57. The case against temperature data adjustments (EU)

Fig. 57.1: The number of weather stations with temperature data in the Northern Hemisphere since 1700 according to Berkeley Earth.

 

There are four major problems with global temperature data.

1) It is not spread evenly

Only about 10% of all available data covers the Southern Hemisphere (compare Fig. 57.2 below with Fig. 57.1 above), while in the Northern Hemisphere over half the data is from the USA alone (as shown in Fig. 57.3). In addition, there is no reliable temperature data covering the oceans from before 1998 when the Argo programme for a global array of 3000 autonomous profiling floats was proposed. The Argo programme has since been used to measure ocean temperatures and salinity on a continuous basis down to depths of 1000m across most of the oceans between the polar regions, but that means we only have reliable data for the last 20 years. 

The result is that only land-based data is available before 1998, and this tends to cluster around urban areas. The solution to this clustering employed by climate scientists is to resort to techniques such as gridding, weighting and homogenization. 

Gridding involves creating a virtual grid of points across the Earth's surface, usually 1° of longitude or latitude apart. This is limited by two factors: computing power and data coverage. As there are unlikely to be any weather stations at these grid points, unless by coincidence, virtual station records are created at these points by averaging the temperatures from the nearest real stations. This averaging of stations is not equal. Instead the average usually weights the different stations according to their closeness in distance (although even stations 1000 km away can be included) and their correlation to the mean of all those datasets. This process of weighting based on correlation is often called homogenization. 

 

Fig. 57.2: The number of weather stations with temperature data in the Southern Hemisphere since 1750 according to Berkeley Earth.

 

2) It does not go back far enough in time

As I have shown previously, the earliest temperature records are from Germany (see Post 49) and the Netherlands (see Post 41) and go back to the early 18th century. However, there is no Southern Hemisphere temperature data before 1830, and only two datasets in the USA from before 1810. The principal reason is that the amount of available data is positively correlated with economic development. As more countries have industrialized, the number of weather stations has increased. Unfortunately, climate change involves measuring the change in temperature since a previous epoch or reference period (over say 100 or 200 years), and in those times the availability of data is much, much, worse. So increasing the quality of current data cannot increase the quality of the measured temperature change. This will always be constrained by how much data we had in the distant past.

Fig. 57.3: The number of weather stations with temperature data in the United States since 1700 according to Berkeley Earth.

3) The data is often subject to measurement errors

Over time weather stations are often moved, instruments are ungraded, and the local environment changes as well. The conventional wisdom is that all these changes have profound impacts on the temperature records that need to be compensated for. This is the rationale behind data adjustments. The problem is, none of it is really justified, as I will demonstrate in this post.

If there are problems with the temperature data at different times and locations, these issues should be randomly distributed. That means any adjustments to correct these errors should be randomly distributed as well. This in turn means that averaging a sufficiently large number of stations for a regional or global trend should result in the cancellation of both the errors and the adjustments. As I have shown in many previous posts here, this does not happen. In fact in many cases the adjustments can add (or subtract) as much, or even more, warming (or cooling) to the mean trend than is present in the original data, particularly in the Southern Hemisphere. For examples see my posts for Texas, Indonesia, PNG, the South Pacific (East and West), NSW, Victoria, South Australia, Northern Territory and New Zealand among others.

One contentious issue is the problem of station moves or changes to the local environment. The conventional wisdom is that these will both strongly affect the temperature record. Frankly, I disagree. In my view those who say they will are failing to understand what is being measured. One example is, what would happen if the weather station was to be moved from open ground to an area under a large tree? Does the increased shade reduce the temperature? The answer is no because the thermometer is already in the shade inside its Stevenson screen. Moreover, the thermometer is measuring air temperature, not the temperature on the ground, and the air is continuously circulating. So the air under the tree is at virtually the same temperature as the air above open ground. The one adjustment that does affect temperature is altitude. Air (almost) always gets colder as you ascend in height.

4) There just isn't enough data

There are currently about 40,000 weather stations across the globe. This sounds like a lot, but it is only about one for every 13,000 square kilometres of area. That means that on average, these stations are over 110 km apart, or more than 1° of longitude or latitude. Even today, that is probably the bare minimum of what is required to measure a global temperature. Unfortunately, in previous times, the availability of data was much, much, worse.

