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What connects
seemingly random events
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like floods
in the United Kingdom,
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00:00:31,560 --> 00:00:34,519
droughts in Africa,
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00:00:34,520 --> 00:00:37,479
wildfires in Canada
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and cyclones in the Pacific?
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A boy.
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"El Niño" in Spanish.
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It's the innocent-sounding name
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that Peruvian fishermen gave
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to a climate phenomenon that
regularly devastates our world.
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There is no single phenomenon
in the world
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that can affect
global weather patterns
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00:00:58,320 --> 00:00:59,759
as much as El Niño
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and is, therefore, associated
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with as many natural disasters
as El Niño is.
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One major El Niño event
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00:01:06,360 --> 00:01:12,999
that started in 2015
and which only ended in 2016,
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contributed to catastrophic weather events
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right across the globe.
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El Niño of 2015-16
was one of the major
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and most intense El Niños
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that we've seen
in the historical record.
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It contributed to the longest
coral bleaching ever recorded,
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stretching across the oceans
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from Florida Keys
to the Great Barrier Reef.
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Africa, Malawi, Zimbabwe,
South Africa,
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Mozambique and Ethiopia all
suffered devastating drought,
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inflicting hunger
and disease on millions.
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South America
struggled to cope
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with both drought
and extreme storms.
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The Pacific Ocean's vulnerable,
low-lying islands
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were hit by several cyclones,
one after the other.
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And southeast Asia recorded
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the largest emissions
of wildfire and smoke ever.
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So extensive
was El Niño's impact
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that it even played a part
in major disasters
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across Europe.
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The United Kingdom was hit
by wave after wave
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of record-breaking storms
and floods.
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Floods can kill.
Floods annihilate.
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They destroy.
They're incredibly dangerous.
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In this episode of
Deadly Disasters,
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we will look
at this climate phenomenon
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that has affected
the entire world for millennia.
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Our experts will look at some
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of the most catastrophic
consequences of El Niño,
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and its little sister,
La Niña.
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another climate event
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with devastating effects
around the globe.
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Many of them
are immediately felt,
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and they cause death
and destruction and disruption.
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We will examine the differences
and similarities
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between these two
climate-changing incidents.
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We will consider
how different countries
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have managed their impacts,
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particularly in the developing world,
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where resources
can be stretched thin.
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Eyewitness reports will tell
the human story behind El Niño
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and the personal toll
these disasters take.
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El Niño is a climate phenomenon
that happens every few years,
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when the waters in the eastern
tropical Pacific Ocean
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get unusually warm.
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Normally,
this warm water,
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and the rainy conditions
it causes,
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are in the western Pacific.
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There, the sea level
is naturally higher.
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In fact, normally around
40 to 50 centimeters higher
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near Indonesia than Ecuador.
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00:04:05,760 --> 00:04:08,639
This is, in part,
because of strong trade winds
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blowing westward
across the Pacific.
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They push water
toward Asia and Oceania,
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where it gathers and creates a
slightly tilted ocean surface.
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El Niño causes droughts
in normally damp areas
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in the eastern Pacific,
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such as Indonesia
and Australia,
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while normally drier places,
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like South America's
west coast,
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endure devastating floods.
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But it also impacts the global
atmospheric circulation.
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00:04:38,480 --> 00:04:41,199
It can weaken
the Indian monsoon,
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while bringing heavy rain
to the western United States.
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We are only just beginning
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00:04:48,440 --> 00:04:51,239
to understand
this powerful phenomenon.
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Essentially, El Niño
is quite a new science.
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El Niño have only really been
known about for about 100 years,
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00:04:58,760 --> 00:05:01,919
and it's only been observed
properly for about 40 years,
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00:05:01,920 --> 00:05:05,039
during which time there's been
maybe four big events.
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The first recorded
scientific discussions
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00:05:07,760 --> 00:05:10,599
of El Niño were in the 1890s,
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between the Lima
Geographical Society
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00:05:13,520 --> 00:05:16,919
and the International
Geographic Congress.
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00:05:16,920 --> 00:05:20,279
But we now know that it
stretches at least as far back
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as 10,000 years,
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00:05:21,960 --> 00:05:24,479
to the beginning
of the Holocene Epoch,
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and the end
of the last Ice Age.
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We have detected
chemical signatures
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of increased rainfall
and warmer seas
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in coral samples and other
paleoclimate indicators
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00:05:36,360 --> 00:05:38,759
since the previous Ice Age.
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00:05:38,760 --> 00:05:41,119
Climate scientists
have also shown
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that tree-ring records
from North America,
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especially from the Southwest,
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match the intensity
of El Niño events
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over the last 1100 years.
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These tree rings coincide well
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with the 150 year
sea surface temperature records
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we have from the Pacific.
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During El Niño,
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the warmer surface temperatures
in the eastern Pacific
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change the atmospheric
circulation.
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00:06:08,440 --> 00:06:10,719
This causes
unusually wet winters
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in the southwest United States,
and thus wider tree rings.
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This research was used to help
improve El Niño prediction
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in climate models.
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Predicting its likely events
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over a few months ahead
is now normal.
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But our recognition of El Niño
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and its impacts is helping us
look at our history
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with fresh eyes.
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For instance,
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we know that
from 1789 to 1792,
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the South Asia monsoon
failed many times.
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Research suggests the El Niño
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influenced a mix
of climate anomalies,
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and unusual weather
led to crop failures in Europe.
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This, in turn,
became the catalyst
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for some of the troubles
and desperate anger that,
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in 1789, erupted
into the French Revolution.
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00:07:03,520 --> 00:07:07,159
El Niño has been linked
to at least three large famines
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in the late 19th century.
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British and Indian officials
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noted that extreme weather
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and the collapse
of monsoon circulation
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00:07:15,760 --> 00:07:19,039
resulted in great droughts
and floods.
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Between 30 to 60 million
people died in China,
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India and Brazil.
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Hundreds of millions
endured hunger.
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It was only in the 1960s
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that scientists
definitively linked
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00:07:32,720 --> 00:07:35,039
the alternating warm
and cool patterns
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in the Pacific waters
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and the atmospheric
circulation.
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At least 26 El Niños were
recorded in the last century.
