom (UK), or more specifically Great Britain as the data for Northern Ireland was included in the analysis of the temperature change for Ireland in the last post. Overall the UK has 21 long stations with over 1200 months of data before 2014, of which two are in Northern Ireland and are thus excluded from this analysis. There are also another 73 medium stations with over 480 months of data all of which are within Great Britain or the Isle of Man (for a full list see here). The locations of these 92 long and medium stations are shown on the map in Fig. 141.1 below. What the data from these stations appear to show is that the climate of the UK has warmed gradually by about 0.6°C over the the two hundred years before 1980 but has since warmed further by a similar amount in under forty years.

Fig. 141.1: The (approximate) locations of the 92 longest weather station records in the United Kingdom (excluding Northern Ireland). Those stations with a high warming trend between 1911 and 2010 are marked in red while those with a cooling or stable trend are marked in blue. Those denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

In order to quantify the changes to the climate of the UK the temperature anomalies for all stations with over 480 months of data before 2014 were determined and averaged. This was done using the usual method as outlined in Post 47 and involved first calculating the temperature anomaly each month for each station, and then averaging those anomalies to determine the mean temperature anomaly (MTA) for the country. This MTA is shown as a time series in Fig. 141.2 below and clearly shows that temperatures have increased by about 1°C since 1760.

Fig. 141.2: The mean temperature change for the United Kingdom since 1760 relative to the 1956-1985 monthly averages. The best fit is applied to the monthly mean data from 1871 to 1980 and has a positive gradient of +0.46 ± 0.10 °C per century.

The process of determining the MTA in Fig. 141.2 involved first determining the monthly reference temperatures (MRTs) for each station using a common 30-year reference period, in this case from 1956 to 1985, and then subtracting the MRTs from the raw temperature data to deliver the anomalies. If a station had at least twelve valid temperatures per month within the MRT interval then its anomalies were included in the calculation of the mean temperature anomaly (MTA). The total number of stations included in the MTA in Fig. 141.2 each month is indicated in Fig. 141.3 below. This graph shows that there was a sudden increase in stations in 1973 while some existing station were moved or discontinued at about the same time. In order to include as many of these stations as possible in the MTA the MRT interval was set as 1956-1985 so that it overlapped both periods before and after 1973.

Fig. 141.3: The number of station records included each month in the averaging for the mean temperature trends in Fig. 141.2.

The data in Fig. 141.3 indicates that the greatest coverage of the country for temperature data is after 1973 with up to 76 long and medium stations in operation at any one time. This drops to about 28 in 1930 and to less than five before 1850. This means that the MTA for the UK before 1890 will be less reliable than its values after 1950. Note that a reliable MTA generally needs data from at least sixteen stations (see Post 57 for evidence) otherwise errors in the data from individual stations become significant.

Fig. 141.4: The mean temperature change for the United Kingdom since 1760 relative to the 1956-1985 monthly averages. The best fit is applied to the monthly mean data from 1781 to 1980 and has a moderate positive gradient of +0.29 ± 0.05 °C per century.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 141.5 below. This again was determined by averaging each monthly anomaly from the 92 longest stations and also suggests that the UK climate has warmed by over 1°C. In this case, though, the warming appears to occur almost exclusively after 1875 with the climate being stable before this date and gradually warming (with some significant variation) thereafter.

Fig. 141.5: Temperature trends for the United Kingdom based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1876-2010 and has a positive gradient of +0.80 ± 0.03°C/century.

Comparing the curves in Fig. 141.5 with the published Berkeley Earth (BE) version for the UK in Fig. 141.6 below we see that there is good agreement between the two sets of data. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 141.5 using adjusted data is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 141.6. This is a conclusion that is not unique to this case. In fact it is true of virtually all the country and regional data I have examined for this blog so far.

This means that the simple averaging process used for the data in Fig. 141.5 should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 141.2 and Fig. 141.4. Consequently, any major discrepancy between the adjusted data in Fig. 141.5 and the unadjusted data in Fig. 141.4 cannot be due to the different averaging processes used, but must instead be the result of the Berkeley Earth adjustments.

Fig. 141.6: The temperature trend for the United Kingdom since 1750 according to Berkeley Earth.

Most of the differences between the MTA in Fig. 141.4 and the BE versions using adjusted data in Fig. 141.6 are due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values seen in Fig. 141.4 and Fig. 141.5.