Of course, now there are alternatives. One is to use satellites, but again this only provides data back to about 1980. The other problem with satellites is that their orbits generally no not cover the polar regions. And finally, they can only see what is emitted at the top of the atmosphere (TOA). So they can measure temperatures at the TOA, but measuring surface temperatures can be problematic as the infra-red radiation emitted by the surface is largely absorbed by carbon dioxide and water vapour in the lower atmosphere.

Over the course of the last eleven months I have posted 56 articles to this blog. Over half of these have analysed the surface temperature trends in various countries, states and regions. In virtually every case, the trend I have determined by averaging station anomalies has differed from the conventional widely publicized versions. These differences are largely due to homogenization and data adjustments. 

Homogenization

There are two potential issues with homogenization. Firstly, there are more urban stations than rural ones. This is because stations tend to be located near to where people live. Secondly, urban stations tend to be closer together. So they are more likely to be strongly correlated. As homogenization uses correlation for weighting the influence of each station's data in the mean temperature for the local region, this means that the influence of urban stations will be stronger. 

So both potential issues are likely to favour urban stations over rural ones. Yet it is the urban ones that are more likely to be biased due to the urban heat island (UHI) effect. The result is that that bias is often transmitted to the less contaminated rural stations, thereby biasing the whole regional trend upwards. This is why I do not use homogenization in my analysis. The other problematic intervention is data adjustment.

Data adjustments

The rationale for data adjustments is that they are needed to compensate for measurement errors that may occur from changes of station site, instrument or method. The justification for using them is that climate scientists believe they can identify weak points in the data. Some might call that hubris. The alternative viewpoint is that these adjustments are unnecessary and that averaging a sufficiently large sample will erase the errors automatically via regression to the mean. I will now demonstrate that with real data.

Fig. 57.4: The 5-year average temperature trends for Austria, Hungary and Czechoslovakia together with best fit lines for the interval 1791-1980 (m is the gradient in °C per century). The Austria and Czechoslovakia data are offset by +2°C and -2°C respectively to aid clarity.

In three recent posts I calculated and examined the temperature trends for Czechoslovakia (Post 53), Hungary (Post 54) and Austria (Post 55). The five-year moving averages of the temperature trends in these three countries are shown in Fig. 57.1 above. What is immediately apparent is the high degree of similarity that these trends display, particularly after 1940. This is indicated by the red and black arrows which mark the positions of coincident peaks and troughs respectively in the three datasets.

It turns out that all three datasets are also very similar to that of Germany (see Post 49). This is shown in Fig. 57.5 below. This is not surprising as the four countries are all close neighbours. What is surprising is that there are not greater differences between the four datasets, particularly given the number of adjustments that Berkeley Earth felt needed to be made to the individual station records for these countries when undertaking their analysis.

Fig. 57.5: The 5-year average temperature trends for Austria, Hungary and Czechoslovakia compared to that of Germany.

To understand the potential impact of these adjustments, consider this. The temperature trend for Austria in Fig. 55.1 of Post 55 was determined by averaging up to 26 individual temperature records. Yet the total number of adjustments made to those records by Berkeley Earth in the time interval 1940-2013 was more than 90. That is more than three adjustments per temperature record, or at least one for every 21 years of data. Yet if the adjustments are ignored, and the data for each country is just averaged normally, the results for each country, Austria, Czechoslovakia, Germany and Hungary, are virtually identical. This leads to the following conclusions and implications.

Conclusions

1) The data in Fig. 57.5 indicates that the temperature trends for Austria, Czechoslovakia, Germany and Hungary are virtually identical after 1940. The probability that this is due to random chance is minimal. It therefore implies that the temperature trends for these countries from 1940 onwards are indeed virtually identical. This is not a total surprise as they are all close neighbours.

2) As all the individual temperature anomaly time series used to generate these trends are not identical, and all are likely to have data irregularities from time to time, this also means that those data irregularities are highly likely to be random in both their size and distribution across the various time series. This means that when averaged to create the regional trend, their irregularities will partially cancel. If the number of sites is large enough, the cancellation will be almost total. This is what is seen in Fig. 57.5, and it is why all the trends shown are virtually identical post-1940.

