Rain RecordsLast Updated: February 15, 2025 |
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1 Introduction
In March of 1991 I started a daily record of rainfall. We were in a drought
at the time and on water restrictions, so the garden was suffering
somewhat!
I have recently been asked why I collect the data, in a similar
manner as if the person were asking me why I was wearing a fried egg
on my head. Yes, I suppose I am mad, but I am also a keen gardener, and
rain, or rather, the lack thereof, affects me greatly! :-)
It is somewhat difficult to intelligently present such a large body of
data, but obviously the first thing is to establish a season, since
calendar years are meaningless in the Summer rainfall areas! Hence the 2000
season runs from July 1999 to June 2000, much like SARS really :-) (I guess
that now needs explaining: not Severe Acute Respiratory Syndrome, but the
South African Revenue Service!!)
In all the years of recording, the split at July has let me down only a few
times.
It is hard to make a LOT of sense out of the data. We supposedly have a 7
or so year dry cycle and a 7 or so year wet cycle. It is difficult to
conclude that from my data. The cause of the cycle is apparently the
“El-niño” effect in the Pacific. It certainly has produced
widespread drought, but the trouble is: South-West is where all the
“weather” comes from, and this is interrupted by it.
If this pattern were to have continued, we would be in the hands of
El-niño! The Tropical Complex from the North, however descends from
the North, via Botswana, and has assisted us in Egoli for many years. As a
direct result, the rainfall has been quite good when, for example, the
northern VryStaat has been terrible. The “Usual” pattern would have
catered for the Vrystaat before us!!
The ONI (Oceanic Niño Index) is published in raw data form at
https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php.
Further discussion (focussed on USA effects) is at
https://www.climate.gov/news-features/understanding-climate/climate-variability-oceanic-nino-index.
A positive value of ONI corresponds to a warming El Niño, which generally
implies drought for us, and a negative ONI corresponds to a cooling La
Niña, implying rain. Note that the ONI is expressed as ∘C above or
below a 30-year average. (Sort of kills the "its only 2 degrees"
argument…)
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Figure 1: Season Totals overlaid on the Oceanic Niño Index |
In above figure, it can be seen that there is at least some correlation. In
1990-2, there is a strong El Niño, producing significant drought. 1996-7
was a moderate La Niña, with very wet conditions. So the “strength” of
the ONI does not necessarily correlate. 2010, of course was rather damp, in
the presence of a very strong El Niño…2015 onwards is a bit of a
mixed bag, with 2016 particularly uncorrelated. But 2022 is once again, damp.
Lastly, most publications state that the average rainfall in JoBurg is
500–750mm. JaNee.
2 Current Season, cumulative, for the impatient :-)
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Figure 2: Cumulative current season |
3 Rain Data by Season
3.1 Totals by Season
Simply a plot of the annual total seasonal rainfall. Note that in 1996 we
moved from Crosby to Kensington, ie west JHB to east JHB, but there
shouldn’t be much of a difference :-) <— See note above, I am changing
my mind :-) The average values shown do not include the effects of the
current (incomplete) season, as that would artificially affect them.
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Figure 3: Season totals at the Clark’s |
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Figure 4: Season count totals (wet-days) |
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Figure 5: Average amount of rain per rainy day |
Notice that in very dry years, less rain falls per day (obviously
for far fewer days too) and on very wet years, more falls per day.
But on other years which are not extreme, but do vary quite a lot in
total rainfall, the average amount per rainy day is pretty
constant!! I did not really expect the consistency.
