137: Finland - temperature trends STABLE to 1980

The climate change seen in Finland over the last 200 years closely resembles that seen in Sweden. Between 1830 and 1920 the mean temperature rose by just over 0.5°C. Unfortunately the trend before 1890 is based on the average of less than three datasets so its reliability is open to question. Then from 1920 to 1980 the temperature appears broadly stable before rising again by about 1°C in the 1980s.

Like Norway and Sweden, Finland has an impressive number of weather stations, but only about twenty of them predate 1960. Overall the country has eleven long stations with over 1200 months of data before 2014 but only two have a significant amount of data before 1890. The country also has an additional 106 medium stations with over 480 months of data. These 117 long and medium stations are distributed across the country with a higher concentration in the southwest than elsewhere, and only eighteen are within the Arctic Circle (see Fig. 137.1 below). For a full list of stations see here.

Fig. 137.1: The (approximate) locations of the 117 longest weather station records in Finland. 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 Finland 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. 137.2 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 about 1°C. A similar temperature jump is seen in many regions across Europe, but in this case it is merely comparable to other fluctuations seen in the 5-year average such as those seen in the 1930s. It is therefore hard to ascertain if this jump is real, or exactly where in time this temperature rise is occurring and how much of it is permanent.

Fig. 137.2: The mean temperature change for Finland since 1880 relative to the 1971-2000 monthly averages. The best fit is applied to the monthly mean data from 1896 to 1980 and has a positive gradient of +0.23 ± 0.31 °C per century.

The process of determining the MTA in Fig. 137.2 involved first determining the monthly reference temperatures (MRTs) for each station using a common reference period, in this case from 1971 to 2000, 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. 137.2 each month is indicated in Fig. 137.3 below. The peak in the frequency between 1960 and 1990 suggests that the 1971-2000 interval was indeed the most appropriate interval to use for the MRTs.

Fig. 137.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for Finland in Fig. 137.2.

The data in Fig. 137.3 indicates that the greatest amount of temperature data available in Finland occurs after 1960 with almost 120 long and medium stations in operation at any one time. This drops to about twenty before 1960 and to about ten for most of the first half of the 20th century. Before 1890 there are only two stations in continuous operation, Helsinki (BE ID: 13544) and Helsinki-Vantaa Airport (BE ID: 175422), neither of which have any data before 1829. All the other data before 1840 comes from fragmented data from three or four other stations. 

All this means that the MTA for Finland before 1960 will be less reliable than its values after 1960 while the MTA before 1890 is based on only two stations, both of which are in Helsinki. As an MTA generally needs to be calculated using data from at least sixteen different stations in order to be accurate (see Post 57 for evidence), this suggests that any MTA before 1890 is unlikely to be representative of the country as a whole while the MTA before 1950 may also be slightly biased. Nevertheless, we can calculate an MTA for Norway back to 1740. If we do so we obtain the trends shown in Fig. 137.4 below. This appears to indicate continuous warming of about 1°C from 1840 to 1930 with a further 1°C of warming occurring since 1930. But if we discount the data before 1890 due to insufficient stations, then we are left with the data in Fig. 137.2 which paints a rather different picture.

Fig. 137.4: The mean temperature change for Finland since 1740 relative to the 1971-2000 monthly averages. The best fit is applied to the monthly mean data from 1891 to 2010 and has a slight positive gradient of +1.00 ± 0.18 °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. 137.5 below. This again was determined by averaging each adjusted monthly anomaly from the 117 longest stations and suggests that the climate has warmed continuously by nearly 2°C since 1830. In fact the 10-year average suggests a warming of nearly 2.5°C.

Fig. 137.5: Temperature trends for Finland based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1891-2010 and has a positive gradient of +1.03 ± 0.08°C/century.

Comparing the curves in Fig. 137.5 with the published Berkeley Earth (BE) version for Finland in Fig. 137.6 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. 137.5 using adjusted data is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 137.6. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 137.4 and Fig. 137.2. In other words, any discrepancy between the adjusted data in Fig. 137.5 and the unadjusted data in Fig. 137.4 cannot be due to the averaging process. And any form of weighted averaging would also not affect the results.

Fig. 137.6: The temperature trend for Finland since 1750 according to Berkeley Earth.

Most of the differences between the MTA in Fig. 137.4 and the BE versions using adjusted data in Fig. 137.6 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. 137.4 and Fig. 137.5.

The magnitudes of these adjustments are shown graphically in Fig. 137.7 below. The blue curve is the difference in MTA values between adjusted (Fig. 137.5) and unadjusted data (Fig. 137.4), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. The overall adjustment from 1840 to 2013 is small, less than ±0.1°C (see orange curve). The main impact is an offset in the MTA values of about 0.5°C (see blue curve). This is solely due to a use of different MRT intervals for the data in Fig. 137.4 and that in Fig. 137.5 and so can be ignored.

