3-year trends to August 2019

Summer record hot-dry (as smoothed)

3-year climate trends to August 2019

August raw anomaly data (orange)


Daily maximum temperature anomaly (all x-axes): near the maximum for smoothed values.
Daily minimum temperature anomaly (lower left): near normal.
Subsoil temperature anomaly (lower right): very high.

Moistures (moist is at the bottom)

Rainfall anomaly (upper left): very low.
Cloudiness anomaly (upper right): normal.
Dew point anomaly (middle left): low, like the other recent values.
Daily temperature range anomaly (middle right): very high.

 Latest fully smoothed data (red), summer 2018-19


Daily maximum temperature anomaly peaked at a record +1.79° in January.
Daily minimum temperature anomaly held the record vaue of +2.16° through January and February.
Subsoil rose rapidly from normal.

Moistures (moist is at the bottom)

Rainfall smoothed anomaly peaked negative in January at the record value of minus 31.75 mm per month.
Cloudiness was normal.
Dew point was low.
Daily temperature range was normal.


January data points are marked by squares.

Smoothing Continue reading

Winter 2019 lowest rainfall?

White box eucalyptus tree

White Box Tree

There were several warm spells, mainly as warm days. The warmest was in early July, when days were 4.2° high and nights 4.0°. The only unusual daily temperatures were one high maximum of 27.1° and one low maximum of 11.3° in July.

There were 41 frosts, normally 44.
As in the drought year of 2002, there were only 8 rain days. The highest reading (estimated) was only 5.5 mm on 9 July.

Weather log winter 2019

This winter had the warmest days of the new century (19.5°) but nights that were near normal (3.2°).
Apart from the extremely low rainfall, the other moisture indicators (little cloud, low dew point, wide daily temperature range) were not as severe as in winter 2018.
The total rainfall of 20.9 mm is the 2nd lowest on record for winter. However, it may actually be the lowest. Although the year 1888 had recorded winter rainfall of only 6 mm, there is doubt about that. Daily readings are missing for June and July. The next lowest was 1946, with 29 mm, then 1972 and 1982, both with 32 mm.

winter climate 2019

Data. A Bureau of Meteorology automatic rain gauge operates in the museum yard. From 17 March 2017, 9 am daily readings are published as Manilla Museum, Station 55312.  These reports use that rainfall data when it is available. In this season, I used my own readings until 20 July, when the Museum gauge began recording again. My estimates of early morning dew point have become anomalously low. From 1 August 2019, I use values taken from Tamworth Airport graphs at the time of minimum temperature.
All other data, including subsoil at 750 mm, are from 3 Monash Street, Manilla.

New drought records in August 2019

Rainfall status July-August 2019

Graph of Rainfall Shortages

This graph shows all the present rainfall shortages at Manilla, short term and long term, as percentile values. The latest values, as at the end of August, are shown by a thick black line with large circles. Those from one month earlier are shown by a thinner line with small diamonds. [The method is described in “Further Explanation” below.]

Record low rainfall values

August rainfall of only 5.6 mm at Manilla has brought more drought records. The rainfall totals for 18-, 24-, 36-, 72-, and 84-months are new record lows.
The record-low 36-month total is remarkable. Only the great droughts of 1947, 1914, and 1967 had rainfall nearly so low for so long, but the current 36-month total (1283 mm) is more than 50 mm lower than in those great droughts. Given that Manilla’s mean  annual rainfall is 652 mm, 1283 mm represents less than two years of rainfall in three years.

Severe and extreme rainfall shortages

For plotted durations longer than four months, only the very longest (30 years) is not a severe or extreme rainfall shortage. For durations beyond 84 months (including 30 years) every total is lower than has been seen since 1954, 65 years ago.

Further Explanation

The following notes explain aspects of this work under these listed headings:

Data analysis

Cumulative rainfall totals
Percentile values
Severity of rainfall shortages

Limitations of this analysis

Monthly rainfalls form a single population
Observations are not retrospective
The rain gauge failed

Data analysis

Continue reading

Dry August 2019

Blossoms on a street tree

August Blossoms

Weekly average temperatures steadily increased as is usual in August. Day and night temperatures also were not far from normal. The warmest day reached 27.1° and the coldest night -1.4°. There were 15 frosts, the usual number.
Rain was recorded at the Manilla Museum on the 1st (1.0 mm) and the 12th (4.6 mm).

Weather log august 2019

Comparing August months

This dry month was very like August 2013, with the August months between being mainly rather cooler and wetter.
The mean maximum temperature (20.9°) was above normal by 1.4°, and the mean minimum temperature (3.3°) was near normal. The resulting temperature range (17.6°) was high, agreeing with the rather low cloudiness (26%) and dew point (-1.0°).
The rainfall total of 5.6 mm is at the 8th percentile for July.