Fig. 141.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 141.5 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1921-2000 has a positive gradient of +0.097 ± 0.004 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The magnitudes of these adjustments are shown graphically in Fig. 141.7 above. The blue curve is the difference in MTA values between adjusted (Fig. 141.5) and unadjusted data (Fig. 141.4), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. The overall adjustment from 1900 to 2013 is small, less than +0.2°C. A greater impact is seen before 1880. This appears to change the shape of the long term trend before 1900 from a gradual warming in Fig. 141.4 to a more stable climate in Fig. 141.5. This can be seen more clearly in the comparison curves in Fig. 141.8 below. These also show that the adjustments made after 1900 add slightly to the observed warming. In this case, however, both these corrections are smaller than those seen in other posts, particularly for countries in the Southern Hemisphere.

Fig. 141.8: The 5-year mean temperature change for the United Kingdom since 1760 based on the original raw data from Fig. 141.2 (in blue) and the Berkeley Earth adjusted data from Fig. 141.5 (in red).

Summary

The temperature data from UK stations appears to indicate that the climate of the UK has warmed by about 1°C since 1760, and most of this warming has occurred since 1900 (see Fig. 141.2). In fact over half the warming has occurred since 1980.

The pattern of warming is broadly the same for both the MTA calculated using raw data (See Fig. 141.2) and that based on Berkeley Earth adjusted data (see Fig. 141.5).

The MTA data of the UK before 1900 appears to show more warming than is seen in similar data for Ireland (see Post 140) even though the two territories are near neighbours and their data are more similar after 1900. One reason for this could be the greater population density and industrialization of the UK compared to Ireland. One way to test this hypothesis would be to analyse the temperature for England and Scotland separately and compare these with Ireland. If the England data is the exception then that would support the hypothesis.


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations in the UK with links to their raw data files.

139: Alaska - temperature trends WARMING (probably)

The US state most often linked to climate change is Alaska. This is probably because it is seen as having an Arctic climate even though only about a third of the state actually lies within the Arctic Circle. In fact Alaska is no more northerly than Norway and its Aleutian Island chain stretches further south than London and Berlin. It has an area three times that of France but its population is less than that of Marseille, yet it has an extensive network of weather stations that is greater in data quality than that seen in many industrialized countries. Ordinarily this should be sufficient to determine the temperature change for Alaska to a high level of precision but it isn't. In fact the data is so inconclusive it is difficult to determine whether Alaska has warmed at all over the last one hundred years let alone quantify that warming and discern when exactly it occurred. This is because the natural variation in the long term temperature averages is far greater than the likely warming.

There are one hundred stations in Alaska with over 480 months of data before 2014 including seven long stations with over 1200 months of data. Of the 93 medium stations with over 480 months of data twenty have over 1000 months of data (for a full list of stations see here). The locations of these stations are shown in Fig. 139.1 below.

Fig. 139.1: The (approximate) locations of the 100 longest weather station records in Alaska. Those stations with a high warming trend between 1911 and 2010 are marked in red while those with a cooling or stable trend are marked in blue. Those denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

 

The map in Fig. 139.1 shows that most of the temperature data for Alaska come from stations that are outside the Arctic Circle. In fact of the one hundred longest stations in Alaska only eight are actually inside the Arctic Circle. And while the remainder are fairly evenly distributed geographically, there are significant clusters of stations around Anchorage, Fairbanks and the panhandle along the coast in the southeast between the the border of Canada and the Alexander Archipelago. As usual for simplicity I will disregard this clustering and assume it makes very little difference to the measured temperature change as it only affects the contribution or weighting of about 15% of stations.

In order to quantify the changes to the climate of Alaska the temperature anomalies for all stations with over 480 months of data before 2014 were determined and averaged. This was done using the usual method as outlined in Post 47 and involved first calculating the temperature anomaly each month for each station relative to its monthly reference temperatures (MRT), and then averaging those anomalies to determine the mean temperature anomaly (MTA) for the country. This MTA is shown as a time series in Fig. 139.2 below with the MRTs for each station calculated using data between 1961 and 1990,  (again using the methodology outlined in Post 47).

Fig. 139.2: The mean temperature change for Alaska since 1900 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1921 to 2000 and has a positive gradient of +0.31 ± 0.31 °C per century.

The data in Fig. 139.2 above illustrates the difficulty of determining a definitive temperature trend when the data is subject to significant variability over time. In this case choosing to fit to the data from 1921 to 2000 leads to a small positive gradient of 0.31°C per century, but this is no bigger than the uncertainty and so is not statistically significant. If other fitting intervals are chosen then the gradient can be significantly different. For example, an interval of 1921-1995 results in a gradient of 0.18°C per century while 1926-2005 produces 0.96°C per century. All of which poses the awkward question, which result is correct?