Fig. 137.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 137.5 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 1891-2010 has a positive gradient of +0.021 ± 0.005 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Summary

The temperature data for Finland illustrates the difficulty of determining the true extent of climate change when the data is partial or inadequate. Has the climate of Finland warmed by almost 2.5°C since 1840 as the Berkeley Earth adjusted data in Fig. 137.5 suggests, or has the climate been stable for most of the 20th century as the data in Fig. 137.2 appears to indicate? Is the warming seen before 1900 (when carbon dioxide levels barely increased) due to climate change, or is it due to an urban heat island (UHI) in Helsinki (which accounts for all the data)? Without more data it is hard to tell, but one way we could might be to compare Finland with its neighbours. This I will do in the next post.


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

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

136: Sweden - temperature trends WARMING mostly after 1980

The climate change seen in Sweden over the last 200 years is similar to that seen in Norway over the same period. This is perhaps not surprising given that they are nearest neighbours. The only major difference is the temperature change before 1980. In the case of Norway this was negligible (see Fig. 135.4 in Post 135) and was less than a tenth of the natural variation in the 5-year average. For Sweden there is a modest but distinct upward warming trend from 1860 to 1980 that amounts to about 0.6°C in total. That said this warming is still only comparable with the natural variation in the 5-year average of the mean temperature anomaly (MTA). Then after 1980 the MTA jumps abruptly by about 1°C, just as it did in Norway. The net result is that the temperature trend of Sweden over the last 150 years is one of the few regional trends that actually resembles the global trends published by NOAA, NASA-GISS, Hadley-CRU and Berkeley Earth, but this may not be quite what it seems.

As Sweden has a larger area and larger population than Norway it is not surprising that it has more weather stations. In total Sweden has 25 long stations with over 1200 months of data before 2014 and another 126 medium stations with over 480 months of data (for a full list of stations see here). Their approximate locations are shown on the map in Fig. 136.1 below. The stations are fairly evenly distributed across most of the country, but there does appear to be a greater concentration in the south and only twelve stations (i.e. 8%) are within the Arctic Circle. It does have two of the longest and earliest temperature records though: Uppsala and Stockholm. Both have over 3000 months of more or less continuous data that extend back to before 1760.

 

Fig. 136.1: The (approximate) locations of the 151 longest weather station records in Sweden. 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 Sweden 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. 136.2 and clearly shows that temperatures were rising slowly up until 1980. Then at some point in the 1980s (probably in 1988) the mean temperature appears to increase abruptly by about 1°C.

 

Fig. 136.2: The mean temperature change for Sweden since 1880 relative to the 1971-2000 monthly averages. The best fit is applied to the monthly mean data from 1881 to 1980 and has a positive gradient of +0.46 ± 0.19 °C per century.

 

The process of determining the MTA in Fig. 136.2 involved first determining the monthly reference temperatures (MRTs) for each station using a common reference period, in this case from 1971 to 2000, 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. 136.2 each month is indicated in Fig. 136.3 below. The peak in the frequency between 1960 and 2010 suggests that the 1971-2000 interval was indeed the most appropriate to use for the MRTs.

 

Fig. 136.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for Sweden in Fig. 136.2.

 

The data in Fig. 136.3 indicates that the period of greatest coverage of the country for temperature data is after 1960 with up to 150 long and medium stations in operation at any one time. This drops to about 25 between 1890 and 1960 and to four or less before 1860. This means that the MTA for Sweden before 1860 will be less reliable than its values after 1890. Note that a reliable MTA generally needs data from at least sixteen stations (see Post 57 for evidence). 

Nevertheless, we can calculate an MTA for Sweden back to 1720 and if we do so we obtain the trend shown in Fig. 136.4 below. This appears to show that the MTA exhibited a slow and gentle warming for much of the two hundred years before 1980 before the abrupt jump around 1988, but it can be interpreted differently.

 

Fig. 136.4: The mean temperature change for Sweden since 1720 relative to the 1971-2000 monthly averages. The best fit is applied to the monthly mean data from 1731 to 1980 and has a slight positive gradient of +0.30 ± 0.05 °C per century.

 

If the best fit is performed for the interval 1761-1860 then the gradient is -0.06 ± 0.22°C while the best fit to data from 1861 to 2010 yields a strong positive gradient of +0.99 ± 0.11°C (see Fig. 136.5 below). So changing the fitting interval can change the result; but remember, as Fig. 136.3 shows, the MTA data before 1860 is based on only four station records. Similarly, changing the fitting interval to 1861-2010 also changes the interpretation of the data after 1980. The abrupt jump around 1988 now looks more like a temporary plateauing of the MTA data between 1940 and 1980. So which is correct? The problem is it is difficult to know due to the large natural fluctuations in the MTA data: both could be true or neither could be true. What we do know is that the 1988 jump is seen in the MTA for other countries and for Europe as a whole (see Post 44).