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In 1957-58,
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El Niño caused serious damage
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to the Californian
kelp forests.
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It was only in 1982-83
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that scientists were able
to study a major El Niño
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as it was
actually taking place.
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The unusually warm waters
in the Pacific
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forced fish to seek out
colder waters to survive.
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On Christmas Island,
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sea birds abandoned their young
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to fly over the Pacific
desperately searching for food.
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Almost a quarter of the fur
seal and sea lion populations
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off the Peruvian coast
starved to death.
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Some of the biggest effects
on wildlife
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that we've known about
for the longest with El Niño
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is what happens off Peru.
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You have deaths of sea birds.
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You have deaths of seals,
and in some years,
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collapses in population
of Galapagos penguins.
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Indonesia and Australia
faced terrible droughts
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and Southeast Asia
shut down some of its airports
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because of the thick plumes of
smoke rising from forest fires.
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El Niño is associated
with extreme weather
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and natural disasters in many,
many countries in the world.
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In Spanish,
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"El Niño" translates
as "The Child" or "The Boy."
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The name was given
by Peruvian fishermen
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who noticed the occasional
warming of the ocean
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around December
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and made the connection
to Christmas and Jesus.
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El Niño and La Niña,
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which translates
to "The Girl,"
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are opposite phases
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of the El Niño Southern
Oscillation cycle of ENSO.
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ENSO is the name
for the temperature variations
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between the ocean
and atmosphere
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in the Equatorial Pacific.
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El Niño is the warm and La Niña
the cold phase of the ENSO.
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El Niño is officially declared
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if the eastern tropical
Pacific's surface temperature
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rises half a degree centigrade
above the long-term average.
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One of the most severe El Niño
events was in 1997-98,
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when the Pacific
heated up remarkably,
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by more than three degrees
centigrade.
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The effects of climate change
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on the cycle
are not yet fully established.
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Some scientists
believe climate change
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will make ENSO events
more frequent and intense.
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If right, it is likely
that the economic,
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environmental and societal impacts
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will only get more extreme.
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The three most deadly
El Niños,
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1982-83,
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1997-98 and 2015-16
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were not just because
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of the scale of the chaos
they wreaked.
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But also because
of how unpredictable
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their effects were.
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It is not certain what tips
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the unstable Pacific Ocean
atmosphere system
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into El Niño,
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but a weakening of normal trade
winds that blow west is key.
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For instance,
in 2014,
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a large group of very strong
thunderstorms over Indonesia
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may have been the trigger.
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00:10:59,400 --> 00:11:03,159
An upwelling or
upward movement of ocean water
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can mix upper and lower levels
of seawater together.
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00:11:06,880 --> 00:11:09,959
This brings cool
and nutrient-rich water
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from the bottom of the ocean
to the warmer surface.
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00:11:13,120 --> 00:11:17,119
There, it supports large
populations of phytoplankton,
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00:11:17,120 --> 00:11:21,399
zooplankton, fish,
and fish-eating seabirds.
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00:11:21,400 --> 00:11:23,159
Every few years,
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normal upwelling in the Pacific
Ocean is affected by ENSO.
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During an ENSO,
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the trade winds that blow
from east to west weaken.
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This allows the warmer waters
of the western Pacific
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to move towards the
western coast of South America.
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This suppresses
the normal upwellings of cold,
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nutrient-rich water.
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The marine food chain
is disrupted.
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Warm waters force fish down
to colder, deeper water.
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Seals suffer as they lose
their food source.
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00:11:56,360 --> 00:11:59,199
In the same way,
the fishing economies
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of countries such as Peru
and Ecuador are also hit.
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00:12:03,720 --> 00:12:05,839
We are still trying
to work out
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00:12:05,840 --> 00:12:10,359
the relationship between
El Niño and climate change.
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00:12:10,360 --> 00:12:11,839
What will happen to El Niños
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under climate change,
global warming,
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00:12:13,840 --> 00:12:15,999
is a question
that many people ask.
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00:12:16,000 --> 00:12:17,599
Some studies are suggesting
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00:12:17,600 --> 00:12:20,159
there may be an increase
in frequency and intensity,
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00:12:20,160 --> 00:12:23,239
but other studies suggest that
that may not be the case.
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00:12:23,240 --> 00:12:26,199
So at the moment,
there isn't a strong consensus
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00:12:26,200 --> 00:12:28,079
about future behavior.
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00:12:28,080 --> 00:12:30,879
But the global system
is changing
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00:12:30,880 --> 00:12:32,479
because of global warming,
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00:12:32,480 --> 00:12:34,479
so we're very likely
to see a change
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00:12:34,480 --> 00:12:37,399
in the patterns of El Niño.
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00:12:37,400 --> 00:12:40,439
We know that a rise
in global temperatures
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00:12:40,440 --> 00:12:43,999
leads to an increase
in sea surface temperatures.
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00:12:46,880 --> 00:12:50,079
This is what sparks
the El Niño phenomenon.
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00:12:50,080 --> 00:12:53,839
The relationship between
El Niño and a change in climate
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00:12:53,840 --> 00:12:55,999
is somewhat cyclical.
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00:12:56,000 --> 00:12:58,999
Oceans act as carbon sinks:
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00:12:59,000 --> 00:13:01,439
they capture and store carbon
249
00:13:01,440 --> 00:13:03,759
as dissolved CO2.
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00:13:03,760 --> 00:13:08,919
And carbon dioxide dissolves
more easily in colder waters.
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00:13:08,920 --> 00:13:10,759
During El Niño,
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00:13:10,760 --> 00:13:13,719
sea surface temperatures
increase.
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00:13:13,720 --> 00:13:16,999
This causes less CO2
to be dissolved.
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00:13:17,000 --> 00:13:20,839
The result is more carbon
dioxide in the atmosphere,
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00:13:20,840 --> 00:13:22,879
which causes global warming,
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00:13:22,880 --> 00:13:26,319
which in turn
leads to the climate changing.
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00:13:26,320 --> 00:13:29,079
Bushfires sparked
by the El Niño effect
258
00:13:29,080 --> 00:13:31,799
also release
large amounts of CO2,
259
00:13:31,800 --> 00:13:35,319
which in turn can lead
to greater global warming.
