TEMPERATURE TRENDS IN SOUTH AFRICA:

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1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 24: (24) Published online in Wiley InterScience ( DOI: 1.12/joc.196 TEMPERATURE TRENDS IN SOUTH AFRICA: A. C. KRUGER* and S. SHONGWE South African Weather Service, Private Bag X97, Pretoria 1, South Africa Received 7 March 22 Revised 23 July 24 Accepted 26 July 24 ABSTRACT Time series of South African temperatures were investigated for temporal and spatial trends for the period 196 to 23. For this purpose a total of 26 climate stations were utilized, with each having sufficient data available and not having undergone major moves or changes in exposure that would influence the homogeneity of their data series. The vast majority, a total of 23 stations, showed positive trends in their annual mean maximum temperature series, 13 of them significant, with trends higher for central stations than those closer to the coast. Annual mean minimum temperatures showed 21 stations having positive trends, with 18 significant. Stations not showing significantly positive trends in annual mean minimum temperatures were mostly situated in the central interior. The annual average temperature data series of 24 of the stations showed positive trends, with 18 of them significant. Trends of mean seasonal temperature showed that temperature trends are not consistent throughout the year, with the average trend for autumn showing a maximum and spring a minimum. Monthly trends of average annual temperatures showed large differences in trend between stations, and for each station between months, but similar tendencies in trend between months were found to exist for stations close by and also for groups of stations on a regional basis. Trends in diurnal temperature range are almost equally divided between positive and negative, with the positive trends in the central interior mainly being caused by large positive trends in maximum temperature. It is also shown that, in general, days and nights with relatively high temperatures have increased, while days and nights with relatively low temperatures have decreased. The effects of urbanization on temperature trends are investigated, and the conclusion is that most stations regarded as urban stations are still useful for trend analysis; being situated on the outskirts of cities they are, therefore, not substantially influenced by the urban heat island. El Niño and La Niña events do not seem to play a significant role in the increasing temperatures observed. Copyright 24 Royal Meteorological Society. KEY WORDS: South Africa; linear regression; Student s t test; temperature trends; extremes; El Niño; La Niña; warming 1. INTRODUCTION The purpose of this paper is to inform on temperature trends in South Africa for the period 196 to 23, a period for which reliable temperature data are available. The results presented give an indication of the present state of South African temperatures on a regional basis in relation to the past four decades. Other similar notable studies conducted in the southern African region, as well as the Southern Hemisphere, are from Collins et al. (2), King uyu et al. (2), Salinger and Mullan (1999), Hoffmann et al. (1997), Rosenbluoeth et al. (1997), Unganai (1997), Zheng et al. (1997), Torok and Nicholls (1996), Plummer (1996) and Hughes and Balling (1996). The key results of some of the studies above, done for Africa in particular, are as follows. Mühlenbruch-Tegen (1992) evaluated long-term surface temperature variations in South Africa for the period 194 to For this period no real evidence has been found for overall changes in mean monthly temperatures, and only a small number of stations showed a significant increase in mean annual temperature, all of them situated along the coast. However, trends of seasonal mean temperature showed clear and significant changes, which will be mentioned later for comparison with the results of this * Correspondence to: A. C. Kruger, South African Weather Service, Private Bag X97, Pretoria 1, South Africa; andries@weathersa.co.za Copyright 24 Royal Meteorological Society

