Posts Tagged ‘El Nino’

The Wacky World of Weather Stations: No. 119- Woolshed (Qld)

September 29, 2019

Sunday 29/09/2019

Please refer back to my first post for site specifications and to No. 92- Logan City for 2018 specifications.

Station: Woolshed 33307

Opened: 1998

Daily Temperature data from: 1998

Data used to adjust Acorn sites at: Charters Towers, Townsville.

Location:   Co-ordinates  -19.4168 146.5362

Woolshed map

30km south-west of Townsville.

BOM site plan 2018:

Woolshed plan2018

 2019 Google satellite image:

Woolshed aerial

The station is less than 10 metres from the treeline and 20 metres from a shed.

This station is non-compliant, with temperatures reported at Latest Weather Observations and used to adjust data at Acorn sites.

FAIL

Percentage of all Australian sites not compliant: 16.44%.

That completes stations in Herbert and Lower Burdekin district.  With 6 out of 7 checkable sites not compliant (85.7%) this is the worst region so far.  More than 51% of Queensland stations don’t meet specifications.  Tomorrow we move to the North Tropical Coast and Tablelands district of FNQ- and stay tuned for worse sites to come.

Pacific Sea Level One Year On

November 9, 2016

I was reminded by Jennifer Marohasy of my post a year ago (Pacific Sea Levels- Warming, ENSO, or Wind?) in which I showed that “Sea level rise in Kiribati and the Marshalls has nothing to do with climate change and everything to do with the ENSO cycle, and winds in particular.”

I wonder how things are going after 12 months?

Back then I had a brief exchange with one of the commenters, MorinMoss, a Global Warming Enthusiast, part of which included the following:

Me:

So Morin, getting back to sea levels in the Pacific, what do you think sea level at Kiribati will be a year from now- higher, lower, or the same as now, and why? I reckon it will be lower- because of the ENSO cycle. The Pacific will be in neutral or La Nina phase by then, trades will be dominant, with less westerly wind bursts on the Equator.

 MorinMoss:

Hard to say – there’s so much warm water in the Pacific that I think it’s too early to say how the cycle will progress.
We could be looking at a double-dip El Nino or a strong neutral (or would that be weak neutral?) phase, not proceeding immediately to a La Nina.

http://www.nytimes.com/2015/11/03/science/global-warming-pacific-ocean-el-nino-blob.html

 Me:

Good-oh, we shall see!

So 12 months ago I predicted sea level at Kiribati would be lower because of the ENSO cycle.

Time for a reality check.

This was the position in my post last year:

k-msl-v-nino4

And this is the position now.

kiribati-msl-v-nino4

Kiribati sea level change still precedes NINO4 change, and sea level has fallen from the highest it had been in this record to about average.

Q.E.D.

Poles Apart

November 4, 2016

Satellite data from UAH (University of Alabama- Huntsville) are estimates of temperature in the Lower Troposphere, and thus a good indicator of whether greenhouse warming is occurring.  My next post about the length of The Pause in various regions will be ready in a few days’ time.  Meanwhile, I’ve been looking at the data in a different way.

In this post I will be examining how and when temperatures have changed in discrete regions of the globe, including over land and over oceans.  There are no startling revelations, but a different approach reinforces the need to understand climate variability in different regions.  The important regions of course are the Tropics and the Poles, and fortunately UAH data is available separately for just these three regions.

Firstly, Figure 1 shows the regions for which UAH has atmospheric data.

Fig. 1:  UAH Data Regions

regions

The Northern and Southern Extra-Tropics include the Polar regions, so there are three discrete regions which do not overlap: Tropics, North Polar, and South Polar.  It would be very helpful if Dr Spencer provided data for the Extra Tropical regions excluding the Polar Regions.

For this analysis I use CuSum, which is a simple test of data useful for detecting linearity or otherwise, and identifying sudden changes in trend, or step changes.  It can be used for any data at all- bank balance, car accidents, rainfall, GDP, or temperature.  It is simple to use:  find the mean of the entire data, calculate differences for every data point from this mean, then calculate the running sum (Cumulative Sum) of the differences.  If done correctly, the final figure will be zero.  Plot the CuSum usually by time and identify points of any sudden change in direction.  A generally straight or smoothly curving line indicates linearity, but points of sudden change mean a change in trend or a step change.  (Further, data series with identical start and end points, exactly the same number of data points, and anomalies from the same period- such as UAH- should produce directly comparable CuSums.)  These points, and ranges between them, are then checked in the original data. The usefulness of CuSums will become obvious as we go, especially as they are compared.

