kruger andries final.qxd An analysis of Skukuza climate data A.C. KRUGER, L.B. MAKAMO and S. SHONGWE Kruger, A.C., L.B. Makamo and S. Shongwe. 2002. An analysis of Skukuza climate data. Koedoe 45(1): 1–7. Pretoria. ISSN 0075-6458. Data from the climate station at Skukuza, which has been open from 1912 to the pre- sent, are analysed. This exercise was done to provide the South African Regional Sci- ence Initiative (SAFARI-2000) experimental program with long-term climate statistics and trends. Climate parameters analysed are rainfall, temperature, humidity and sun- shine. In the case of rainfall and temperature, the data was first tested for homogeneity and in only three out of 36 monthly cases, the data proved not to be homogeneous. No monthly rainfall trends proved to be significant (at the 5 % level), with five months indi- cating slightly negative trends and seven slightly positive. Only the monthly maximum temperature series for June proved to be non-homogeneous. The June maximum tem- perature trend and the February, March, May, July and December minimum temperature trends were significantly positive. The annual time series for minimum temperature were also significantly positive. The monthly results were reiterated by the seasonal results, with the winter maximum temperature trend and the autumn and summer mini- mum temperature trends significantly positive. Ten months showed negative tempera- ture diurnal range trends with only March being significant. All long-term statistics of rainfall, temperature, humidity and sunshine were found to be typical of a savanna type climate in the southern hemisphere, although average monthly sunshine hours were somewhat less than the norm, due to frequent influx of moist air from the Mozambique Channel. Key words: Skukuza, SAFARI-2000, climate, trends. A.C. Kruger, Directorate: Climate Systems, South African Weather Service, Private Bag X097, Pretoria, 0001 South Africa (andries@weathersa.co.za); L.B. Makamo and S. Shongwe, Directorate: Climate Systems, South African Weather Service, Private Bag X097, Pretoria, 0001 South Africa. ISSN 0075-6458 1 Koedoe 45/1 (2002) Introduction The South African Regional Science Initia- tive (SAFARI-2000) experimental program is developed for southern Africa to explore, study and address linkages between land- atmosphere processes and the relationship of biogenic, pyrogenic or anthropogenic emis- sions and the consequences of their deposi- tion to the functioning of biogeophysical and biogeochemical systems (SAFARI-2000 Home Page). One of the SAFARI-2000 sites is about 13 km WSW of Skukuza in the Mpumalanga province. Many scientists are involved in the project or will use data forth- coming from it. However, climate data from the site itself only has a measuring period of about two years, from 2000 to 2001. The pur- pose of this paper is to provide an analysis of the data of the South African Weather Ser- vice climate station at Skukuza, entailing the calculations of long-term averages and trends, for the purpose of background data to interpret measurements at the flux measure- ment site. General climate characteristics of the area The climate station of Skukuza is situated at 24º59'S, 31º36'E at a height of 263 m above sea level. The area the station is situated in is generally known as the Lowveld and is kruger andries final.qxd 2005/12/09 11:32 Page 1 directly east of the eastern escarpment. According to the new climate regions devel- oped by the South African Weather Service, loosely based on the vegetation regions of Low & Rebelo (1996) and the Köppen cli- mate classification, Skukuza is situated in the Lowveld Bushveld region, which receives moderate summer precipitation (500–700 mm p.a.) with maximum rainfall in January. Warm to hot temperatures are usually experienced and no frost occurs. The humidity is usually fairly high and this makes summer days uncomfortable. Sun- shine duration during summer is below aver- age for this typical savanna climate, due to the influx of moist air from the coast and exacerbated by the proximity of the southern African escarpment close by towards the west. This type of climate lends itself to game, cattle