Implications

1) If the temperature trends for Austria, Czechoslovakia, Germany and Hungary are virtually identical after 1940, as conclusion #1 suggests, then it is reasonable to suppose that they should be virtually identical before 1940 as well. But they aren't, as the data in Fig. 57.5 illustrates. This is because the trends in each case are based on the average of too few individual anomaly time-series for the irregularities from each station time-series to be fully cancelled by the irregularities from the remainder. Before 1940 there are only sixteen valid temperature records in Austria, three in Hungary and three in Czechoslovakia. Germany, on the other hand has about thirty.

2) However, if it is true that all the temperature trends for Austria, Czechoslovakia, Germany and Hungary before 1940 should be the same, then there is no reason why we cannot combine them all into a single trend. This would dramatically increase the number of individual time-series being averaged, and so reduce the discrepancy between the calculated value for the trend and the true value. This has been done in Fig. 57.6 below.

Fig. 57.6: The temperature trend for Central Europe since 1700. The best fit is applied to the interval 1791-1980 and has a negative gradient of -0.05 ± 0.07 °C per century. The monthly temperature changes are defined relative to the 1981-2010 monthly averages.

 

The data in Fig. 57.6 represents the temperature trend for the combined region of Austria, Czechoslovakia, Germany and Hungary. The trend after 1940 is the same as that seen in those individual countries and the gradient of the best fit line for 1791-1980 more closely resembles the equivalent lines for Germany and Hungary than it does those of Austria and Czechoslovakia. But now we also have a more accurate trend before 1940. The question is, how much more accurate?

 

Fig. 57.7: The number of station time-series included in the average each month for the temperature trend in Fig. 57.6

 

The data from Austria, Czechoslovakia, Germany and Hungary suggest that approximately 20 different time-series are required in the average for the irregularities in the different station time-series to almost fully cancel. The graph in Fig. 57.7 suggests that this threshold is surpassed for almost every month of every year after 1830.

 

Fig. 57.8: The temperature trend for Central Europe since 1700. The best fit is applied to the interval 1831-2010 and has a positive gradient of 0.62 ± 0.07 °C per century. The monthly temperature changes are defined relative to the 1981-2010 monthly averages.

 

If we now calculate the best fit to the data in Fig. 57.8, but only use data after 1830, we get a gradient for the trend line of 0.62 °C per century. This equates to a temperature rise since 1830 of over 1.1 °C.

 

 

Fig. 57.9: The temperature trend for Central Europe since 1700. The best fit is applied to the interval 1781-2010 and has a positive gradient of 0.21 ± 0.05 °C per century. The monthly temperature changes are defined relative to the 1981-2010 monthly averages.

 

However, you could argue that the regional monthly average data in Fig. 57.6 is still reasonably accurate all the way back to 1780 as it continues to have over a dozen temperature records incorporated into the average every month of every year after this time. In which case the temperature rise since 1780, as indicated by the best fit line in Fig. 57.9, is actually less than 0.5 °C. This suggests that we can be reasonably confident that temperatures in central Europe between 1750 and 1830 were fairly similar to those of today.

Summary

What I have demonstrated here is that adjustments to the raw temperature data are unnecessary and can be avoided simply by averaging sufficient datasets (i.e. more than about 20).

I have also shown that it is highly likely that the mean temperature in central Europe is not much higher now than it was at the start of the Industrial Revolution (1750-1830). 

Disclaimer: No data were harmed or mistreated during the writing of this post. This blog believes that all data deserve to be respected and to have their values protected.

56. Switzerland - temperature trends STRONG WARMING 2°C

The temperature trend for Switzerland is qualitatively very different from that of most of its neighbours. The warming is continuous from 1750 onwards (see Fig. 56.1 below) with a trend of +0.46 °C per century up until 1985. This equates to about 1 °C of warming before 1985. The main similarity it shares with the trend from other central European counties (Germany, Austria, Hungary, Czechoslovakia) is the abrupt jump in temperatures around 1988. This adds an additional 0.9 °C of warming compared to temperatures between 1961 and 1980. So in total there is over 2 °C of warming from 1750 until 2010.

Fig. 56.1: The temperature trend for Switzerland since 1750. The best fit is applied to the interval 1756-1985 and has a positive gradient of +0.46 ± 0.05 °C per century. The monthly temperature changes are defined relative to the 1981-2010 monthly averages.