Summary Table of Summed rainfall by Month
Season | Jul | Aug | Sep | Oct | Nov | Dec | Jan | Feb | Mar | Apr | May | Jun | Total |
1992 | 0.0 | 0.0 | 17.0 | 63.5 | 27.0 | 67.0 | 29.5 | 29.0 | 82.5 | 21.0 | 0.0 | 11.0 | 347.5 |
1993 | 0.0 | 28.0 | 12.0 | 37.5 | 160.0 | 143.0 | 61.5 | 52.5 | 104.0 | 36.0 | 0.0 | 0.0 | 634.5 |
1994 | 0.0 | 6.5 | 1.0 | 222.5 | 77.0 | 135.0 | 112.5 | 108.0 | 31.0 | 80.0 | 0.0 | 0.0 | 773.5 |
1995 | 0.0 | 4.0 | 6.5 | 79.0 | 48.0 | 128.0 | 192.0 | 75.0 | 136.0 | 67.0 | 41.0 | 0.0 | 776.5 |
1996 | 0.0 | 11.5 | 6.5 | 147.8 | 165.5 | 240.5 | 201.0 | 248.5 | 61.0 | 81.0 | 52.0 | 7.0 | 1222.2 |
1997 | 0.0 | 24.5 | 5.0 | 135.0 | 72.0 | 191.0 | 230.5 | 87.5 | 363.5 | 44.5 | 133.0 | 7.0 | 1293.5 |
1998 | 11.0 | 7.0 | 70.0 | 59.0 | 138.0 | 120.5 | 245.5 | 71.0 | 30.0 | 22.0 | 0.0 | 0.0 | 774.0 |
1999 | 0.0 | 0.0 | 29.5 | 98.0 | 239.0 | 155.5 | 90.5 | 89.0 | 77.5 | 65.0 | 37.0 | 8.5 | 889.5 |
2000 | 1.5 | 1.0 | 17.5 | 15.0 | 77.0 | 206.5 | 225.5 | 401.5 | 307.5 | 71.5 | 39.0 | 2.0 | 1365.5 |
2001 | 0.0 | 9.0 | 47.0 | 122.5 | 150.5 | 138.0 | 39.0 | 135.0 | 71.0 | 22.5 | 53.5 | 3.0 | 791.0 |
2002 | 0.0 | 3.0 | 100.0 | 114.0 | 158.0 | 142.0 | 107.0 | 95.0 | 96.0 | 19.0 | 12.0 | 64.0 | 910.0 |
2003 | 0.0 | 20.5 | 5.0 | 106.0 | 27.0 | 185.5 | 128.0 | 85.5 | 66.5 | 7.0 | 0.0 | 18.0 | 649.0 |
2004 | 0.0 | 6.0 | 4.0 | 93.0 | 94.5 | 72.0 | 149.0 | 177.5 | 115.5 | 56.5 | 0.0 | 14.0 | 782.0 |
2005 | 26.5 | 5.5 | 0.0 | 47.5 | 52.5 | 199.5 | 219.0 | 160.0 | 88.5 | 92.5 | 4.0 | 0.0 | 895.5 |
2006 | 0.0 | 0.0 | 1.5 | 54.0 | 158.0 | 134.0 | 217.0 | 259.0 | 121.0 | 24.5 | 2.5 | 0.0 | 971.5 |
2007 | 1.5 | 42.0 | 9.5 | 63.0 | 143.5 | 230.5 | 95.5 | 33.0 | 62.5 | 49.0 | 0.0 | 38.0 | 768.0 |
2008 | 0.8 | 0.0 | 46.0 | 170.0 | 95.0 | 122.0 | 199.5 | 63.5 | 159.0 | 30.0 | 65.5 | 29.5 | 980.8 |
2009 | 0.0 | 0.0 | 0.0 | 111.0 | 137.5 | 105.5 | 198.5 | 67.5 | 107.5 | 3.5 | 32.0 | 21.0 | 784.0 |
2010 | 0.0 | 24.5 | 8.5 | 148.5 | 149.5 | 189.5 | 324.0 | 152.0 | 114.5 | 196.5 | 44.5 | 0.0 | 1352.0 |
2011 | 0.0 | 0.0 | 0.0 | 68.5 | 122.5 | 303.5 | 206.5 | 93.5 | 213.0 | 106.0 | 24.0 | 53.5 | 1191.0 |
2012 | 0.0 | 6.0 | 5.0 | 90.0 | 59.0 | 235.0 | 185.5 | 67.5 | 101.0 | 19.0 | 0.0 | 3.0 | 771.0 |
2013 | 0.0 | 2.5 | 121.0 | 73.5 | 131.0 | 133.5 | 147.5 | 87.0 | 73.5 | 146.0 | 11.0 | 0.0 | 926.5 |
2014 | 0.0 | 9.5 | 6.0 | 154.0 | 152.0 | 247.0 | 50.5 | 124.0 | 236.0 | 65.0 | 2.0 | 8.5 | 1054.5 |
2015 | 0.0 | 2.0 | 22.0 | 52.0 | 154.5 | 364.0 | 167.5 | 117.5 | 65.5 | 42.0 | 0.0 | 2.0 | 989.0 |
2016 | 31.0 | 1.0 | 75.0 | 12.0 | 89.0 | 104.0 | 186.0 | 210.5 | 144.0 | 16.5 | 63.0 | 19.5 | 951.5 |
2017 | 28.0 | 0.0 | 4.0 | 86.0 | 188.5 | 153.5 | 170.0 | 294.5 | 50.0 | 43.0 | 49.5 | 0.0 | 1067.0 |
2018 | 11.0 | 0.0 | 0.0 | 140.5 | 154.5 | 207.0 | 93.0 | 123.5 | 195.5 | 90.0 | 25.0 | 7.0 | 1047.0 |