 

Fig. 136.5: The mean temperature change for Sweden since 1820 relative to the 1971-2000 monthly averages. The best fit is applied to the monthly mean data from 1861 to 2010 and has a positive gradient of +0.99 ± 0.11 °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. 136.6 below. This again was determined by averaging each monthly anomaly from the 151 longest stations and it suggests that the climate was fairly stable before 1870 but then warmed by over 1.5°C thereafter. In fact the 10-year average suggests a warming of almost 2°C. Moreover the data in Fig. 136.6 is in good agreement with the MTA based on unadjusted data in Fig. 136.4.

 

Fig. 136.6: Temperature trends for Sweden 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. 136.6 with the published Berkeley Earth (BE) version for Sweden in Fig. 136.7 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. 136.6 using adjusted data is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 136.7. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 136.4. In other words, any discrepancy between the adjusted data in Fig. 136.6 and the unadjusted data in Fig. 136.4 cannot be due to the averaging process.

Fig. 136.7: The temperature trend for Sweden since 1750 according to Berkeley Earth.

Most of the (slight) differences between the MTA in Fig. 136.4 and the BE versions using adjusted data in Fig. 136.7 are instead mainly due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These can lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values seen in Fig. 136.4 and Fig. 136.6.

The magnitudes of these adjustments are shown graphically in Fig. 136.8 below. The blue curve is the difference in MTA values between adjusted (Fig. 136.6) and unadjusted data (Fig. 136.4), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. The change in the overall adjustment from 1876 to 2010 is small, less than +0.06°C while the much larger 0.4°C offset is due to the difference in MRT intervals used to determine the anomalies in Fig. 136.4 and Fig. 136.6 and can be ignored. What this shows is that the BE adjustments in this case are small which is why the data in Fig. 136.4 and Fig. 136.6 agree so well.

Fig. 136.8: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 136.6 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 1876-1980 has a positive gradient of +0.046 ± 0.002 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Summary

According to the raw unadjusted temperature data, the climate of Sweden has warmed gradually for over 150 years by about 1.5°C in total (see Fig. 136.4). There is some evidence of an abrupt jump of 1°C around 1988 but this depends on how one interprets the data and the fitting process. The temperature before 1860 appear to have been stable for over one hundred years.

In this instance the adjusted temperature data from Berkeley Earth closely follows that of the unadjusted data (see Fig. 136.6).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

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

51. The Baltic States - temperature trends STABLE to 1980

The Baltic States are the countries of Lithuania, Latvia and Estonia that used to be part of the USSR and are now part of the EU. For the purpose of geographical convenience I will also include the enclave of Kaliningrad in this analysis, for while it is actually a part of Russia, it is not contiguous with Russia, but is instead bordered by Poland, Lithuania and the Baltic Sea.

The mean temperature trend for the region is shown in Fig. 51.1 below. This was achieved by averaging the temperature anomalies for all the weather station temperature records in the region, where the temperature anomalies were measured relative to the monthly reference temperature (MRT) in each case. The MRTs were calculated for the interval 1991-2010. This is rather later and shorter (only 20 years rather than 30) than usual due to the need to maximize the available data and avoid the jump in temperature in 1988. For a more detailed explanation of the MRT calculation process, see Post 47.

 

Fig. 51.1: The temperature trend for the Baltic States since 1775. The best fit is applied to the interval 1781-1980 and has a negative gradient of -0.08 ± 0.08 °C per century. The monthly temperature changes are defined relative to the 1991-2010 monthly averages.

 

For 200 years up to 1980 there was no anthropogenic global warming (AGW) occurring in the Baltic States. In fact the mean temperature for the region fell by about 0.15 °C. Then around 1988 it suddenly jumped by about 1.1 C (see Fig. 51.1 above). Even then the temperature is less than it was in the 1820s, although the data for that period needs to be treated with some caution. That is because it is based on less than five station temperature records (see Fig. 51.2 below). 

However, the more significant factor in explaining the caution over the temperature peak around 1824 in Fig. 51.1 is probably the fragmentation of some of the temperature records in that era, particularly for Dorpat, Tallinn and Riga. This, when combined with the low number of stations overall, can lead to discontinuities in the temperature trend. 

Having said that, data from Vilnius, Sovetsk and Mitau all appear to show similar peaks in the temperature trend around 1824, and their data are continuous. So maybe the peak around 1824 is real. In which case temperatures in the 1820s really were higher than today.

Fig. 51.2: The number of station records included each month in the mean temperature trend for the Baltic States when the MRT interval is 1991-2010.