2 193 A. C. KRUGER AND S. SHONGWE study. Hughes and Balling (1995) examined the maximum and minimum temperature trends for South Africa for the period 196 to 199, but also compared the different results obtained for urban and non-urban stations. Maximum temperatures increased by.11 C per decade and.12 C per decade on average for non-urban and urban stations respectively, but for minimum temperatures a non-significant trend of.7 C per decade on average for non-urban stations and a significant trend of.34 C per decade for urban stations were determined. Their results will be compared with those found in this study, where the effect of urbanization on temperature trends is examined, as it is important to make an assessment of the severity of urban contamination of climate data, especially when assessments of the historical variability and changes of climate are made. King uyu et al. (2) investigated trends in mean surface minimum and maximum air temperatures over eastern Africa, from the Sudan southwards to include Botswana, Zimbabwe and Mozambique, for 71 stations for the period 1939 to Large spatial and temporal variations were found, mostly depending on whether the station is close to a large water feature. The results for the northern part of the study showed less spatial variability and generally indicate night-time warming and daytime cooling. The southern parts showed mixed results, with the Mozambique Channel even showing general cooling. Unganai (1997) investigated surface temperature variations over Zimbabwe, one of South Africa s northern neighbours, for the period 1897 to At national level, maximum temperatures showed a warming trend during all seasons studied, whereas minimum temperatures either showed no trend or slight cooling. The general change in temperature was subsequently not attributed to global warming due to an increase in greenhouse gases, because of the absence of significant increases in night-time temperatures. Notably, two warm phases were identified: the first was from the mid-193s to the late 194s, and the second was from the early 198s to the end of the period of study. All of the above studies, however, do not include the mid and late 199s, which showed in general a continued upward trend in global temperatures. Therefore, it is possible that, by including the 199s and the early part of this century, markedly different results in trends than those for the previous studies of Africa, and in particular South Africa, might be obtained. With global warming a reality (Datsenko and Sonechkin, 1999; Jones et al., 1999; Peterson et al., 1999; Easterling et al., 2), whether caused by natural variability or anthropogenically induced (Tett et al., 1999; Stott et al., 21), it is important to be informed and regularly updated on observed regional temperature trends. These results can aid with verification of climate model studies, which in turn assist with contingency planning for agriculture and water supply, for example, for the future. 2. DATA Quality-controlled daily maximum and minimum temperature data for stations with the minimum period of data available, i.e. 196 to 23, were extracted from the South African Weather Service climate database. To make sure that trend results are accurate for a location, data sets should be as complete as possible. A condition for a climate station to be included in the study, therefore, was to have (for the determination of all trends) at least 9% of data available for the period 196 to 23. If gaps occur in a data set for a specific climate station, it also should not be concentrated only in one part of its time series, e.g. at the beginning or end, but more evenly dispersed. Data series of climate stations were also compared graphically with surrounding stations where possible, to check for visible outliers. Where any doubt existed as to the correctness of temperature values, they were deleted before analysis. The metadata of each station were then scrutinized for possible moves and changes in exposure of instrumentation. After the above-mentioned exercises, a total of 26 climate stations remained that had sufficiently complete data sets, and which were deemed not to have moved substantially to influence the homogeneity of their time series. The positions of these climate stations in South Africa are shown in Figure 1. There is some overlap of stations with those used in previous studies, e.g. Mühlenbruch-Tegen (1992) and Hughes and Balling (1996), but some stations were omitted because of gaps in their time series, or after inspection of their metadata.

3 SOUTH AFRICAN TEMPERATURE TRENDS 1931 Figure 1. Locations of the 26 stations in South Africa used in the study, with names of provinces in italics 3. ANALYSES AND RESULTS Analyses were performed over the period 196 to 23, as temperature data before this period are not sufficiently quality controlled. Linear trends were determined for maximum, minimum and average annual mean temperatures, seasonal mean temperatures, monthly mean temperatures and annual means of the diurnal range of temperatures. Also, similar to the approach followed by Collins et al. (2), trends of the annual frequencies and runs of days and nights with maximum and minimum temperatures respectively in certain temperature categories were determined. The effect of urbanization on temperature trends was investigated for urban stations by comparing trends with non-urban stations close by, where possible. Different subperiods from 196 to 23 were compared to examine whether there was any change in temperature trends throughout the period of investigation. The possible influence of El Niño and La Niña events on temperature trends was also investigated for those stations that we know are in the part of South Africa in which climate is significantly affected by these events. The correlation co-efficients of all trends were tested for significance by a two-sided t-test, and where trends are indicated to be significant in the discussions of results they are at the 5% level. In sections of results where analyses do not only comprise determinations of linear trend, additional analysis methods are discussed in detail Trends in mean annual maximum, minimum and average temperature Trends calculated for the mean annual maximum temperatures of the 26 stations used in the study are shown in Figure 2. A total of 23 out of 26 stations show positive trends, with 13 of them significant. Spatially, stations with significant trends in mean annual maximum temperature are mostly close to the coast, with the exception of Bloemfontein, Polokwane, Upington and Vanwyksvlei. However, trends seem to be higher for these central stations than for those closer to the coast. Of the annual average minimum temperatures in Figure 3, 21 stations showed a positive trend, with 18 of them significant. Four stations had negative trends, but none of these was significant. Stations that did not show positively significant trends were mostly situated in the central interior, but not all stations located here showed the same tendency. These are Pretoria PUR (purification works in the centre of the city of Pretoria) and Pretoria UP (an experimental farm where some development also took place during the period of record) with significantly positive trends. Because of their location, the effects of urbanization are likely

