39. Namibia - temperature trends

When it comes to temperature data Namibia is not much better than Botswana. In total, there have only ever been 34 weather stations in Namibia (compared to 20 in Botswana). Of these only five are medium stations with more than 480 months of data, although nine have more than 450 months of data. This includes only two with more than 900 months of data and only four with any data before 1960. There is only one long station with over 1200 months of data (Windhoek), and only Walfisch Bay has any data before 1900. Unfortunately, both of these stations have portions of data that are clearly erroneous. The most likely explanation is that these data segments have either been incorrectly converted from Fahrenheit to Celsius when they were already in Celsius, or were not converted when they should have been.

 

Fig. 39.1: The temperature trend for Windhoek since 1911 according to Berkeley Earth (BE).

For the case of the Windhoek data, it is the data for the period 1911-1920 that is in question, as illustrated in Fig. 39.1 above. There is clearly an offset of more than 25 °C between the data before 1920 and the data after that date. What appears to have happened here is that some data that was correctly already in Celsius was assumed incorrectly to be in Fahrenheit. So when an unwanted correction of (x - 32)÷1.8 was applied to the data, the data was offset in a negative direction. Reversing this correction appears to remove the offset, as illustrated in Fig. 39.2 below.

Fig. 39.2: The temperature trend for Windhoek since 1911. The best fit is applied to the interval 1944-2001 and has a gradient of +2.21 ± 0.26 °C per century. The monthly temperature changes are defined relative to the 1971-1990 monthly averages.

The resulting temperature trend for Windhoek is strongly positive. However, the opposite is true for the only other significant temperature record that pre-dates 1920. This is the temperature record from Walfisch Bay, which is located at sea level on the coast about 200 km to the west of Windhoek (which is at altitude).

Fig. 39.3: The temperature trend for Walfisch Bay since 1885 according to Berkeley Earth (BE).

Like the Windhoek temperature record, the one for Walfisch Bay contains a significant amount of erroneous data (see Fig. 39.3 above). In this case, most of the questionable data have values that are forty degrees too large. This is almost certainly because these data values are recorded in Fahrenheit not Celsius. If we apply the appropriate correction, then the resulting data exhibits a strong negative trend as shown in Fig. 39.4 below. There are, however, ten data readings in Fig. 39.3 (from October 1941 to July 1942) where the offset is only about twenty degrees Celsius. The reason for this error is harder to ascertain and so these data points have been excluded from Fig. 39.4.

Fig. 39.4: The temperature trend for Walfisch Bay since 1885. The best fit is applied to all the data and has a negative gradient of -2.23 ± 0.16 °C per century. The monthly temperature changes are defined relative to the 1971-1990 monthly averages.

These are not the only station records with a significant amount of data before 1970, though. The graph below (Fig. 39.5) indicates that there are at least three other stations with such data. One is at J. G. H. Van Der Wath Airport (Berkeley Earth ID: 156958) which is at altitude near Keetmanshoop, while the other two are at Lüderitz (Berkeley Earth ID: 139074 and 156957) on the coast and about 200 km to the west of Keetmanshoop.

Fig. 39.5: The number of sets of station data included each month in the temperature trend for Namibia when the MRT interval is 1971-1990.

If we look at the data for J. G. H. Van Der Wath Airport (Berkeley Earth ID: 156958) we see that it exhibits a weak negative trend before 1980 of -0.43 ± 0.41 °C per century, but then shows a strong positive trend after 1980 of 3.3 ± 0.7 °C per century (see Fig. 39.6 below). Given the proximity of this station to both South Africa and Botswana, it is perhaps not surprising that the temperature trend resembles each of the trends seen in both those countries (see Fig. 37.2 and Fig. 38.1).

Fig. 39.6: The temperature trend for J. G. H. Van Der Wath Airport since 1933. The best fit is applied to the interval 1934-1978 and has a negative gradient of -0.43 ± 0.41 °C per century. The monthly temperature changes are defined relative to the 1971-1990 monthly averages.

The only other temperature data in Namibia from before 1970 comes from two stations at Lüderitz, a small coastal town (population: 12,500) in the south of the country on a similar latitude to Keetmanshoop. The two stations have different time frames that overlap between 1973 and 1986. The earliest data comes from Lüderitz Bay (Berkeley Earth ID: 156957) and extends from 1941 to 1986. The later data is for Lüderitz Diaz Point (Berkeley Earth ID: 139074) and extends from 1973 to 2013.

 

Fig. 39.7: The temperature trend for two stations in Lüderitz since 1941. The anomalies up to and including 1980 are for Lüderitz Bay (Berkeley Earth ID: 156957) while those from 1981 onwards are for Lüderitz Diaz Point (Berkeley Earth ID: 139074). The best fit is applied to the interval 1941-1995 and has a positive gradient of 0.27 ± 0.20 °C per century. The monthly temperature changes are defined relative to the 1971-1990 monthly averages.