The trend in Fig. 56.1 was determined by averaging the anomaly time series from the 38 longest temperature records in Switzerland and Leichtenstein (for a list see here), although there is only one significant station in Leichtenstein: Vaduz. Each monthly anomaly was calculated relative to the 1981-2010 average temperature for that month of the year. For a more detailed explanation of monthly reference temperatures (MRTs) and how anomalies are calculated, go to Post 47. 

Of these 38 records, six are long stations with over 1200 months of data and twelve are medium stations with over 480 months of data. Unusually, Switzerland also has a significant number of stations with between 360 and 480 months of data: twenty in total. As this is more than the number of long and medium stations combined, and as the length of these records is still significant, they too were included in the trend calculation in Fig. 56.1.

Fig. 56.2: The number of station records included each month in the mean temperature trend for Switzerland when the MRT interval is 1981-2010.

The number of stations used to determine the mean temperature each month in Fig. 56.1 is shown in Fig. 56.2 above. In addition, the locations of the long and medium stations are indicated in Fig. 56.3 below. It can be seen that almost all the station temperature time series have a warming trend, and the long stations are mainly located near to the major cities.

Fig. 56.3: The locations of long stations (large squares) and medium stations (small diamonds) in Switzerland. Those stations with a high warming trend are marked in red. Those with cooling or stable trends are marked in blue.

If we now look at the Berkeley Earth version of the temperature trend we see a rather different picture. The trend is virtually flat before 1985, with a sudden jump of over 1 °C occurring in 1987 (see Fig. 56.4 below). This means that Berkeley Earth are only claiming about 1 °C of warming in Switzerland since pre-industrial times, whereas the raw data in Fig. 56.1 suggest the true value is double that. One caveat to this, however, is that the temperature time series in Fig. 56.4 does show a dip in temperatures of almost 0.5 °C is the 19th century. So if the trend is measured from about 1850, the total warming is probably about 1.5 °C, and thereby in line with IPCC claims for the Northern Hemisphere.

Fig. 56.4: Temperature trend in Switzerland 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 1756-1985 and has a gradient of +0.06 ± 0.02 °C/century.

The temperature trends in Fig. 56.4 above are once again almost identical to the official Berkeley Earth version shown below in Fig. 56.5. So the difference between the trends in Fig. 56.1 and Fig. 56.4 cannot be in the averaging process. It must be due to the adjustments.

Fig. 56.5: The temperature trend for Switzerland since 1750 according to Berkeley Earth.

These adjustments are shown in Fig. 56.6 below. Unusually they have a negative trend, indicating that they actually reduce the overall trend rather than adding to it. In fact the total reduction can be viewed as being between 1 °C and 1.25 °C, depending on the time interval chosen.

Fig. 56.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 56.4 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 1756-1985 has a negative gradient of -0.398 ± 0.005 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Summary

1) The climate in Switzerland appears to have warmed more than neighbouring countries (Germany, Austria, etc) since 1750. The warming of 2 °C is even more than is seen in the IPCC global trend.

2) Part of the warming is due to a sudden jump in temperatures of approximately 0.9 °C that occurred in the mid-1980s (see Fig. 56.1). This is similar to the jumps seen in equivalent trend data for neighbouring countries (Germany, Austria, Hungary, Czechoslovakia).

3) Unlike its neighbours, Switzerland appears to have experienced significant and continuous warming of over 1 °C from 1750 to 1980 (see Fig. 56.1)

4) The temperature trend based on Berkeley Earth adjusted data shows no warming before 1985 (see Fig. 56.4), although there is significant variation in the trend with temperatures in the 18th century higher than those in the 19th century.

55. Austria - temperature trends STABLE to 1980

The temperature trend for Austria from 1780 to 1950 is qualitatively very similar to that of its neighbour Hungary over the same time period. In both cases the temperature declined from around 1800 to about 1880, and then rose again afterwards. Thus temperatures in the middle part of the 20th century were broadly similar to those in 1800. This can be seen most clearly by comparing the 5-year moving average for Austria in Fig. 55.1 below (yellow curve) with the equivalent curve for Hungary in Fig. 54.1 in Post 54. For this period the temperature trend is therefore stable but with considerable natural variation. This also suggests that the trend in Fig. 55.1 is accurate as it is in effect corroborated by the data from its neighbour, Hungary.