4 1932 A. C. KRUGER AND S. SHONGWE Cape Columbine* Cape Town* Cape Point* Jonkershoek Cape Agulhas* Cape St. Blaize* Cape St. Francis Port Elizabeth* East London* Durban* Cape St. Lucia Langgewens Upington* Vanwyksvlei* Addo* Armoedsvlakte Bloemfontein* Glen College Cedara Emerald Dale Pretoria PUR Pretoria UP Bela Bela Polokwane* Musina Skukuza Climate Station Figure 2. Trend () in annual mean maximum temperature for the period (asterisk indicates significant trend at the 5% level) Cape Columbine* Cape Town* Cape Point* Jonkershoek* Cape Agulhas* Cape St. Blaize Cape St. Francis* Port Elizabeth East London* Durban* Cape St. Lucia* Langgewens* Upington* Vanwyksvlei Addo* Armoedsvlakte Bloemfontein Glen College Cedara* Emerald Dale* Pretoria PUR* Pretoria UP* Bela Bela Polokwane Musina* Skukuza* Climate Station Figure 3. Trend () in annual mean minimum temperature for the period (asterisk indicates significant trend at the 5% level) to be reflected in the temperature trends of these stations, especially the Pretoria PUR, but this is discussed more fully in Section 3.5. Looking at annual average temperatures in Figure 4, 24 of the stations show positive trends, 18 of them significant, and scattered throughout South Africa. The exceptions again are some of the stations in the central interior, as well as Port Elizabeth on the south coast. From the results discussed above, it is evident that there is a general pre-dominating positive trend in temperature, although not always significant, for the period 196 to 23 over South Africa. These results are consistent with those of Mühlenbruch-Tegen (1992) and Hughes and Balling (1996), albeit with a larger percentage of stations showing significant trends, which indicates a continuation of positive temperature trends experienced for the period 1949 to 1989 and 196 to 199 respectively for the two studies mentioned.

5 SOUTH AFRICAN TEMPERATURE TRENDS Cape Columbine* Cape Town* Cape Point* Jonkershoek* Cape Agulhas* Cape St. Blaize* Cape St. Francis* Port Elizabeth East London* Durban* Cape St. Lucia* Langgewens* Upington* Vanwyksvlei* Addo* Armoedsvlakte Bloemfontein Glen College Cedara* Emerald Dale Pretoria PUR* Pretoria UP Bela Bela Polokwane* Musina Skukuza* Climate Station Figure 4. Trend () in annual mean temperature for the period (asterisk indicates significant trend at the 5% level) 3.2. Seasonal trends To ascertain whether certain seasons showed consistently higher or lower temperature trends than others, the mean annual data series examined were subdivided into seasons, with autumn defined as the months from March to May, winter from June to August, spring from September to November and summer from December to February. The results obtained for the above seasons are shown in Figures 5 to 8 respectively, which clearly indicate that temperature trends over the last 44 years are not consistent between seasons. The average trend for all 26 stations for autumn was found to be.21 C per decade, for winter it was.13 C per decade, for spring it was.8 C per decade and for summer it was.12 C per decade. It is also interesting to note that 15 of the stations showed significant positive trends for autumn, 7 for winter, 5 for spring and 11 for summer. Consistent with the study of Mühlenbruch-Tegen (1992) for the period , the season with the highest mean temperature trend is autumn, and that with the lowest trend is spring. Spatially, the six stations with non-significant trends for autumn show little spatial coherence, except for the southern coast, where all trends were non-significant, contrary to the fact that most of these stations showed significantly positive trends in mean annual temperature. The results of the remaining seasons, with lower average trend of mean temperature than autumn, revealed even less spatial coherence Monthly trends The results obtained from the seasonal analysis (where clear differences in average trends of mean temperature between seasons were revealed, but without any clear spatial coherence in results) suggest that it is worthwhile investigating the trends in finer detail. After analyses of monthly trends of all the stations, it was found that there are large temporal differences in trends between months for individual stations. The monthly trends of each of the stations were then plotted and investigated for similarities between them. Similar monthly tendencies with regard to differences from month to month were found to exist, between stations close to each other and also sometimes even on a regional basis. From the graphs shown in Figure 9, it can be noted that stations in the same vicinity showed, in a broad sense, similar monthly differences in trend, i.e. similar increases and decreases in trend from one month to another, as well as months of minimum and maximum trend. A map of the maximum monthly mean temperature trends is shown in Figure 1, and it can clearly be seen that the magnitudes of monthly trends have some similarities between stations in larger areas, rather than merely between stations close by. Almost all of the stations in the country, excluding the southern regions,

