152: Belarus - temperature trends STABLE before 1980

When it comes to analysing the temperature data of Belarus the biggest problem is the low quantity of data. There is no data before 1880 and only three stations have data before 1950, two of which are long stations with over 1200 months of data (for a full list of stations see here). On a more positive note, there are seventeen medium stations with over 480 months of data and these are quite evenly distributed across the country. That means it should be possible to construct a reliable measure of the overall mean temperature change for Belarus, at least for the last sixty years. What this data then shows is that the climate of Belarus appears to have been fairly stable over the hundred years prior to 1980, but then in 1988, like much of Europe, the temperature suddenly increased by about 1.1°C (see Fig. 152.1 below).

Fig. 152.1: The mean temperature change for Belarus since 1880 relative to the 1981-2010 monthly averages. The best fit is applied to the monthly mean data from 1881 to 1980 and has a statistically insignificant positive gradient of +0.23 ± 0.23 °C per century. After 1980 there is an abrupt warming of 1.1°C.

In order to quantify the changes to the climate of Belarus 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 of the nineteen valid stations relative to its own monthly reference temperature (MRT). Then those anomalies were averaged to determine the mean temperature anomaly (MTA) for the whole country for each month. The MRTs for each station in Belarus were calculated using the same 30-year period, namely from 1981 to 2010. The resulting MTA for Belarus is shown as a time series in Fig. 152.1 above and clearly shows that temperatures were rising slowly (at about 0.23°C per century) for about 100 years up until 1980 but that this rise was only comparable to the uncertainty in the trend and so is not significant. After 1980, however, the MTA suddenly increases by about 1.1°C. Such behaviour is seen in the MTA for many other European countries and for Europe as a whole (see Post 44).

The total number of stations included in the MTA in Fig. 152.1 each month is shown in Fig. 152.2 below. The peak in the frequency after 1970 indicates why the 1981-2010 interval was determined to be the most appropriate to use for calculating the MRTs in this case.

Fig. 152.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for Belarus in Fig. 152.1.

The locations of the nineteen stations used to calculate the MTA in Fig. 152.1 are indicated on the map in Fig. 152.3 below. These stations appear to be distributed very evenly across the country with no significant clusters. This means that a simple average of their temperature anomalies should be just as accurate as any of the gridding or homogenization processes that are used by the main climate science groups in their analyses.

Fig. 152.3: The (approximate) locations of the 19 longest weather station records in Belarus. Those stations denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 152.4 below. This again was determined by averaging the anomalies each month from the nineteen longest stations and also suggests that the climate was warming very slightly before 1980 and then more rapidly thereafter. In this case, however, the post-1980 warming is more continuous and gradual in nature than that seen in the raw data in Fig. 152.1.

Fig. 152.4: Temperature trends for Belarus based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the 12-month moving average data over the period 1881-1980 and has a positive gradient of +0.25 ± 0.08°C/century.

If we compare the curves in Fig. 152.4 with those from the published Berkeley Earth (BE) version for Belarus shown in Fig. 152.5 below, we see that there is excellent agreement between the two sets of data at least as far back as 1880. This indicates that the simple averaging of adjusted anomalies used to generate the BE MTA in Fig. 152.4 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 152.5. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 152.1. What is more difficult to explain is how Berkeley Earth was able to determine the mean temperature of Belarus as far back as 1750 when there appears to be no reliable data before 1880.

Fig. 152.5: The temperature trend for Belarus since 1750 according to Berkeley Earth.

But if we next compare the adjusted data in Fig. 152.4 with the raw data shown in Fig. 152.1 we see that there is excellent agreement between these two sets of data as well (see Fig. 152.6 below).

Fig. 152.6: A comparison of the 5-year mean temperature change for Belarus since 1880 between the original raw data from Fig. 152.1 (in blue) and the Berkeley Earth adjusted data from Fig. 152.4 (in red).

The small differences between the MTA from the raw data in Fig. 152.1 and that from the BE adjusted data in Fig. 152.4  are 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. 152.1 and Fig. 152.4. The magnitudes of these adjustments are shown graphically in Fig. 152.7 below.

Fig. 152.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 152.4 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 1911-2010 has a negative gradient of -0.242 ± 0.016 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The blue curve in Fig. 152.7 is the difference in MTA values between adjusted (Fig. 152.4) and unadjusted data (Fig. 152.1), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both are relatively small with the former adding a slight cooling to the data since 1911 of about 0.24°C. The large offset between the blue curve and the orange curve in Fig. 152.7 is due to the different MRT intervals used for calculating the anomalies in Fig. 152.1 (1981-2010) and in Fig. 152.4 (1961-1990).

