Some may argue that part of the reason for this difference lies in the number of stations used (only ten), or the lack of data from the much larger group of seventeen medium length stations (with 401-1200 months of data each) that could have been utilized. To see if data from these stations does make a significant difference I have repeated the analysis process from the previous post, but with the seventeen medium length stations included alongside the original ten long stations.
The first problem we have, though, is that most of these medium stations have data that only stretches back in time to about 1960 and most of their data is post 1970. That means we cannot use the 1961-1990 period to determine the monthly reference temperatures (MRTs) that are needed to remove the seasonal variations (for an explanation of the MRT see Post 4). So instead I have chosen to use the period 1981-2000, which while not as long, is a period for which all 27 stations have at least 80% data coverage. After calculating the anomalies for each station, as before, the trend was determined by using the averaging method represented by Eq. 5.11 in Post 5. This gives the trend profile shown in Fig. 8.1 below.
This trend is virtually identical to the one presented in the last post (see Fig. 7.6), which suggests that the additional data makes little difference to the slope, although there is a slight reduction in the noise level post-1970. The best fit line indicates a warming trend of only 0.27 ± 0.04 °C per century, again almost identical to that from the long stations alone (0.29 ± 0.04 °C per century). This also suggests that the choice of time period for the MRT has little effect as well. Yet if we look at the Berkeley Earth adjusted data we get a different picture.
If we use Berkeley Earth adjusted data for both long and medium stations to determine the local warming trend for New Zealand we get the data in Fig. 8.2 above. The best fit line shows a significant +0.60 ± 0.04 °C per century upward slope.
This is even more evident if we look at the 1-year and 5-year moving averages (see Fig. 8.3 above). But if we look at the real data in Fig. 8.1 and plot the 1-year and 5-year moving averages (see Fig. 8.4 below) we again get a different trend entirely from that in Fig. 8.3.
The question is, why are the data in Fig. 8.3 and Fig. 8.5 so different? The answer is breakpoint alignment.
If we subtract the data in Fig. 8.4 from that in Fig. 8.3 we get the curves in Fig. 8.5 above. This data is the result of corrections that have been imparted into the data by Berkeley Earth, via a technique called breakpoint alignment or breakpoint adjustment, supposedly to correct for systematic data errors, such as those described above: station moves, changes in instruments and changes to the time of day of measurement. These adjustment are in effect attempting to identify systematic errors between temperature records or within temperature records, and compensate for them.
Yet these changes by Berkeley Earth are clearly not neutral. They do not merely iron out undulations in order to reveal the trend more clearly, they actually add to the trend. In this case these adjustments add 0.33 °C per century to the overall trend. That is more than the original trend in Fig. 8.1, and is why the gradient of the Berkeley Earth best fit line in Fig. 8.3 and Fig. 8.4 is more than double that for the original data in Fig. 8.1 and Fig. 8.4. This is why there is so much scepticism about global warming. Many people outside the climate science community do not trust the data or the analysis. And this is not just a problem with Berkeley Earth. All the major groups do it; it is just that Berkeley Earth are more transparent about it.
What the analysis here has shown is that having more data for recent epochs does not really improve the quality of data in the overall trend, or the confidence level of the conclusions that can be derived from that data. It is more important to have ten long temperature records than twenty (or even a hundred) short ones. Yet herein lies a paradox. The longer the temperature record, the less its quality is trusted by the climate scientists, and the more they seek to fragment if into shorter records via the use of breakpoints. We will see this more clearly later when I look in more detail at the Horlicks that is breakpoint alignment.
Addendum
Close inspection of Fig. 8.1 suggests that the spread of the data is greater before 1940 than it is thereafter. This is a consequence of the increased number of datasets that are used to calculate the trend in the latter half of the 20th century compared to the first half and the 19th century. The number of datasets involved in constructing the average temperature trend shown in Fig. 8.1 is indicated below in Fig. 8.6.
Fig. 8.6: The number of sets of station data included each month in the temperature trend for New Zealand.
In summary, there were between 5 and 11 datasets used to calculate the trend between 1870 and 1940, and up to 25 thereafter. Given that the standard deviation of the anomalies in most individual temperature records is approximately 1.0 °C, this implies that the standard deviation of the monthly data in the temperature trend should be about 60% greater before 1940 compared to 1980 and later. It also means the uncertainty in the mean trend will increase slightly as you go back in time, from about ±0.2 °C after 1980, to about ±0.35 °C before 1940. Nevertheless, in my view, this indicates that the temperature trend from 1860-1940 is almost as reliable as that for much later years (1960-2010) despite the reduced amount of data. For while the uncertainty before 1940 may be almost double its post 1960 value, it is still significantly less than the natural variation seen in the 5-year moving average temperature.
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