Graphs like this show how the trends of temperature differ between the coldest days (or nights) of the year, the hottest ones, and all those ranked in between.
This first post on this topic is a “sampler” of Manilla data that I will present. It compares my first 9-year period March 1999 to February 2008 with the 9-year period September 2003 to August 2012, four and a half years later.
All the days (or nights) of the year are arranged from the coldest on the left to the hottest on the right. Columns show by how much the day or night of that rank has trended warmer or cooler during the nine years. (See also Notes below.)
In the earlier period (blue), most winter days and a few mid-summer days cooled at 0.1 to 0.2 degrees per year. Days in spring and autumn, and cooler days in summer warmed at less than 0.1 degrees per year.
In the later period (red), all days of the year cooled, but there was a gradient from no cooling in midwinter to extremely rapid cooling (more than 0.3 degrees per year) in midsummer.
In the earlier period (blue), nights in the warmer half of the year, and in midwinter warmed at about 0.1 degrees per year. There was no warming either in midsummer or in the warmer part of winter.
In the later period (red), it was now in the cooler half of the year that nights warmed at about 0.1 degrees per year. Nights in the warmer part of summer cooled more and more rapidly as they approached midsummer, where the cooling rate was 0.25 degrees per year.
[The 50-year average warming of this part of australia is 0.015 degrees per year. That is, less than two tick-marks on the y-axis.]
This graph and its commentary appeared as a post in “weatherzone” forums on 25/10/12:
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More frequent hot days do not come in a three year cycle, but in a 1.5 year cycle related to ENSO.
The Hot Day data set
The graph of number of hot days per year
The graph on the left is one I posted earlier. The height of each data point represents the number of hot days in a year, plotted near January. The pattern of points led me to join them by a smooth curve. This curve swings up and down rather regularly, with five peaks and five dips in the fifteen years. That is, more frequent hot days seem to come in a three-year cycle.
Is this cycle “real”? Should we look for a cause? Will the cycle continue?
Probably not! The points of measurement are one year apart. Cycles that are only three years long may be “aliases” of different and shorter undetectable cycles. (See Note below on Nyquist frequency.)
More detailed hot day data
Other graphs already shown include further data: the number of hot days in each month, and the 13-year average number of hot days in each calendar month. From these I have calculated a relative frequency. That is, the ratio of the actual number to the average number for that month.
Only the months of November, December, January and February have enough hot days to calculate a relative frequency, but these can show changes within the hotter months of each year.
The daily maximum temperature data set
A graph that I posted in “El Niño and my climate” shows a curve of smoothed monthly means of daily maximum temperature anomalies. The yearly cycle of summer-to winter temperature has been removed. I have also applied a smoothing function, which makes the monthly points of measurement effectively two or three months apart. As a result, cycles longer than about six months can be detected.
There are about 10 peaks and 10 dips in the 15.5 year curve. They define a cycle of about 1.5 years wavelength. That cycle is so much longer than the minimum-detectable six month cycle that “aliasing” is not likely.
The reality of this temperature curve is supported by its close similarity to the recognised curve of the El Niño – Southern Oscillation (ENSO), as read from NINO3.4 Pacific Ocean sea surface temperature anomalies.
A combined graph of hot day and temperature data
The graph at the top of the page presents the monthly smoothed maximum temperature anomaly again, using the scale at the left. To this I have added data on the number and frequency of hot days.
The annual number of hot days is shown in blue, in blue boxes. The boxes are placed higher or lower according to the number, but the height is adjusted to match other data better.
A “Hot Day Index” is shown by blue diamonds. This index is based on the relative frequency of hot days in each month that has data. I have re-scaled the values to improve the match. (See Note on Re-scaling below.)
Matching hot days with temperature
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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.
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This post is the twelfth in a set for the 12 calendar months that began with March. Graphs are sixteen-year logs of the monthly mean anomaly values of nine climate variables for Manilla, NSW, with fitted trend lines. I have explained the method in notes at the foot of the page.
Raw anomaly values for February
Extreme values of February anomalies were as follows:
Daily Maximum Temperature Anomalies (3) -4.2 deg: February 2008; -3.3 deg: February 2012; -3.3 deg: February 2013;
Daily Mean Temperature Anomalies (1) -3.3 deg: February 2008;
Rainfall Anomalies (1) +120 mm: February 2012;
Dew Point Anomalies (2) -4.6 deg: February 2014; -4.6 deg: February 2015.
Trend lines for February
All heat indicator quartic trends began slightly low and ended slightly low. They had a low peak about 2004, and a trough later. The trough was deepest and earliest for daily maximum temperature (2011), followed by daily mean temperature in 2012, daily minimum temperature in 2014, and subsoil temperature in 2015 or later.
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This post is the eleventh in a set for the 12 calendar months that began with March. Graphs are sixteen-year logs of the monthly mean anomaly values of nine climate variables for Manilla, NSW, with fitted trend lines. I have explained the method in notes at the foot of the page.
Raw anomaly values for January
Extreme values of January anomalies were as follows:
Daily Maximum Temperature Anomalies (1) -3.7 deg: January 2012;
Rainfall Anomalies (5) -70 mm: January 2002; -75 mm: January 2003; +80 mm: January 2004; +94 mm: January 2006; -85 mm: January 2014;
Dew Point Anomalies (2) +3.1 deg: January 2006; -7.4 deg: January 2014.
Trend lines for January
All heat indicator quartic trends began low and ended slightly high, and had a low peak in 2003, -05, or -06, and a shallow trough about 2012.
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