 

From 1951 to 1980 the mean temperature in Austria increases slightly. Then around 1988 there is a sudden jump in temperature of about 1 °C similar to that seen in Hungary, Czechoslovakia, the Baltic States, Germany and Denmark. In fact comparing the mean temperature for the period 1991-2010 with that for 1961-1980 indicates a sudden rise of 0.99 °C, while the average for 1991-2010 is 1.37 °C above the overall 1781-1950 trend (see the red best fit line in Fig. 55.1).

Fig. 55.1: The temperature trend for Austria since 1767. The best fit is applied to the interval 1781-1950 and has a positive gradient of +0.05 ± 0.08 °C per century. The monthly temperature changes are defined relative to the 1981-2010 monthly averages

The best fit line in Fig. 55.1 is calculated for the period 1781-1950. The reasons for this choice are statistical accuracy and impartiality. I could have chosen the period 1781-1980. This would have represented a full two centuries of data, but it would give a misleading value for the trend (of 0.20 ± 0.06 °C per century) because it would be calculated over a non-integer number of cycles in the natural variability. This variability peaks around 1780 and 1950. That is why the trend in Fig. 55.1 is calculated between those two dates. 

Fitting to the full length of the data also poses similar drawbacks. In addition, the anomaly data clearly shows a different form of behaviour after 1980 compared to before. It would therefore be inappropriate to analyse both time-frames with a single best fit line. For that reason I have restricted the linear regression analysis to the 1781-1950 interval. For more explanation of the rationale I have employed here I suggest referring to the discussion of Fig. 4.7 in Post 4, the discussion of Fig. 18.3 in Post 18, and the discussion of Fig. 30.3 in Post 30.

Fig. 55.2: The number of station records included each month in the mean temperature trend for Austria when the MRT interval is 1981-2010.

The anomalies used to calculate the trend in Fig. 55.1 were determined relative to the mean temperatures for the interval 1981-2010. This interval corresponds to a maximum in the number of available station records that had over 480 months of data (see Fig. 55.2 above) and therefore should lead to more accurate results for the trend. In all, 27 stations in Austria have over 480 months of data (see here), of which 26 have sufficient data in the MRT interval to qualify for inclusion in the overall trend. The exception is Obir (Berkeley Earth ID: 5111) which although having 1153 months of data has none after 1944. It is therefore excluded. For a detailed explanation of MRTs and their use in determining the temperature anomalies please refer to Post 47.

Of the 26 station records included in the trend in Fig. 55.1 fifteen had over 1200 months of data. The geographical locations of these long stations are shown on the map in Fig. 55.3 below. The remaining medium stations (with over 480 months of data) are also shown as small diamonds.

Fig. 55.3: The locations of long stations (large squares) and medium stations (small diamonds) in Austria. Those stations with a high warming trend are marked in red. Those with cooling or stable trends are marked in blue.

The map in Fig. 55.3 illustrates how evenly the long and medium stations in Austria are distributed across the country. This allows their anomalies to be averaged without any need for different weightings for different stations to be employed. This equal weighting approach was used to construct the trend in Fig. 55.1. I have also used it to construct a Berkeley Earth version based on their adjusted data. This is shown in Fig. 55.4 below.

Fig. 55.4: Temperature trend in Austria since 1767 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 1831-1980 and has a gradient of +0.36 ± 0.03 °C/century.

There are two things that are striking about the trend for the Berkeley Earth adjusted data in Fig. 55.4. Firstly, it agrees almost exactly with the trend published by Berkeley Earth and shown in Fig. 55.5 below even though the trend in Fig. 55.4 uses an equal station weighting approach while the trend in Fig, 55.5 does not. This suggests that adjusting the station weightings has a minimal effect on the result, and so validates the approach taken to calculate the trends in both Fig. 55.4, and more importantly Fig. 55.1. But secondly, much of the cooling between 1820 and 1900 is erased. The result is that the temperature trend for 1831-1980 is reduced from +0.73 ± 0.10 °C per century to a more modest +0.36 ± 0.03 °C per century. In other words, the trend looks more like the IPCC hockey stick.

Fig. 55.5: The temperature trend for Austria since 1750 according to Berkeley Earth.