In my opinion there is no obvious answer, but there are two factors that we could consider that may shed some additional light on the problem. The first of these is to choose an appropriate fitting interval based on the cycle of the natural variations (i.e. fitting from peak to peak), while the second is to concentrate on data that is the result of averaging the greatest number of station records. 

In Post 4 I explained how the best fit line to a single period of a sine wave gives a non-zero gradient (see Fig. 4.7) whereas fitting to a cosine wave does not. This is because a cosine wave is symmetric about the y-axis while the sine wave is anti-symmetric. As most temperature data tends to oscillate over time due to natural variations it therefore follows that the gradient of any fit to that data will depend on the interval chosen relative to the peaks of those natural oscillations. 

In order to avoid biasing the gradient due to asymmetry in the fitting range, the range should be symmetric relative to the natural oscillations. These natural oscillations are seen most clearly in the 5-year moving average (see the yellow curve in Fig. 139.2). So the fitting range should be chosen so that it starts and ends on a peak in the 5-year average, or alternatively starts and ends on a trough. The best fit in Fig. 139.2 does not do this. It starts near a trough at 1921 and ends on a plateau in 2000. But if we change the fitting interval from 1914 to 2003 then the interval starts and ends on a peak in the 5-year average. The result is the best fit shown in Fig. 139.3 below.

Fig. 139.3: The mean temperature change for Alaska since 1900 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1914 to 2003 and has a positive gradient of +0.71 ± 0.26 °C per century.

The gradient of the best fit in Fig. 139.3 is more than twice that in Fig. 139.2 even though the data hasn't changed. This is simply a result of changing the fitting interval. Of course the underlying reason why a change of fitting interval makes such a big difference in this case is that the natural fluctuations in the 5-year average are so large. These changes in temperature can exceed 2°C in less than five years. So we could ask, is the temperature rise of about 0.7°C indicated by the best fit in Fig. 139.3 really that significant in comparison?

Fig. 139.4: The number of station records included each month in the mean temperature anomaly (MTA) trend for Alaska in Fig. 139.2 and Fig. 139.3.

The second factor in determining any choice of fitting range is the quantity of data available. The graph in Fig. 139.4 above shows the number of stations included in the MTA in Fig. 139.2 and Fig. 139.3. From 1920 onwards there are over twenty stations each month. In the previous post and in Post 57 I argued that at least ten, and possibly over twenty-five stations are needed in order for the MTA to be reliable, so this condition is satisfied for all months after January 1920. The data before 1920 will therefore be much less reliable, but there is still enough data to allow us to calculate an approximate MTA as far back as the 1820s. This is shown in Fig. 139.5 below.

Fig. 139.5: The mean temperature change for Alaska since 1820 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1911 to 2010 and has a positive gradient of +0.73 ± 0.22 °C per century.

The data in Fig. 139.5 indicates that it is possible to calculate and MTA as far back as 1829, but before 1900 there are gaps in the data and most of the MTA data for this period is based on an average of anomaly data from less than three different stations. So that raises questions over its reliability.

So how should we interpret this data? The station frequency data in Fig. 139.4 suggests only data after 1900 or even 1920 is sufficiently reliable. As for the data after 1900, there are many ways to interpret it. For example, if we just look at data from 1901 to 1975 the best fit (as determined from trough to trough) is strongly negative (see Fig. 139.6 below). But after 1975 the temperature appears to increase abruptly by about 1°C. So is this interpretation of the temperature trend any more believable than those shown in Fig. 139.2 or Fig. 139.3? It is hard to tell, again because of the high level of natural variability in the data which could be varying on multiple timescales. Such multi-frequency variability is potentially indicative of chaotic or fractal behaviour as I discussed in Post 9, Post 17 and Post 42.

Fig. 139.6: The mean temperature change for Alaska since 1900 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1901 to 1975 and has a negative gradient of -0.52 ± 0.33 °C per century.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 139.7 below. This again was determined by averaging the anomalies for each month from the one hundred longest stations in Alaska and suggests that the climate of Alaska has warmed by over 1°C since 1870, but with large natural variations of up to 1.5°C in the 10-year average.

Fig. 139.7: Temperature trends for Alaska based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1876-2010 and has a positive gradient of +1.00 ± 0.06°C/century.