 

If we combine the anomalies from the two Lüderitz stations we get the temperature trend shown above in Fig. 39.7. This has a very weak upward trend before 1990 which is followed by a sudden jump in temperature just before the year 2000. This temperature jump is similar in size to those seen after 1980 in data from Botswana (see Fig. 38.3), but it occurs about ten years later.  On the one hand this suggests that the temperature jump is a real phenomenon as it is seen in multiple station records, not just in Namibia, but also in Botswana, and to a lesser extent in South Africa. However, the variation in its timing across the different countries is a concern and means that we cannot completely trust its authenticity. What we cannot do is just ignore it.

Fig. 39.8: The temperature trend for Namibia since 1885. The best fit is applied to the interval 1944-2001 and has a positive gradient of +2.28 ± 0.17 °C per century. The monthly temperature changes are defined relative to the 1971-1990 monthly averages.

In addition to the five stations mentioned so far, there are another four stations with more than 450 months of data, as indicated in Fig. 39.5 above. Combining and averaging the anomalies from these nine stations yields the overall temperature trend shown in Fig. 39.8 above. This trend shares many features with those seen for Botswana (see Fig. 38.3) and South Africa (see Fig. 37.2). However, it also hints at the possibility of higher temperatures in the 19th century that would contradict the accepted conventional view of global warming in the 20th century. What is clear, though, is that once again there are significant differences between the actual raw data presented here and the temperature trend constructed by Berkeley Earth (see Fig. 39.9 below). The two most obvious differences are the temperature rises after 1980 and before 1920, both of which have been adjusted down by Berkeley Earth.

Fig. 39.9: The temperature trend for Namibia since 1860 according to Berkeley Earth.

Conclusions

The lack of high quality data makes definitive conclusions for the temperature trend in Namibia difficult. However, by comparing the Namibia data with that from neighbouring countries we can detect commonalities that allow some conclusions to be drawn.

1. For the majority of the 20th century little or no warming has occurred in Namibia, just as the same can be said for Botswana and South Africa.
2. There appears to have been a significant warming period after 1990. However, it is unclear what the cause of this is, and how long term it might be. It appears to be too abrupt and too large to be solely due to carbon dioxide.
   
3. There is weak evidence that 19th century temperatures in Namibia may have been much higher than those in the 20th century, just as we have seen previously in South America, Australia, New Zealand and the South Pacific. While the data before 1900 in each of these regions is scarce, the fact that there appears to be a consistent pattern across these regions for the temperature data that does exist would imply that the data is probably sound.
   

38. Botswana - temperature trends STABLE to 1980

Botswana illustrates some of the challenges in analysing temperature data in Africa. Simply, there just isn't enough data. In fact there is more temperature data for California than there is for the whole of Africa.

In total, there have only ever been twenty weather stations in Botswana. Of these only six are medium stations with more than 480 months of data. This includes only two with more than 900 months of data and only three with any data before 1960. There are no long stations with over 1200 months of data and there is no data before 1900. Moreover, as the map in Fig. 37.1 illustrates, those medium stations that do exist are not evenly distributed, but are instead concentrated along the South African border.

 

Fig. 38.1: The temperature trend for Botswana since 1917 based on an average of twelve stations records overall and only two before 1960. The best fit is applied to the interval 1917-1976 and has a negative gradient of -0.60 ± 0.29 °C per century. The monthly temperature changes are defined relative to the 1991-2010 monthly averages.

The lack of data also means that the overall temperature trend is very sensitive to the individual contributions from one or two atypical station records. This is highlighted in the difference between the trends shown in Fig. 38.1 above and Fig 38.3 below. 

The trend in Fig. 38.1 was constructed by the usual method of averaging the temperature anomalies from the various stations for each month from the earliest temperature observation (which for Botswana is January 1917) until the latest (October 2013). As I have explained before, the monthly anomaly is the change in the monthly temperature from a pre-defined reference temperature for that month and they are used so that temperature changes over time for different stations and different regions may be more easily compared. The mathematics of their calculation is explained here. However, there are a number of problems that arise when trying to calculate these monthly reference temperatures (MRTs).

The first thing to note is that the MRTs are different for each station record, and are also different for each of the twelve calendar months within each record in order to eliminate, or at least minimize, seasonal variations. The MRTs are usually determined by averaging a set of temperature readings from the same calendar month within that particular temperature record (although some climate science groups appear to corrupt this process by using a process of homogenization to combine data from adjacent stations). Ideally this averaging is done by choosing a time interval that is both reasonably long, and also one over which there is very little overall change in temperature. For these reasons a thirty year time interval of 1951 to 1980 would probably be best. It is long enough for the MRT values to be close to the true mean, and it appears that many temperature records around the world exhibit much less variation in temperature over this time period in comparison to both earlier and later time intervals. It is also the time interval that most of the climate science groups initially chose when highlighting climate change in the 1980s and 1990s.