The temperature trend shown in Fig. 51.1 is the average of just 23 medium and long station records with over 480 months of data. Of these, seven are long stations with more than 1200 months of data. In fact four have over 1800 months (or 150 years) of data. The 23 stations are also distributed evenly over the region as shown in Fig. 51.3 below, with each of the four regions (Kaliningrad, Lithuania, Latvia and Estonia) also containing one of the four longest records. The HTML links above link to a list of stations for each region.

Fig. 51.3: The locations of long stations (large squares) and medium stations (small diamonds) in the Baltic States. Those stations with a high warming trend are marked in red.

What is interesting is comparing the trend based on the original true temperature data in Fig. 51.1 with the equivalent trend based on the data used by Berkeley Earth after they have adjusted the data. The Berkeley Earth version is shown in Fig. 51.4 below.

Fig. 51.4: Temperature trend in the Baltic States since 1775 derived by aggregating and averaging the Berkeley Earth adjusted data for all long and medium stations. The best fit linear trend line (in red) is for the period 1841-2010 and has a gradient of +0.45 ± 0.04 °C/century.

Unlike the original data which has a slight negative trend before 1980, the Berkeley Earth adjusted data has a strong positive trend of 0.45 °C per century. In total this equates to a warming of over 0.8 °C before 1980. When the temperature jump after 1980 is included, the total temperature rise since 1800 is over 2 °C. This may be consistent with IPCC briefings, but it is not consistent with the actual real data in Fig. 51.1.

Fig. 51.5: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 51.4 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 1841-2010 has a gradient of +0.351 ± 0.007 °C per century. The orange curve shows the contribution from breakpoint adjustments.

Overall, the Berkeley Earth adjustments appear to add between 0.6 °C and 1.0 °C to the warming, depending on how you view it. If we consider the net adjustments made to the data (the blue curve in Fig. 51.5 above) which are the difference between the mean anomalies in Fig. 51.1 and Fig. 51.4, these appear to add about 0.6 °C of warming. The difference in the gradients, however, results in over 0.9 °C of warming being added. Either way, these are significant modifications to the real data that completely change its properties.

Summary

1) In the 200 years before 1980 the mean temperature of the region decreased by 0.15 °C (see Fig. 51.1).

2) Once again we see a sudden rise in temperature in 1988 of about 1 °C that is difficult to explain (see Fig. 51.1). Similar rises were seen in Poland (see Post 50), Germany (see Post 49) and Denmark (see Post 48).

3) Even after the 1988 temperature rise, temperatures post-2000 are still below those pre-1830 (see Fig. 51.1).

4) The temperature trend based on Berkeley Earth adjusted data has a warming of over 0.8 °C before 1980 and over 1 °C of additional warming after 1980 (see Fig. 51.4).

5) Adjustments made to the temperature data by Berkeley Earth via breakpoint adjustments and homogenization have profoundly changed both the magnitude of the warming since 1800 and its significance (see Fig. 51.4 and Fig. 51.5).

50. Poland - temperature trends WARMING 0.9°C

There are over 100 temperature records for Poland. The longest is the Warsaw record (Berkeley Earth ID: 157587) which dates back to 1779 (see Fig. 50.1 below) and exhibits a strong warming trend of 0.71 °C per century. However, this warming trend is not continuous but has considerable variability, with temperatures in the 1930s being comparable to those of today.

 

Fig. 50.1: The temperature trend for Warsaw since 1779. The best fit is applied to the interval 1811-2010 and has a positive gradient of +0.71 ± 0.08 °C per century. The monthly temperature changes are defined relative to the 1951-1980 monthly averages. 

 

Of the 100 or more stations in Poland (for a full list see here), 60 have over 480 months of data (these are medium stations) and five have over 1200 months of data (long stations). In fact over 40 of the medium station have over 720 months (or 60 years) of data which is fairly unusual. This is because there was a significant and abrupt increase in the number of weather station records in Poland in 1951. Similar investments in new stations are seen in many other countries as well in the latter part of the 20th century, but these tend to occur around 1960 or 1970-1973.

The locations of these long and medium stations are shown below in Fig. 50.2. The map indicates that the stations are fairly evenly distributed across Poland which means that a simple average of the anomalies from all these stations should approximate very well to the temperature trend for the country as a whole.

Fig. 50.2: The locations of long stations (large squares) and medium stations (small diamonds) in Poland. Those stations with a high warming trend are marked in red. 

 

In order to determine the mean temperature change for Poland, I first calculated the temperature anomalies for each temperature record relative to its monthly means (MRTs) for the period 1951-1980. These anomalies were then averaged to produce the trend shown in Fig. 50.3 below.

The 1951-1980 interval was chosen because it allowed the maximum number of stations to be included in the mean (see Fig. 50.4 below) while also avoiding the sudden jump in temperatures seen around 1988 in many European temperature records (see Post 44 and Post 49) that could destabilize the MRTs. For a moredetailed description of how the monthly reference temperatures (MRTs) are calculated and why, please refer to Post 47.

