Tuesday, February 16, 2021

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).


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