There are two primary indicators that can be used to
determine if the ENSO climate system is experiencing
an El Nino event.
a) The Southern Oscillation Index (SOI)
The first indicator is an atmospheric based metric
called the Southern Oscillation Index (SOI). The
Australian Bureau of Meteorology (BOM) defines the
SOI as being the standardised anomaly of the monthly
Mean Sea Level Pressure (MSLP) difference between
Tahiti and Darwin, such that :
SOI = 10 x (Pdiff - [Pdiff])
SD(Pdiff)
where
Pdiff = [Monthly Tahiti MSLP] - [Monthly Darwin MSLP]
[Pdiff] = the long-term average of Pdiff for the month.
SD(Pdiff) = the long-term standard deviation of Pdiff for
the month. [The climatology period used is
from 1933 to 1992]
and the symbols [ and ] are used to indicate that an
average is being taken of the parameter in question.
Using the Australian BOM's convention, SOI values
range from -35 to + 35. El Nino conditions are considered
to be present if the SOI drops below -8 for a sustained
period of time.
Ref: http://www.bom.gov.au/climate/glossary/soi.shtml
b) The Nino 3.4 SST Index or Oceanic Nino Index (ONI)
The second indicator is a sea-surface temperature
(SST) based metric called the Nino 3.4 SST Index or
the Oceanic Nino Index. It relies upon SST anomalies
in a region of the equatorial Pacific ocean between
120 and 170 degree W longitude and -5 to +5 degree
latitude.
El Nino conditions are considered to be present if the
three month running mean of SST anomalies in the Nino
3.4 region have five consecutive months that exceed 0.5
C. [Note: The climatology period for this particular
index are based upon NOAA Extended Reconstruction
Sea Surface Temperatures ( i.e. ERSST.v3 SSTs) that
use the base period 1971 - 2000].
Ref: http://www.ncdc.noaa.gov/teleconnections/enso/indicators/sst.php
c) The Bivariate EnSo Time Series (or BEST) Index
The El Nino is part of a coupled oceanic and atmospheric
phenomenon known as the ENSO. The Nino 3.4 SST
anomaly index is normally used to determine if El Nino
conditions exist in the eastern and central equatorial
Pacific Ocean. However, its sole use neglects atmospheric
processes. A better index would be one that effectively
combines the information from the Nino 3.4 SST anomaly
index with that from the SOI index, which does include
atmospheric processes that are involved in establishment
and maintenance of El Nino events.
Smith and Sardeshmukh [2000] have created a
Bivariate EnSo Time Series (BEST) index that effectively
combines the atmospheric component of the ENSO (i.e.
the SOI index) with the oceanic component (i.e Nino 3.4 SST
anomaly index).
Ref: Smith, C.A. and P. Sardeshmukh, 2000,
The Effect of ENSO on the Intraseasonal
Variance of Surface Temperature in Winter.,
International J. of Climatology, 20 1543-1557.
Ref: http://www.esrl.noaa.gov/psd/people/cathy.smith/best/
[N.B. The SOI index is taken from Phil Jones at the Climate
Research Unit (CRU) of East Anglia which is defined slightly
differently to that used by the Australian BOM. In addition,
the SST data used is the Met Office Hadley Centre's sea
ice and SST data set known as HadISST1.]
Ref: http://www.cru.uea.ac.uk/cru/data/pci.htm
The first step in the creation of BEST index is to remove
the monthly mean climatology for the period 1898 - 2000
from both indices. After that the values are standardized
by the month so that each month has a mean of 0 and a
standard deviation of 1.0 for all years during the output
time period. Next, the resulting SST and SOI values are
averaged for each month of the time series. Finally, either
a 3 or 5 month running mean is applied to both time series.
Ref: http://www.esrl.noaa.gov/psd/people/cathy.smith/best/details.html
Smith and Sardeshmukh (2000) present a table that lists all of the
months where the SST index exceeds 1.28 standard deviations
above the mean for that given month AND the SOI index exceeds
1.28 standard deviations below the mean for that given month as
well. These months are determined from data that cover the years
from 1871 to 2014 and which have had a five month running mean
applied.
In addition, Smith and Sardeshmukh (2000) present a slightly
less stringent list of El Nino months (covering the period from 1
871 to 2014) that uses 0.96 standard deviation cut-off rather than
1.28.
Ref: http://www.esrl.noaa.gov/psd/people/cathy.smith/best/
Ref: http://www.esrl.noaa.gov/psd/people/cathy.smith/best/table33.txt
There is a possibility that some of the weaker El Nino
events could be triggered by stochastic processes within the
ENSO climate system. Under these circumstances, it would
be prudent to:
a) use Smith and Sardeshmukh's less stringent criteria to
ensure that we have as many El Nino events as possible,
to ensure that we have adequate statistics for our analysis.
b) limit our sample to the those El Nino events that last
for more than three months to weed out the marginal
or weak events that could be triggered by these
stochastic processes.
Hence, the El Nino events sample that is adopted for
this series of posts uses the less stringent selection criteria
and only includes those El Nino events that last longer
than three months.
d) The El Nino Events Sample
Table 1 shows all of the El Nino Events that meet
our selection criteria that occurred between 1871
and 2014.
Table 1
_________________________Mean___Mean
_______Starting__Decimal__Delta___Apse
_Year___Month___Year__Distance__Angle
Supplement to Table 1
N.B. The information in columns four and five
will be used in blog post IV.
Columns one and two show the starting
year and month of each strong El Nino event.
Column three shows the decimal year of the start
of the El Nino event.
Column four shows the mean difference in lunar
distance (in kilometres) between consecutive
crossings of the Earth's equator averaged over
a period of six months centred on the beginning
of the starting month of the El Nino event.
Ref: Walker J.: Lunar Perigee and Apogee Calculator,
1997, available on-line at:
http://www.fourmilab.ch/earthview/pacalc.html,
Column five shows the mean angle of longitude
of the lunar line-of-apse averaged over a period
of six months centred on the beginning of the
starting month of the El Nino event.
Ref: Ray, R.D. and Cartwright, D.E.: Times of
peak astronomical tides, Geophys. J. Int., 168,
999–1004, 2007.
The El Nino events that have an (*) in column 2
are those events that just fall short of our selection
criterion because they only last for three months.
They have been included in Table 1 for completeness.
e) Extending the sample to events prior to 1871
A data set that extends the SOI index back to 1866
is available for download from the NOAA site at:
http://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/SOI/
This time series shows that there was a strong El Nino
event that started around January 1868. Data for this
event has been added as a supplement to Table 1.
f) El Nino Event Near the Epoch Boundaries
The strong El Nino event for 1905 appears to
be a continuation of the ~ 9 year spacing pattern
for El Nino events that is evident in epoch 2 ( i.e.
1896 to 1905), even though it crosses over into
very beginning of epoch 3 (which starts on the
18th of April 1901).
In like manner, the moderately strong El Nino
event for 1993 occurs just at the end of epoch
5, even though it appears to be an extension of
the ~ 9 year spacing pattern that is evident in
epoch 6 (1993 to 2002).
As a consequence, both of these boundary El Nino
events have been move into the adjacent tidal epochs
where they better match the commonly observed
9 (and sometimes 4.5) year spacing.
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