3-year trends to June 2017

Parametric plots of smoothed climate variables at Manilla
A 13-month “Mackellar cycle”

3-year climate trends to June 2017

June raw anomaly data (orange)

In June 2017 the daily maximum temperature was normal. Moisture variables were low on the graphs, showing rather high moisture. Both daily minimum temperature and subsoil temperature were high. For each variable, the raw value was close to the smoothed value of June 2016, just twelve months earlier.

 Fully smoothed data (red)

The latest available fully-smoothed data point, December 2016, showed warming and drying. Only the dew point anomaly had just passed a “dry” peak. Smoothed subsoil temperature anomaly, which had reached a record low value in November, began to rise, like both of the air temperature anomalies.

The Mackellar cycle

Manilla’s climate variables often move in the cycle of “droughts and flooding rains” from Dorothea Mackellar’s poem “My Country”.*

In that cycle, temperature and moisture move together: hot with dry, cold with wet. On my graphs, hot is to the right. The top four graphs have dry at the top. (I count daily temperature range anomaly as a moisture indicator: high values show dryness.)

The “Mackellar cycle” drives the anomaly values up and down the blue trend lines that skew from cold-and-wet at the lower left to hot-and-dry at the upper right. The path is seldom straight, as any lead or lag of moisture will curve it into an ellipse.

Ellipses on the graphs show the cycle has been strong for two years since the winter of 2015. Its period has been very short: only twelve or thirteen months. Daily maximum air temperature anomaly reached a peak in February of both 2016 and 2017 (hot in late summer-autumn), and reached a trough in August-September 2016 (cold in late winter-spring).

On the top four graphs the cycle advances around an ellipse clockwise. A peak of dryness (up) comes several months before the related peak of daily maximum temperature anomaly (right). Similarly, wetness (down) comes before low temperature (left). I have posted already about the way this cycle skewed the seasons in 2016.

The two graphs at the bottom contain only temperatures. Circles on those graphs show that both the daily minimum temperature anomaly and the subsoil temperature anomaly have been lagging the daily maximum temperature anomaly by several months during these last two years (and not before).


In a post to a “weatherzone” forum, I have annotated (in green) the graph for Dew Point Anomaly versus Daily Max Temp Anomaly. It is the one that shows most clearly the elliptical trace caused by the cycles. That forum thread: “Climate Driver Discussion 2017 (Enso, IOD, PDO, SAM etc.)” has almost no reports of climate cycles observed in Australia.


Note:

Fully smoothed data – Gaussian smoothing with half-width 6 months – are plotted in red, partly smoothed data uncoloured, and raw data for the last data point in orange. January data points are marked by squares.
Blue diamonds and the dashed blue rectangle show the extreme values in the fully smoothed data record since September 1999.

Normal values are based on averages for the decade from March 1999.* They appear on these graphs as a turquoise (turquoise) circle at the origin (0,0). A range of anomalies called “normal” is shown by a dashed rectangle in aqua (aqua). For values in degrees, the assigned normal range is +/-0.7°; for cloudiness, +/-7%; for monthly rainfall, +/-14 mm.

 * Normal values for rainfall are based on averages for the 125 years beginning 1883.


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

House June warmth profiles: II

Part II: Daily temperature cycles, west wing

Graph of temperatures in the house west wing in mid-winter

I report here on the thermal performance of a solar-passive house in Manilla, NSW, during five days at the winter solstice of 2016. The house is described briefly in a Note below.
This post is about the 2-storied west wing of the house, which is less successful. The more successful east wing will be considered later. An earlier post showed that average temperatures decreased with height. Go to Part I.

This five-day period was a testing time for the unheated solar-passive house. Days were at their shortest, some nights were frosty, and overcast persisted for two days. It fell within a cold, wet, and cloudy winter.

Observations

View of the house from the street

House From the Street

In this wing, seen on the right in the photo, five thermometer stations define a profile in height. They are:

Subsoil in the garden near the house;
On the downstairs floor slab;
On the downstairs wall;
On the upstairs wall;
OUTDOORS, on the wall of the upstairs veranda.

During the five days I made 84 observations at each station at intervals as shown. They define the daily temperature cycles. I observed the amount of cloud in Octas (eighths of the sky) at the same intervals.

Table of west wing temperaturesThis table lists for each thermometer station the five-day values of the average, maximum, and minimum temperatures, and the temperature range.

The daily cycles

Subsoil

Continue reading

Annual Rainfall Extremes at Manilla NSW: I

I. Better graphs of Manilla’s annual rainfall and its scatter

Manilla 21-year rainfall medians

Background

The first two graphs  are new versions of graphs in an earlier post, published also as an article in “The Manilla Express” (28/2/17) and in the “North West Magazine” (20/3/17).

