El Niño and My Climate

ENSO and Manilla NSW temperature anomalies over sixteen years

Temperature

The first graph shows that the temperature at Manilla NSW agreed very closely with El Niño and La Niña temperatures for a good part of the last sixteen years.
The El Nino – Southern Oscillation (ENSO) is shown by NINO3.4 monthly anomaly values, and temperature at Manilla, NSW is smoothed monthly mean daily maximum temperature anomalies. (See the Note below.)
Values of Manilla temperatures agree with those of ENSO through the major temperature peaks and troughs in the spring seasons of 2002, 2006, 2007, 2009, and 2010. In the two highest peaks of 2002 and 2009 and the deep trough of 2010, Manilla temperature extremes were more than a month ahead of ENSO temperature extremes.
Since mid-2011, the two curves do not agree well:
* A La Nina in summer 2011-12 that was very weak produced the deepest of all troughs in Manilla temperature.
* An El Nino in winter 2012 resulted in heat at Manilla, but not until four months later.
* In spring 2013, when there was no El Nino at all, Manilla had a heat wave just like those with the El Nino’s of 2002 and 2009, .
The record for ENSO since January 2013 is unlike that earlier this century: it flutters rather than cycles.
To show slower changes, I have drawn cubic trend lines for both of the variables. These also agree closely, with ENSO going from a maximum (2004) to a minimum (2011) seven years later. Manilla temperature trends remained ahead of ENSO temperature trends by one or two years.

Rainfall

ENSO and Manilla NSW rainfall anomalies over sixteen years.

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Log of the Southern Oscillation Index with climate shifts

SOI plot with climate shifts

This graph relates to a graph of the cumulative values of the Southern Oscillation Index, posted earlier and copied below.

SOI CUSUM plotThe graph above is in a more familiar form . It may help to explain what the earlier graph means. That is, that the SOI was dominated by positive values (towards La Niña) for about fifty-nine years before 1976, and was dominated by negative values (towards El Niño) for twenty-four years after that date. From 2000 the trend seems to be upward, showing La Niña dominance again. Broadly, these were straight-line CUSUM  relationships throughout each of the periods, as shown by the coloured trend lines. Slopes on a CUSUM plot represent offsets of the mean monthly value: the mean SOI in the earlier period was +1.4 units, and that in the second period was -3.5 units. Since 2000, the mean monthly value is around +1.0 units. Continue reading

17 Years of “Droughts and Flooding Rains” at Manilla

Manilla 17-year smoothed rainfall anomaly record

Times when Dorothea Mackellar’s “droughts and flooding rains”* affected Manilla in the years from 1997 are shown by the wavy line on this graph. The climate swings in and out of times of high and low rainfall.

Peaks or troughs were often a year or two apart, but most of them were not very far from the normal rainfall value. Only two of the troughs were so far below normal that they were severe droughts: August 2002, and December 2013 (or maybe later). Milder droughts came in October 2006 and September 2009.
The rainfall in these 17 years was not below the long-term average, but slightly above it. As well as droughts there were two peaks of extremely high rainfall: in July 1998 (when the new Split-Rock reservoir suddenly filled) and in November 2011. These “deluges” had rainfall that was further from normal than the low rainfall in the droughts. Other rainfall peaks came in November 2005, October 2008, and October 2010.
In total, there were nine peaks and troughs with rainfall outside the normal range. Six of them came in the spring months of September, October or November.
Peaks and troughs in rainfall at Manilla quite often come near times of La Niña and El Niño. These are events in the record of Pacific Ocean temperatures called ENSO (El Niño – Southern Oscillation). The ENSO record for the last 17 years is shown in the second graph.

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Predict weather from ENSO?

(Someone asked me to set down my thoughts about this.)

“Droughts and flooding rains” *

The climates of places in Australia cycle from hot, arid and dry, to cold, humid and wet every couple of years. (Dorothea Mackellar said she loved a sunburnt country “of droughts and flooding rains”*) This is a kind of quasi-biennial oscillation (QBO).  For more about the QBO, see this post, and the links in it. The cycles get weaker and stronger, more droughty or more rainy, and sometimes take about one year, sometimes three or more.

The climate of the Pacific Ocean has similar cycles, called the Southern Oscillation, discovered by Gilbert Walker a century ago. The pressure difference between Darwin and Tahiti oscillates in a way that reflects other widespread changes in climate. This is now called the El Niño – Southern Oscillation (ENSO) and it is monitored by sea-surface temperature around Nauru in the Pacific Ocean, called NINO3.4. Now that we have up-to-date data on NINO3.4, the public has been led to believe that the data can be used to forecast Australian weather. It really can’t.

Problem No.1: Weather varies from place to place.

Every district in Australia has different weather, so one size does not fit all. Wasyl Drosdowsky made a map defining the regions that have consistent relationships to ENSO and other indices, but nobody has taken up the idea. (I would if I was boss of the Bureau of Meteorology!) Drosdowsky’s regions are rather similar to the States, but Victoria and the southern half of South Australia form a single region.

Problem No.2: Forecast is too late.

The ENSO cycle does not predict a cycle in any part of Australia because it happens at about the same time, and it takes a month or more to collate the data. Weather prediction from ENSO is always late. Consequently, there is a business to predict ENSO some months ahead. These predictions are very unreliable. Then the predictions of ENSO values are used to predict Australian weather, with vague statements of which regions will be affected.

To make matters worse, my Manilla data from 1999 shows that my weather happens in advance of the ENSO changes. I compared the ENSO log from 1999 to 2011 with smoothed daily maximum temperature anomaly, smoothed monthly rainfall anomaly, and smoothed early morning dew point anomaly. If droughts and deluges happen before peaks and troughs of ENSO at other places in Australia, this makes prediction from ENSO even less likely to work.

[Note added 14/07/2015. Updated graphs comparing the ENSO log from 1999 to 2014 with smoothed daily maximum temperature anomaly and smoothed monthly rainfall anomaly at Manilla are in this post. Manilla’s climate has not related very well to ENSO since mid-2011.]


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


Data are cheap; information is expensive!


Originally posted on 12/5/2013 to a thread “ENSO Discussion 2013” on a “weatherzone forum.

3-year trends to August 2013

Parametric plots of smoothed climate variables at Manilla
“Still warm and dry”Trends to August 2013.

The raw value of maximum temp anomaly for August was lower than for July. Other variables were typical of “drought”, except for minimum temp, which was normal.

The fully-smoothed data point for February 2013 completes a summer season that moved away from drought. By February, smoothed values of anomalies for rainfall, temperature range, and minimum temperature had returned to normal, but dew point was still very low, and cloudiness and subsoil temperature were high.

El Niño – Southern Oscillation (ENSO)

The first points on these graphs (September 2010) just catch the La Niña event of spring 2010, which was followed by another La Niña event in spring 2011. At Manilla, both events produced extremely low daily maximum temperature. The 2010 event produced extremes of cloudiness, humidity (high dew point), narrow daily temperature range, and low subsoil temperature. The 2011 event produced quite different results: extremely high rainfall and extremely cold nights.

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.