260
00:13:35,320 --> 00:13:38,559
ENSO is one of the most
important phenomena
261
00:13:38,560 --> 00:13:41,399
affecting our global climate.
262
00:13:41,400 --> 00:13:44,079
It impacts
the atmospheric circulation,
263
00:13:44,080 --> 00:13:47,719
which leads to changes
in temperature and rainfall.
264
00:13:47,720 --> 00:13:51,999
The equatorial Pacific climate
behaves as a "coupled system."
265
00:13:52,000 --> 00:13:54,519
This is because
the states of the ocean
266
00:13:54,520 --> 00:13:57,479
and the atmosphere
depend on each other.
267
00:13:57,480 --> 00:14:00,479
Some research
suggests El Niño events
268
00:14:00,480 --> 00:14:04,839
are increasing in both
intensity and frequency,
269
00:14:04,840 --> 00:14:08,399
resulting in increased
extreme weather events.
270
00:14:08,400 --> 00:14:11,159
For instance,
unusually hot weather
271
00:14:11,160 --> 00:14:13,759
is becoming more frequent
in Sri Lanka.
272
00:14:13,760 --> 00:14:16,999
Certain regions have suffered
record temperatures,
273
00:14:17,000 --> 00:14:19,239
as well as very heavy rains.
274
00:14:19,240 --> 00:14:23,639
These extreme events
cause severe damage to crops,
275
00:14:23,640 --> 00:14:26,999
depriving farmers
of a stable income.
276
00:14:27,000 --> 00:14:29,239
Fishermen also suffer
when heavy rains
277
00:14:29,240 --> 00:14:31,719
stop them from going to sea.
278
00:14:31,720 --> 00:14:33,919
Natural disasters
such as floods
279
00:14:33,920 --> 00:14:36,039
and landslides
become more frequent,
280
00:14:36,040 --> 00:14:38,999
leading to loss of lives
and homes.
281
00:14:39,000 --> 00:14:41,919
Diseases spread,
roads are blocked,
282
00:14:41,920 --> 00:14:43,839
food prices soar,
283
00:14:43,840 --> 00:14:48,399
and countries' vital
infrastructures are destroyed.
284
00:14:48,400 --> 00:14:53,799
In 2015, El Niño struck
with particular ferocity.
285
00:14:53,800 --> 00:14:55,999
Its effects were widely felt
286
00:14:56,000 --> 00:14:59,679
and devastated vast areas
across the globe.
287
00:14:59,680 --> 00:15:01,759
There was
a very extensive disruption
288
00:15:01,760 --> 00:15:03,439
to the rainfall patterns.
289
00:15:03,440 --> 00:15:06,679
And that was associated
with food security problems
290
00:15:06,680 --> 00:15:08,079
throughout the globe,
291
00:15:08,080 --> 00:15:10,799
particularly
in parts of Indonesia
292
00:15:10,800 --> 00:15:12,359
and also parts of Africa,
293
00:15:12,360 --> 00:15:14,799
with up to about
60 million people
294
00:15:14,800 --> 00:15:17,159
faced with
food security issues
295
00:15:17,160 --> 00:15:19,759
directly associated
with that event.
296
00:15:19,760 --> 00:15:22,119
Countries across
southern Africa
297
00:15:22,120 --> 00:15:26,319
experienced a bewildering array
of extreme weather.
298
00:15:28,960 --> 00:15:32,279
South Africa experienced
one of its worst droughts
299
00:15:32,280 --> 00:15:34,639
for 30 years.
300
00:15:34,640 --> 00:15:37,679
Many small farmers
went out of business.
301
00:15:37,680 --> 00:15:41,279
The government declared
five out of its nine provinces
302
00:15:41,280 --> 00:15:44,239
drought disaster areas
for agriculture.
303
00:15:44,240 --> 00:15:47,320
Dams were at an all-time low.
304
00:15:50,080 --> 00:15:54,239
Thousands of hectares of land
were left with brittle stalks
305
00:15:54,240 --> 00:15:56,279
from the previous
year's harvest.
306
00:15:56,280 --> 00:15:59,879
The effects on wildlife
were dramatic.
307
00:15:59,880 --> 00:16:04,239
Impala and hippopotamuses
grew emaciated.
308
00:16:04,240 --> 00:16:08,399
Buffalo and hippopotamuses
died in droves.
309
00:16:08,400 --> 00:16:10,639
But jackals and crocodiles
310
00:16:10,640 --> 00:16:13,959
thrived on the increased
food sources.
311
00:16:13,960 --> 00:16:16,039
The United Nations warned
312
00:16:16,040 --> 00:16:18,879
that about 50 million people
faced hunger
313
00:16:18,880 --> 00:16:21,359
across southern
and eastern Africa,
314
00:16:21,360 --> 00:16:25,879
as the continent struggled with
its worst drought in decades.
315
00:16:25,880 --> 00:16:27,479
One of the things
about El Niño
316
00:16:27,480 --> 00:16:30,919
is that it does affect
very large geographical areas,
317
00:16:30,920 --> 00:16:33,799
and so if we take the example
of southern Africa,
318
00:16:33,800 --> 00:16:37,239
you have a drought occurring
across multiple countries.
319
00:16:37,240 --> 00:16:39,399
And that can lead
to additional problems
320
00:16:39,400 --> 00:16:41,639
to what you might find
just internally
321
00:16:41,640 --> 00:16:43,679
if the drought occurs
within the country.
322
00:16:43,680 --> 00:16:46,719
The worst hit was Ethiopia.
323
00:16:46,720 --> 00:16:49,359
There, more than
2 million children
324
00:16:49,360 --> 00:16:51,679
needed treatment
for malnutrition
325
00:16:51,680 --> 00:16:55,519
and over 10 million people
needed food aid.
326
00:16:55,520 --> 00:16:58,119
If the situation
continues like this...
327
00:16:58,120 --> 00:17:03,159
we need the international
community's support.
328
00:17:03,160 --> 00:17:05,799
The crisis even hit Ethiopians
329
00:17:05,800 --> 00:17:09,239
not at immediate risk
of going hungry.
330
00:17:09,240 --> 00:17:12,919
3.9 million children
and teenagers
331
00:17:12,920 --> 00:17:15,879
no longer had access
to education.