The next figures show CuSum plots for various regions.

Fig. 2:  UAH CuSums for all regions

cusums-all

Points to note:

The brown line at the top is the South Polar region.  The line wobbles about zero, indicating little relative change in temperature from the mean.  Contrast this with the North Polar region (the blue line at the bottom.)  The Polar regions are conspicuously different from the other regions and from each other.

The spaghetti lines clustered in the middle are CuSums for (in order from top to bottom): Southern Extra-Tropics; Southern Hemisphere; Tropics; Globe; Northern Hemisphere; Northern Extra-Tropics.

The red arrows point to wobbles coinciding with major ENSO events.  These changes in direction indicate trend changes or step changes in the original data.  There are other changepoints, notably 2002-2003.

The vertical red line joins changepoints in all the CuSums in mid-1991 following the eruption of Mt Pinatubo.

Fig. 3: UAH CuSums for the Tropics, South Polar, and North Polar regions

cusums-np-sp-tropics

Note there is little similarity between CuSums for the only regions with discrete data, and you have to look carefully to see North Polar CuSums changing some months after Tropics, but not always.

The next plots show the differing responses of Land and Ocean areas.

Fig. 4:   UAH CuSums for the Globe, Land and Ocean

cusums-land-ocean

Note that Land areas have greater relative temperature changes than the Oceans, and that the Global mean closely mirrors the Ocean CuSums (as the Globe is mostly Ocean).  The major turning point is in 1997-98.

Fig. 5:  UAH CuSums for the Tropics, Land and Ocean

cusums-tropics-land-ocean

Note once again the mean CuSums closely follow that of the Ocean as 20 degrees North to 20 degrees South is mostly water.  The changepoints are very distinct.

Fig. 6:  UAH CuSums for the North Polar region, Land and Ocean

cusums-np-land-ocean

Note that all CuSums are close, but after 1982 Ocean CuSum changes relatively more than Land- the blue line has switched to below the mean.  The main changepoints are 1991, 1993-94, 2002, 2009, and 2015.

Fig. 7:  UAH CuSums for the South Polar region, Land and Ocean

cusums-sp-land-ocean

Now that is interesting.  Note all three CuSums have similar changepoints, but Land varies more than Ocean and after 1992 Land is largely negative, Ocean is largely positive.  The Land CuSum range is about half of the North Polar equivalent.

Remember CuSums in Figure 4 showed Land temperatures must vary more than Ocean (though not in the North Polar region).  The next figures show plots of UAH original data (not CuSums).

Fig. 8:  UAH original data for the Globe, Land and Ocean

graphs-globe-land-ocean

I find a visual representation demonstrates greater relative variation in Land temperatures well.

Fig. 9:  UAH original data for the Tropics, Land and Ocean

graphs-tropics-land-ocean

Note much greater fluctuation with ENSO, and Land varying a little more that Ocean.

Fig. 10:  UAH original data for the North Polar region, Land and Ocean

graphs-np-land-ocean

Note the much greater variation, but Land is more often than not masked by Ocean.

Fig. 11:  UAH original data for the South Polar region, Land and Ocean

graphs-sp-land-ocean

Note the much greater range in Land data, with large non-linear multi-year swings- calculate a linear trend for Land at your peril.

Having found changepoints, we can now analyse periods between them.  One way is to calculate means, and step changes between periods.

Fig. 12:  UAH original data for the Tropics based on CuSum changepoints

steps-tropics

I deliberately ignored the 2001 changepoint- it made very little difference to means and appears to be a continuation of the series starting in 1997.  Note the step changes are very small, and the final step change is reliant on current data and will change.  While I have shown means and steps, the data are decidedly non-linear with sharp spikes and multi-year rises and falls.

Fig. 13:  UAH original data for the North Polar region based on CuSum changepoints

steps-np

Note the large step change in the mid-1990s occurs before the 1997-98 El Nino.  The range is much greater than the Tropics.

As the Land data for the South Polar region looks more interesting, I decided to use Land instead of the mean.

Fig. 14:  UAH original data for the South Polar region (Land data) based on CuSum changepoints

steps-sp-land

Up and down like a toilet seat!

Conclusions:

The data series are characterised by step changes and multi-year rises and falls.

