Record 15-month Drought in 2018

The 15 months to date is the driest 15 months in the Manilla rainfall record from 1883.

Rainfall shortages August and September 2018

Graph of Rainfall Shortages

This graph shows all the present rainfall shortages at Manilla, short term and long term, in terms of percentile values. The latest values, as at the end of September, are shown by a black line with black circles. Those from one month earlier, at the end of August, are shown by a thinner line with smaller white circles.

Changes this month

The September rainfall total of 12.5 mm was at the 18th percentile. That raised short-term totals (2-, 3-, and 4-month totals) compared with those of a month ago. However, totals fell very much lower for 5-, 6-, 9-, 15-, 18-, and 24-months.

Extreme shortages

Extreme shortages, seen less than 1% of the time since 1883, are now seen for the durations of 5, 6, 9, 15 and 18 months. This drought is now worse than the drought of 2002. In that drought the longest duration of extreme shortage was only 12 months: 307 mm (at the 0.2th percentile) from December 2001 to November 2002.

A record rainfall shortage

The 15-month total of 400 mm is the lowest in the 136-year record. It is a rate of 26.7 mm per month, 49% of normal, and at the 0.06th percentile. It beats the previous lowest 15-month total of 404 mm that was set in May 1912.
The last time that records for low rainfall were set at Manilla was nearly 50 years ago. Those records were: only 1 mm rainfall in the two months to April 1971, and only 14 mm in the four months to June 1971.

Long-term shortages

The 6-year rainfall total (3244 mm) is a severe shortage, unchanged for three months. These values are lower than any 6-year rainfall totals since 1962. When rainfall shortages of such long duration persist, rainfall does not maintain the groundwater levels or river flows required for irrigation or town supply.
A serious 20-year shortage (9.7th percentile) has developed in this month. Such a very long-term shortage has not been seen since 1949. Up to that date, the Namoi River had suffered decades of low flow, which was followed later by much higher flows. Manilla’s mean annual rainfall has been above normal from 1949 until recently.


Classes of rainfall shortage

I have adopted two classes of rainfall shortage from the classes of “Rainfall deficiency” defined by the Bureau of Meteorology in their Climate Glossary as follows:

“Serious rainfall deficiency: rainfall lies above the lowest five per cent of recorded rainfall but below the lowest ten per cent (decile range 1) for the period in question,
“Severe rainfall deficiency: rainfall is among the lowest five per cent for the period in question.
“Areas where the rainfall is lowest on record for the given time period are also shown.”

The Manilla rainfall record allows me to be more exact than the Bureau. Because the record extends back 134 years, it includes more than 1200 cumulative monthly rainfall values. I can identify percentile ranks even below the 0.1th percentile.
To the Bureau’s two classes of deficiency I add a third:

“Extreme deficiency (or extreme shortage): rainfall lies below the lowest one percent for the period in question.”


Manilla rainfall records

Manilla Post Office rain gauge, Station 055031, was read daily from 1883 to 26 March 2015. Then, for 15 months there was no official Manilla rain gauge. A Bureau of Meteorology automatic rain gauge was re-located to the museum yard and operated as Station 055031 from 23 May 2016 to 7 October 2016 (4 months). It failed, and did not operate for 5 months. After repair, the gauge was read automatically at 9 am daily as Station 055312: Manilla (Museum). It failed again after 6 months, on 24 September 2017. The web-page for Station 055312 shows that, since its repair on 15 March 2018, the gauge has been unreliable, with readings frequently missed. No readings were recorded in September 2018.
Since April 2015, I have read my rain gauge in Monash Street Manilla daily. I have used these readings when official readings are lacking. The gauge is not precise, the site does not meet specifications, and it is 1 km from the Post Office. However, the daily readings are seldom more than 3 mm higher or lower than available official Manilla readings.

Drought Sixth Month: August 2018

Rainfall status, July and August 2018.

Graph of Rainfall Shortages

This graph shows all the present rainfall shortages at Manilla, short term and long term, in terms of percentile values. The latest values, as at the end of August, are shown by a black line with black circles. Those from one month earlier, at the end of July, are shown by a thinner line with smaller white circles.
The classes of rainfall shortage are:
• Serious shortage: below the 10th percentile;
• Severe shortage: below the 5th percentile;
• Extreme shortage: below the 1st percentile. [See note below on my usage “Extreme shortage”.]