Climate for August 2019


I have reported separately on the on-going drought that continues to break low-rainfall records at durations of 15-months and longer.

Data. A Bureau of Meteorology automatic rain gauge operates in the museum yard. From 17 March 2017, 9 am daily readings are published as Manilla Museum, Station 55312.  These reports use that rainfall data when it is available.  No 9 am readings were recorded from August 2018 to 19 July 2019. Recording resumed on 20 July 2019.
My estimates of early morning dew point have drifted anomalously low. From August 2019, I use data from the Tamworth Airport published graphs.
All other data, including subsoil at 750 mm, are from 3 Monash Street, Manilla.

Hot and dry records in January 2019

In January 2019, the smoothed anomaly value of monthly rainfall reached a record low (-31.8 mm/month), and that of monthly mean maximum temperature a record high (+1.79°).

Rainfall and temperature trajectory Sep2016 toFeb 2019

[This graph is extracted from a forthcoming post in the series “3-year trends…”. ]

This graph shows temperature and rainfall anomalies, not raw data. It shows how far the actual values differ from normal. The 30 data points from September 2016 to February 2019 (coloured red) are smoothed to show only cycles longer than one year.

The earliest data point, September 2016, had temperature and rainfall just beyond the normal range on the cool and wet side (lower left). Since that date, all the smoothed data points have fallen close to the sloping Mackellar trend line (blue) from cool-wet to hot-dry. (See the note below: Mackellar trend line.)
In the 4 months up to January 2017, warming and drying was rapid, passing completely through the “normal” range. Next, some cooling and wetting occurred to May 2017, then warming and drying resumed to a full drought in March 2018. Through the year 2018, drought prevailed, with a rainfall anomaly always below -25 mm. The temperature anomaly fell to only +1 deg by August, but rose again while rainfall fell. Records for low rainfall and high temperature were broken repeatedly.
January 2019 had the lowest smoothed monthly rainfall anomaly of the 21st century (-31.8 mm/month), and the highest monthly mean maximum temperature (+1.79°).
The following month, February 2019, had a slightly decreased temperature anomaly, and an increased rainfall anomaly. Later data points with less smoothing applied suggest that the smoothed record values of January may stand for some time.


Mackellar trend line

The insight of Dorothea Mackellar that this is a land “of droughts and flooding rains” *
is expressed in these graphs by a blue trend line passing through the “Normal” point in the centre (aqua) and extending both to “Droughts” with high temperature and low rainfall at the top right and to “Flooding Rains” with low temperature and high rainfall at the bottom left. Smoothed data points for anomalies of mean monthly daily maximum temperature and monthly rainfall totals generally lie close to the sloping blue line in such graphs for all of the last 20 years. (Search “3-year climate trends”, this one, for example).

Notice that record high and low values of smoothed anomalies of rainfall and daily maximum temperature (dates marked in blue) lie close the this blue line, supporting the estimate.
Empirically, one degree of increase in temperature anomaly matches 20 mm of decrease in monthly rainfall anomaly: the Mackellar Constant for Manilla is -20mm/month/degree.

* By arrangement with the Licensor, The Dorothea Mackellar Estate, c/- Curtis Brown (Aust) Pty Ltd.

21-C Rain ENSO IPO: Scatterplot

The anomaly of monthly rainfall at Manilla, NSW varied with that of ENSO for only a part of the 21st century to date.

Scatterplot Rainfall vs ENSO

This connected scatterplot relates the smoothed anomaly of the El Niño-Southern Oscillation (ENSO) to the smoothed and 2-month-lagged anomaly of monthly rainfall at Manilla, NSW. The earlier data, from September 1999 to September 2011, is plotted in blue, and the later data, from October 2011 to November 2018, in red.

The same data was displayed as a dual-axis line plot in an earlier post titled “21-C Rain-ENSO-IPO: Line graphs”. Data sources are linked there.

The line plot revealed two things: the relationship changed from earlier to later times, and there was a better match when the rainfall data was lagged by two months. To clarify, I prepared various scatterplots with fitted regressions.

Raw data scatterplots

Scatterplots of the raw data values yielded regressions with very low values of the coefficient of determination (R-squared). For the whole population, R-squared was 0.028. I then checked the coefficient when I lagged the rainfall by 1-, 2-, or 3-months. A 1-month lag almost doubled the coefficient to 0.041; a 2-month lag gave 0.055, and a 3-month lag gave 0.041 again.
My observation that Manilla rainfall typically leads ENSO by 2 months is confirmed.