The Polar regions are “poles apart” in their climate behaviours.  Explanations might include: different geography (an ocean almost surrounded by land but subject to warming and cooling currents vs a continent isolated from the rest of the world by a vast ocean); different snow and ice albedo responses; different cloud influences.

The Global mean combines data from regions with very different climatic behaviour.  Averaging hides what is really going on.  The Tropics are governed by ENSO events, and the Poles are completely different.

Please Dr Spencer can you provide separate data for 20-60 degrees North and South?

Comments and interpretations are most welcome.

How Significant Is This El Nino?

December 3, 2015

For months we have been told how this is a strong El Nino, similar to the “Super El Nino” of 1997-98. How does it really stack up?

As data for sea surface temperatures are not available before 1950, the Southern Oscillation Index (SOI) data from 1876 are the best for long term analysis. In this post I am using SOI data from the BOM archive.

The Bureau uses sustained (three month mean) SOI values of 7 or less as an indication of El Nino conditions. This plot shows three month mean SOI values from 1876:

Fig. 1: Three month mean SOI values from 1876

3m soi
It is plain that as of November 2015 the three month mean is still nowhere near as low as it has been in several past El Ninos (and 1997-98 was not the lowest either!)

The next graph compares the length of El Ninos.

Fig. 2:  El Nino length

EN length -7

Plainly 1941-42 was the one to beat, and El Nino conditions will need to persist for another 18 months to compare. Another four to six months is more likely, and of course there could be a double up of another El Nino next year (as happened in the 1990s).

I next calculate the relative strength of El Nino conditions, by summing the (inverted) SOI values of all months in El Nino i.e. that have a three month mean of -7 or less.

Fig. 3:  El Nino cumulative strength

EN strength -7

Unless we get another six months of values below -20 we won’t beat 1997-98 into fourth place.

Of course, we are only in the seventh month of this El Nino- how does it compare with this stage of previous El Ninos?

Fig. 4: Three month mean SOI value for seventh month of cycle

EN strength 7th mth -7

The November 2015 value is the black dot- in sixth place.

Compared with the strength of previous El Ninos, the seven month value of this one is also in sixth place:

Fig. 5:  Cumulative strength in seventh month of cycle

EN strength 7th mth integral -7

Another interesting method of comparison is to change the definition of “El Nino” to “El Nino or Neutral” i.e. periods between La Ninas.

Fig. 6:  Length of El Nino or Neutral conditions

EN length EN or neut

Note the two periods of nearly seven years without La Ninas in the 1980s and 1990s, separated by a 12 month La Nina- immediately followed by the 1997-98 event, and then another five year period. 2014-15 is not unusual.

The integral of SOI values, as a measure of the strength of El Nino:

Fig. 7:  Cumulative strength, El Nino or Neutral conditions

EN strength EN or neut

Currently this event is in 12th place, and if it runs strongly for another six months it could sneak into seventh place.

Compared with other events, at the 22nd  month this event ranks fourth.

Fig. 8:  Cumulative strength at 22nd month of cycle

EN strength 7th mth integral EN or neut

Conclusion:

The current El Nino event is not going to break any records, unless it continues for several years!

It is nowhere near the most intense, nor the longest, nor the strongest.

It cannot compare with the intensity of previous El Ninos, as measured by three month average values, such as in 1896, 1905, or 1983.

It cannot compare with the length of previous El Ninos, such as the 1941-42 event, or the series of years of El Nino and neutral conditions in the 1980s and 1990s.

Depending on the measure used, it is fourth or sixth strongest for this stage of the cycle. If it continues strongly, its final strength might reach seventh or perhaps even fourth place. But that is unlikely. According to the Bureau, this event will peak before the end of 2015, and finish by mid-Autumn.

Fig. 9:  Model outlooks for El Nino end

Despite the hopes of the global warming enthusiasts, this is just another moderately strong El Nino which may cause a spike in world temperatures in the first half of next year, but is nothing to get excited about.

Pause Update September 2015

September 11, 2015

UAH v6.0 data for August were released on Wednesday.  Here are updated graphs for various regions showing the furthest back one can go to show a zero or negative trend (less than +0.01C/ 100 years) in lower tropospheric temperatures.  The strongest El Nino since 1997-98 is affecting some regions more than others.

Globe:

global aug

Due to the strong El Nino, global temperatures are expected to continue to increase until May or June of 2016 (at least until February).  This will shorten the Pause.