Fig. 152.8: A comparison of the 5-year mean temperature change for Belarus (blue curve) with that of the Baltic States in Post 51 (red curve).

As mentioned at the start of this post, the main weakness of the data for Belarus is the lack of good data before 1950 which obviously raises questions over its accuracy and reliabilty. One way to test the accuracy is to compare the Belarus data with that from neighbouring states to see what the level of similarity is. This has been done in Fig. 152.8 above where the comparator set is data from the Baltic States in Post 51. As can clearly be seen, the level of agreement between the two datasets is very good, particularly after 1950. However, even before 1950 there is good agreement even though the Belarus temperature trend is based on data from three stations at most. This suggests that the MTA for Belarus in Fig. 152.1 is reliable and likely to reflect the true climate of Belarus as far back as 1880.

Summary

The raw temperature data for Belarus clearly shows that the climate was stable up until 1980. Any warming in the trend over this period was significantly less than the natural variation in the mean temperature anomaly (MTA) that was seen for all timescales up to ten years in duration (see Fig. 152.1 and Fig. 152.4).

After 1980 the climate has warmed sharply by about 1.1°C. This behaviour is similar to patterns seen across Europe. The reason for this abrupt temperature increase is still unknown as it does not correlate with increases in carbon dioxide levels in the atmosphere.

There appears to be a very good level of correlation between the MTA trend for Belarus and that for the Baltic States reported in Post 51. This allows each to in effect corroborate the other and therefore strengthen the validity of each.



Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Long station = a station with over 1200 months (100 years) of data before 2014.

Medium station = a station with over 480 months (40 years) of data before 2014.

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

150: Malta - temperature trends STABLE before 1980

The difficulty in determining the extent of climate change in Malta is the lack of data. According to Berkeley Earth (BE) there are only two stations with over 480 months of data and one of those (A. M. D.) has virtually no data after 1934. The other station is Luqa (BE ID:156721) which is situated near the main airport and actually has over 1800 months of data, so it could be a good indicator of the climate of Malta as a whole. Its monthly mean temperature anomaly (MTA) relative to the period 1981-2010 is shown in Fig. 150.1 below.

 

Fig. 150.1: The mean temperature change for Luqa since 1840 relative to the 1981-2010 monthly averages. The best fit is applied to the monthly mean data from 1881 to 1980 and has a slight positive gradient of +0.05 ± 0.11 °C per century.

 

The data in Fig. 150.1 indicates that there was virtually no climate change in Malta before 1980. Then after 1980 the local temperature appears to have risen by about 0.6°C, although this depends on how one interprets the data. If one uses the 5-year average (yellow line) as a guide the temperature appears to increase by over 1°C from 1880 to 2010. However, average temperatures in 2010 are only about 0.6°C above the 1881-1980 best fit line (in red) which is virtually horizontal. So this would indicate that temperatures in 2010 are only about 0.6°C above average.

 

Fig. 150.2: Temperature trends for Luqa based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1886-2010 and has a positive gradient of +0.56 ± 0.03°C/century.

 

A similar temperature trend for Luqa is seen in its Berkeley Earth (BE) adjusted data (see Fig. 150.2 above) which appears to have zero adjustments after 1870. However, the actual published BE trends for Malta shown in Fig. 150.3 below appear to exhibit more warming over the period from 1890 to 2000 (~1.6°C) than is seen in the Luqa data in Fig. 150.2 (~1.4°C). It is also interesting that the temperature trend in Fig. 150.3 extends back to 1750 even though there appears to be no temperature data for Malta before 1850 (for a list of stations in Malta see here).

 

 Fig. 150.3: The temperature trend for Malta since 1750 according to Berkeley Earth.

 

If we compare the raw data for Luqa with the BE adjusted version we find that there is virtually no difference between the two (see Fig. 150.4 below). It is actually very unusual for such a long dataset not to undergo at least one breakpoint adjustment so this result is quite surprising.

 

Fig. 150.4: The 5-year average of the monthly mean temperature change for Luqa since 1820 based on the original raw data from Fig. 150.1 (in blue) and the Berkeley Earth adjusted data from Fig. 150.2 (in red).