and goat farming, subtropical fruit, vegetables and sugarcane through irri- gation, and ecotourism. Analysis of rainfall To obtain a general idea of the rainfall cli- mate of Skukuza, trends and long-term sta- tistics are calculated. But before any analy- ses can be done, the data first have to be checked for overall quality, as inhomo- geneities can influence the results signifi- cantly, especially in the case of trend calcu- lations. Homogeneity of rainfall data To test for the homogeneity of Skukuza rain- fall data, the non-parametric run test described by Thom (1966) was applied to monthly time series for January to Decem- ber. This test is based on the number of runs (or groups of consecutive data points) above or below the median value of the time series. The results are shown in Table 1. In the sec- ond column the number of runs are shown which should ideally be about half of the total years used in the calculation (in this case about 80 years of data), to accept the time series as homogeneous. The third col- umn shows the results when compared to the Koedoe 45/1 (2002) 2 ISSN 0075-6458 Table 1 Results of run test to determine homogeneity of monthly rainfall time series Month Number of runs Result Jan 49 Homogeneous Feb 38 Homogeneous Mar 34 Non-homogeneous Apr 37 Homogeneous May 34 Non-homogeneous Jun 44 Homogeneous Jul 39 Homogeneous Aug 37 Homogeneous Sep 36 Homogeneous Oct 43 Homogeneous Nov 38 Homogeneous Dec 38 Homogeneous lower and upper 10 % significance limits. Two of the months, March and May, showed possible inhomogeneities in their series, with much fewer than the ideal number of runs. This might indicate a possible trend or slip- page in the mean. This is however not evi- dent from the trend calculations, of which the results are shown in the following sec- tion. Thus, another possible explanation for the inhomogeneity results is that there might be relatively large clusters of consecutive months with rainfall above or below the median value, but not distributed in a way to cause a trend in the data. For March the largest clusters or runs with four or more consecutive values above or below the medi- an are from 1912 to 1919 (below the medi- an), 1929 to 1934 (above the median), 1943 to 1946 and 1962 to 1966 (below the medi- an), 1967 to 1972 (above the median), and 1973 to 1976 and 1982 to 1986 (below the median). For May the runs are 1934 to 1937 (above the median), 1943 to 1946 (below the median), 1948 to 1951 (above the median), 1962 to 1965 and 1967 to 1970 (below the median), and 1979 to 1983 and 1990 to 1993 (above the median). Except for 1943 to 1946 and 1962 to 1965, none of the above periods are the same for both March and May, thus mostly excluding the probability of artificial biases introduced to the climate series, caus- ing recorded values to be too high or low. Also, no mention is made in the metadata of kruger andries final.qxd 2005/12/09 11:32 Page 2 the station of changes in exposure during, just before or just after the mentioned peri- ods, which lets one come to the conclusion that the above clusters are most possibly nat- ural phenomena, a true reflection of the rain- fall received at the station. No attempt was thus made to adjust data in the series before further analysis. Trends in rainfall Table 2 shows the analysis of linear trends in monthly rainfall time series for Skukuza for the period 1912 to 2001. The month with the highest trend is December with a very small positive value of 0.41 mm p.a. None of the trends calculated were significant at the 5% significance level. Trends were also calcu- lated for seasonal rainfall, where summer is defined as the months from December to February, autumn from March to May, win- ter from June to August and spring from September to November. The results are shown in Table 3. Again, very small trends were detected, the highest being 1.4 mm p.a. for summer while none of the trends were significant. These results indicate that the long-term rainfall average for Skukuza has remained fairly constant over the past 90 years. ISSN 0075-6458 3 Koedoe 45/1 (2002) Long-term rainfall statistics Figure 1 and Table 4 show long-term rainfall