6 1934 A. C. KRUGER AND S. SHONGWE Cape Columbine* Cape Town* Cape Point* Jonkershoek Cape Agulhas Cape St. Blaize Cape St. Francis Port Elizabeth East London* Durban* Cape St. Lucia* Langgewens* Upington* Vanwyksvlei* Addo* Armoedsvlakte Bloemfontein Glen College* Cedara* Emerald Dale Pretoria PUR* Pretoria UP Bela Bela Polokwane* Musina Skukuza* Station Figure 5. Autumn mean temperature trend () for the period (asterisk indicates significant trend at the 5% level) Cape Columbine* Cape Town* Cape Point Jonkershoek Cape Agulhas Cape St. Blaize Cape St. Francis* Port Elizabeth East London Durban* Cape St, Lucia* Langgewens Upington Vanwyksvlei Addo Armoedsvlakte Bloemfontein Glen College Cedara Emerald Dale Pretoria PUR* Pretoria UP Bela Bela Polokwane* Musina Skukuza* Station Figure 6. Winter mean temperature trend () for the period (asterisk indicates significant trend at the 5% level) show their month of maximum trend to be April, with the exception of Pretoria PUR. This station, however, also shows a very high trend for April. These results coincide with those for the seasons, where autumn is the season of maximum trend. In the south the results are mixed, possibly indicating that additional or other factors than for the rest of the country might contribute to the increase in temperature there. The months of minimum trends are shown in Figure 11, indicating that for the interior the largest part shows a minimum trend in early summer from September to December. The exception is the far eastern regions, where the minimum trends occur in January, as for the climate stations of Cape St Lucia and Skukuza. In the south and southeast, minimum trends tend to occur either in March or July, whereas in the southwest the results are mixed. The poor spatial coherence in the results for the southwestern Cape, for both maximum and minimum monthly trends, can be explained by examining the graph in Figure 9 for three stations in the

7 SOUTH AFRICAN TEMPERATURE TRENDS Cape Columbine* Cape Town Cape Point* Joershoeknk Cape Agulhas* Cape St. Blaize* Cape St. Francis Port Elizabeth East London Durban Cape St. Lucia Langgewens Upington Vanwyksvlei Addo Armoedsvlakte Bloemfontein Glen College Cedara Emerald Dale Pretoria PUR Pretoria UP* Bela Bela Polokwane Musina Skukuza Station Figure 7. Spring mean temperature trend () for the period (asterisk indicates significant trend at the 5% level) Cape Columbine* Cape Town* Cape Point* Jonkershoek Cape Agulhas* Cape St. Blaize Cape St. Francis* Port Elizabeth East London* Durban* Cape St. Lucia Langgewens Upington* Vanwyksvlei* Addo* Armoedsvlakte Bloemfontein Glen College Cedara* Emerald Dale Pretoria PUR Pretoria UP Bela Bela Polokwane Musina Skukuza Station Figure 8. Summer mean temperature trend () for the period (asterisk indicates significant trend at the 5% level) area, indicating monthly maxima in trends in February, May and December, and minima in June/July and November. The causes of the differences and similarities of mean monthly temperature trends can probably only be explained with the aid of general circulation models, where gradual changes in circulation over decades on a monthly basis can be investigated Trends in diurnal temperature range The general global trend is for the diurnal range trend to be negative over the last century (Easterling et al., 2) due to the fact that, in general, trends in minimum temperatures are higher than trends in maximum temperature. However, results on a regional basis may not necessarily be the same. The