Northern Hemisphere:

NH

Southern Hemisphere:

S hemis aug

Tropics (20N – 20S):

tropics aug

Tropical Oceans:

tropic oceans aug

The bulk of solar heating of the Earth occurs in the tropics, which is  mostly ocean, and ENSO events occur here.  Since October 1992, very much before the 1997-98 Super El Nino, there has been no warming at all.

North Polar:

N Pole aug

South Polar:

S Pole aug

Oops!  For the whole of the satellite record, there has been NO warming in the atmosphere above Antarctica.  Remember, one of the “fingerprints” of global warming due to the Enhanced Greenhouse Effect is greater warming towards the Poles.

USA 49 States:

USA aug

Australia:

aust aug

There has been no warming in the atmosphere above Australia for almost the whole lives of the current cohort of 1st Year Uni students. Just for comparison, the Australian ACORN-SAT surface data show a pause since February 2002- since they were in Preschool.

aust acorn

The Pause continues.

Extreme La Nina events – an alternative view

January 28, 2015

Yesterday the ABC hyped up their climate alarmism to another new level with their uncritical and unabashed reporting of a claim by the CSIRO that Extreme La Niña events … will almost double in frequency as the climate warms”.

“Lead author Dr Wenju Cai, chief scientist at Australia’s CSIRO Oceans and Atmosphere Flagship, says their work shows La Niña events will occur every 13 years compared with a past frequency of one every 23 years.”

This is the paper:

Increased frequency of extreme La Niña events under greenhouse warming, by Wenju Cai et al., published yesterday.

Time for a reality check.

The authors say they used climate data from 1900 to 2005, and 21 climate models to predict conditions for 2006-2099, and that an extreme La Nina is defined by Central Pacific sea surface temperature anomalies of more than 1.5C below normal.  They claim that an increase in severe El Ninos will lead to an increase in following extreme La Ninas.

In the paywalled article I suspect the Central Pacific region they use is actually the Nino 4 region.  In this analysis I use data from the Nino3.4 region, which is the overlap between Nino 3 and Nino 4, covering Latitudes 5 degrees South- 5 North and Longitudes 170 degrees West- 120 West.  This is the most common data region used.   I downloaded data from http://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/Nino34/ and calculated monthly anomalies from the 1961-1990 means.  There are data from 1870, however I chose to use data from 1876 to match Southern Oscillation Index (SOI) data.

Here are the results:

Fig.1: Nino 3.4 anomalies.  Note 1900 & 2005 limits, and +/- 1.5C thresholds.

nino34

By screening for events of +/- 1.5 or more, we remove the clutter and identify extreme events:

Fig.2: Nino 3.4 data exceeding +/- 1.5C

extreme enso events

The paper claims that the incidence of extreme La Ninas will increase from one per 23 years to one per 13 years.  While there are more extreme La Ninas in the last 45 years, I count seven La Ninas from 1900 to 1999, which is one per 14 years.  There were three very high El Nino peaks since 1970, but there are clusters of extreme El Ninos in the first and last thirds of the record.  So possibly the claim for increased La Nina frequency was for an increase in the frequency of abrupt swings from El Nino to La Nina.

Fig.3:  12 monthly change in Nino 3.4 anomalies. +/- 3C is the threshold for swings from extreme El Nino to extreme La Nina.

12m enso chg

Fig.4: Removing the clutter, change exceeding +/- 3C.

extreme enso change

There we have it.  The extreme changes since 1900 have all been in the last 45 years.  Is this due to Greenhouse warming or natural climate change? Could it have anything to do with the Interdecadal Pacific Oscillation? Or is it an artefact of my arbitrary choice of extreme threshold?

More importantly, does the Southern Oscillation Index (SOI) tell the same story?

SOI data are from the BOM website.

Fig.5:  12 month running mean of the SOI inverted.  Threshold is +/- 8.  Note the historical rises and falls.

 12m soi

Fig.6: Nino 3.4 and 12 month inverted SOI match fairly well, although SOI values lag by up to 2 years.

soi v nino34

Fig.7:  El Nino and La Nina conditions per SOI criteria (+/- 8).  An extreme ENSO event might be +/- 16, although I have not seen that mentioned anywhere.

12m soi tests

Again note the clusters of El Ninos, and the spread of La Ninas, in small groups with large gaps between.