The difference in the trends from 1831-1980 for the data in Fig. 55.1 and Fig. 55.4 is the result of adjustments made to the data by Berkeley Earth. These adjustments are commonplace in the Berkeley Earth data and have been documented in many of my previous posts, but usually they tend to increase the trend compared to that seen for the raw data. In this case, though, these adjustments actually reduce the trend between 1831 and 1980. However, before 1831 the adjustments effectively add warming to the trend by reducing temperatures before 1830. The net effect of these two sets of adjustments is to flatten the curve between 1770 and 1980 and make it appear more like a hockey stick. These adjustments are shown in Fig. 55.6 below.

Fig. 55.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 55.4 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 negative gradient of -0.394 ± 0.004 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Conclusions

1) The temperature trend for Austria is qualitatively very similar to that of its neighbour Hungary. This effectively allows the trends from these two adjacent countries to corroborate each other's results. 

2) The temperature trend for Austria is stable up until 1980. The net upward trend of 0.4 °C is comparable to the natural variation. 

3) After 1980 there is a sudden increase in temperature of about 1 °C that occurs around 1988. The reason for this is unknown.

54. Hungary - temperature trends STABLE to 1980

If you are searching for climate change in Hungary then you are likely to be disappointed. Yes, there is variability: there always is. But there is no clear upward trend before 1980 as Fig. 54.1 below demonstrates. After 1980 the mean temperature jumps by about +0.72 °C relative to the 1961-1980 average and +0.36 °C relative to the long term trend. This means that the overall trend from 1796-2010 is +0.22 ± 0.06 °C per century. This represents only a very modest warming of less than 0.5 °C since pre-industrial times, over half of which could be accounted for by urban heating effects (see Post 14 and Post 29). The rest is within the expected limits of natural variability.

Fig. 54.1: The temperature trend for Hungary since 1780. The best fit is applied to the interval 1796-1985 and has a positive gradient of +0.08 ± 0.08 °C per century. The monthly temperature changes are defined relative to the 1981-2010 monthly averages.

The trend in Fig. 54.1 above is the result of averaging the anomalies from nineteen station records with over 480 months of data. Of these three are long stations with over 1200 months of data while the rest are medium stations. All nineteen stations have significant data after 1975 (see Fig. 54.2 below). For that reason the period 1981-2010 was chosen for calculating the monthly reference temperatures (MRTs). For a description of MRTs and their use in determining the anomalies see Post 47.

Fig. 54.2: The number of station records included each month in the mean temperature trend for Hungary when the MRT interval is 1981-2010.

The frequency distribution in Fig. 54.2 above indicates that the trend data in Fig. 54.1 after 1973 will be more reliable than the trend data before 1973. However, the trend data before 1973 is consistent with similar data from Czechoslovkia (Post 53), Germany (Post 49) and the Baltic States (Post 51). The data is also fairly evenly distributed across the country (see Fig. 54.3 below), and so its mean is likely to be representative of the overall true temperature trend for Hungary.

Fig. 54.3: The locations of long stations (large squares) and medium stations (small diamonds) in Hungary. Those stations with a high warming trend are marked in red.

Despite this, the trend shown in Fig. 54.1 is significantly different from that calculated by Berkeley Earth using adjusted data rather than the actual raw data. Averaging the adjusted data gives the trend in Fig. 54.4 below.

Fig. 54.4: Temperature trend in Hungary since 1780 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 1796-2010 and has a gradient of +0.34 ± 0.02 °C/century.

The trend based on Berkeley Earth adjusted data in Fig. 54.4 above now has a significant warming trend that is at least 50% more than is seen in the original data in Fig. 54.1. It also agrees almost exactly with the published version shown below in Fig. 54.5.

Fig. 54.5: The temperature trend for Hungary since 1750 according to Berkeley Earth.

The difference between the adjusted data and the raw data is illustrated below in Fig. 54.6. Overall it amounts to an additional warming contribution since 1840 of nearly 0.5 °C. This is more than the total warming seen in the raw data in Fig. 54.1 (about +0.47 °C).

Fig. 54.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 54.4 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 +0.285 ± 0.007 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Conclusions

1) The surface temperatures in Hungary were stable up until 1980. Thereafter they experienced a modest increase of between 0.36 °C and +0.72 °C that occurred abruptly around 1988 (see Fig. 54.1).

2) The warming seen in the raw data (in Fig, 54.1) is significantly less than that seen in the Berkeley Earth adjusted data (see Fig. 54.4).