8 1936 A. C. KRUGER AND S. SHONGWE South-western Cape Cape Columbine Cape Town Cape Point Jonkershoek Southern Cape Cape Agulhas Cape St Blaize Month Month.5 South-eastern Cape.5 Southern KwaZulu-Natal Cape St Francis Port Elizabeth Addo Durban Cedara Emerald Dale Month Month Northern Gauteng Pretoria PUR Pretoria UP Bela Bela Limpopo and Mpumalanga Polokwane Musina Skukuza Month Month Figure 9. Trends of monthly mean temperature () for various regions in South Africa for the period trends in South Africa for 196 to 23 were found to be almost equally divided between positive and negative trends in mean annual diurnal temperature range, as indicated in Figure 12. Twelve stations showed positive trends, with five of them significant, and 14 stations showed negative trends, with six of them significant. In a regional sense, coastal stations showed mixed positive and negative trends, with only Cape St Francis in the south and Durban in the east showing significant and substantial decreases in diurnal range. In the interior, stations in a central part around the southern Free State, Northern Cape and North- West provinces, showed high positive trends, due in part to the high trends in annual mean maximum temperature, but also because of the small or even negative trends in annual mean minimum temperatures for some of the stations. Other stations with the same tendency are situated in the northern interior, but their trends in diurnal temperature range were much smaller, although significant for Bela Bela. In between the above two groups of stations with positive trends are the stations of Gauteng and KwaZulu-Natal provinces, with negative trends, ranging from about.5 C per decade for Cedara to about.35 C per decade for Pretoria PUR. Although some of these stations with negative trends showed a substantial significant increase in minimum temperatures, the trends in maximum temperatures were almost zero or negative.

9 SOUTH AFRICAN TEMPERATURE TRENDS 1937 Figure 1. Month of maximum monthly mean temperature trend in South Africa for the period (1 = January, 2 = February, 3 = March,...,12= December) Figure 11. Month of minimum monthly mean temperature trend in South Africa for the period (1 = January, 2 = February, 3 = March,...,12= December) 3.5. Trends in extreme temperatures and temperature events Changes in annual frequencies of the amount of days with maximum and minimum temperatures in defined categories are investigated based on some of the indices developed by Collins et al. (2), but also taking into account the temperature categories employed by the forecasting section of the South African Weather Service, with which temperature thresholds are defined for forecasting purposes, e.g. when a day is defined as very hot, hot, cool or cold. The indices selected are shown in Table I, from which one can see, for example, that a very hot day is defined as a day with a maximum temperature equal or higher then 35 C, a cold night

10 1938 A. C. KRUGER AND S. SHONGWE Cape Columbine Cape Town Cape Point Jonkershoek Cape Agulhas Cape St. Blaize Cape St. Francis* Port Elizabeth* East London* Durban* Cape St. Lucia Langgewens Upington Vanwyksvlei* Addo Armoedsvlakte Bloemfontein* Glen College Cedara Emerald Dale* Pretoria PUR* Pretoria UP* Bela Bela* Polokwane Musina Skukuza Climate Station Figure 12. Annual mean diurnal range trend () for (asterisk indicates significant trend at the 5% level) Table I. Temperature indices used in the analysis of extreme temperatures and temperature events. (T x : maximum temperature; T n : minimum temperature) Maximum temperature extreme indices Minimum temperature extreme indices Very hot days: T x 35 C Hot nights: T n 2 C Hot days: 3 C T x < 35 C Warm nights: 15 C T n < 2 C Hot-day events: T x 3 C for 3 5 days Warm-night events: T n 15 C for 3 5 days Cold days: T x 15 C Very cold nights: T n C Cool days: 15 C <T x 19 C Cold nights: C <T n 5 C Cool-day events: T x 19 C for 3 5 days Cold-night events: T n 5 C for 3 5 days event is defined as three to five consecutive days with the minimum temperature equal to or lower than 5 C, etc. The results for maximum temperature indices are shown in Figure 13, from which it is evident that days with warmer temperatures have generally increased while days with cooler temperatures have decreased. Very hot days are rare in parts of the country, especially the coast, where in certain areas no trends were determined, or could not be determined at all, as for the south coast. The same applies to hot-day events. Significant increases in very hot days are shown where they are a common occurrence, as in the Northern Cape (Upington and Vanwyksvlei). In the case of hot days, high or significant increases were also determined for places where they frequently occur, as in the case of Polokwane, Skukuza and Durban. However, there are exceptions, as in the case of the Pretoria stations, which show a negative trend, and also Upington and Vanwyksvlei. For these latter two stations it might be that more days gradually began to fall in the very hot day category during the study period, with fewer days consequently available for the hot day category from year to year, and hence the low trends seen for these stations for the last-mentioned category. There was a general decline in cold days, but the results for cool days were mixed. Most stations showed an increase in hot-day events, with the exception of three stations. Cool-day events, in general, declined, and some quite substantially, e.g. Bloemfontein with 2.11 days per decade, Cape St Blaize with 2.46 days per decade, and Cape Columbine with 2.93 days per decade. Figure 14 shows maps for minimum temperature categories and indicates that, in general, warmer nights have increased while cooler nights have decreased. Here, it must also be noted that very cold nights and cold-night events rarely or never occur at coastal stations, as indicated on the relevant maps. Hot nights have