332
00:17:15,880 --> 00:17:17,599
These problems
don't go away overnight.
333
00:17:17,600 --> 00:17:19,159
They don't go away in a decade.
334
00:17:19,160 --> 00:17:21,159
I mean,
this is a long-haul process.
335
00:17:21,160 --> 00:17:26,279
Somalia, Sudan,
and Kenya's crops also failed,
336
00:17:26,280 --> 00:17:29,959
leaving a total of more
than 20 million people
337
00:17:29,960 --> 00:17:33,599
food insecure in the region.
338
00:17:33,600 --> 00:17:36,159
The drought took many
officials by surprise.
339
00:17:36,160 --> 00:17:39,039
Although El Niño
had been forecast,
340
00:17:39,040 --> 00:17:43,119
it normally brings more rain
to the region, not less.
341
00:17:43,120 --> 00:17:44,999
When El Niño strikes,
342
00:17:45,000 --> 00:17:49,639
it often exposes weaknesses
in countries' infrastructures.
343
00:17:53,560 --> 00:17:56,759
The 2015-16 event
344
00:17:56,760 --> 00:18:01,279
brutally revealed Zambia's
overreliance on hydropower.
345
00:18:01,280 --> 00:18:04,239
Ninety-five percent
of the country's energy
346
00:18:04,240 --> 00:18:05,799
was generated this way.
347
00:18:05,800 --> 00:18:07,239
When the droughts hit,
348
00:18:07,240 --> 00:18:09,759
the dammed lakes
couldn't cope.
349
00:18:22,320 --> 00:18:25,119
Water levels
in the Kariba dam,
350
00:18:25,120 --> 00:18:28,639
one of Zambia and Zimbabwe's
main sources of hydropower,
351
00:18:28,640 --> 00:18:34,359
fell to a record low
of 12 percent in January 2016.
352
00:18:34,360 --> 00:18:37,999
We're seeing a drastic
reduction, that's very scary.
353
00:18:38,000 --> 00:18:41,719
And that tells me we're doing
something wrong as a country.
354
00:18:41,720 --> 00:18:43,239
We're doing something wrong
as a region.
355
00:18:43,240 --> 00:18:45,399
And perhaps, we're doing
something wrong globally.
356
00:18:45,400 --> 00:18:47,479
And therefore,
this is a call to action
357
00:18:47,480 --> 00:18:49,639
for us to do everything
that we must
358
00:18:49,640 --> 00:18:52,559
to reduce
the global carbon emissions
359
00:18:52,560 --> 00:18:53,999
to the minimum levels.
360
00:18:54,000 --> 00:18:57,439
Industry was also badly hit.
361
00:18:57,440 --> 00:18:59,759
In Zambia,
because of the impacts
362
00:18:59,760 --> 00:19:02,559
of the El Niño
on the hydropower,
363
00:19:02,560 --> 00:19:05,599
they had an overall impact
on national GDP
364
00:19:05,600 --> 00:19:07,519
of between 1 and 2 percent.
365
00:19:07,520 --> 00:19:09,839
Zambia's copper
mining industry
366
00:19:09,840 --> 00:19:11,879
accounts for
almost three quarters
367
00:19:11,880 --> 00:19:14,599
of the country's
foreign exchange earnings.
368
00:19:14,600 --> 00:19:17,159
It was crippled
by the power cuts.
369
00:19:17,160 --> 00:19:19,999
In September 2015,
370
00:19:20,000 --> 00:19:24,279
the mining giant Glencore
made a staggering announcement.
371
00:19:24,280 --> 00:19:28,799
As owners of a large part of
Zambia's Mopani Copper Mines,
372
00:19:28,800 --> 00:19:33,519
they planned
to lay off 3800 workers.
373
00:20:07,400 --> 00:20:09,279
The Anglo-Swiss company
374
00:20:09,280 --> 00:20:12,559
laid the blame largely
on the power shortages.
375
00:20:12,560 --> 00:20:16,959
Zimbabwe, famously once
the region's breadbasket,
376
00:20:16,960 --> 00:20:19,279
was one of the countries
worst hit.
377
00:20:19,280 --> 00:20:22,359
The country's president,
Robert Mugabe,
378
00:20:22,360 --> 00:20:24,599
declared a state of disaster.
379
00:20:24,600 --> 00:20:26,399
In less than a month,
380
00:20:26,400 --> 00:20:31,079
people needing food aid
rose from 3 to 4 million.
381
00:20:31,080 --> 00:20:34,479
Even cocoa bean yields
were badly affected,
382
00:20:34,480 --> 00:20:37,119
meaning its price
hit a four-year high
383
00:20:37,120 --> 00:20:38,799
as a result of the drought.
384
00:20:38,800 --> 00:20:40,559
And production was lost
385
00:20:40,560 --> 00:20:44,359
in the world's major cocoa
producer, the Ivory Coast.
386
00:20:44,360 --> 00:20:47,519
Farmers whose families
had relied on the cocoa bean
387
00:20:47,520 --> 00:20:50,679
for generations were forced
to hunt for other work,
388
00:20:50,680 --> 00:20:54,759
often illegal and dangerous,
or starve.
389
00:20:54,760 --> 00:20:56,919
Such was the scale of
the destruction
390
00:20:56,920 --> 00:20:59,279
that in the summer
of 2016,
391
00:20:59,280 --> 00:21:03,679
the southern African countries
launched an emergency appeal.
392
00:21:03,680 --> 00:21:06,559
They asked for $2.8 billion,
393
00:21:06,560 --> 00:21:09,479
to help them feed
the almost 40 million people
394
00:21:09,480 --> 00:21:14,079
suffering in the worst regional
droughts for 35 years.
395
00:21:14,080 --> 00:21:15,879
But the very scale
of the droughts
396
00:21:15,880 --> 00:21:18,119
made giving help
particularly difficult.
397
00:21:18,120 --> 00:21:20,519
International organizations
398
00:21:20,520 --> 00:21:23,999
despaired of providing
resources to match the need.
399
00:21:24,000 --> 00:21:25,799
Children were forced
from home,
400
00:21:25,800 --> 00:21:27,159
leaving healthcare,
401
00:21:27,160 --> 00:21:30,239
security and loved ones behind.