3) The adjustments made to the data by Berkeley Earth (see Fig. 54.6) add more warming than is seen in the raw data (see Fig. 54.1)

4) Current temperatures, while higher than the 1795-1980 average, are actually similar to those seen in the 1790s and 1940s (see 5-year moving average in Fig. 54.1).

53. Czechoslovakia - temperature trends PARABOLIC

Even though the old state of Czechoslovakia is on the opposite side of Poland to the Baltic States (see Post 51), it has very a similar temperature trend since 1771 (see Fig. 53.1 below). There is a negative trend before 1980, and then a sudden jump in temperatures around 1987-1988. However, there is one significant difference. While the discontinuity in 1987-1988 of +0.93 °C is similar to that seen in the Baltic States, the negative slope beforehand is much greater (-0.45 °C per century compared to only -0.08 °C per century). The result of this is that temperatures in the region before 1830 appear to be even greater than they are now. In fact the mean temperature for 1791-1830 was over 0.1 °C higher than the mean for 1991-2010.

Fig. 53.1: The temperature trend for the Czech Republic and Slovakia since 1771. The best fit is applied to the interval 1781-1980 and has a negative gradient of -0.45 ± 0.07 °C per century. The monthly temperature changes are defined relative to the 1981-2010 monthly averages.

Unfortunately, the quality of the data for this region is not as good as that for the Baltic States. That is why I have combined the current states of the Czech Republic and Slovakia into one post. The extent of the data can be seen in Fig. 53.2 below. While there is data that goes as far back as 1771, it only comes from three stations before 1930, and two before 1900; all are in the Czech Republic.

Fig. 53.2: The number of station records included each month in the mean temperature trend for the Czech Republic and Slovakia when the MRT interval is 1981-2010.

Overall there are 3 long stations in the old state of Czechoslovakia with over 1200 months of data, and all are in the Czech Republic. In addition there are another 25 medium stations with over 480 months of data, of which 12 are in Slovakia. The locations of these stations are shown in Fig. 53.3 below. What is clear is that the medium stations are evenly dispersed while the long stations are all in the north-west of the Czech Republic. It is also clear that most of the medium stations show a warming trend. The reason for this is simple. Almost all are modern stations with data that starts in 1973. Their data therefore coincides with the overall warming period in Fig. 53.1 above from 1973 to 2013. On the other hand, two of the three stations with cooling trends only have data from the 19th century where the overall trend is negative.

Fig. 53.3: The locations of long stations (large squares) and medium stations (small diamonds) in the Czech Republic and Slovakia. Those stations with a high warming trend are marked in red.

The question is, given the paucity of data before 1950, how reliable is the trend in Fig. 53.1 above? In my view the bast way to answer that is by comparing it with neighbouring trends such as those for Germany, Poland and the Baltic States. Other than Poland these all have consistent negative trends in the 19th century and early 20th century. That suggests that the trend in Fig. 53.1 is consistent.

Fig. 53.4: Temperature trend in the Czech Republic and Slovakia since 1771 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 1831-1980 and has a gradient of +0.49 ± 0.04 °C/century.

Unfortunately, that is not the view of the climate scientists. If you average the adjusted data created by Berkeley Earth you get the trend shown in Fig. 52.4 above. Now, instead of a negative trend of -0.45 °C per century between 1831 and 1980, we have a positive trend of +0.49 °C per century. This is consistent with the published trend for the Czech Republic shown in Fig. 53.5 below.

Fig. 53.5: The temperature trend for the Czech Republic since 1750 according to Berkeley Earth.

This means that the adjustments made by Berkeley Earth have added up to 1.4 °C of warming since 1830. This van be seen in just as clearly in Fig. 53.6 below where the total adjustments are shown to equate to over 1.3 °C of warming since 1800. The blue curve in Fig. 53.6 is the difference between the real data in Fig. 53.1 and the adjusted data in Fig. 53.4.

Fig. 53.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 53.4 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 1801-1980 has a gradient of +0.707 ± 0.009 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Conclusions

1) Czechoslovakia experienced a prolonged cooling from 1800 to 1980 before seeing a rapid warming after 1987.

2) Temperatures today in the Czech Republic and probably Slovakia are still below those seen in the first quarter of the 19th century. 

3) Once again Berkeley Earth adjustments to the raw data have added significant warming. In this case up to 1.4 °C.

4) Once again there is a large positive temperature discontinuity of almost 1 °C around 1987-1988. Origin unknown!