As I’m sure you’re
aware, in a few days time the United Nations Framework Convention on Climate
Change (UNFCCC) will meet for the twenty-first session of the Conference of
Parties (COP21). Over 190 nations will gather in Paris to discuss a collective
agreement on climate change, with the aim of staying within the 2oC
global warming target.
Despite a GlobeScan poll on behalf
of the BBC suggesting that public support for a global deal on
climate change has declined, I hope that the outcome will reignite general public
conversation and support. It’s important that everyone gets on board with this,
as the conference will not only address CO2 emissions, but also how
business is conducted in terms of production and farming. Collectively,
consumers can have a lot of power which needs to be utilised.
It’s likely there’s also going to be
something else quite momentous going on at the same time as the COP21 summit...
the peak of the 2015 El Niño event.
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Figure 1: Niño 3.4
SST Anomaly (oC) predictions from dynamical and statistical models
for Nov 2015.
Source: InternationalResearch Institute |
As can be seen, for all models, the
highest point lies in the Nov(15) – Dec(15) – Jan(16) period. The differences
between the model predictions are the result of two main factors. The first,
and most obviously, being the construction of the model. Models are not able to
fully capture an entire process, they are tools enabling us to analyse,
predict, and learn about a process, and hence there will always be a degree of uncertainty
within them. The second reason for differences is the actual uncertainty in the
forecast. Forecasts made between June and December generally have a better skill*
due to the reasoning that this is when El Niño events are active. As might also
be expected, skills usually decrease as lead time increases.
*A forecast “skill” is the level of
accuracy a model forecasts in comparison to a reference model.
The figures in Table 1 below give
average SST values for the different model types, supporting the trends seen in
the scatter plot.
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Table 1: Average Niño 3.4 SST Anomaly (oC) for given models over seasonal 3 month periods in 2015 – 2016.
Source: InternationalResearch Institute |
Most of the models predict El Niño SST
to slightly increase in strength until about the end of the year, and then
gradually weaken through 2016. Although the El Niño will be steadily dying
away, it is expected to still be a strong force through the first 4 or so
months of 2016. The associated probabilities with these predictions is at least
99% up to around Feb 16, then exponentially falls away to about 50% by May –
July 16.
Figure 2 below shows a longer term
trend of model predictions, emphasising the strength of the El Niño which we
are currently experiencing. It also shows the model forecasts for the past 21
months in addition to the Nov 2015 predictions (as seen in Figure 1). It allows
us to see the evolution of model predictions as more data is gathered from the
progressing conditions. Models are continually updated and re-run when new data
is obtained to produce up-to-date forecasts and analysis of the processes at
play.
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Figure 2: Niño 3.4
SST Anomaly (oC) predictions from dynamical and statistical models
for 22 months.
Source: InternationalResearch Institute |
The high SST anomalies that are being
seen mean that the ocean is unable to absorb as much heat as it otherwise would
during these months. This factor along with CO2 levels breaking
records and reaching a massive 400.35ppm, is what is causing the expectation
that 2015 will be the hottest year on record.
Join me next time when we’ll look at
what dynamical models and statistical models are, the differences between them,
and why these different types of models exist for the modelling of ENSO.
The different forecasts of the models are really interesting! I will definitely be checking back to find out more.
ReplyDeleteThanks Alice, next post is up now!
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