 

As there is no data from Malta to compare the Luqa data against we could instead compare it with temperature data from the nearby Italian islands of Lampedusa (BE ID: 155869) and Pantelleria (BE ID: 175525 ). The locations of these islands relative to Malta and Sicily is shown in the map in Fig. 150.5 below. Lampedusa is about 150 km from both Malta and Pantelleria.

Fig. 150.5: The (approximate) locations of the weather stations in Malta (Luqa), Lampedusa and Pantelleria. Those stations denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

 

Unfortunately the temperature data from Lampedusa and Pantelleria only start around 1960 but both sets show temperature rises after 1980 that are similar to that seen in the Luqa data. There is also good correlation in the high frequency (less than 12 months) fluctuations, but the medium timescale fluctuations with peak widths of more than 12 months are not well correlated.

 

Fig. 150.6: A comparison of the 5-year average temperature change for the islands of Malta, Lampedusa and Pantelleria since 1960.

 

The other data that we could compare Luqa with is that of Italy. This is shown in Fig. 150.7 below and here the medium timescale fluctuations in the two datasets correlate much better.

 

Fig. 150.7: A comparison of the 5-year average temperature change for Malta and Italy.

 

 

Summary

The temperature data for Malta clearly shows that the climate warmed by over 0.6°C after 1980 (see Fig. 150.1).

Before 1980 there is a large amount of natural variation in the temperature data but no overall upward trend.

The temperature trend for Malta can only be determined using one set of station data: Luqa (BE ID:156721). This makes it very unreliable. Comparing it with the neighbouring islands of Lampedusa and Pantelleria only confirms the temperature trend after 1960 (see Fig. 150.6).

There does appear to be a good correlation between the temperature trend of Luqa in Malta and that of Italy in Fig. 148.2 of Post 148 extending back as far as 1890 (see Fig. 150.7). This would suggest that the temperature trends of Malta and Italy have been very similar over at least the last 150 years.



Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Long station = a station with over 1200 months (100 years) of data before 2014.

Medium station = a station with over 480 months (40 years) of data before 2014.

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

148: Italy - temperature trends STABLE before 1980

Whereas France only has four long stations with over 1200 months of data, Italy has at least twelve long stations, most with data stretching back over two hundred years. This means it is possible to determine  with a high degree of certainty the extent of climate change in Italy as far back as 1820. What this climate data shows is that the climate of Italy was stable for almost two hundred years up until 1980. Then over the last forty years it has warmed by about 1°C.

In addition to its twelve long stations, Italy also has 81 medium stations with over 480 months of data (for a full list see here). The locations of these 93 stations are shown on the map in Fig. 148.1 below. While the stations are generally spread evenly, there is a higher concentration of long stations in the north of the country compared to the south, and some clustering around Milan, Venice and Rome.

Fig. 148.1: The (approximate) locations of the 93 longest weather station records in Italy. 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 Italy 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 temperature (MRT), and then averaging those anomalies to determine the mean temperature anomaly (MTA) for the whole country for each month. The MRTs for each station in Italy were calculated using the same 30-year period, namely from 1961 to 1990. 

The resulting MTA is shown as a time series in Fig. 148.2 below and clearly shows that temperatures were stable for over two hundred years up until 1980. Then they appear to increase rapidly by about 1.0°C over thirty years. That said, the change is comparable in size and speed to natural variations seen in earlier parts of the trend such as in 1940. On the other hand the MTA after 1980 is based on data from many more stations (up to ninety) and so is likely to be more accurate.

Fig. 148.2: The mean temperature change for Italy since 1740 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1881 to 1980 and has a slight positive gradient of +0.03 ± 0.12 °C per century.

The total number of stations included in the MTA in Fig. 148.2 each month is shown in Fig. 148.3 below. The peak in the frequency around 1970 suggests that the 1961-1990 interval was indeed the most appropriate to use for the MRTs. It also indicates that data from about ten stations were used to calculate the MTA for almost every month back to 1820. As fifteen stations appears to the minimum number needed to provide an accurate MTA, this suggests that the trend in Fig. 148.2 is reliable at least as far back as 1820.

Fig. 148.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for Italy in Fig. 148.2.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 148.4 below. This again was determined by averaging each month the anomalies from the 93 longest stations but here the picture is slightly different from that depicted in Fig. 148.2. Instead of a stable MTA we see a positive trend of over 0.5°C per century suggesting that the climate was warming before 1980. This clearly contradicts the raw data in Fig. 148.2.