402
00:21:30,240 --> 00:21:31,679
Put simply,
403
00:21:31,680 --> 00:21:34,359
the scale of the crisis
far outstripped
404
00:21:34,360 --> 00:21:35,839
the capacity of communities
405
00:21:35,840 --> 00:21:38,279
and the resources
of the governments.
406
00:21:38,280 --> 00:21:41,559
In under a year, El Niño
407
00:21:41,560 --> 00:21:44,799
was putting decades of global
development gains at risk.
408
00:21:44,800 --> 00:21:49,319
This double contradiction can
be seen vividly in Ethiopia.
409
00:21:49,320 --> 00:21:51,399
It suffered from severe drought
410
00:21:51,400 --> 00:21:53,319
in the northern parts
of the country.
411
00:21:53,320 --> 00:21:55,799
The droughts
inflicted two consecutive
412
00:21:55,800 --> 00:21:58,159
poor crop
and pasture seasons.
413
00:21:58,160 --> 00:22:03,239
18 million people needed
food assistance in 2016.
414
00:22:03,240 --> 00:22:05,959
This was the greatest need
the country had faced
415
00:22:05,960 --> 00:22:08,079
since the 1984 famine,
416
00:22:08,080 --> 00:22:11,959
which sparked the Live Aid
campaign run by Bob Geldof.
417
00:22:11,960 --> 00:22:14,639
In contrast,
the south of the country
418
00:22:14,640 --> 00:22:18,279
suffered torrential rains
and flash floods.
419
00:22:18,280 --> 00:22:21,039
The floods arrived after
nearly 18 months of drought
420
00:22:21,040 --> 00:22:24,519
that left communities
ill prepared to cope.
421
00:22:24,520 --> 00:22:26,719
The long drought
reduced the ground's ability
422
00:22:26,720 --> 00:22:31,079
to absorb water,
which exacerbated the floods.
423
00:22:31,080 --> 00:22:32,399
When you have
two different types
424
00:22:32,400 --> 00:22:33,759
of disasters
in one country,
425
00:22:33,760 --> 00:22:36,479
that provides a particular
problem for aid,
426
00:22:36,480 --> 00:22:39,319
because when you have a heavy
drought and a heavy flood,
427
00:22:39,320 --> 00:22:42,199
the crops will fail everywhere,
but for different reasons.
428
00:22:42,200 --> 00:22:45,319
The myriad of impacts,
the unpredictability,
429
00:22:45,320 --> 00:22:47,639
but also the scale of El Niño,
430
00:22:47,640 --> 00:22:50,239
presents international
organizations
431
00:22:50,240 --> 00:22:52,639
with almost
unprecedented challenges.
432
00:22:52,640 --> 00:22:56,199
This can be seen vividly
in the range of devastation
433
00:22:56,200 --> 00:23:00,919
the 2015-16 El Niño wreaked
on the Pacific Islands.
434
00:23:00,920 --> 00:23:03,399
It threatened
their very existence.
435
00:23:08,280 --> 00:23:10,279
Almost two million tourists
436
00:23:10,280 --> 00:23:14,359
visited the multitude
of islands in 2015,
437
00:23:14,360 --> 00:23:17,519
but the Pacific Islands
weren't to be spared.
438
00:23:17,520 --> 00:23:19,559
Their small populations,
439
00:23:19,560 --> 00:23:21,559
remoteness,
few resources,
440
00:23:21,560 --> 00:23:25,559
and dependency on foreign aid
only made them more vulnerable.
441
00:23:25,560 --> 00:23:29,039
The problems associated
with extreme events
442
00:23:29,040 --> 00:23:32,039
are made much worse
on small island states
443
00:23:32,040 --> 00:23:33,679
because they tend to be
remote,
444
00:23:33,680 --> 00:23:35,519
they tend to be
relatively poor,
445
00:23:35,520 --> 00:23:41,359
and they don't have easy lines
of communication for food,
446
00:23:41,360 --> 00:23:43,799
aid money,
shelter, et cetera,
447
00:23:43,800 --> 00:23:45,359
to come into those countries.
448
00:23:45,360 --> 00:23:47,039
For example, a small island
449
00:23:47,040 --> 00:23:48,959
developing state
in the Pacific,
450
00:23:48,960 --> 00:23:53,759
it may be half a day's journey
from the nearest rich country,
451
00:23:53,760 --> 00:23:56,079
which is probably Australia
or maybe Hawaii,
452
00:23:56,080 --> 00:23:58,239
which are themselves
relatively sparsely populated,
453
00:23:58,240 --> 00:24:00,719
and aid workers will have
to travel to themselves.
454
00:24:00,720 --> 00:24:02,279
And of course,
455
00:24:02,280 --> 00:24:06,159
if harbor, or more importantly,
an airfield is damaged
456
00:24:06,160 --> 00:24:09,239
then the planes can't land,
and the aid can't come in.
457
00:24:09,240 --> 00:24:13,599
Wave after wave of cyclones
swept across the islands:
458
00:24:13,600 --> 00:24:17,079
Pam, Maysak, Raquel.
459
00:24:17,080 --> 00:24:18,679
Pam was the strongest storm
460
00:24:18,680 --> 00:24:20,759
to ever strike
the South Pacific.
461
00:24:20,760 --> 00:24:24,119
On Vanuatu,
entire villages were destroyed.
462
00:24:24,120 --> 00:24:25,839
Eleven people were killed
463
00:24:25,840 --> 00:24:28,399
and thousands were left
without shelter.
464
00:24:42,200 --> 00:24:44,559
There was to be no respite.
465
00:24:44,560 --> 00:24:46,559
Scarcely had the cyclones left
466
00:24:46,560 --> 00:24:48,639
then the islands
were hit by drought.
467
00:24:48,640 --> 00:24:51,119
States of emergency
were declared in Palau,
468
00:24:51,120 --> 00:24:52,839
the Marshall Islands,
469
00:24:52,840 --> 00:24:55,279
and the Federated States
of Micronesia.
470
00:24:55,280 --> 00:24:57,079
Koror, Palau's capital,
471
00:24:57,080 --> 00:25:00,439
recorded its lowest rainfall
in 65 years.
472
00:25:00,440 --> 00:25:03,399
People had to ration water
to survive.