In that article, I said:
“This Manilla rainfall record is one counter-example to the snow-balling catalogue of reported extreme climatic events.”
My claim was not well supported. While the two graphs showed that recent annual rainfalls have been normal, with little scatter, they do not show whether there were any extreme events.

However, Manilla’s annual rainfall record can be analysed to show extreme events. This post considers the Total Range within a 21-year sampling window as a measure of extremes. Using that measure, extremes were at their highest in the 19th century, before anthropogenic global warming began.

A following post discusses kurtosis as another measure, with a different result.

The two improved graphs

The re-drawn graphs of historical records in this post use a 21-year sampling window, as before. They now have an improved smoothing procedure: a 9-point Gaussian curve. (The weights are stated below.)

1. Yearly Rainfall Totals

The first graph (above) represents the normal rainfall as it changes. The earlier version showed the arithmetic mean. The new version uses the median value (the middle, or 50th percentile value) instead.
The new version is less “jumpy” due to better smoothing. The median varies much more than the mean does. All the same, most features of the shape are unchanged: very low annual rainfall from 1915 to 1950; very high rainfall from 1955 to 1982; normal rainfall since 1983. There are some shape changes: rainfall before 1900 does not plot so high; from 1911 to 1913 there is a respite from drought; the highest rainfall by far now appears from 1970 to 1980.

As before, one can say:
“Present rainfall will seem low to those who remember the 1970’s, but the 1970’s were wet times and now is normal. Few alive now will remember that Manilla’s rainfall really was much lower in the 1930’s.”

In addition, this new version makes the pattern of growth and sudden collapse obvious. Collapses amounting to 100 mm came within a few years after both 1900 and 1978. Growth in the 58 years from 1920 to 1978 came at the phenomenal and unsustainable rate of 33 mm per decade. By the 1970’s, elderly residents of Manilla would have seen rainfall increase decade by decade throughout their lives.
(I noted this pattern of growth and collapse in an earlier post about Manilla’s summer rainfall.)

Manilla 21-year rainfall Inter-quartile Range

2. Yearly Near-Mean Rainfall Scatters

The plot on this second graph is changed only by better smoothing. However, the titles are changed. I realised that the Inter-quartile Range is not a good general indicator of spread or, in this case, of reliability of rainfall (as I had assumed). Inter-quartile Range measures the scatter of values that are close the middle: just the middle 50%. My new title refers to “near-mean” scatter. Any values that could be called “extreme” fall very far beyond the Inter-quartile Range.

Two more measures of scatter

An alternative measure of scatter in data is the Standard Deviation. In normally distributed data, the Standard Deviation extends 34% each side of the median (and mean). The “Standard Deviation Range” then extends from the 16th percentile to the 84th percentile. It includes a much larger proportion (68%) of a population than the Inter-quartile Range (50%) does. However, it also says nothing about extremes, which will lie far out in the residual 32% “tails” of the data.

The broadest measure of scatter is the Total Range from the lowest to the highest value. This measure does include any extreme values that exist in the data.
In the present case, each calculation uses a sample that includes only 21 points. The lowest data point is close to the 5th percentile and the highest data point is close to the 95th percentile of a similar continuous curve.

All three measures of scatter graphed

Manilla 21-year rainfall Total Range, Standard Deviation Range and Inter-quartile Range

Continue reading

House June warmth profiles: I

Graph of house temperatures versus height

Where is the warmth in a house?

People are building houses that should keep warm in winter with little heating.
Some parts of the house will stay warmer than other parts. Which parts? How warm?
Answers are not easily found. I hope this temperature record from a house with only personal heating may be useful. This was a time when the house was under extreme stress due to cold weather.

Over a five-day period in winter 2016, I read thermometers frequently at a number of stations around the house. I have selected those stations that form profiles from top to bottom of two wings of the house: the two-storied west wing, and the east wing that is one-storied with a clearstory.
To find how my house differs from yours, see the note below: “Key features of the house”.

Selected thermometer stations

In the West Wing (two-storied)

OUTDOORS, upstairs veranda (+4.7 metres);
Wall upstairs at head height (+4.2 metres);
Wall downstairs at head height (+1.5 metres);
Floor slab surface downstairs (0.0 metres);
Garden subsoil at -0.75 metres.

In the East Wing (single-storied)

Clearstory space at +3.5 metres;
Wall in the hallway at head height (+1.5 metres);
OUTDOORS, in a Gill Screen (+1.5 metres);
Floor slab surface in the en-suite (0.0 metres);
Solid “heat bank” beneath the floor slab (-0.75 metres).