 

Fig. 50.3: The temperature trend for Poland since 1779. The best fit is applied to the interval 1811-2010 and has a positive gradient of +0.45 ± 0.08 °C per century. The monthly temperature changes are defined relative to the 1951-1980 monthly averages. 

While the trend in Fig. 50.3 above is the result of averaging over 60 separate records, no more than 58 are included in any single monthly average, and before 1950 this is typically less than ten (see Fig. 50.4 below). Overall, the temperature trend exhibits a significant warming of about 0.9 °C since 1800, but this is much less than that seen in the trend for Warsaw as shown in Fig. 50.1 above. The difference is almost certainly due to anthropogenic effects such as the urban heat island (UHI) effect or waste heat emissions from human and industrial activity. Overall such direct anthropogenic surface heating (DASH) would be expected to increase the temperature of the whole of Poland by about 0.2 °C.

The other detail that is noticeable about the data in Fig. 50.3 is that the temperatures in the 1930s were similar to those of today. This is despite temperatures appearing to have jumped suddenly by about 0.84 °C in 1988. A similar and larger jump of 0.97 °C was seen in the temperature data across Germany at the same time (see Post 49).

Fig. 50.4: The number of station records included each month in the mean temperature trend for Poland when the MRT interval is 1951-1980.

What is clear is that the warming seen in Poland, while significant, is much less than that expected based on IPCC and Berkeley Earth reports. These have suggested that the warming is over 1.5 °C and fairly monotonic. In reality there is a large amount of what looks like natural variation in the data that persists even for very long time-averaged data such as the 5-year moving average.

Fig. 50.5: Temperature trend in the Poland since 1779 derived by aggregating and averaging the Berkeley Earth adjusted data for all long and medium stations. The best fit linear trend line (in red) is for the period 1801-1980 and has a gradient of +0.32 ± 0.03 °C/century.

For comparison, the temperature trend that results from averaging the temperature data after it has been adjusted by Berkeley Earth is shown in Fig. 50.5 above. This trend shows a modest warming of 0.32 °C per century before 1980, or about 0.6 °C in total, followed by a major temperature increase of over 1 °C after 1980. This trend is also virtually identical to the one published by Berkeley Earth (see here) as shown in Fig. 50.6 below.

Fig. 50.6: The temperature trend for Poland since 1750 according to Berkeley Earth.

If we look at the difference between the mean trend in Fig. 50.3 (based on the original true data) and the trend in Fig. 50.5 that is the result of using the Berkeley Earth adjusted data we see that the adjustments made by Berkeley Earth are again not neutral. In fact the Berkeley Earth adjustments add nearly 0.6 °C of warming since 1840 (see Fig. 50.7 below).

Fig. 50.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 50.5 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 1841-2010 has a gradient of +0.335 ± 0.007 °C per century. The orange curve shows the contribution from breakpoint adjustments.

Conclusions

It is clear from the results shown here that temperatures in Poland have increased over the last 250 years, but by how much and for what reason remains unclear. There has certainly not been the catastrophic warming due to carbon dioxide emissions (i.e. more than 1.5 °C) that has been claimed by climate scientists, although there might have been some warming from this source. However, such warming cannot realistically be greater than 0.7 °C (i.e. the 0.9 °C seen in Fig. 50.3 minus the 0.2 °C we would expect from DASH or UHI effects). The problem is that any remaining warming that may be due to CO₂ emissions does not correlate well with CO₂ levels in the atmosphere over time. And then there is the uncertainty over the amount that natural variation in the temperature record may be contributing to the relatively short-term trends (less than 250 years) that we are observing.

We can probably claim with a fair degree of confidence that the data after 1950 in Fig. 50.3 is likely to be highly reliable as it is based on over 50 station records that are evenly spaced geographically (see Fig. 50.2). But this raises the question of what is causing the sudden jump in temperatures seen in 1988 which is also seen in other countries such as Germany (see Post 49).

For data before 1950, this is based on between about four and ten station records, at least back to 1830. The overall trend for 1831-1980 suggests a total temperature rise of only about 0.35 ± 0.15 °C, which is less than the standard deviation of the temperature fluctuations in the 5-year moving average for that period. This suggests that these temperature changes could be explained by natural variability.

Finally, it is apparent that once again there is a large discrepancy (0.6 °C) between any temperature rises seen in the raw data (see Fig. 50.3) and the rises claimed by climate scientists (see Fig. 50.5). This difference is largely due to adjustments made to the raw data by climate scientists (see Fig. 50.7).

49. Germany - temperature trends PARABOLIC

If any country in Europe were to exhibit the effects of anthropogenic global warming (AGW) and climate change, then you might expect that country to be Germany. Except that it doesn't.