473
00:25:03,400 --> 00:25:05,999
Wells became brackish
or ran dry.
474
00:25:06,000 --> 00:25:09,079
Staple foods such as
breadfruit and bananas
475
00:25:09,080 --> 00:25:12,039
shriveled on trees.
476
00:25:12,040 --> 00:25:13,959
Micronesia's islands
and atolls
477
00:25:13,960 --> 00:25:18,039
are not always the paradises
they can seem from photographs.
478
00:25:18,040 --> 00:25:20,479
They can quickly run out
of drinking water.
479
00:25:20,480 --> 00:25:24,439
Relief agencies struggled to
bring water to remote atolls,
480
00:25:24,440 --> 00:25:28,199
a day's boat ride
from the main islands.
481
00:25:28,200 --> 00:25:31,879
But El Niño damaged the
Pacific Islanders' livelihoods
482
00:25:31,880 --> 00:25:33,599
in other ways.
483
00:25:33,600 --> 00:25:36,319
The warmer water
has less oxygen.
484
00:25:36,320 --> 00:25:38,239
Less mixing of water
485
00:25:38,240 --> 00:25:41,959
leads to reduced production of
microscopic plants and animals
486
00:25:41,960 --> 00:25:43,479
needed for tuna.
487
00:25:43,480 --> 00:25:46,279
Particularly skipjack
and yellowfin.
488
00:25:46,280 --> 00:25:49,079
The warmer water
in the western Pacific
489
00:25:49,080 --> 00:25:51,279
shifted the tuna's
spawning grounds
490
00:25:51,280 --> 00:25:53,159
to the central and eastern
491
00:25:53,160 --> 00:25:55,679
equatorial regions
of the Pacific.
492
00:25:55,680 --> 00:25:58,559
This dramatically reduced
the catches
493
00:25:58,560 --> 00:25:59,879
for the island fishermen,
494
00:25:59,880 --> 00:26:03,479
having a severe
economic impact.
495
00:26:07,760 --> 00:26:11,119
Despite the country's obsession
with talking about the weather,
496
00:26:11,120 --> 00:26:13,119
dramatic meteorological events
497
00:26:13,120 --> 00:26:15,519
have been relatively rare
in the UK.
498
00:26:15,520 --> 00:26:19,999
However, in 2015,
all this changed.
499
00:26:20,000 --> 00:26:23,199
The UK is used to floods.
We have regular floods.
500
00:26:23,200 --> 00:26:26,199
Almost every year
there is a major flood,
501
00:26:26,200 --> 00:26:29,079
but in 2015,
the flooding was extreme.
502
00:26:29,080 --> 00:26:32,839
I don't think anybody was
prepared for the extreme flood
503
00:26:32,840 --> 00:26:35,519
that Storm Desmond
especially brought with it.
504
00:26:35,520 --> 00:26:36,919
Humid air,
505
00:26:36,920 --> 00:26:39,479
borne by strong
southwesterly winds,
506
00:26:39,480 --> 00:26:42,719
dumped huge quantities of rain
over Northern Ireland,
507
00:26:42,720 --> 00:26:46,640
Wales, northwest England,
and Scotland.
508
00:26:47,760 --> 00:26:50,119
It began with Storm Desmond,
509
00:26:50,120 --> 00:26:53,199
which dropped over 33
centimeters of rain on Cumbria
510
00:26:53,200 --> 00:26:56,959
between the 4th
and the 5th of December.
511
00:26:56,960 --> 00:27:00,479
It broke the national record
for rainfall in a day.
512
00:27:00,480 --> 00:27:02,279
Sitting in the house,
I saw the water
513
00:27:02,280 --> 00:27:04,639
coming up under the tiles.
You know.
514
00:27:04,640 --> 00:27:06,519
It's quite frightening.
515
00:27:06,520 --> 00:27:10,839
Horrendous, it's-it's mad.
516
00:27:10,840 --> 00:27:14,679
It's terrible,
I don't know what to do.
517
00:27:14,680 --> 00:27:18,439
Carlisle and other areas
of Cumbria were flooded.
518
00:27:18,440 --> 00:27:21,759
More than 5000 homes
were affected in Cumbria
519
00:27:21,760 --> 00:27:23,679
and Lancashire alone.
520
00:27:23,680 --> 00:27:26,519
We need to make sure they get
all the support they need,
521
00:27:26,520 --> 00:27:28,919
get the insurance claim
paid quickly,
522
00:27:28,920 --> 00:27:31,399
get them the alternative
accommodation,
523
00:27:31,400 --> 00:27:34,559
make sure the council
picks up the furniture
524
00:27:34,560 --> 00:27:36,679
and the things they've had
to throw out of their houses.
525
00:27:36,680 --> 00:27:38,799
And then try and get them back
in as soon as possible.
526
00:27:38,800 --> 00:27:41,919
The average person is out
of their home for nine months
527
00:27:41,920 --> 00:27:44,599
after a flood.
And after Storm Desmond,
528
00:27:44,600 --> 00:27:46,639
many people in Carlisle
529
00:27:46,640 --> 00:27:49,719
were not back in their homes
for two years.
530
00:27:49,720 --> 00:27:53,319
People suffer with post-
traumatic stress disorder.
531
00:27:53,320 --> 00:27:55,639
They're anxious
every time it rains.
532
00:27:55,640 --> 00:27:58,679
It's a very deeply
personal experience.
533
00:27:58,680 --> 00:28:01,239
Storm Eva followed Desmond.
534
00:28:01,240 --> 00:28:03,799
Eva brought with her
more heavy rain,
535
00:28:03,800 --> 00:28:06,959
which fell on
the already saturated earth.
536
00:28:06,960 --> 00:28:08,519
People don't realize
537
00:28:08,520 --> 00:28:11,559
that just a few inches
of water can float a car,
538
00:28:11,560 --> 00:28:14,799
that a few inches of water
can knock you off your feet,
539
00:28:14,800 --> 00:28:17,479
that you can fall down
manhole covers
540
00:28:17,480 --> 00:28:21,079
that have been lifted
by the sheer volume of water,
541
00:28:21,080 --> 00:28:24,639
that little streams
become torrents
542
00:28:24,640 --> 00:28:26,759
and people haven't woken up
543
00:28:26,760 --> 00:28:29,359
to smell the floodwater,
as it were.