Changes this month

Rain late in August raised the one month and two month rainfall totals out of the class of “serious shortage”. The total for August (28.2 mm) is at the 40th percentile for the month, and the total for July and August is at the 10th percentile. The three-month total, which had been an extreme shortage, fell to become only a severe shortage.

Extreme shortages

Extreme shortages, seen less than 1% of the time since 1883, are now seen for the durations of 4, 5, 6, and 15 months. Without last week’s rain, the 6 month total would have been one of the lowest ever recorded.
There is an extreme shortage at 15 months, due to low rainfall in mid-2017, in the months of July (13.2 mm), August (13.8 mm), and September (5.5 mm).

Long-term shortages

The 6-year rainfall total for August (3252 mm) is a severe shortage, only slightly above that of July (3234 mm). Both these values are lower than any 6-year rainfall totals since 1962. When rainfall shortages of such long duration persist, rainfall does not maintain the groundwater levels or river flows required for irrigation or town supply.

[A graph showing rainfall shortages to the end of September 2018 is in the later post: “Record 15-month Drought in 2018”.]


Note: The term “Extreme shortage”

I have adopted classes of rainfall shortage from the classes of “Rainfall deficiency” defined by the Bureau of Meteorology in their Climate Glossary as follows:

“Serious rainfall deficiency: rainfall lies above the lowest five per cent of recorded rainfall but below the lowest ten per cent (decile range 1) for the period in question,
“Severe rainfall deficiency: rainfall is among the lowest five per cent for the period in question.
“Areas where the rainfall is lowest on record for the given time period are also shown.”

The Manilla rainfall record allows me to be more exact than the Bureau. Because the record extends back 134 years, it includes more than 1200 cumulative monthly rainfall values. I can identify percentile ranks even below the 0.1th percentile.
To the Bureau’s two classes of deficiency I add a third:

“Extreme deficiency (or extreme shortage): rainfall lies below the lowest one percent for the period in question.”

Short Droughts are Worst

The shorter the drought, the less rainfall there is in it. The longer the drought, the more rainfall. News reports give the false impression that hardly any rain falls during a drought, even if the drought lasts a long time. That is not true.

To prove the point, I have made graphs and a table showing the very worst droughts that Manilla ever had: the very worst short droughts, year-long droughts and 30-year droughts.

Lowest ever rainfalls

Graphs of the driest times

The first graph shows how the driest two month drought had only one millimetre of rain, while the driest longer periods had very much more, up to over 5000 mm of rain in 120 months (10 years). That may seem obvious. So long as there is a little rain in most months, the longer the period, the bigger the rainfall total. But there is more to it than that.

The second graph shows the average rate of rainfall during each worst drought: the rainfall per month. The rate is not steady as you might expect. It too becomes higher as longer droughts are measured. Through the worst two-month drought, only half a millimetre of rain fell per month. Through the worst 12-month drought no less than 24 mm fell per month. The worst 120-month drought had 47 mm per month on average. That is not far below the normal average monthly rainfall of 54.3 mm per month.

The third graph builds on this comparison. Each drought rainfall rate is shown as a percentage of the normal rainfall rate. While those worst droughts that were shorter than than five months had less than 10% of normal rainfall, no droughts that were longer than five months ever had so little. Droughts lasting for 12 months never had rainfall lower than 44% of normal. As for the decade-long droughts mentioned in the news, the driest decades in history had rainfall rates more than 85% of normal. Such record dry times are hard to see in rainfall figures, although they surely deplete surface and underground water storages.

[These graphs show clearly why droughts are not well defined by the percentage of normal rainfall. Percentile values are more satisfactory, but they too have problems.]

Manilla’s list of driest times

Table of lowest rainfallsThe table shows all the figures mentioned for each of the driest times on record in 134 years at Manilla.
Records can be broken, but it seldom happens. These records have stood for a very long time – at least the forty-six years since 1971.

Many of these record-setting droughts had dates of onset or breaking that were members of a rather small set. In particular, the year 1911 saw the onset of nearly half of them.

 

[This table was amended on 14/8/2018. The original table had two errors, now corrected.
1. The lowest 30-month total was not 1082 mm (36.1 mm/month; 66.5%) set March 1911 to August 1913. It was 1078 mm (35.9 mm/month; 66.2%) set May 1964 to October 1966.
2. There were not 14 rainless months, but 15. The month missed was April 1971.]