Comparing the curves in Fig. 139.7 with the published Berkeley Earth (BE) version for Alaska in Fig. 139.8 below we see that there is good agreement between the two sets of data as far back as 1880. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 139.7 using adjusted data is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 139.8. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 139.2 and Fig. 139.5. In other words, any discrepancy between the adjusted data in Fig. 139.7 and the unadjusted data in Fig. 139.5 cannot be due to the averaging process. Any form of weighted averaging would also not affect the results.

Fig. 139.8: The temperature trend for Alaska since 1820 according to Berkeley Earth.

Most of the differences between the MTA in Fig. 139.6 and the BE versions using adjusted data in Fig. 139.7 are instead mainly due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values seen in Fig. 139.5 and Fig. 139.7.

Fig. 139.9: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 139.7 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1921-2000 has a positive gradient of +0.262 ± 0.009 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The magnitudes of these adjustments are shown graphically in Fig. 139.9 above. The blue curve is the difference in MTA values between adjusted (Fig. 139.7) and unadjusted data (Fig. 139.5), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. The overall adjustment from 1920 to 2000 is small, about +0.2°C. Nevertheless, it can be seen in the difference in the 5-year means (see Fig. 139.10 below) for the unadjusted data (blue curve) and the adjusted data (red curve). The difference, though, is about ten times less than the variability in the two MTAs over time. The data in Fig. 139.10 also highlights the difficulty in interpreting the data. If the data between 1940 and 1980 were missing or ignored, then one could postulate that Alaska has seen fairly consistent warming since 1900 amounting to about 1°C in total. But if the 1940-1980 data is included the data all looks very random.

Fig. 139.10: The 5-year mean temperature change for Alaska since 1900 based on the original raw data (in blue) and the Berkeley Earth adjusted data (in red).

Summary

The temperature data for Alaska demonstrates the difficulty in determining an accurate temperature trend for a region when the climate is subject to a high degree of variability.

It is possible that the climate has warmed by almost 1°C since 1900 (see Fig. 139.3), or it might not have warmed at all (see Fig. 139.2).

If the climate has warmed, this warming may have been fairly continuous (see Fig. 139.3), or it could have been fairly recent, occurring mainly after 1980 (see Fig. 139.6).

The one thing we can say is that the difference between the temperature rise based on Berkeley Earth adjusted data (see Fig. 139.7) and that based on the raw unadjusted data (see Fig. 139.5) is small (less than 0.3°C) and much less that the 5-year natural variability of the data (about 2°C).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations in Alaska with links to their raw data files.

74. Bangladesh - temperature trends WARMING 0.3°C

Despite being surrounded by India on threes sides, Bangladesh has a slightly different temperature trend to its larger neighbour. This may be because of a reduction in reliable data after 1999 where, in the case of India, the temperature rises abruptly by about 0.6°C; in the case of Bangladesh it does not. Between 1930 and 1990 where Bangladesh has the majority of its temperature data, the agreement with India is actually quite good.

 

Fig. 74.1: The (approximate) locations of the long and medium temperature records in Bangladesh. Those stations with a high warming trend between 1921 and 2010 are marked in red while those with cooling or stable trends are marked in blue. Those denoted with squares are long stations with over 1200 months of data.

 

Overall there are 17 temperature records for Bangladesh that have over 480 months of data (for full list see here). Of these three are long stations with over 1200 months of data, while the remainder are medium stations. In fact all the medium stations have at least 600 months of data. The locations of these stations are shown in Fig. 74.1 above. Their geographical spread is fairly even, which suggests that any simple average of their temperature anomalies should yield a fairly accurate approximation to the true mean temperature anomaly for the region. It can also be seen that over half of the stations have stable or cooling trends for the 90 years up to the end of 2010. 

Just as for my previous regional analyses, the monthly temperature anomalies for each station were calculated by subtracting the monthly reference temperature (MRT) for the relevant month from the unadjusted mean temperature for that month. These anomalies from the various long and medium records were then averaged to determine the mean temperature trend for the region. The resulting mean monthly temperature anomaly is shown in Fig. 74.2 below.

 

Fig. 74.2: The temperature trend for Bangladesh based on an average of anomalies from all long and medium stations. The best fit is applied to the monthly mean data from 1921 to 2010 and has a positive gradient of +0.27 ± 0.08 °C per century. The monthly temperature changes are defined relative to the 1931-1960 monthly averages.

