After Brazil, Argentina probably has the best temperature data in the whole of South America. And if judged on station density as well as length, it may even be better.
The longest dataset is for Buenos Aires Observatorio which is the third longest temperature record in South America behind Rio de Janeiro and Santiago. It has over 1800 months of data dating back to 1856. In addition there are another six long stations with over 1200 months of data, and another 76 with over 480 months of data.
Fig. 61.1: The temperature trend for Argentina since 1850. The best fit is applied to the interval 1856-2005 and has a positive gradient of +0.63 ± 0.07 °C per century. The monthly temperature changes are defined relative to the 1961-1990 monthly averages.
The temperature trend in Fig. 61.1 above was derived by averaging the
temperature anomalies from all the stations with more than 300
months of data which also had at least twelve years of data within the interval of 1961-1990. This amounted to 94 stations in total (for a list see here). The interval of 1961-1990 was used to determine the monthly reference temperatures (MRTs) against which the temperature anomalies are determined, as explained in Post 47.
The
trend in Fig. 61.1 is clearly strongly positive as indicated by the red best fit line. However, the temperature rise is not uniform. In fact there is evidence of a sharp jump of about 0.4°C around 1967 that is both preceded and succeeded by about thirty years of temperature stability. Moreover, the trend from 1930 onwards is the result of averaging over 50 different sets of temperature data, as shown in Fig. 61.2 below. This suggests the trend after 1930 is highly reliable, as
I explained in Post 57
previously, while that before 1900 will probably be much less so.
Before 1900 the data is very volatile, probably due to the combination of natural temperature variability and a shortage of stations that could reduce this variability through the averaging process. After 1900 the temperature rises, but not in a way that is correlated with carbon dioxide levels in the atmosphere. Nor is the temperature rise remotely close to the 1.0 °C claimed by climate scientists for the average in the Southern Hemisphere. The total temperature rise appears to be between 0.4°C and 0.7°C.
Fig. 61.2: The number of station records included each month in the mean temperature trend for Argentina when the MRT interval is 1961-1990.
The geographical distribution of the long and medium stations in Argentina is
illustrated in Fig. 61.3 below. These are classed as either warming
stations (in red) or stable/cooling stations in blue. The criteria for
determining if a station is warming are two-fold. First, the
temperature trend must exceed twice the error in the trend in order to
be statistically significant. Second, the overall temperature rise must
exceed 0.25 °C in order for it to exceed the threshold below which it could be
considered as merely a random fluctuation in the data. As I have pointed
out previously, this threshold of 0.25°C may be on the low side as natural
fluctuations in the long-term temperature trend may be much greater than this as the 5-year moving average in Fig. 61.1 appears to indicate.
Fig. 61.3: The locations of long stations (large squares) and medium stations (small diamonds) in Argentina. Those stations with a high warming trend are marked in red. Those with cooling or stable trends are marked in blue.
Clearly Fig. 61.3 shows that the majority of stations in Argentina have
warmed over their history, although a significant proportion (almost 40%) have not. It is also clear from Fig. 61.3 that
there is a good spread of stations around Argentina, but with a much higher concentration of stations in the north of the country than in the south. However, this does not appear to affect the simple averaging
approach employed here to determine the regional temperature trend in Fig. 61.1 as the following graphs will show.
Fig. 61.4: Temperature trend in Argentina since 1850 derived by aggregating and averaging the Berkeley Earth adjusted data for all medium stations. The best fit linear trend line (in red) is for the period 1891-2010 and has a gradient of +0.86 ± 0.03 °C/century.
The accuracy of the simple averaging process used in Fig. 61.1 can be tested by comparing two different trends that were each calculated using the same data but with different averaging techniques. The regional
trend for Argentina in Fig. 61.4 above was calculated using
Berkeley Earth adjusted data and the simple averaging method. The trend shown in Fig. 61.5 below and published by Berkeley Earth was calculated using
the same Berkeley Earth adjusted data, but with different weightings for each station based on station density and correlation with its neighbours. The data in the two graphs appear virtually identical, despite the fact that slightly few stations were used to generate the trends in Fig. 61.4.
This comparison of the trends in Fig. 61.4 and Fig. 61.5 clearly shows that a simple average of the
adjusted data from the Berkeley Earth data files (Fig. 61.4) gives the same result
for the regional trend in Argentina as the Berkeley Earth version does (Fig. 61.5), even though
Berkeley Earth
appears to use weighted averages for its regional averaging. This in
turn also suggests that weighted averaging is probably not necessary in Argentina.
Fig. 61.5: The temperature trend for Argentina since 1850 according to Berkeley Earth.
What
is also apparent is that there are some distinct differences between the
temperature
trend produced by Berkeley Earth in Fig. 61.5 and that which can be
derived from the original data in Fig. 61.1.
The total difference is illustrated in Fig. 61.6 below and amounts to an
additional 0.26°C of warming over the last century. This is the result of adjustments made to the original data by Berkeley Earth. This explains the difference in trend gradient in Fig. 61.4 compared to that in Fig. 61.1. However, as I demonstrated in Post 57 previously, most of these temperature adjustments are
unnecessary.
Fig. 61.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 61.4 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 1911-2010 has a positive gradient of +0.26 ± 0.04 °C per century. The orange curve shows the contribution just from breakpoint adjustments.
Conclusion
The results here indicate that
global warming in Argentina has probably been modest (less than 0.5°C in the last 100 years) and may
have occurred mainly in the 1960s.