11 SOUTH AFRICAN TEMPERATURE TRENDS 1939 Figure 13. Trends (days/decade) in daily maximum temperature indices (asterisk indicates significant trend at the 5% level) increased significantly on the east coast (East London, Durban and Cape St Lucia) and the eastern interior (Skukuza), as well as the Northern Cape interior (Upington), whereas warm nights have increased significantly along the Western Cape coast and areas in the Eastern Cape (Cape St Francis and Addo). Also, Pretoria PUR (the only interior station) experienced a significant increase in warm nights. The only significant decrease in very cold nights occurred at Pretoria PUR, a climate station that often shows different results than others in the same region, which could be partly due to urbanization (see Section 3.6). In the case of cold nights, the coastal stations of Cape Town and Durban showed significant decreases, and in the interior the same was the case for Addo and Pretoria UP. Significant increases in warm-night events occurred scattered throughout South Africa, for stations along the coast as well as the interior. Some spatial coherence in significant increases was evident on the west

12 194 A. C. KRUGER AND S. SHONGWE Figure 14. Trends (days/decade) in daily minimum temperature indices (asterisk indicates significant trend at the 5% level) coast and Eastern Cape, Northern Cape, KwaZulu-Natal, Gauteng and Mpumalanga provinces. Significant decreases in cold-night events occurred in the same areas Effects of urbanization on temperature trends The data for an urban climate station will not be representative of its surrounding non-urban areas, but this is not necessarily wholly true for trends in some climatic parameters, specifically in this case for temperature. Only when an area in which a station is situated has undergone substantial growth in population and or industrial development in the period of study, to increase or intensify the urban heat island, will urbanization have a probable bearing on the size of trend, with a gradual increase compared with non-urban stations nearby.

13 SOUTH AFRICAN TEMPERATURE TRENDS 1941 Stations that underwent substantial increased urbanization in their vicinities during the study period are Cape Town, Port Elizabeth, East London, Durban, Pretoria PUR and Pretoria UP. In this section we compare the temperature trends of the above stations with the remaining non-urban stations. In the case of mean annual maximum temperature trends, the urban stations show, on average, a non-significant positive trend of.7 C per decade compared with a significant.16 C per decade for non-urban stations; for mean annual minimum temperature trends is a significant.17 C per decade (urban) compared with a non-significant.11 C per decade (non-urban). Pretoria PUR, which is located in the centre of Pretoria, in contrast to other urban stations, which are located at airports more on the outskirts of cities, exhibits temperature trends that seem to be most likely contaminated by urbanization. This station shows a significant increase in mean annual minimum temperature of.34 C per decade compared with.16 C per decade at Pretoria UP, more on the outskirts of the city. Other stations identified as urban do not show the same contrast in temperature trends when compared with other stations in their region. It seems that for the stations used in the study, except for Pretoria PUR, other influences on the region where the climate station is situated have a much greater effect on its temperature trends than whether it is classified as urban or non-urban. Hughes and Balling (1996) also divided stations into urban and non-urban groups and calculated average diurnal range trends for both groups, and found that, in general, non-urban stations showed a more positive trend than urban stations. This means that there should have been a stronger increase in minimum temperatures compared with maximum temperatures for urban stations than for non-urban stations. We did a similar exercise and found average trends of.3 C per decade for non-urban stations and.7 C per decade for urban stations. The biggest reason for the difference in trends seems to be a lower increase in mean maximum temperature trends for urban stations than for non-urban stations, although the differences in mean minimum temperature trends between urban and non-urban station also seem to play some role to a lesser extent. These trends are similar in sign to those found by Hughes and Balling (1996), with trends of.4 C and.22 C respectively. However, our results for urban stations are much closer to zero than their study, indicating a possible decrease in trend for the last decade Changes in temperature trends between different periods from 196 to 23 It is already established that most stations showed a significant increase in mean annual temperature for the period 196 to 23, as shown in Figure 3, but previous studies did not show these largely positive trends for most climate stations in their studies (Mühlenbruch-Tegen, 1992; Hughes and Balling, 1996), probably because the period 1991 to 23 was not included. Globally, the last decade of the previous century was shown to be substantially warmer than previous decades. Therefore, we decided to quantify the average difference in trends of mean annual temperatures, between the periods 196 to 199 and 1991 to 23, with the exception of Pretoria PUR, for which the temperature data are most probably contaminated by urbanization. The period for 196 to 199 has an average mean temperature of C and a trend of.11 C per decade for the remaining 25 stations, whereas the period 1991 to 23 has an average mean temperature of C and a trend of.9 C per decade. There is not much difference between the trends for the two periods, and the average trend for the latter period is even slightly lower than for the former. It can thus be concluded that there is no gradual increase in annual mean temperature trends from 196 to 23. To investigate whether there was more of an abrupt increase in annual mean temperatures on a shorter time scale, the time series was subjected to a Student s t-test for the differences in mean of annual mean temperatures between the period from 196 to a specific year and the period after that year to 23. The higher the absolute value of the test statistic, the larger the difference is deemed to be in mean temperature between the period before a specific year and the period after that year, for the number of years utilized for each period. The change in the test statistic from year to year is shown in Figure 15. If the trend in annual mean temperature had stayed more or less constant, or if there had been a gradual increase in temperature trend throughout the whole period from 196 to 23, then the graph would have shown a gradual decrease in the values of the time series of the test statistic, but this is not the case. From 1983, with a small number of exceptions, there is, rather, an increase in the test statistic from year to year, indicating a change in trend.