Fig. 148.4: Temperature trends for Italy based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1881-1980 and has a positive gradient of +0.53 ± 0.04°C/century.

But if we next compare the curves in Fig. 148.4 with those from the published Berkeley Earth (BE) version for Italy shown in Fig. 148.5 below, we see that there is excellent agreement between the two sets of data at least as far back as 1770. This indicates that the simple averaging of adjusted anomalies used to generate the BE MTA in Fig. 148.4 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 148.5. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 148.2.

Fig. 148.5: The temperature trend for Italy since 1750 according to Berkeley Earth.

The differences between the MTA in Fig. 148.2 and the BE versions using adjusted data in Fig. 148.4  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. 148.2 and Fig. 148.4. The magnitudes of these adjustments are shown graphically in Fig. 148.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 148.4) and unadjusted data (Fig. 148.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Between 1880 and 1980 both are considerable with the former leading to an additional warming since 1880 of over 0.5°C.

Fig. 148.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 148.4 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 1881-1980 has a positive gradient of +0.510 ± 0.009 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The overall impact of the BE adjustments can be seen more clearly if we compare the 5-year averages for the raw data (from Fig. 148.2) and the BE adjusted data (from Fig. 148.4). This comparison is shown in Fig. 148.7 below. It clearly shows that the trend based on adjusted data (red curve) exhibits considerably more warming since 1840 but slightly less since 1990.

Fig. 148.7: The 5-year mean temperature change for Italy since 1740 based on the original raw data from Fig. 148.2 (in blue) and the Berkeley Earth adjusted data from Fig. 148.4 (in red).

Summary

The raw unadjusted temperature data for Italy clearly shows that the climate was stable from 1780 to 1980 (see Fig. 148.2).

In contrast, the BE adjusted data claims that the climate first cooled and then warmed by 0.5°C from 1880 to 1980 (see Fig. 148.4).

After 1980 the climate has clearly warmed by about 1°C but this is still only of the same magnitude as the natural variations in the climate, so it may be too early to state definitively how much of the warming is permanent and how much more is still to come.



Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Long station = a station with over 1200 months (100 years) of data before 2014.

Medium station = a station with over 480 months (40 years) of data before 2014.

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

147: France - temperature trends STABLE before 1980

What is surprising about France is the poor quality of its temperature data. Its data is worse than for Spain, Italy, Germany, the UK, Norway, Sweden and Finland. And yet France is the de-facto home of metrology, the country that gave us SI units.

The longest temperature record in France is for Bourges in the middle of the country. It is one of only four long stations with over 1200 months of data in France. There are a further 91 medium stations in France with over 480 months of data (for a full list see here). The locations of all these 95 stations are shown on the map in Fig. 147.1 below. In this analysis I have also included two stations in the Channel Islands; a long station in Guernsey and a medium station in Jersey. The reason for this is that they are much closer to France than England and so it is more reasonable for their data to be combined with data from France than with that from the UK. It also results in another long station being included in the analysis for France thereby improving the reliability of its long-term trend.

Fig. 147.1: The (approximate) locations of the 97 longest weather station records in France and the Channel Islands. Those stations with a high warming trend 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 France 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 temperature (MRT), and then averaging those anomalies to determine the mean temperature anomaly (MTA) for the whole country for each month. The MRTs for each station in France were calculated using the same 30-year period, namely from 1961 to 1990. The resulting MTA is shown as a time series in Fig. 147.2 below and clearly shows that temperatures were fairly stable for over 120 years up until 1980. Then they appear to increase suddenly by over 0.8°C.

Fig. 147.2: The mean temperature change for France since 1820 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1861 to 1980 and has a slight positive gradient of +0.22 ± 0.11 °C per century.

The total number of stations included in the MTA in Fig. 147.2 each month is shown in Fig. 147.3 below. The peak in the frequency around 1990 suggests that the 1961-1990 interval was an appropriate one to use for the MRTs as it enabled all but five of the 97 datasets to be included in the MTA. All five of these medium station datasets had no data after 1900 and at least four exhibited a negative temperature trend. This suggests that in the 19th century the climate of France was cooling not warming.