There are over 135 sets of weather data for Germany that contain over 480 months of data (see here). Of these 34 are long stations with over 1200 months of data while the remainder I denote as medium stations. In fact ten temperature records have over 2000 months of data. This makes the temperature data for Germany some of the best available.

The geographical locations of these weather stations are indicated on the map below (see Fig. 49.1). This shows that both the long and medium stations are distributed fairly evenly, although there appear to be slightly fewer medium stations in the former East Germany. The stations are also differentiated according to the strength of their warming trend. Those with a large warming trend are marked in red, where a large trend is defined to be one that is both greater than 0.25 °C in total and also more than twice the uncertainty. 

The threshold of 0.25 °C is set equal to the temperature rise that one would expect in the EU as a whole due to waste heat or direct anthropogenic surface heating (DASH) due to human and industrial activity. In fact for Germany, based on its population, area and energy consuption, we would expect the temperature rise since 1700 due to DASH to be at least 0.6 °C (see Post 14), even without the effects of an enhanced greenhouse effect.

 

Fig. 49.1: The locations of long stations (large squares) and medium stations (small diamonds) in Germany. Those stations with a high warming trend are marked in red.

 

The longest data set is for Berlin-Tempelhof (Berkeley Earth ID: 155194) which has data that extends back to 1701. This data is shown in Fig. 49.2 below as the temperature anomaly after subtracting the monthly reference temperatures (MRTs) based on the 1971-2000 averages. The method for calculating the anomalies and MRTs from the raw temperature data is described in Post 47. However, there are two caveats that need to be applied to the data in Fig. 49.2. Firstly, there are significant gaps in the data before 1756, and secondly any data before 1714 needs to be treated with caution simply because thermometers did not exist then, at least not in their current form. 

Fig. 49.2: The temperature trend for Berlin-Tempelhof since 1700. The best fit is applied to the interval 1821-1980 and has a positive gradient of +0.13 ± 0.10 °C per century. The monthly temperature changes are defined relative to the 1971-2000 monthly averages.

In order to determine the temperature trend for Germany I have averaged the temperature anomalies from all 135 long and medium stations. The result is shown in Fig. 49.3 below. All stations with data less than 480 months are excluded as they add no real value to the result, particularly if the data is very recent (i.e. after 1980). This is because the temperature change over time is small, typically 1 °C per century, so you really need at least 40 years of data to detect a measurable trend above the noise.

Fig. 49.3: The temperature trend for Germany since 1700. The best fit is applied to the interval 1756-2005 and has a negative gradient of -0.02 ± 0.05 °C per century. The monthly temperature changes are defined relative to the 1971-2000 monthly averages.

What is immediately apparent is that the trend in Fig. 49.3 differs significantly from the widely publicized IPCC version. Firstly, temperatures before 1850 appear to be higher than they are now, not lower. Secondly, temperatures were stable or declining for over 150 years prior to 1980, not rising. And finally, the mean temperature appears to jump suddenly in 1988 just as the IPCC was being established. Some of these traits are also seen in the mean temperature trend I constructed for the whole of Europe that was published in Post 44. The 19th century cooling is also seen in the temperature data of New Zealand (see Post 8) and Australia (see Post 26).

 

Fig. 49.4: The amount of temperature data from Germany included in the temperature trend each month for three different choices of MRT interval.

As I pointed out in Post 47, the choice of interval for determining the MRTs can influence the number of station records that are included in the final average for the temperature trend, and thus can also influence the nature of the trend itself. In order to test how robust the trend in Fig. 49.3 is regarding changes to the MRT interval, I repeated the calculation for three different MRT intervals. The curves in Fig. 49.4 above show how the number of stations in the final trend changes for each of the different MRT intervals. 

It is clear that there is very little difference between choosing MRT intervals of 1956-1985 and 1971-2000, although the latter does result in a slightly larger number of stations being included in the trend calculation after 1960. The advantage of using the former interval is that it corresponds to a part of the temperature record where the mean temperature is fairly stable whereas the latter interval spans the abrupt increase in temperature seen around 1988. Despite this, in both cases the final trends are very similar, with the best fit in each case being -0.015 °C/century for the 1971-2000 MRT and -0.032 °C/century for the 1956-1985 MRT. In both cases the fitting range was 1756-2005.

The 1901-1930 interval enables more data from before 1930 to be included in the trend (from stations that were closed down before 1930), but significantly less after 1950 when many new stations were set up. Nevertheless, the final trend is almost identical to the those for other two MRT intervals with the best fit being only slightly higher at +0.0004 °C/century. In all three cases temperatures before 1850 were about as high as those after 2000, and in all three cases the mean temperature trend exhibited a large jump in temperature in 1988 as is shown clearly in the 5-year moving average in Fig. 49.3.

Fig. 49.5: The temperature trend for Germany since 1750 according to Berkeley Earth.