Fig.8:  12 month SOI change exceeding +/- 16.  Horizontal lines indicate the threshold for an annual swing of +/- 24 units, which is associated with some dramatic weather events.

extreme  soi change

I left all of the changes >16, to show the historical spread.  Note there were three extreme La Nina (< -24) changes from 1876- 1916, and three from 1960- 2000, and four from 1973- 2014.  There is no unusual trend.

How does this correspond with the observed rainfall record, especially for South East Australia, which is predicted to receive more extremes of rain and drought due to greenhouse warming?

Fig. 9:  Number of months of severe deficiency.

SE Oz severe droughts

Fig. 10:  Number of very wet months.

SE Oz ext wets

Not very alarming.

Queensland is especially susceptible to ENSO events.

Fig. 11:  The match for Queensland wet years is better.

Qld ext wets

Fig. 12:  But not for droughts!

Qld ext dry

Where are the extreme El Ninos?  Call me underwhelmed.

Depending on the index used, the criteria used, and the length of the record used, you can say we’ve had an increase in extreme ENSO swings, or no noticeable change other than a long period (70 to 90 years?) cycle of more and less extreme changes.

My money’s on the latter, but Time will tell.

The Rhythm of Life has a Powerful Beat

January 30, 2014

Here’s a fresh look at global temperatures as calculated by the University of Alabama, Huntsville- the UAH dataset– from satellite measurements of the Temperature of the Lower Troposphere (TLT).

Warwick Hughes suggests that there has been a drift in the measurements since about 2005, such that calculated temperatures are too high, and we await a proposed correction.  However, we can live with that.

Here are plots of TLT for various regions of the globe.

Fig.1:  12 month running means of Global anomalies and Tropical anomalies (the region of the Earth between 20 degrees North and 20 South, which gets the majority of the solar radiation striking the Earth).Glob - Tropics

The two sets move in lock step, with a much larger variation in the Tropics than the world as a whole.

What causes these large variations?

Fig. 2: Global and Tropical anomalies with the SOI inverted, and scaled by a factor of 30.Glob - Tropics v SOI

SOI is the acronym for the Southern Oscillation Index, calculated from pressure differences between Tahiti and Darwin, and is a reasonably good indicator of El Nino or La Nina conditions.  The ENSO cycle (El Nino Southern Oscillation) originates in the tropical Pacific.  El Nino brings warmer temperatures to the world; La Nina is associated with cooler temperatures.  I have inverted the SOI to show this relationship, and scaled it down by 30 to fit on the graph.

Note how the 12 month mean of SOI precedes the temperature data.  Here’s a plot with the SOI advanced 5 months.

Fig.3:  SOI advancedGlob - Tropics v SOI adv'd

While the peaks (El Ninos) match very closely, I have marked periods following the major eruptions of El Chichon and Mt Pinatubo, which cooled temperatures for several years.  I also suggest that the atmospheric dust and cooler surfaces upset the ENSO cycle as traced by the SOI.  Note also that temperatures in the 2010-2011 La Nina appear higher than expected.

Fig.4: SOI advanced with Tropic and Australian land TLT.Australia

Note how Australian temperatures appear to fluctuate about as much as the Tropics (we’re one third north of 20S after all).  Australian temperatures are influenced by events in the Indian Ocean and Southern Ocean as well as the Pacific, so the match isn’t exact.

I will look at Australian data specifically in another post.

Finally, here’s a way to check on that other “finger print” of the enhanced greenhouse effect, as espoused by Dr Karl Braganza: land areas are expected to warm faster than oceans, supposedly showing that greenhouse gases, not ocean currents, drive global warming.

Fig. 5: Global Land and Ocean TLT.land v oceans

Well of course that proves it- land areas are indeed warming faster than oceans.

However, have a closer look at the timing of the switches between warming and cooling.  If well mixed greenhouse gases are warming both land and oceans, it would be expected that oceans, with higher specific heat and enormous thermal inertia, would take longer to warm.  The land response would be almost immediate.  Oceans would not be expected to warm before the land, and if anything might show a slight lag.

Fig.6: close up of the 1998 Super El Nino.land v oceans 1997-99

The oceans change phase about one month before the land.  They definitely do not lag behind.

And what causes these rapid changes?

Fig.7: Land, ocean, and the SOI advanced 5 months.land v oceans v soi

 

The world’s temperatures respond to the powerful beat of ENSO events- as well as large explosive volcanic