Fig. 147.3 also indicates that data from less than ten stations were used to calculate the MTA for almost every month before 1945. As fifteen stations appears to the threshold number needed to provide an accurate MTA, this suggests that the trend in Fig. 146.2 is reliable only as far back as 1950. In fact most of the MTA trend before 1930 is dependent on data from only six stations. Of these, two are based in large cities (Paris and Marseille) and appear to exhibit strong linear warming trends (over 1.7°C since 1900) consistent with an urban heat island effect, and three have fragmented data (Bourges, Guernsey, and Montpellier). So only one (Chateauroux) is of any real quality and it has warmed by only about 0.3°C from 1900 to 2013.

Fig. 147.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for France in Fig. 147.2.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 147.4 below. This again was determined by averaging each month the anomalies from the 97 longest stations and suggests that the climate was slowly warming before 1980 by about 0.3°C since 1860. While this is slightly more than the 0.2°C suggested in Fig. 147.2, the difference is not that significant.

Fig. 146.4: Temperature trends for France based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1861-1980 and has a positive gradient of +0.31 ± 0.04°C/century.

Next, if we compare the curves in Fig. 147.4 with those from the published Berkeley Earth (BE) version for France shown in Fig. 147.5 below, we see that there is excellent agreement between the two sets of data at least as far back as 1825. This indicates that the simple averaging of adjusted anomalies used to generate the BE MTA in Fig. 147.4 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 147.5. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 147.2.

Fig. 147.5: The temperature trend for France since 1750 according to Berkeley Earth.

Any differences between the MTA in Fig. 147.2 and the BE versions using adjusted data in Fig. 147.4  are 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. 147.2 and Fig. 147.4. The magnitudes of these adjustments are shown graphically in Fig. 147.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 147.4) and unadjusted data (Fig. 147.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both are minimal with the former leading to an additional warming since 1860 of between 0.1°C and 0.2°C.

Fig. 147.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 147.4 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 1861-1980 has a positive gradient of +0.079 ± 0.010 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The overall impact of the BE adjustments can be seen more clearly if we compare the 5-year averages for the raw data (from Fig. 147.2) and the BE adjusted data (from Fig. 147.4). This comparison is shown in Fig. 147.7 below. It clearly shows that the trend based on adjusted data (red curve) exhibits more warming before 1900 but very little extra afterwards.

Fig. 147.7: The 5-year mean temperature change for France since 1780 based on the original raw data from Fig. 147.2 (in blue) and the Berkeley Earth adjusted data from Fig. 147.4 (in red).

Summary

The raw unadjusted temperature data for France clearly shows that the climate warmed by less than 0.2°C from 1880 to 1980 (see Fig. 147.2)

In contrast, the BE adjusted data claims that the climate warmed by 0.3°C over the same period (see Fig. 147.4).

After 1980 the climate has clearly warmed by almost 1°C (see Fig. 147.7).

The temperature data before 1980 presented here clearly disagree with that of Spain in Post 146. However, as the MTA for Spain over the 100 years before 1950 is based on data from between twelve and fifty different stations compared to only about five for France, that would suggest that the Spain data is the more accurate.



Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Long station = a station with over 1200 months (100 years) of data before 2014.

Medium station = a station with over 480 months (40 years) of data before 2014.

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

142: Scotland - temperature trends STABLE before 1980

In my previous post I looked at the temperature trends for Great Britain, i.e. the United Kingdom (UK) minus Northern Ireland. These exhibited a large amount of warming (over 1°C), most of which has occurred after 1980. This is not surprising as it is in agreement with other temperature trends that I have analysed, most of which also appear to exhibit some warming after 1980. However, in Great Britain there was still significant warming before 1980, albeit at a much slower rate compared to the post-1980 period. This is more unusual and is also slightly different to the situation found in Ireland (see Post 140) where any warming before 1980 was negligible. So why the difference? Is Ireland the outlier, or is it Great Britain? 

One way to find out is to look separately at the constituent parts of Great Britain: England, Scotland and Wales. If some of these are more similar to Ireland, then that may suggest Ireland is not the outlier but some other parts of the UK may be. Unfortunately there are only about eight stations in Wales of any note, of which only five are medium stations with over 480 months of data, and none have more than a thousand months of data. This means that it is only possible to determine an accurate temperature trend for Wales since 1970. As the most significant differences in the temperature data of Ireland and Great Britain occur well before 1970, the data from Wales is unlikely to be of much use is determining the cause. So for this analysis I will concentrate on England and first Scotland where the quality of the data is far greater.

Fig. 142.1: The (approximate) locations of the 22 longest weather station records in Scotland. 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.