Relations Among Rainfall Moments

Six graphs of rainfall moment relations

Twelve-monthly values of rainfall since 1883 at Manilla NSW yield the four moments of their frequency distributions: mean, variance, skewness, and kurtosis. I plotted the history of each moment (when smoothed) in an earlier post.
Here, I compare the moments in pairs. Connected scatterplots reveal the trajectory of each relationship with time.
Some linear and cyclic trends persist through decades, but none persists through the whole record.
The first image is an index to the suite of six graphs of pair-wise relationships that I present below.

Rainfall variance vs. mean

Trajectory of Variance versus Mean

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Rainfall kurtosis vs. HadCRUT4, revised

Patterns of rainfall kurtosis and global temperature.

The kurtosis of annual rainfall at Manilla NSW forms a time-series that matches the time-series of global surface temperature when detrended.

[REVISED:
Earlier posts were based on rainfall data sets that were too small. Estimates of kurtosis and skewness were unstable. For details please read “Rainfall kurtosis matches HadCRUT4” and “Rainfall kurtosis vs. HadCRUT4: scatterplots”.]

The variables

These two climate variables have little in common. Manilla, NSW, is a single station that has a 134-year record of daily rainfall only. That yields estimates of rainfall kurtosis, an indicator of the relative frequency of extreme values.
HadCRUT4 is one of several century-long estimates of near-surface temperature for the whole world. [See Note below: “Data Sources”.]

The visual match of the patterns

The first graph (a dual-axis line chart) shows that these two variables have similar patterns of variation over time.

I found the best visual match by:
* scaling 0.5 units of Manilla rainfall kurtosis to 0.1° of detrended HadCRUT4 temperature;
* aligning the kurtosis value of -0.3 units with the zero of detrended temperature;
* lagging the rainfall by two years.

Features that the two patterns have in common are:
* matching main peaks at 1897, 1942 and 2005, each higher than the one before;
* persistent low values in the 1910’s, 1920’s, 1950’s, 1960’s, 1970’s and early 1980’s;
*some matching minor peaks and troughs.

Regression rainfall kurtosis on HadCRUT4.

The correlation chart

The second graph is a correlation chart. The linear regression of kurtosis on detrended temperature has the reasonable R-squared value of 0.67.
As I have made it a connected scatterplot, you can see how the relation has changed through time. From the first data point in 1898 (in red) both variables decreased together to the lowest temperature in 1910. Both peaked in 1942, having risen since 1920, later falling until 1955-56. The final rise to the highest peak (2005) was continuous from 1984 for temperature, but the rise in kurtosis was not. It fell slightly in 1990, then remained static until 1998.
All rainfall figures actually came two years earlier. [See note below: “Manilla’s 2-year lead”.] The assigned two-year lag not only makes peaks match on the first graph. It sharpens the reversals on the second graph. On a trial connected scatterplot without lag, these reversals had been smooth clockwise curves.

What it means

As evidence of extreme behaviour in climate

It is said that more extremes in climate will occur as the world becomes warmer. The evidence is not strong. Most data sets are overwhelmed by noise, and “extreme” is seldom defined with rigor.
In the present case, I believe that the definition of “extreme” that I use is sound: that is, the kurtosis of a frequency-distribution. The instability of kurtosis when based on my small samples had been an issue. In this revision I have increased the sample population size from 21 to 125.

My rainfall data set that displays more and less extreme behaviour is not general but local. It can merely suggest that data elsewhere may reveal functional relationships.

De-trended global temperature

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Moments of Manilla’s 12-monthly Rainfall

Manilla 12-monthly rainfall history: Four moments

REVISED, WITH MORE PRECISE DATA
Supersedes the post “Moments of Manilla’s Annual Rainfall Frequency” (15 November 2017). This post includes twelve times as much data.[See Note below: “Data handling”]

Comparing all four moments of the frequency-distributions

Yearly rainfall for Manilla, NSW, has varied widely from decade to decade, but it is not only the mean amounts that have varied. Three other measures have varied, all in different ways.