14 1942 A. C. KRUGER AND S. SHONGWE 1-1 Test statistic Figure 15. Time series of Student s t-test for the difference in means. The value of the test statistic indicates the difference between the average temperature from 196 to a specific year (on the x-axis) and the average temperature after the specific year to 23 From the above, the conclusion is that, on average for the 25 stations, there was from about 1982 a rather abrupt increase in annual mean temperatures. In this regard it is interesting to note that, on average, the mean annual temperature trend for the stations from 196 to 1982 is a non-significant.4 C per decade, whereas the trend is almost zero,.1 C per decade, for the period from 1983 to 23. For the whole period from 196 to 23 the average trend in mean annual temperature is a significant.13 C per decade. There was therefore, on average for all stations, a somewhat abrupt increase in mean annual temperatures during the early 198s, the main cause of the significant trend determined for the study period as a whole. Year 3.8. The influence of El Niño and La Niña events on average annual temperatures To test whether the trends in temperatures are forced partly by El Niño and La Niña events, regression analysis was performed using average late-summer (January to March) NINO3 sea-surface temperatures (SSTs) and average late-summer temperatures. This procedure was applied to all stations within the area of South Africa which had a significantly negative correlation between late-summer NINO3 SSTs and latesummer rainfall, as established by Kruger (1999). This area covers more or less a broad band over the central parts of the country, from northwest to southeast, and includes eight stations, namely Upington, Vanwyksvlei, Armoedsvlakte, Glen College, Bloemfontein, Addo, Cedara and Emerald Dale. All the above stations showed a significant correlation between late-summer NINO3 SSTs and temperature. From the linear correlations determined between late-summer NINO3 SSTs and temperature, time series for the relevant stations could be constructed as predicted by the NINO3 SSTs. None of the time series of temperatures predicted by NINO3 SSTs showed a significant trend. This was also the case where the trends of the observed average late-summer temperatures were significant. Examples are given in Figure 16(a) and (b) for the stations of Cedara and Upington respectively. In both cases it is clear that, although the observed trends were significantly positive, the trends predicted by NINO3 SSTs showed only small non-significant positive trends. Therefore, it seems that increases in late-summer temperatures are not forced by the occurrence of El Niño and La Niña events. 4. DISCUSSION AND CONCLUSIONS The results presented agree to a large extent with previous similar studies on South African temperature trends (Mühlenbruch-Tegen, 1992; Hughes and Balling, 1996), except that more stations used in the study showed significantly positive results in temperature trends. For the climate stations utilized in this study, trends of