2019 | 0.0 | 0.0 | 20.0 | 70.0 | 87.5 | 95.5 | 290.5 | 244.5 | 57.0 | 222.0 | 0.0 | 0.0 | 1087.0 |
2020 | 0.0 | 0.0 | 24.0 | 3.5 | 160.0 | 292.0 | 76.0 | 180.0 | 86.5 | 128.5 | 0.0 | 18.0 | 968.5 |
2021 | 0.0 | 0.0 | 9.0 | 73.5 | 252.0 | 186.0 | 119.0 | 162.5 | 99.0 | 32.0 | 11.0 | 21.0 | 965.0 |
2022 | 0.0 | 1.0 | 8.0 | 96.0 | 211.5 | 240.5 | 299.0 | 118.5 | 140.5 | 203.5 | 24.0 | 27.0 | 1369.5 |
2023 | 2.0 | 0.0 | 0.0 | 47.0 | 272.5 | 206.0 | 50.5 | 394.0 | 70.5 | 44.0 | 102.5 | 9.0 | 1198.0 |
2024 | 0.0 | 0.0 | 18.5 | 32.0 | 106.0 | 103.0 | 279.0 | 33.5 | 55.0 | 102.5 | 16.0 | 4.0 | 749.5 |
2025 | 0.0 | 0.0 | 8.5 | 43.0 | 73.0 | 92.5 | 124.5 | 81.5 | 0.0 | 0.0 | 0.0 | 0.0 | 423.0 |
Avg | 3.3 | 6.3 | 20.8 | 86.1 | 128.9 | 172.6 | 162.1 | 138.9 | 114.6 | 68.2 | 25.6 | 12.0 | 948.3 |
Bottom right is the overall average.
3.2 Monthly Totals by Wet and Dry Months
It is difficult to present the monthly data, as there are now too many
years of it, and we are running out of graph space :-)
It is to be noted that the really wet months are a tad random!! And yes,
Feb 2000 was a reasonably damp month. Note too that May ’97 in the “dry”
months was rather special, leading to the pretty good seasonal total, even
so late in the year.
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Figure 6: “Wet” part of the season—monthly totals |
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Figure 7: “Dry” part of the season—monthly totals |
3.3 Lies, Damned lies, and Statistics
Another way of looking at this is the min/mean/max type of graph per
month. I have also added the First Quartile, Median, Third Quartile. I
think that the month of February shows beautifully the classic question so
often asked by newcomers to statistics: “What is the difference between a
mean and a median”. The difference between min/max and 1st and 3rd
quartiles is even more marked. The difference is caused by a
once-off 30mm in 1992, and a once-off 401.5mm in 2000.
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Figure 8: Min,mean,max and 1st quartile,median,3rd quartile by month. |
Also of interest is a similar graph of the number of rainy days by month.
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Figure 9: Min,mean,max and 1st quartile,median,3rd
quartile rainy days by month. |
4 Rain Data detail
For those oddballs that really like detailed stuff, here is the data on a
yearly and a monthly basis.
4.1 Per Year
4.2 Per Year Cumulative
The cumulative graphs show very nicely “when” the season “kicks-in”.
Some “good” seasons are awful to begin with, some start off with a bang,
but fizzle dismally.
4.3 Per Month
Note the scale changes: “Wet” and “Dry” months have different maxima on
the yranges, but are consistent within those classifications for comparison
purposes.
The online version is "http://ytdp.ee.wits.ac.za/rain.html"
This document was translated from LATEX by
HEVEA.