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

Southern Oscillation Index: CUSUM plot

SOI CUSUM plot

This graph is a log of cumulative values of the monthly Southern Oscillation Index for the last 139 years. (See Note added 25th August 2014 below.)

(See also Note Added 19 December 2015 regarding the mis-match between this SOI record and the climate record at Manilla.)

(See Note added 27/3/2016 below, for a prior construction of this graph.)

High values of the SOI (contrary to NINO3.4 values for the ENSO index) relate to deluges in Australia and low values relate to droughts.

This is the CUSUM technique, invented in 1954 by E.S.Page. Pay attention to the slopes on the graph.

I have identified major El Niño and La Niña events on the graph. La Niñas have extreme upward slopes and El Niños exteme downward slopes.
The main feature of the graph, which is obscure in graphs that do not use CUSUM, is that La Niñas dominated the 60-year period from 1917 to 1976, and El Niños dominated the 25-year period from 1976 to 2000. I have drawn linear trend lines to make this clear. The first trend line (La Niña dominant) begins at an SOI CUSUM value of -30 in May 1917 and ends at a value of +960 in February 1976, yielding a slope of +1.4 SOI units per month. The second trend line (El Niño dominant) ends at a value of -40 in December 1999, yielding a slope of -3.5 SOI units per month.
The tendency to El Niños in the second period was greater than the tendency to La Niñas in the first period by a factor of more than two.
Although the period since 2000 is very short, the trend seems to slope upward at about +1.0 SOI units per month.

These decadal changes in the short-term mean value of the SOI are graphed in a later post. That graph does not use the CUSUM concept, and the changes in the mean value are overwhelmed by month-to-month variation.


I posted discussion of an earlier version of this graph in “Weatherzone” Forums >> Weather >> Climate and Climate Change >> ENSO Discussion 2012 Post #1103736


Note added 25th August 2014

Another CUSUM SOI graph

By searching the net for “cusum soi” I find that a plot of the cumulative sum of values of the Southern Oscillation Index was published by Cordery and Yao in 1993: “Non stationarity of phenomena related to drought”.

Neither the data nor the approach of Cordery and Yao are the same as mine.

Data

Cordery and Yao used monthly normalised SOI anomaly data supplied by the Bureau of Meteorology, as I did. They mention that “Prior to 1933 there are 7 gaps in the SOI sequence resulting from a total of 102 months of data missing from the Papeete pressure record.” I have not found any note of this with the Bureau’s current data table.
Apart from an (unexplained) reduction in the scale of CUSUM values by a factor of 500, there are important differences in detail. During the time of La Niña dominance, I find that the major CUSUM peaks (La Niña turning to El Niño) in 1918, 1939, and 1976 lie almost in one line. Cordery and Yao’s plot has the 1939 peak relatively much higher: the second highest on the record after the 1976 peak, and almost as high.

Approach

Cordery and Yao used CUSUM to show that the SOI series was not stationary for a part of the time. I used it to identify persistent shifts in the SOI mean value.


Note added 19 December 2015

The influence of the Southern Oscillation index on the climate of Manilla, NSW is cryptic at best.
In particular, the inter-decadal changes shown on this graph are not expressed at all in the episodes of drought at this station. Extreme droughts were concentrated in the period from 1900 to 1950 as shown here.

I have discussed the mis-match with the SOI in another post.

In that post, I also pointed out:
“The record for this site provides no support for any relation at all between global temperature and drought.”


Note added 27 March 2016

Prior construction of this graph.
I constructed this CUSUM SOI graph in 2012 on my own initiative, without knowledge of a prior construction by David Archibald in 2010. His graph (yellow background colour) appears to have an identical trace. Without adding linear trend lines, Archibald identifies the same end points of the long period of La Nina dominance followed in 1976 by a period of El Nino dominance.
Archibald published his graph in a guest post in “Watt’s Up With That”:

My graph and Archibald’s can both by found in a search of images for “southern oscillation index”.


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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Manilla Dew Point leads ENSO by three months

Manilla dew point lags NINO3.4 sea surface temperature by 3 months.