544
00:28:29,360 --> 00:28:32,039
And they don't grasp
just how dangerous
545
00:28:32,040 --> 00:28:35,359
flooding can be
and how it can kill people.
546
00:28:35,360 --> 00:28:36,799
It can and it does.
547
00:28:36,800 --> 00:28:38,319
The ensuing floods
548
00:28:38,320 --> 00:28:41,279
engulfed thousands of homes
and businesses,
549
00:28:41,280 --> 00:28:44,759
swelling rivers
and breaking bridges.
550
00:28:44,760 --> 00:28:46,719
River levels stayed high
551
00:28:46,720 --> 00:28:49,439
and over 70 flood warnings
were issued
552
00:28:49,440 --> 00:28:53,199
as the rain continued
to fall remorselessly.
553
00:28:53,200 --> 00:28:55,239
On the 22nd of December,
554
00:28:55,240 --> 00:28:57,919
communities in Cumbria
were flooded again.
555
00:28:57,920 --> 00:29:01,879
For some, it was the third time
in under a month.
556
00:29:01,880 --> 00:29:04,479
It's not Christmas to us
in Carlisle,
557
00:29:04,480 --> 00:29:06,199
I don't think at the moment.
558
00:29:06,200 --> 00:29:08,279
You don't feel very festive
when you've been through this.
559
00:29:08,280 --> 00:29:10,159
We did all the topographical
surveys.
560
00:29:10,160 --> 00:29:12,039
We worked all
the measurements out,
561
00:29:12,040 --> 00:29:15,359
built a flood bund
last year and the year before,
562
00:29:15,360 --> 00:29:17,159
installed pumps this year,
563
00:29:17,160 --> 00:29:18,799
nearly finished paying for it,
564
00:29:18,800 --> 00:29:21,759
but unfortunately, I'm told
there is a foot of water
565
00:29:21,760 --> 00:29:23,199
in church this morning.
566
00:29:23,200 --> 00:29:25,279
On Christmas Day,
567
00:29:25,280 --> 00:29:28,559
more than 100 flood alerts
and warnings were issued,
568
00:29:28,560 --> 00:29:31,279
as Storm Eva
battered the country.
569
00:29:31,280 --> 00:29:33,999
There was to be no respite.
570
00:29:34,000 --> 00:29:37,639
Once again, northern England
was the worst hit.
571
00:29:37,640 --> 00:29:39,239
On Boxing Day,
572
00:29:39,240 --> 00:29:41,599
people in West Yorkshire
and Lancashire
573
00:29:41,600 --> 00:29:44,519
had to be evacuated
as flooding hit Leeds,
574
00:29:44,520 --> 00:29:47,959
York and greater Manchester.
575
00:29:47,960 --> 00:29:51,119
There are no words
that describe the devastation.
576
00:29:51,120 --> 00:29:52,759
Roads were washed away.
577
00:29:52,760 --> 00:29:54,799
Bridges were washed away.
578
00:29:54,800 --> 00:29:58,079
Flood defenses
were overtopped and breached.
579
00:29:58,080 --> 00:30:01,319
People's homes
were flooded to the ceiling
580
00:30:01,320 --> 00:30:04,079
and businesses were annihilated.
581
00:30:04,080 --> 00:30:06,759
Among the rivers
to burst its banks
582
00:30:06,760 --> 00:30:09,159
was the River Ouse in York,
583
00:30:09,160 --> 00:30:10,999
where 500 homes were flooded
584
00:30:11,000 --> 00:30:12,919
and the Army
was called in to help.
585
00:30:12,920 --> 00:30:15,159
I'm now left feeling really,
really angry.
586
00:30:15,160 --> 00:30:17,959
I've got two little boys
who are out of their houses.
587
00:30:17,960 --> 00:30:20,479
We don't know where
we're going to be living.
588
00:30:20,480 --> 00:30:21,839
It's going to take months
and months
589
00:30:21,840 --> 00:30:23,559
and months for this
to be restored.
590
00:30:23,560 --> 00:30:25,599
The inconvenience
is indescribable.
591
00:30:25,600 --> 00:30:28,679
Individuals suffered hugely.
592
00:30:28,680 --> 00:30:30,559
Having been flooded myself,
593
00:30:30,560 --> 00:30:33,519
I know how awful
being flooded is.
594
00:30:33,520 --> 00:30:35,959
And I don't think anybody
can convey
595
00:30:35,960 --> 00:30:38,199
the true awfulness
of being flooded.
596
00:30:38,200 --> 00:30:39,679
But people's houses,
597
00:30:39,680 --> 00:30:42,039
because of the sheer volume
of water,
598
00:30:42,040 --> 00:30:43,999
will have found
that their furniture
599
00:30:44,000 --> 00:30:46,199
wasn't where it was
when they left it.
600
00:30:46,200 --> 00:30:48,519
It will have been covered
with a thick,
601
00:30:48,520 --> 00:30:52,279
horrible smelling,
sludgy brown filth
602
00:30:52,280 --> 00:30:54,439
and going into their homes--
603
00:30:54,440 --> 00:30:57,439
The smell--
You cannot describe the smell.
604
00:30:57,440 --> 00:31:00,239
It really gets you
at the back of your throat,
605
00:31:00,240 --> 00:31:02,639
and no filming
will ever tell you
606
00:31:02,640 --> 00:31:05,199
how truly awful
the smell will be.
607
00:31:05,200 --> 00:31:08,199
Many communities
were still trying to recover
608
00:31:08,200 --> 00:31:10,200
from the aftermath
of Storm Desmond.
609
00:31:12,520 --> 00:31:15,799
Hundreds of people were forced
to evacuate their homes,
610
00:31:15,800 --> 00:31:18,879
as rivers burst their banks
in the Cumbrian towns
611
00:31:18,880 --> 00:31:22,439
of Appleby,
Keswick and Kendal.
612
00:31:22,440 --> 00:31:24,799
Scotland, northern England
613
00:31:24,800 --> 00:31:28,319
and Ireland
were all overwhelmed.
614
00:31:28,320 --> 00:31:30,719
Flood defenses
failed to cope with the rain
615
00:31:30,720 --> 00:31:33,119
cascading through the rivers.