 

The MRTs are different and specific to each station, but were always calculated using data from the same time period (in this case 1931-1960) for each station using the method described previously in Post 47. This ensures that the baseline reference temperature for each station is consistent so that all temperature changes over time are measured relative to the same point in time. However, no choice of 30-year MRT interval would have enabled all 17 station records to be included in the mean temperature in Fig. 74.2. This is because one station Berhampore (Berkeley Earth ID: 5388) has no data after 1957, while two stations, Dacca Tejgaon (Berkeley Earth ID: 152645) and Sylhet (Berkeley Earth ID: 152652), have virtually no data before 1956. An MRT interval of 1931-1960 allowed Berhampore to be included, thus increasing the number of stations with data before 1930 from three to four (see Fig. 74.3 below).I decided this was more beneficial in terms of overall data quality than having an extra two sets of station data after 1957.

Fig. 74.3: The number of station records included each month in the mean temperature trend for Bangladesh in Fig. 74.2.

 

The mean temperature trend for Bangladesh shown in Fig. 74.2 exhibits a slight warming of about 0.25°C after 1920. Yet the official Berkeley Earth trend suggests the warming is much greater, being almost 1°C after 1920 and nearly 1.5°C since 1830 (see Fig. 74.4 below). This is despite the fact that there is no real temperature data before 1875. So which data trend is correct?

 

Fig. 74.4: The temperature trend for Bangladesh since 1800 according to Berkeley Earth.

 

Well, if we average the Berkeley Earth adjusted data from all 15 stations used in this analysis (the adjusted data is listed on the Berkeley Earth site along with the raw data) we obtain trends that are very similar to those in Fig. 74.4 as the data in Fig. 74.5 below shows. This demonstrates two points. Firstly, it provides strong evidence that the averaging method we use to combine anomalies from the different stations is sufficiently accurate to avoid the need to use gridding and homogenization techniques. If this were not true then the data in Fig. 74.4 and Fig. 74.5 would not agree so well, but the uniform geographical distribution of stations across Bangladesh clearly facilitates this. But secondly, it shows that most of the warming presented in Fig. 74.4 comes from adjustments made to the data, and not from the raw data itself, otherwise the data in Fig. 74.5 would agree with the data in Fig. 74.2.

 

Fig. 74.5: Temperature trends for Bangladesh based on the average of anomalies for all long and medium stations using Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1921-2010 and has a gradient of +0.74 ± 0.03°C/century.

 

Finally, comparing the adjusted data in Fig. 74.5 with the unadjusted data in Fig. 74.2 allows us to quantify the contribution made to the trends in Fig. 74.4 by the Berkeley Earth data adjustments. These net adjustments are shown below in Fig. 74.6.

 

Fig. 74.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 74.5 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1921-2010 has a positive gradient of +0.431 ± 0.014 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

 

The data in Fig. 74.6 indicate that the adjustments made to the data by Berkeley Earth add at least 0.4°C of warming to the overall temperature trend after 1930. This explains why Fig. 74.4 and Fig. 74.2 appear so different.

 

Summary

It is clear from the temperature trend calculated using the raw data (see Fig. 74.2) that there has been no significant climate change in Bangladesh over the last 80 years. The long term temperature rise of 0.24°C is much less than the observed natural variation in the mean temperature.

The small temperature rise of 0.24°C since 1920 could be due to increased greenhouse gas emissions globally. Carbon dioxide levels in the atmosphere have increased from 307 ppm in 1930 to nearly 420 ppm today. But this temperature rise is much less than what mainstream climate science claims should be the case for this magnitude of change in CO₂.

Addendum

The regional average in Fig. 74.2 was calculated using 15 of the 17 possible sets of station data because of the choice of MRT interval. The stations at Dacca Tejgaon (Berkeley Earth ID: 152645) and Sylhet (Berkeley Earth ID: 152652) were excluded so that the station with much earlier data at Berhampore (Berkeley Earth ID: 5388) could be included. If the MRT interval is instead chosen to be 1951-1980 the reverse occurs with only Berhampore being excluded. The resulting mean temperature trend is shown below in Fig. 74.7. It has a slightly higher warming trend, but is otherwise very similar to Fig. 74.2.

Fig. 74.7: The temperature trend for Bangladesh based on an average of anomalies from all long and medium stations. The best fit is applied to the monthly mean data from 1921 to 2010 and has a positive gradient of +0.31 ± 0.08 °C per century. The monthly temperature changes are defined relative to the 1951-1980 monthly averages.