15 SOUTH AFRICAN TEMPERATURE TRENDS 1943 (a) 21.5 Cedara Temperature ( C) Predicted Observed Linear trendpredicted Linear trendobserved (b) Temperature ( C) Year Upington Year Predicted Observed Linear trendpredicted Linear trendobserved Figure 16. Time series and trend lines of observed late-summer (January to March) average temperatures (square) and late-summer temperatures as predicted by NINO3 SSTs (diamond) for (a) Cedara and (b) Upington. Solid and broken lines indicate trend as explained in the legend maximum, minimum and average mean annual temperature do not, in all cases, coincide with the general trend of the average global time series. But in most cases they do, showing largely positive trends on average. Similar observations were made by King uyu et al. (2) in their study of eastern African temperature trends and Unganai (1997) in his study of Zimbabwean temperature trends. Temperature trends were also found not to be consistent between seasons, with autumn being the season of highest temperature trends on average and spring being the season of lowest trends. However, there does not seem to be much spatial coherence in the results of temperature trends for specific seasons. The results of monthly mean trends, like those for the seasons, showed similarities in trends on a regional basis. Almost countrywide, April was determined to be the month of highest temperature trend, except for the southern parts, where results are mixed, possibly indicating that additional or other factors than for the rest of the country might contribute to the increase in temperature there. The months of minimum trends indicated that, for the interior, the largest part shows a minimum trend in early summer from September to December, except for the far eastern regions where the minimum trends occur in January. In the south and southeast the minimum trends tended to occur either in March or July, whereas in the southwest the

16 1944 A. C. KRUGER AND S. SHONGWE results were mixed. A conclusion from the above results is that it is advisable to investigate trends for as short a time scale as possible, as seasonal trends can show more detail of trends than average annual series (as in this case), whereas a monthly time series, showing even more detail in trends, lends itself to further investigation of temperature trends and its causes on a regional basis. With a relatively large focus presently in climate research on the downscaling of general circulation model (GCM) results to smaller regions, the results obtained in this study can be applied for verification purposes, and downscaled GCM results can in turn be utilized to explain the monthly or seasonal differences in trend. Trends in diurnal temperature range also show that results on a regional basis do not necessarily coincide with the general global trends, which are negative over the last century (Easterling et al., 2). Positive and negative diurnal range trends seem to occur more or less as frequently as each other. Partly due to relatively high maximum temperature trends, many stations in the interior showed positive diurnal range trends, whereas at the coast the results were not as coherent spatially. Examining the days and nights with temperatures between, at, or below certain threshold values, in most cases it is evident that warmer days and nights have increased, while cooler days and nights have decreased. Significant results in trends were found in areas where specific temperature indices were occurring on a relatively frequent basis. As could be expected, the same types of result were found with runs of hot and cold maximum and minimum daily temperatures. Climate stations that can be classified as urban stations were investigated to see whether their trends were substantially different from those in the same region. We came to the conclusion that the results of temperature trends of the urban stations used in the study are still useful, as most of these stations are situated on the outskirts of cities. The exception is Pretoria PUR, whose results were consistently different than those in the same region. Where the trend results of urban stations were, on average, notably different than the rural stations was in the case of diurnal range trends. Urban stations have, on average, lower trends than non-urban stations, confirming the results of Hughes and Balling (1996). Although it is widely accepted that the average temperatures for the 199s were substantially warmer than preceding decades (18.48 C for 1991 to 23 compared with C for 196 to 199), trends in temperatures in South Africa have not increased during the last decade. The average temperature trend from 1991 to 23 is.9 C per decade, compared with.11 C per decade from 196 to 199. It was found that there was rather a relatively strong increase in average temperatures in the early 198s, this being the main cause of the general increase in temperature over the whole period from 196 to 23. While the average trend in annual mean temperatures is a significant.13 C per decade for 196 to 23, non-significant trends of.4 C per decade and.1 C per decade were found for 196 to 1982 and 1983 to 23 respectively. The rainfall season was one of the driest and hottest over much of South Africa due to an extreme El Niño event, but it seems that average temperatures have never fully recovered since then. Consequently, we tested whether the trends in temperatures were found to be forced partly be El Niño and La Niña events. Although there was a significant correlation between average late-summer NINO3 SSTs and late-summer temperatures over the same area which had a significant correlation between the same SSTs and rainfall (Kruger, 1999), the indications are that El Niño and La Niña events do not play a significant role in the observed significant increases in late-summer temperatures. REFERENCES Collins DA, Della-Marta PM, Plummer N, Trewin BC. 2. Trends in annual frequencies of extreme temperature events in Australia. Australian Meteorological Magazine 49: Datsenko NM, Sonechkon DM Refinement of time series of mean annual air temperature for the Northern and Southern Hemispheres in the 19th century. Russian Meteorology and Hydrology 1: Easterling DR, Karl TR, Gallo KP, Robinson DA, Trenberth KE, Dai A. 2. Observed climate variability and change of relevance to the biosphere. 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