Connected scatterplots of smoothed and lagged data

The smoothing function used in the dual-axis line plot of the earlier post makes a good visual match. That suggests that local rainfall and ENSO are physically related at a periodicity no shorter than 12 months.
Using the smoothed and 2-month-lagged data, I have made the scatterplots shown in the graph above.
The better-matched data from September 1999 to September 2011 (blue) has a satisfactory R-squared of 0.498, nearly 20 times greater than that of the raw data. The very poorly-matched data from October 2011 to November 2018 (red) has an R-squared value of 0.040, no better than the raw data.

Patterns in the sequence of rainfall and ENSO values

In the above graph, I have joined the consecutive smoothed data points to make a connected scatterplot. Because little noise remains, clear patterns appear.

Matched rainfall and ENSO

The pattern up to September 2011 (blue) is mainly a series of ellipses, some clockwise and some anti-clockwise. They are almost parallel to the regression line:

y = -0.047x-0.246

The blue point furthest to the top left is that for September 2002, a time of extreme drought and El Niño.
The blue point furthest to the bottom right is that for December 2010, a time of very high rainfall and La Niña.

Discordant rainfall and ENSO

The pattern from October 2011 (red) swings about wildly and does not repeat. The regression (with a trivial coefficient of determination) is nearly horizontal. Near its ends are the extreme drought of June 2018 and the deluge of January 2012, both at times when ENSO was near neutral. At the top of the graph is the Super El Niño of November 2015, when Manilla rainfall was normal.


Scatterplots, connected scatterplots and regressions confirm that a strong relation between rainfall at Manilla and ENSO failed in 2011 as the IPO was rising from a negative toward a positive regimen.

21-C Rain-ENSO-IPO: Line graphs

From 1999, rainfall at Manilla NSW matched ENSO only up to 2011, before the IPO became positive.

Manilla rain, ENSO, IPO

This graphical log compares the rainfall at Manilla NSW with the El Niño-Southern Oscillation (ENSO) and the Inter-decadal Pacific Oscillation (IPO) through the 21st century to date. Values shown are anomalies, smoothed. (See Notes below on “Data”, “Smoothing”, and “Lagged Rainfall”.)

Rainfall (black) uses the left axis scale; the ENSO (magenta) and the IPO (green) use the inverted right axis scale.

[21st century temperature and rainfall at Manilla are compared as smoothed data in the post “21-C Climate: Mackellar cycles”.]

Matches between rainfall and ENSO

There is an excellent match between the rainfall and ENSO values in the left part of the graph.
I improved the visual match by various means:
1. The ENSO scale (magenta) is inverted, because positive values of the ENSO anomaly relate to negative values of rainfall anomaly here.
2. The scales are harmonised: the zero values are aligned, and 20 mm of monthly rainfall anomaly is scaled to (minus) one degree of ENSO anomaly.
3. Smoothing is applied to suppress cycles shorter than 12 months.
4. Rainfall anomaly values are lagged by two months. (See the Note below.)
As lagged, most peaks and troughs of rainfall coincide with troughs and peaks of ENSO, and their sizes (as scaled) are often similar.

Failure to match rainfall and ENSO

In the right part of the graph, the match between rainfall and ENSO fails. There are extreme mismatches: the Super-El Niño of 2014-16 had no effect on local rainfall, the rainfall deluge of 2011-12 came with a mild and declining La Niña, and the extreme drought of 2018 came while ENSO was neutral.
By visual inspection, I judge that a close relation of rainfall to ENSO, which had applied for the twelve years up to September 2011, then failed for the following seven years.

Influence of the IPO

The inter-decadal Pacific Oscillation (IPO) affects the relation between ENSO and Australian weather. (See note below “Effect of the IPO”.)

Power et al.(1999) show that Australian seasonal weather and its prediction align with ENSO only when the IPO is negative. It follows that a good match between ENSO and Manilla rainfall was expected while the IPO (green) was negative from 1999 to 2013, and was not expected from 2014 to 2017. The trend of the IPO through 2016-17 makes it likely that the IPO continued positive through 2018, as the mismatch between rainfall and ENSO persisted.
Power et al. note that the relation is not sensitive to the width of a neutral zone chosen to separate the positive and negative regimens of the IPO. In this particular case, the rainfall/ENSO match failed as the IPO rose through minus one degrees. However, the rainfall/ENSO match began in 1999, much earlier than the time when the IPO fell through minus one degrees.

Scatter plots

In a following post I show scatter plots and regressions for the periods of match and mismatch on this graphical log.




Continue reading