Irrespective of which interval is used to determine the MRTs, the resulting temperature trend I have constructed and published in Fig. 49.3 differs significantly from that published by Berkeley Earth which is shown in Fig. 49.5 above. The difference, as I have noted before, is due to homogenization and breakpoint adjustments used by Berkeley Earth to create their adjusted anomalies for each station. Averaging their adjusted anomalies yields the trend shown below in Fig. 49.6, which is virtually identical to the one shown above in Fig. 49.5. This demonstrates that it is not a difference in averaging method that is responsible for the difference between my results in Fig. 49.3 and the Berkeley Earth result. So it must be a difference in the anomaly data itself that is responsible. This can only be due to the adjustments made by Berkeley Earth.

Fig. 49.6: Temperature trend in Germany since 1750 derived by aggregating and averaging the Berkeley Earth adjusted data for all long and medium stations. The best fit linear trend line (in red) is for the period 1801-1980 and has a gradient of +0.29 ± 0.03 °C/century.

The actual temperature difference between the data in Fig. 49.6 and that in Fig. 49.3 is shown below in Fig. 49.7 (blue curve) as the the total adjustment made to the data by Berkeley Earth. The data in Fig. 49.7 highlights two points of note. Firstly, the Berkeley Earth adjustments are not neutral: they add about 0.3 °C to the warming after 1840. Secondly, the adjustments flatten the curve before 1840 and so remove the warm period that mirrors the one seen after 1988. In so doing these adjustments radically change the nature of the temperature trend from an oscillatory one in Fig. 49.3 to the infamous hockey stick shape in Fig. 49.6 that is now synonymous with anthropogenic global warming (AGW).

Fig. 49.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 49.6 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 1841-2010 has a gradient of +0.173 ± 0.003 °C per century. The orange curve shows the contribution from breakpoint adjustments.

Conclusions

The results I have presented here clearly show that the real temperature trend for Germany over the last 300 years differs significantly from the conventional view of global warming. These differences can be summarized as follows.

1) Temperatures before 1840 were comparable to those of today (see Fig. 49.3).

2) The overall temperature trend since 1800 is broadly flat (see the best fit line in Fig. 49.3). 

3) At least 0.6 °C of any temperature rise since 1700 should be due to direct anthropogenic surface heating (DASH) or waste heat from human activity, and not from greenhouse gas emissions.

4) There is a large and seemingly unnatural temperature rise of 0.97 °C in 1988 that occurs at the very moment the IPCC is being formed (see the 5-year mean in Fig. 49.3).

5) Berkeley Earth adjustments have added 0.3 °C of warming to the temperature trend since 1840 and erased most of the warm temperatures before 1840 (see Fig. 49.7).

6) Of the 1.5 °C of warming since 1750 claimed by Berkeley Earth (see Fig. 49.6), 0.6 °C could be due to DASH (see point 3 above) and 0.3 °C is due to adjustments made to the temperature data by Berkeley Earth (see point 5 above).

48. Denmark - temperature trends STRONG WARMING 1.8°C

In total, Denmark has twenty-two sets of temperature data that exceed 480 months in length (see here). Of these, eight contain over 1200 months of data (long stations), with the longest being Copenhagen (Berkeley Earth ID: 154574) which has continuous data from 1798, and some data fragments that go as far back as 1768. This suggests that the country has a similar number of station temperature records as New Zealand (see Post 8), but surprisingly it is less than is found for the Danish autonomous territory of Greenland which has a population of less than 60,000 and which I will look at in detail at some point in the future.

Fig. 48.1: The locations of long stations (large squares) and medium stations (small diamonds) in Denmark. Those stations with a high warming trend are marked in red.

The distribution of these weather stations in Denmark is indicated in Fig. 48.1 above. It shows a fairly even spread that covers most of the country. It also shows that most of the station data exhibits some significant degree of warming, with only two stations exhibiting a cooling trend (defined as being a trend that is less than twice the uncertainty in the trend).

The data from Denmark is interesting in one other respect in that, of its fourteen medium length station temperature records (i.e. those with over 480 months of data but less than 1200), four have no data after 1970 but do have data going back to the 19th century, while six have no data before 1970. This means that these two groups of stations require different time periods for the calculation of the reference temperatures needed to find their monthly temperature anomalies. For an explanation of the rationale and process used to determine the temperature anomalies via the calculation of monthly reference temperatures (MRTs), please refer to my previous post.

 

Fig. 48.2: The maximum amount of temperature data available from Denmark each month for inclusion in the mean temperature trend.

This problem is illustrated in Fig. 48.2 above. The two peaks in the frequency distribution indicate the two different possibilities for the MRT period. As I pointed out in Post 47, ideally the MRT period needs to be about 30 years in length with at least 40% data coverage. One way to circumvent this problem is to calculate the temperature trend for two MRT time intervals (the data in Fig. 48.2 suggests that 1891-1920 and 1971-2000 should be optimal), compare the results, and if necessary take a weighted average. 