Unfortunately, in many countries in the Southern Hemisphere there is much less temperature data before 1960 compared to that which was recorded post-1980. For that reason it is often better to choose a later time interval such as 1961-1990, or a shorter one of perhaps only twenty years, say 1981-2000.

The next problem, though, is that the temperature records in a particular region or country will not all be of the same length. More importantly, they usually have different amounts of data within the the MRT interval. The question here is, how many months of data do you need to average in order for the MRT to be sufficiently accurate? The higher the proportion needed, the more station records that will be excluded. Ideally we would want all stations to have 100% data coverage within the MRT time interval for all twelve months of the year. But equally, we would, ideally, also want all the station records to be included in the overall trend. In practice very few stations would meet the criterion of 100% data coverage so a lower threshold needs to be set. I generally choose between 40% and 60% with a higher threshold for a shorter MRT interval.

Ultimately the only way to determine the optimum method of determining the MRTs is to test different approaches. In the case of countries with a large amount of data, the different choices for the MRT time interval and the data coverage threshold have little overall impact. However, for countries like Botswana with small numbers of stations, these choices matter because the exclusion of one or two sets of station data can have a major impact on the final temperature trend. This is illustrated in the difference between the trend in Fig. 38.1 above and the one in Fig. 38.3 below. 

The temperature trend in Fig. 38.1 was constructed by first calculating the monthly reference temperatures (MRTs) for each station for the period 1991-2010. For this analysis only the fourteen stations with more than 180 months of data in total were included in the process (for a list see here). In addition, in order to optimize the accuracy in determining the MRT for each month for each station, only stations with data in more than 60% of months (i.e. 12 months) in the MRT period of 1991-2010 were included in the calculation. This resulted in twelve station records being included and two being excluded. The resulting number of station records incorporated in the trend for each month is shown below in Fig. 38.2.

Fig. 38.2: The number of sets of station data included each month in the temperature trend for Botswana when the MRT interval is 1991-2010.

Unfortunately, one of the stations that was excluded was Gaborone (Berkeley Earth ID: 152785), which is one of only three stations with any data before 1959. The other station excluded was Mahalapye (Berkeley Earth ID: 5699) which only has data from 1961 to 1990. The effect of including both these stations can be seen in Fig. 38.3 below. The effect is to change the temperature trend before 1976 from a negative trend of -0.60 °C per century to a positive one with a trend of +0.71 °C per century. This was achieved simply by changing the MRT interval to 1961-1990. While this resulted in the inclusion of the two stations at Gaborone and Mahalapye, it also meant that six stations with virtually no data before 1990 were excluded. This in turn has had a slight impact on the trend from 1990 onward, and in particular the magnitude of the cooling from 2002 onward.

Fig. 38.3: The temperature trend for Botswana since 1917 based on an average of three station records before 1960 but only eight in total. The best fit is applied to the interval 1917-1976 and has a positive gradient of +0.72 ± 0.26 °C per century. The monthly temperature changes are defined relative to the 1961-1990 monthly averages.

Conclusions

What the Botswana temperature data illustrates is the difficulty of deriving conclusive conclusions about climate change when there is insufficient data. The temperature trend before 1976 could be strongly positive (as shown in Fig. 38.3) or strongly negative (as shown in Fig. 38.1), depending on how representative the Gaborone data is of the country as a whole. Given previous evidence from Australia, Indonesia and South America regarding the disparity in temperature trends between large cities and the rest of the country, I would suggest that the Gaborone data is more likely to be an outlier even though Gaborone is hardly a megacity (its population is about 230,000). In which case it is more likely that the temperature trend in Botswana before 1976 would be very similar to that for South Africa (i.e. stable and flat) rather than the more or less continuous warming trend that has been claimed by groups such as Berkeley Earth (see Fig. 38.4 below).

Fig. 38.4: The temperature trend for Botswana since 1860 according to Berkeley Earth.

The other feature of note in both Fig. 38.1 and Fig. 38.3 is the large temperature rise from 1980 until 2002, followed by a smaller but significant decline. This temperature rise coincides with a much smaller one seen in the South Africa temperature data (see Fig. 37.2), but the warming in Botswana is about four times larger. It may be tempting to discount this warming as spurious or just bad data (as many climate scientists do when the data is not to their liking), but it features in too many different station temperature records to be ignored that easily. Instead it hints at the possibility of a more worrying phenomenon for climate scientists: namely that natural fluctuations in the regional temperature could be much larger and more persistent than they currently accept is possible.