I based the graph on 125-month (decadal) sub-populations of the 134-year record. I plotted data for every month, at the middle month of each sub-population.
I analysed each sub-population as a frequency-distribution, to give values of the four moments: mean (drawn in indigo), variance (drawn in orange), skewness (drawn in green) and kurtosis (drawn in blue).

[For more about the moments of frequency-distributions, see the post: “Kurtosis, Fat Tails, and Extremes”.]

Each trace of a moment measure seems to have a pattern: they are not like random “noise”. Yet each trace is quite unlike the others.

Twenty-first century values are on the right. They are remarkable in three of the four moments. First, the mean rainfall (indigo) stays near the long-term mean, which has seldom happened before. By contrast, two moments are now near historical extremes: variance (orange) is very low and kurtosis (blue) very positive. Skewness (green) is rather negative.

To my knowledge, such a result has not been observed or predicted, or even suspected, anywhere.

[Note. The main difference from the earlier 4-moment graph based on more sparse data is that skewness does not trend downward.]

Manilla 12-monthly rainfall history: Mean

The mean 12-monthly rainfall (the first moment)

The first moment of the frequency-distribution of 12-monthly rainfall is the mean, or average. It measures of the amount of rain.

As I have shown before, the rainfall was low in the first half of the 20th century, and high in the 1890’s, 1950’s and 1970’s. Rainfall crashed in 1900 and again in 1980.

Manilla 12-monthly rainfall history: Variance

12-monthly rainfall variance (the second moment)

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Annual Rainfall Extremes at Manilla NSW: V

V. Extremes marked by high kurtosis

Manilla annual rainfall kurtosis

This graph shows how the extreme values of annual rainfall at Manilla, NSW have varied, becoming rarer or more frequent with passing time.
The graph quantifies the occurrence of extreme values by the kurtosis of 21-year samples centred on successive years.

The main features of the pattern are:
* Two highly leptokurtic peaks, showing times with strong extremes in annual rainfall values. One is very early (1897) and one very late (1998).
* One broad mesokurtic peak, in 1938, showing a time with somewhat weaker extremes.
* Broad platykurtic troughs through the 1910’s, 1920’s, 1950’s, 1960’s and 1970’s, decades in which extremes were rare.
All these features were evident in the cruder attempts to recognise times of more and less occurrence of extremes in Parts I, II, III and IV of this series of posts. This graph is more precise, both in quantity and in timing.

Superseded

ALL the results shown in this post are based on sparse data. They are superseded by results based on much more detailed data in the post “Relations Among Rainfall Moments”.

However, kurtosis (the fourth moment of the distribution) does not distinguish extremes above normal from those below normal. It is known that some early dates at Manilla had extremes that were above normal, and some late dates had extremes that were below normal.

Use of skewness

Extremes above normal are distinguished from those below normal by the third moment of the distribution, that is, the skewness.
Manilla Annual rainfall history: SkewnessThe post “Moments of Manilla’s Yearly Rainfall History” shows graphs of the time sequence of each of the four moments, including the skewness (copied here) and the kurtosis ( the main graph, copied above). The skewness function, like the kurtosis function, relates to the most extreme values of the frequency distribution, but to a lesser extent (by the third power, not the fourth).

I have shown the combined effect of kurtosis and skewness on the occurrence of positive and negative extremes in this data set in the connected scatterplot below.

Manilla rain skew vs.kurt

The early and late times of strong extremes were times of strongly positive and strongly negative skewness respectively. As kurtosis fell rapidly from the initial peak (+0.9) in 1897 to slightly platykurtic (-0.4) in 1902, the skewness also fell rapidly, from +0.7 to +0.3.
Much later, in mirror image, values were almost the same in 1983 as in 1902, then kurtosis rapidly rose while skewness rapidly fell, until kurtosis reached +0.9 and skewness -0.3 by 1998.
Between 1902 and 1983, while kurtosis remained below -0.2, the pattern was complex. In the decades of strong platykurtosis (below -0.9) there were extremes of skewness: +0.7 in 1919 and -0.3 in 1968.
Note that the skewness range was as high in times of low kurtosis as in times of high kurtosis, and the same applies to kurtosis range in relation to skewness. Conversely, when either moment was near its mean, the range of the other was not high.


See also:
“Rainfall kurtosis matches HadCRUT4” and “Rainfall kurtosis vs. HadCRUT4 Scatterplots”.