Scotland has nine long stations with over 1200 months of data before 2014 and a further thirteen medium stations with over 480 months of data. These stations are well distributed across the region as the map in Fig. 142.1 above illustrates. This means a simple average of their monthly temperature anomalies should yield a reasonably accurate temperature trend for the country as a whole. This trend is shown in Fig. 142.2 below.

Fig. 142.2: The mean temperature change for Scotland since 1760 relative to the 1956-1985 monthly averages. The best fit is applied to the monthly mean data from 1826 to 1975 and has a slight positive gradient of +0.18 ± 0.07 °C per century.

In order to quantify the changes to the climate of Scotland 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 temperature (MRT), and then averaging those anomalies to determine the mean temperature anomaly (MTA) for the whole country for each month. The MRTs for Scotland were calculated using the same 30-year period as for the UK in Post 141, namely from 1956-1985. The resulting MTA is shown as a time series in Fig. 142.2 and clearly shows that temperatures were fairly stable for over 150 years up until 1975 with only a slight increase being detectable. However, this increase is less than the natural variation in the 5-year average (see the yellow curve in Fig142.2).

Then at some point in the 1980s (probably in 1988) the mean temperature appears to increase abruptly by about 1°C. This is a phenomenon that has been seen in many other temperature trends across Europe. There is also some evidence of additional warming before 1840 which results in an average trend of +0.28°C per century from 1781 to 1980, a 50% increase on the trend for 1826-1975 in Fig. 142.2. However, as the trend before 1850 is based on data from only two stations (see Fig. 142.3 below) it cannot be relied upon.

Fig. 142.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for Scotland in Fig. 142.2.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 142.4 below. This again was determined by averaging each month the anomalies from the 22 longest stations and suggests that the climate was fairly stable before 1880 but then warmed by over 1°C thereafter. In fact the 10-year average suggests there was no warming from 1781 to 1920 but the trend from 1901 to 2020 shows a warming of over 0.75°C. Not only that but the warming is more continuous in nature than the raw data in Fig. 142.2 indicates.

Fig. 142.4: Temperature trends for Scotland based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1826-1975 and has a positive gradient of +0.33 ± 0.03°C/century.

What is also apparent is that the trend in Fig. 142.4 for data from 1826 to 1975 is almost double the equivalent trend in Fig. 142.2. The reason for this is the adjustments made to the data by Berkeley Earth (BE). These adjustments 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. 142.4 and the raw data in Fig. 142.2. The magnitudes of these adjustments are shown graphically in Fig. 142.5 below. 

Fig. 142.5: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 142.4 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 1851-2010 has a positive gradient of +0.158 ± 0.002 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The blue curve in Fig. 142.5 is the difference in MTA values between the adjusted data (Fig. 142.4) and the unadjusted data (Fig. 142.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Overall these adjustments appear to add almost 0.3°C of warming to the trend between 1840 and 2010. Before 1840 the adjustments reduce the warming. The overall impact can be seen more clearly if we compare the 5-year averages for the raw data and the BE adjusted data as is shown in Fig. 142.6 below.

Fig. 142.6: The 5-year mean temperature change for Scotland since 1760 based on the original raw data from Fig. 142.2 (in blue) and the Berkeley Earth adjusted data from Fig. 142.4 (in red).

What the data in Fig. 142.6 shows is the amount of warming that has been added by the BE adjustments. While it is less than the natural warming it is still significant and adds over 0.2°C of warming to the period from 1876 to 2010. The result is a trend of 0.74°C per century after 1875 (as shown in Fig. 142.7 below) compared to only 0.57°C per century for the raw data in Fig. 142.2 for the same period. The main impact of the adjustments before 1900 appears to be to flatten the curve and thus eliminate any

Fig. 142.7: Temperature trends for Scotland 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 +0.74 ± 0.03°C/century.

Summary

What the raw data for Scotland shows is that the climate was stable for 150 years up to 1975 with warming of less than 0.18°C per century. This is similar to that seen in Ireland of 0.14°C per century (see Fig. 140.2 in Post 140) and significantly less than the value of 0.46°C per century for Great Britain (see Fig. 141.2 in Post 141). This suggests that Ireland and Scotland are not the outliers. So is England, and why?


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Long station = a station with over 1200 months (100 years) of data before 2014.

Medium station = a station with over 480 months (40 years) of data before 2014.