(This material justifies a statement in the post “Predict weather from ENSO?”)

The graphs above are like those in two previous posts, but show how Manilla smoothed monthly dew point anomalies, like temperature anomalies and rainfall anomalies, relate to the El Niño-Southern Oscillation (ENSO).

High (El Niño) values of Sea Surface Temperature (NINO3.4) are shown here to relate to low humidity at Manilla, NSW. As humidity data, I estimate dew points daily at sunrise. Dew points, like Sea Surface Temperatures, are expressed in degrees celsius, but corresponding anomalies take the opposite sense. The first graph plots the Manilla dew point anomaly, given a  negative sign, and the NINO3.4 anomaly. To improve the match, I have lagged the Manilla dew points by three months. As an example, I have noted on the graph the match of Manilla’s November 2005 humidity peak with the La Nina ENSO peak of February 2006.

To the eye, the over-all match is better than in either the rainfall or the maximum temperature plots of earlier posts. The two curves here match very well from 2000 to 2007.

The second graph shows the discrepancy between the two curves. Dashed lines show limits of a good match at +/-0.5 degrees. The nature of each larger discrepancy is noted. (“Here” in text boxes means “at Manilla”.)
After 2007 there are large mis-matches between Manilla dew point and ENSO. Dew point fluctuations suddenly become less than might be expected from NINO3.4 values. It may be relevant that, as I posted elsewhere  in July 2010, skies suddenly became very much cloudier at Manilla after August 2007.

I have also tried plotting the following variables against NINO3.4:

Daily minimum temperature;
Daily temperature range;
Percent cloudy mornings;
Subsoil temperature.

None of them matches NINO3.4 well enough to display.

The three sets of graphs show “teleconnections” between Sea Surface Temperatures in the equatorial Pacific and climate variables at Manilla in inland NSW, Australia. Climatic peaks come earlier at Manilla than in the Pacific:

Peaks of daily maximum temperature come one month earlier;
peaks of rainfall come two months earlier;
peaks of Dew Point come three months earlier.

In a simple-minded way, it seems to me more likely that Australia’s climate drives the Southern Oscillation than the other way around. I know that this is speculation. (Sort of like Abraham Ortellius suggesting in 1587 that Africa and South America might have drifted apart.)

Notes
1. High frequency noise is reduced in the case of the Manilla monthly data by a Gaussian smoothing function of half-width six months.
2. On advice, I represent the El Nino – Southern Oscillation phenomenon (ENSO) by the NINO3.4 area anomalies from the OISSTv2 data set.
My enquiries about the best data to use are in this “weatherzone”  thread.
The ensemble of sea surface temperatures does not have much high-frequency noise. There is some, however, and I have used the same smoothing as used in the (formerly authoritative) Oceanic Nino Index (ONI), that is, a running mean of each three monthly values.


This was posted originally in a “weatherzone” forum, with the date 12 November 2011. It is posted here with the nominal date 29 November 2011.

 

Manilla rainfall extremes reflect NINO3.4 temperature

Manilla rainfall matches NINO3.4 sea surface temperature.

(This material justifies a statement in the post “Predict weather from ENSO?”)

The graphs above are like those in an earlier post, but show how Manilla monthly rainfall anomalies, rather than maximum temperature anomalies relate to the El Nino-Southern Oscillation (ENSO). Most people using ENSO  want to predict Australian regional rainfall.

In the second graph I have improved the match at peaks and troughs of smoothed Manilla monthly rainfall anomalies and NINO3.4 sea surface temperature anomaly data in two ways.
1. I converted the sea surface temperature anomaly (degrees C) into a model of resultant rainfall anomaly (mm) by multiplying by minus fifteen.
2. I added 3.7 mm of rainfall to the Manilla figures, and I lagged the data by two months.

To the eye, the over-all correspondence between actual and modelled rainfall is good, but not quite as good as in the temperature graphs. One form of mis-match is that two of the greatest rainfall deficits (“El Nino” Nov-06, Dec-09) are broader and shallower than in the model. (Perhaps an arithmetic measure of rainfall anomaly is not the best.)