Part I: Average temperature values

SUMMARY RESULT
In the ground under the floor slab the temperature would be just warm enough for winter comfort. Above the floor slab, the higher you go, the colder it gets.

Results

The graph above plots mean temperature against height above the floor slab. (The mean temperature is the time-average over the five days.)

Comparing east wing, west wing, and outdoors

The single-storied east wing was several degrees warmer at all heights than the two-storied west wing. The east wing has advantages: thermal mass, perimeter insulation in the footings, less shading, and a more compact shape.
Continue reading

Wet Autumn 2017

Sunset photo.

Manilla Sunset

Autumn this year had normal temperatures, in stark contrast to very high temperatures both in the summer and in the autumn of last year. The decline to winter was not smooth, however, but went by steps. For three weeks in each month there was no cooling then, after some rain, there was a sudden cooling through three, four, or five degrees.
Rain fell frequently except for two gaps of a fortnight each, the first coming in mid-April. The second ended with 32.8 mm of rain registered on May the 20th. There were 26 rain days, which is twice usual number, and more than in any autumn in the new century.

Graphical log for autumn 2017

There was plenty of moisture. Only the early morning dew point (8.1°) was low, by half a degree. The daily temperature range was a narrow 14.5°, and the cloudiness a high 41%.
The total rainfall of 192.8 mm was at the 80th percentile, far above the autumn average of 134 mm. There has not been a wetter autumn since 1990 (203 mm). A little earlier there was a cluster of wetter autumns: 1977 (307 mm), 1979 (203 mm), 1982 (238 mm), 1983 (314 mm: 4th wettest), and 1988 (231 mm). Autumn 1894 was the very wettest, with 388 mm.

Climate for autumn 2017


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. All other data, including subsoil at 750 mm, are from 3 Monash Street, Manilla.

Warm Wet May 2017

Photo of blossoms on a gum tree

Mugga Ironbark Blossoms

The weather was normal for the first half of the month, bringing a mild first frost on the 11th, close to the normal date for it. Then the weather became warmer and wetter. Rain totalling 32.8 mm was recorded on the 20th, while the minimum temperature of 14.0° that morning was 8.6° above normal. The weekly average temperature rose to 3.8° above normal, before falling below normal as the rain eased towards the end of the month. The last two mornings were frosty.
In all, there were five rain days (over 0.2 mm) when there are usually three.

Weather log for May 2017

Comparing May months

Like May last year, this month was about one degree warmer than normal, unlike May of 2007, which was half a degree warmer again. The dew point (4.7°) was a little low, the daily temperature range (15.3°) normal, the cloudiness (32%) and the rainfall rather high.
The total rainfall of 55.6 mm was at the 70th percentile, well above the May average of 41 mm. There are no shortages of rainfall for groups of months to this date.

Climate for May 2017


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. All other data, including subsoil at 750 mm, are from 3 Monash Street, Manilla.

3-year trends to May 2017

Parametric plots of smoothed climate variables at Manilla
“Record cold subsoil November 2016”3-year climate trends to May 2017

May raw anomaly data (orange)

While not far from normal, May 2017 was warm and humid (“Interglacial”), in contrast to April, which had been cool and arid (“Glacial”).The daily temperature range remained normal as both maximum and minimum temperature anomalies rose. Subsoil temperature rose above normal.

 Fully smoothed data (red)

The most recent fully-smoothed data point, for November 2016, completes data for the spring season. Following a winter that had been cool and moist, spring showed rapid warming and drying. The November dew point seems to have reached a minimum: one not nearly as low (arid) as in the previous two years.
The smoothed anomaly of daily minimum temperature, which had hit a record high value in May 2016, approached a minimum value that was near normal in October, and began to rise again.
Smoothed subsoil temperature anomaly reached a new record low value of -1.16° in November. It beat a record that was set in March 2008, a few months after the global temperature minimum of October 2007.


Note:

Fully smoothed data – Gaussian smoothing with half-width 6 months – are plotted in red, partly smoothed data uncoloured, and raw data for the last data point in orange. January data points are marked by squares.
Blue diamonds and the dashed blue rectangle show the extreme values in the fully smoothed data record since September 1999.

Normal values are based on averages for the decade from March 1999.* They appear on these graphs as a turquoise (turquoise) circle at the origin (0,0). A range of anomalies called “normal” is shown by a dashed rectangle in aqua (aqua). For values in degrees, the assigned normal range is +/-0.7°; for cloudiness, +/-7%; for monthly rainfall, +/-14 mm.

 * Normal values for rainfall are based on averages for the 125 years beginning 1883.