140: Ireland - temperature trends STABLE before 1980

The island of Ireland has nineteen weather stations with over 480 months of data before the end of 2013. All but two of these are in the Republic of Ireland. The two stations in Northern Ireland (Armagh and Belfast Airport) are though both long stations with over 1200 months of data. In addition there are a further six long stations in the Republic of Ireland together with eleven medium stations (for a full list see here). The locations of these nineteen stations are shown on the map in Fig. 140.1 below. Other than a small cluster around Dublin, the stations are evenly spread across the island. This means that any average of the temperature anomalies from these nineteen stations should approximate well to the true relative temperature change for Ireland. What this averaging shows is that the climate of Ireland was fairly stable until 1980 but with medium term fluctuations of up to 1°C in the mean temperature. After 1980 the mean temperature has probably risen by about 1°C. In other words, the rise since 1980 is comparable to the fluctuations.

Fig. 140.1: The (approximate) locations of the 19 longest weather station records in Ireland. Those stations with a high warming trend 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 Ireland 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 region. This MTA is shown as a time series in Fig. 140.2 and clearly shows that temperatures were fairly stable up until 1980. However at some point in the 1980s (probably in 1988) the mean temperature appears to increase abruptly by almost 1°C.

Fig. 140.2: The mean temperature change for Ireland since 1820 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1846 to 1975 and has a positive gradient of +0.14 ± 0.08 °C per century.

The process of determining the MTA in Fig. 140.2 involved first determining the monthly reference temperatures (MRTs) for each station using a common reference period, in this case from 1961 to 1990, 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. 140.2 each month is indicated in Fig. 140.3 below. The peak in the frequency between 1960 and 2010 suggests that the 1961-1990 interval for the MRTs was a good choice.

Fig. 140.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for Ireland in Fig. 140.2.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 140.4 below. This again was determined by averaging each monthly anomaly from the nineteen longest stations and suggests that the climate was fairly stable before 1920 but then warmed thereafter. In fact the 10-year average suggests a warming of almost 1.5°C from 1840 to 2000. Not only that but the warming is more continuous in nature than the raw data in Fig. 140.2 actually shows.

Fig. 140.4: Temperature trends for Ireland based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1896-2005 and has a positive gradient of +0.63 ± 0.04°C/century.

If we compare the curves in Fig. 140.4 with the published Berkeley Earth (BE) version for Ireland in Fig. 140.5 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. 140.4 using adjusted data is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 140.5. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 140.2.

Fig. 140.5: The temperature trend for Ireland since 1750 according to Berkeley Earth.

Any differences between the MTA based on raw unadjusted data in Fig. 140.2 and the BE version using adjusted data in Fig. 140.4 are 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. 140.2 and Fig. 140.4. 

Fig. 140.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 140.4 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 1881-2010 has a positive gradient of +0.028 ± 0.003 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The magnitudes of these adjustments are shown graphically in Fig. 140.6 above. The blue curve is the difference in MTA values between adjusted (Fig. 140.4) and unadjusted data (Fig. 140.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. The overall adjustment from 1880 to 1990 is small, less than ±0.1°C. The largest adjustments to the data occur after 1990 and before 1880. These adjustments add almost 0.2°C of warming to the data after 1990 and add almost 0.3°C of cooling to the data before 1880. While these changes are small in themselves, cumulatively they add almost 0.5°C to the warming trend. The full impact of these adjustments can be seen most clearly by comparing the the 5-year moving averages of the data in Fig. 140.2 and Fig. 140.4 as shown in Fig. 140.7 below.

Fig. 140.7: The 5-year mean temperature change for Ireland since 1820 based on the original raw data from Fig. 140.2 (in blue) and the Berkeley Earth adjusted data from Fig. 140.4 (in red).

Summary

According to the raw unadjusted temperature data, the climate of Ireland remained stable for 150 years up until the 1980s (see Fig. 140.2). Then it suddenly increased in temperature by almost 1°C. Why?

In contrast, adjusted temperature data from Berkeley Earth claims to show that the climate of Ireland has warmed more or less continuously since 1900. This warming is a bit more than 1°C (see Fig. 140.4).

Comparing the adjusted MTA data (see Fig. 140.4) with the unadjusted MTA data (see Fig. 140.2) suggests that the adjustments may have added up to 0.5°C to the overall warming since 1850 (see Fig. 140.7).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations in the Republic of Ireland 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.