The third graph shows how much Manilla rainfall, as adjusted, differs from the rainfall “predicted” by the NINO3.4 model. Dashed lines show limits of a good match at +/- 7.5 mm (corresponding to +/-0.5 degrees). The nature of each larger discrepancy is noted.

A good match demands lagging actual rainfall at Manilla by two months. That implies that peaks and troughs in Manilla rainfall anomalies happen two months before the matching anomalies of NINO3.4. I wonder if prediction is even practical if that is the case in other parts of Australia.

Notes
1. High frequency noise is reduced in the case of the Manilla monthly data by a Gaussian smoothing function of half-width six months.
2. On advice, I represent the El Nino – Southern Oscillation phenomenon (ENSO) by the NINO3.4 area anomalies from the OISSTv2 data set.
My enquiries about the best data to use are in this “weatherzone”  thread.
The ensemble of sea surface temperatures does not have much high-frequency noise. There is some, however, and I have used the same smoothing as used in the (formerly authoritative) Oceanic Nino Index (ONI), that is, a running mean of each three monthly values.


This was posted originally in a “weatherzone” forum, with the date 28 October 2011. It is posted here with the nominal date 16 November 2011.

(Note added: Updated to include 2013 here.)

 

Manilla temperature matches NINO3.4 temperature.

Manilla maximum air temperature matches NINO3.4 sea surface temperature.

[This material justifies a statement in the post “Predict weather from ENSO?”]

[Note added:
This post relating ENSO to Manilla temperature is matched by similar posts relating ENSO to Manilla rainfall and to Manilla humidity (dew point). Manilla climate peaks and troughs generally happen before the related ENSO peaks and troughs, not after them.]

Smoothed daily maximum temperature anomalies for 140 months at Manilla, NSW are compared with NINO3.4 region Sea Surface Temperature anomalies. They match very closely, especially at peaks and troughs of the Southern Oscillation. The first graph is a log of the data as described in the notes below.
The match can be improved, as in the second graph, by making two adjustments. The reference periods for the anomalies are not the same. In any case it is pure coincidence that the temperature values are so close. I have chosen to add 0.2 degrees to the Manilla figures. At several of the major peaks and troughs the Manilla temperature leads the Sea Surface temperature by one month. I have chosen to lag all the Manilla temperatures by one month.
The third graph quantifies the remaining discrepancies. For most of this short record, the adjusted, one-month lagged Manilla smoothed daily maximum temperatures agreed with ENSO3.4 Sea Surface Temperatures within a margin of 0.5 degrees. Periods when the discrepancy was greater are noted on the graph.
At first (Sep-99 to Nov-00: 15 months) Manilla temperatures were in phase with the Southern Oscillation but one degree warmer.
For a time (Dec-00 to Dec-01: 13 months) there was no agreement.
From Jan-02 to Jun-03 (18 months) temperatures agreed.
From Jul-03 to May-06 (35 months) there was again no agreement.
In the long period (59 months) from Jun-06 to the end of the record in Apr-11, temperatures agreed except for one interruption: Manilla temperature lagged by three months at the La Nina trough of Feb-08, causing a discrepancy of minus one degrees.
In the 140-month record, Manilla temperatures faithfully followed Sea Surface temperatures in 77 months (55%), and were in phase in another 15 months (11%). Times when there were large discrepancies were generally times when the Southern Oscillation was near-neutral.


Notes
1. High frequency noise is reduced in the case of the Manilla monthly data by a gaussian smoothing function of half-width six months.
2. On advice, I represent the El Nino – Southern Oscillation phenomenon (ENSO) by the NINO3.4 area anomalies from the OISSTv2 data set.
My enquiries about the best data to use are in this “weatherzone”  thread.
The ensemble of sea surface temperatures does not have much high-frequency noise. There is some, however, and I have used the same smoothing as used in the (formerly authoritative) Oceanic Nino Index (ONI), that is, a running mean of each three monthly values.


This was posted originally in a “weatherzone” forum, with the date 25 October 2011. It is posted here with the nominal date 28 October 2011, and made “sticky” on 27 May 2014.