statistics for the period 1912 to 2001. Simi- lar statistics is supplied by Scholes et al. (2001), but only for a shorter period, ending in 1999. The analyses reveal a typical sum- mer rainfall climate in the southern hemi- sphere. From the absolute maximum and minimum monthly rainfall it is clear that the rainfall is highly variable, making the area prone to frequent droughts and floods. Temperature The same approach was followed with tem- perature analyses as in the case of rainfall. Firstly the data was checked for homogene- ity, and after that long-term trends and statis- tics were calculated. Homogeneity of temperature data As with rainfall, the run test described by Thom (1966) was used to test monthly time series for homogeneity. The total number of years of data is 42 years (1960 to 2001). Table 2 Monthly rainfall trends (mm p.a.) for the period 1912 to 2001 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Trend –0.25 0.25 –0.13 0.13 –0.02 –0.03 –0.03 0.08 0.07 0.18 0.08 0.41 Table 3 Seasonal rainfall trends (mm p.a.) for the period 1912 to 2001 Season Autumn Winter Spring Summer Trend –0.07 0.07 1.1 1.4 Fig. 1. Average monthly rainfall (mm) for the period 1912 to 2001. kruger andries final.qxd 2005/12/09 11:32 Page 3 Koedoe 45/1 (2002) 4 ISSN 0075-6458 Table 4 Rainfall statistics (mm) for the period 1912 to 2001 Statistic Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Absolute Monthly Maximum 835 531 260 222 83 110 132 182 193 231 434 331 Absolute Monthly Minimum 8 0 4 0 0 0 0 0 0 0 0 1 Maximum daily rainfall 103.5 119.5 86.5 71.5 56.5 40.1 75.2 40.0 85.6 44.4 67.3 99.5 Average amount of rainy days (>= 0.1 mm) 9.8 9.6 8.8 5.7 3.0 2.1 1.8 2.3 3.3 7.0 10.6 9.8 Table 5 Results of run test to determine homogeneity of maximum and minimum temperature time series Month Maximum Maximum Minimum Minimum temperature temperature temperature temperature runs result runs result Jan 23 Homogeneous 17 Homogeneous Feb 19 Homogeneous 16 Homogeneous Mar 21 Homogeneous 24 Homogeneous Apr 24 Homogeneous 20 Homogeneous May 23 Homogeneous 24 Homogeneous Jun 26 Non-homogeneous 19 Homogeneous Jul 19 Homogeneous 18 Homogeneous Aug 23 Homogeneous 17 Homogeneous Sep 22 Homogeneous 22 Homogeneous Oct 25 Homogeneous 19 Homogeneous Nov 23 Homogeneous 17 Homogeneous Dec 23 Homogeneous 25 Homogeneous According to the test, the ideal number of runs should be approximately 21 for a homo- geneous data set. The results for the maxi- mum and minimum temperatures are shown in Table 5. The third and last columns show the results of the test when compared to the lower and upper 10 % significance limits. Only the maximum temperature series for July showed possible inhomogeneities in its data series, indicating a high number of short runs in the series. This may in turn indicate a climatic vaccilation of the mean, or relative- ly short cycles in the series, although this was not verified by graphical analysis. Trends in maximum and minimum tempera- ture Table 6 shows the trends of monthly average maximum and minimum temperatures. For the maximum temperature, only July showed kruger andries final.qxd 2005/12/09 11:32 Page 4 a significant trend at the 5 % level. For the minimum temperature, five of the months showed significantly positive trends, as well as the annual average. These results are con- sistent with global trends where the mini- mum temperatures show higher positive trends than the maximum temperature (Easterling et al. 2000), causing the diurnal range in temperature to become progres- sively smaller. Table 7 shows the seasonal trends for maximum and minimum temper- atures. The maximum temperature trend in winter, as well as the minimum temperature trend in autumn and summer, showed sig- nificantly positive trends. ISSN 0075-6458 5 Koedoe 45/1 (2002) Table 6 Monthly and average trend of maximum and mini- mum temperatures (°C p.a.) for the period 1960 to 2001 (* indicates significance at the 5% level) Month Maximum Minimum Temperature Temperature Jan –0.020 0.007 Feb –0.005 0.029* Mar –0.006 0.035* Apr 0.026 0.021 May 0.010 0.034* Jun 0.037* 0.011 Jul 0.008 0.041* Aug 0.009 0.015 Sep –0.002 0.026 Oct –0.009 0.018 Nov 0.015 0.018 Dec –0.001 0.019* Average 0.005 0.024* Table 7 Seasonal trends of maximum, minimum and aver- age temperatures (°C p.a.) for the period 1960 to 2001 (* indicates significance at the 5 % level) Season Maximum Minimum Average Temperature Temperature Temperature Autumn 0.010 0.030* 0.020 Winter 0.018* 0.029 0.024* Spring 0.000 0.020 0.010 Summer –0.009 0.018* 0.013 Table 8 Trends of monthly diurnal temperature range (°C p.a.) for the period 1960 to 2001 (* indicates significance at the 5 % level) Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Trend -0.027 -0.034 -0.041* 0.005 -0.025 0.027 -0.033 -0.007 -0.028 -0.027 -0.004 -0.020 Trends in diurnal range of temperature Table 8 shows the monthly trends in diurnal range of temperature. As can be expected, corresponding with the relative trends in maximum and minimum temperature, the trend is negative for most months, although only the trend for March is significant. For the seasonal trends of diurnal range, as shown in Table 9, all the results were nega- tive. Autumn shows the highest negative trend of –0.023 ºC per year. Long-term temperature statistics Figure 2 and Table 10 show temperature sta- tistics for the total period of record (1960 to 2001). Similar statistics is supplied by Scholes et al. (2001), but for the period until 1999. Summer temperatures are hot, while during the winter it is mostly warm and pleasant. Minimum temperatures rarely drop below freezing point during winter, but even at this time of the year maximum tempera- tures can reach levels in the mid-thirties. kruger andries final.qxd 2005/12/09 11:32 Page 5 Humidity Because of frequent influxes of moist air from the east, the humidity should be rela- tively high. This is reflected in Table 11. The average monthly humidity at 14:00 SAST, Koedoe 45/1 (2002) 6 ISSN 0075-6458 Table 9 Trends of seasonal diurnal temperature range (°C p.a.) for the period 1960 to 2001 Season Autumn Winter Spring Summer Trend –0.023 –0.010 –0.021 –0.017 Table 10 Long-term temperature statistics (°C) for the period 1960 to 2001 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Absolute minimum 11.3 10.0 7.6 5.6 0.8 –4.4 –3.8 –4.2 1.3 6.4 9.9 2.0 Absolute maximum 43.0 45.6 42.0 41.3 39.2 35.3 36.4 38.0 42.6 43.6 42.8 42.4 Table 11 Relative humidity (%) at 14:00 SAST for the period 1978 to 2001 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average 53 54 53 48 43 38 39 38 41 45 52 51 Lowest monthly 39 37 40 35 30 29 28 30 33 36 39 36 Highest monthly 66 77 67 57 64 57 58 60 57 56 84 62 Table 12 Monthly sunshine data (hours) for the period 1960 to 2001 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total average 7.3 7.3 7.2 7.5 8.0 8.1 8.1 8.1 7.5 6.7 6.2 7.0 Lowest average 4.8 5.2 4.4 5.4 6.4 6.7 6.4 5.8 5.5 5.0 4.2 4.8 Highest average 9.1 9.6 9.3 9.4 9.4 9.4 9.6 9.5 9.3 8.5 7.8 10.8 which is usually the driest time of the day, ranges from a maximum of 54 % for Febru- ary to a minimum of 38 % for June and August. Sunshine Average sunshine data for 1960 to 2001 is shown in Table 12. One can see that, although daylight hours in summer is much longer than in winter, the sunshine hours show the opposite, indicating cloudier weather during summer. This region actual- ly receives markedly less sunshine than the kruger andries final.qxd 2005/12/09 11:32 Page 6 norm for savanna regions, the reason being the frequent influx of moist air from the east, with its accompanying fog and cloud. Discussion and conclusions The motivation for this paper is to supply researchers, and other interested parties involved in the SAFARI-2000 project, suffi- cient long-term background data to serve as a baseline for comparison to future observa- tions at the flux measurement site close by. Meta data and homogeneity tests suggest that the data is generally of a high quality, suitable for trend analyses. The average rain- fall (monthly and seasonal) stayed fairly constant during the previous century. How- ISSN 0075-6458 7 Koedoe 45/1 (2002) Fig. 2. Average monthly maximum and minimum temperature (°C) for the period 1960 to 2001. ever, there has been a marked increase in minimum temperature since the 1960s, espe- cially during the summer and