 

Fig. 48.3: The temperature trend for Denmark since 1750. The best fit is applied to the interval 1851-2000 and has a positive gradient of +1.18 ± 0.09 °C per century. The monthly temperature changes are defined relative to the 1971-2000 monthly averages.

If we choose 1971-2000 as our reference period for the MRTs, then the overall temperature trend is as shown in Fig. 48.3 above. The number of stations included each month in this overall trend is shown in Fig. 48.4 below. Overall, up to seventeen stations are included, but before 1970 that drops to less than ten with only one station with data before 1870. The result is that there appears to be a fairly continuous warming trend from 1851 to 2000 as indicated by the data in Fig. 48.3.

Fig. 48.4: The number of sets of station data included each month in the temperature trend for Denmark when the MRTs are calculated for the period 1971-2000.

Now consider what happens if we choose 1891-1920 as our reference period for the MRTs. The result is that there are more stations included before 1970, but less after (see Fig. 48.5 below). This also changes the form of the temperature trend in Fig. 48.6.

Fig. 48.5: The number of sets of station data included each month in the temperature trend for Denmark when the MRTs are calculated for the period 1891-1920.

What we now see in Fig. 48.6 is a much smaller warming trend before 1980 (less than 0.6 °C with possibly higher temperatures before 1800), but a more pronounced jump in temperatures after 1988. This similar to the trend seen for South Africa (see Post 37) and also for Europe as a whole (see Post 44). It is important to note, though, that all the data before 1860 in both Fig. 48.6 and Fig. 48.3 comes from just one station record: Copenhagen (Berkeley Earth ID: 154574). This means the accuracy and reliability of this data cannot be truly ascertained.

Fig. 48.6: The temperature trend for Denmark since 1750. The best fit is applied to the interval 1768-1980 and has a positive gradient of +0.30 ± 0.05 °C per century. The monthly temperature changes are defined relative to the 1891-1920 monthly averages.

The analysis outlined above means that we have two possible results for the temperature trend in Denmark. Both are fairly similar, and for once both are in general agreement with the trend published by Berkeley Earth (see Fig. 48.7 below). But can we combine them into a single result?

Fig. 48.7: The temperature trend for Denmark since 1750 according to Berkeley Earth.

The answer is yes. If we take the weighted average of each of the two trends in Fig. 48.3 and Fig. 48.6 we get the result shown in Fig. 48.8 below. The relative weightings of each month's data is determined by the number of stations included in the average for that month as indicated in Fig. 48.4 and Fig. 48.5 respectively. There is, though, one other factor we need to take into account: the different MRT intervals for the two original trends. Without a correction term this will distort the final data.

In order to allow for the differing MRTs, the trend curve in Fig. 48.3 needs to be first adjusted upwards so that the mean temperature anomaly for the period 1891-1920 is zero in order to be consistent with the data in Fig. 48.6. This requires an upward adjustment of 0.634 °C. Only after this adjustment has been made can the weighted average be determined.

Fig. 48.7: The weighted temperature trend for Denmark since 1750. The best fit is applied to the interval 1851-2000 and has a positive gradient of +1.02 ± 0.09 °C per century. The monthly temperature changes are defined relative to the 1891-1920 monthly averages.

Conclusions

The data from Denmark appears to show a warming trend of about 1.5 °C since 1850. This is by far the largest warming seen in any of the regional records that I have investigated so far. It is also one of the few that appears to agree with IPCC reported values. However, this is not as straightforward as it seems. For a start changing the MRT interval from 1971-2000 (as in Fig. 48.3) to 1891-1920 (as in Fig. 48.6) dramatically reduces the temperature trend before 1980. So which one is correct? 

Then there is the problem of the sudden jump in temperature in 1988 of 0.93 °C. A similar jump was seen in the temperature trend for the Europe data in Post 44 as well. The reason for this is still unclear (at least to me). In Post 45 I speculated that it could be the result of improved air quality in Europe due to EU legislation. Alternatively, it could be the consequence of a change in measurement method, such as a change from liquid-in-glass thermometers to electronic systems which occurred around that time. What is strange is the timing and suddenness of this increase. 

Whatever the true scale of the temperature rise in Denmark since 1750, it cannot be explained entirely by direct anthropogenic surface heating (DASH) or waste heat. The best estimate of the expected magnitude of DASH for Denmark (based on its population density) is about 0.35 °C since 1850. However, this could be greater if the source of the heating from human industrial activity is concentrated around the locations of the major weather stations. For example, a city like Greater London with an area 1569 km² consumes over 132 TWh of energy each year. This equates to a power density of 9.6 W/m², or an effective temperature rise of over 4 °C. Clearly something similar but less extreme could be occurring around the major cities in Denmark, but at the moment, without direct measurement data, that remains as speculation.