autumn months. This result corresponds to the aver- age global trend (Easterling et al. 2000), and can also be considered a true reflection of temperature trends in the area, since no meaningful urbanisation or increased pollu- tion has taken place since the starting point of the time series. Long-term rainfall and temperature statistics indicate a highly variable climate, typical of the African savanna. References EASTERLING D.R., T.R. KARL, K.P. GALLO, D.A. ROBINSON, K.E. TRENBERTH & A. DAI. 2000. Observed climate variability and change of rel- evance to the biosphere. Journal of Geophysical Research 105: 20101–20114. LOW, A.B. & A.G. REBELO (eds.). 1996. Vegetation of South Africa, Lesotho and Swaziland. Preto- ria: Department of Environmental Affairs and Tourism. SCHOLES, R.J., N. GUREJA, M. GIANNECCHINNI, D. DOVIE, B. WILSON, N. DAVIDSON, K. PIGGOTT, C. MCLOUGHLIN, K. VAN DER VELDE, A. FREEMAN, S. BRADLEY, R. SMART & S. NDALA. 2001. The environment and vegetation of the flux mea- surement site near Skukuza, Kruger National Park. Koedoe 44(1): 73–83. SAFARI-2000 WWW HOME PAGE. 2002. Virginia State University. Virginia. U.S.A. (http:// safari.gecp.virginia.edu/) THOM, H.C.S. 1966. Some methods of climatologi- cal analysis. Geneva, Switzerland: World Mete- orological Organization. (WMO Technical Note; no. 81.) kruger andries final.qxd 2005/12/09 11:32 Page 7 Koedoe 45/1 (2002) 8 ISSN 0075-6458 kruger andries final.qxd 2005/12/09 11:32 Page 8 << /ASCII85EncodePages false /AllowTransparency false /AutoPositionEPSFiles true /AutoRotatePages /None /Binding /Left /CalGrayProfile (Dot Gain 20%) /CalRGBProfile (sRGB IEC61966-2.1) /CalCMYKProfile (U.S. Web Coated \050SWOP\051 v2) /sRGBProfile (sRGB IEC61966-2.1) /CannotEmbedFontPolicy /Error /CompatibilityLevel 1.4 /CompressObjects /Tags /CompressPages true /ConvertImagesToIndexed true /PassThroughJPEGImages true /CreateJDFFile false /CreateJobTicket false /DefaultRenderingIntent /Default /DetectBlends true /ColorConversionStrategy /LeaveColorUnchanged /DoThumbnails false /EmbedAllFonts true /EmbedJobOptions true /DSCReportingLevel 0 /EmitDSCWarnings false /EndPage -1 /ImageMemory 1048576 /LockDistillerParams false /MaxSubsetPct 100 /Optimize true /OPM 1 /ParseDSCComments true /ParseDSCCommentsForDocInfo true /PreserveCopyPage true /PreserveEPSInfo true /PreserveHalftoneInfo false /PreserveOPIComments false /PreserveOverprintSettings true /StartPage 1 /SubsetFonts true /TransferFunctionInfo /Apply /UCRandBGInfo /Preserve /UsePrologue false /ColorSettingsFile () /AlwaysEmbed [ true ] /NeverEmbed [ true ] /AntiAliasColorImages false /DownsampleColorImages true /ColorImageDownsampleType /Bicubic /ColorImageResolution 300 /ColorImageDepth -1 /ColorImageDownsampleThreshold 1.50000 /EncodeColorImages true /ColorImageFilter /DCTEncode /AutoFilterColorImages true /ColorImageAutoFilterStrategy /JPEG /ColorACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /ColorImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000ColorACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000ColorImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasGrayImages false /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 300 /GrayImageDepth -1 /GrayImageDownsampleThreshold 1.50000 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages true /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /GrayImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000GrayACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000GrayImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasMonoImages false /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 1200 /MonoImageDepth -1 /MonoImageDownsampleThreshold 1.50000 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict << /K -1 >> /AllowPSXObjects false /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly false /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile () /PDFXOutputCondition () /PDFXRegistryName (http://www.color.org) /PDFXTrapped /Unknown /Description << /ENU (Use these settings to create PDF documents with higher image resolution for high quality pre-press printing. 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