616
00:31:33,120 --> 00:31:34,839
If these defenses
had not been in place,
617
00:31:34,840 --> 00:31:38,199
you're potentially looking at as
much as two meters more water.
618
00:31:38,200 --> 00:31:40,679
That's six feet more water
going into people's houses.
619
00:31:40,680 --> 00:31:43,079
So the tens of millions
that have been spent on defenses
620
00:31:43,080 --> 00:31:45,239
has been really valuable.
621
00:31:45,240 --> 00:31:49,599
Tens of thousands of properties
were also left without power,
622
00:31:49,600 --> 00:31:51,719
dozens of schools were closed,
623
00:31:51,720 --> 00:31:55,120
around 40 bridges
were either damaged or shut,
624
00:31:56,960 --> 00:31:59,359
and rail links
were severely disrupted.
625
00:31:59,360 --> 00:32:00,679
It's not a quick fix.
626
00:32:00,680 --> 00:32:02,919
It takes a long time
to recover.
627
00:32:02,920 --> 00:32:06,279
And in fact, some people haven't
recovered from it to this day.
628
00:32:06,280 --> 00:32:08,999
It truly is life-changing.
629
00:32:09,000 --> 00:32:12,919
The Army had to be drafted in
to help with the evacuations.
630
00:32:12,920 --> 00:32:15,999
That means supporting
the work of the police,
631
00:32:16,000 --> 00:32:17,559
the environment agency,
632
00:32:17,560 --> 00:32:19,839
and all the other people
that are now deployed out here.
633
00:32:19,840 --> 00:32:21,759
And we're working
alongside them
634
00:32:21,760 --> 00:32:24,519
and will continue to do so
for as long as it takes.
635
00:32:24,520 --> 00:32:27,279
Even the Royal National
Lifeboat Institution
636
00:32:27,280 --> 00:32:29,359
was called upon to help.
637
00:32:29,360 --> 00:32:31,639
So when you've got extreme
floods like that,
638
00:32:31,640 --> 00:32:34,319
and you've got
hard engineered defenses
639
00:32:34,320 --> 00:32:37,839
overtopped and-and breached,
640
00:32:37,840 --> 00:32:40,799
and you see trees
coming down the hillsides
641
00:32:40,800 --> 00:32:43,399
and loads and loads of rocks,
642
00:32:43,400 --> 00:32:47,359
it's very difficult to actually
stop that from happening.
643
00:32:47,360 --> 00:32:49,879
In Tadcaster
in north Yorkshire,
644
00:32:49,880 --> 00:32:52,039
the town's bridge collapsed.
645
00:32:52,040 --> 00:32:54,159
It split the town in two.
646
00:32:54,160 --> 00:32:57,119
Residents had to take
a 16-kilometer detour
647
00:32:57,120 --> 00:32:59,279
to get from one side
to the other.
648
00:32:59,280 --> 00:33:02,559
The floods made giving help
particularly hard
649
00:33:02,560 --> 00:33:05,879
as they swept through
the town's only medical center.
650
00:33:05,880 --> 00:33:08,039
In their descriptions
of the event,
651
00:33:08,040 --> 00:33:11,879
residents compared the town
to a warzone.
652
00:33:11,880 --> 00:33:14,359
The Royal Air Force
used helicopters
653
00:33:14,360 --> 00:33:16,079
to drop huge sandbags
654
00:33:16,080 --> 00:33:18,919
into the breach
of the River Douglas.
655
00:33:18,920 --> 00:33:21,239
The UK's meteorological office
656
00:33:21,240 --> 00:33:24,159
analyzed the reasons
for the December floods.
657
00:33:24,160 --> 00:33:26,359
They confirmed that El Niño
658
00:33:26,360 --> 00:33:29,279
had contributed to
a persistent weather pattern,
659
00:33:29,280 --> 00:33:35,119
which led to unusually warm,
moist air reaching the UK.
660
00:33:35,120 --> 00:33:38,919
I don't think people are aware
that a disaster as such
661
00:33:38,920 --> 00:33:41,479
may happen
because of climate change
662
00:33:41,480 --> 00:33:44,839
and because of effects
like El Niño.
663
00:33:44,840 --> 00:33:48,479
It's an unusual concept
to get our heads around.
664
00:33:48,480 --> 00:33:51,559
I don't think people
have the first clue
665
00:33:51,560 --> 00:33:54,519
that something that happens
in the Pacific Ocean,
666
00:33:54,520 --> 00:33:56,919
where the Pacific Ocean
is heating up,
667
00:33:56,920 --> 00:34:01,079
can possibly bring so much rain
to our country.
668
00:34:01,080 --> 00:34:04,239
It's something that we've
got to become aware
669
00:34:04,240 --> 00:34:06,639
that may happen more
in the future.
670
00:34:06,640 --> 00:34:08,879
December 2015
671
00:34:08,880 --> 00:34:12,199
turned out to be not just
the wettest December on record,
672
00:34:12,200 --> 00:34:16,719
but also the wettest month
ever in the UK.
673
00:34:16,720 --> 00:34:20,559
The UK is still grappling
with the problems of storms
674
00:34:20,560 --> 00:34:22,239
and the floods they bring,
675
00:34:22,240 --> 00:34:25,039
even though changes have
been made to infrastructures
676
00:34:25,040 --> 00:34:27,519
and how the country responds.
677
00:34:27,520 --> 00:34:29,199
The sheer scale
of the challenge
678
00:34:29,200 --> 00:34:31,399
has led the government
to change its approach
679
00:34:31,400 --> 00:34:32,799
from one of protection
680
00:34:32,800 --> 00:34:34,639
and building
higher flood defenses,
681
00:34:34,640 --> 00:34:38,039
to improving communities'
resilience and infrastructure
682
00:34:38,040 --> 00:34:40,599
to when floods do happen.
683
00:34:40,600 --> 00:34:44,719
Organizations like local wildlife trusts
684
00:34:44,720 --> 00:34:47,559
are advising on better
landscape management
685
00:34:47,560 --> 00:34:50,119
such as installing
flood storage areas,
686
00:34:50,120 --> 00:34:53,879
planting trees, and getting
farmers to plow across slopes
687
00:34:53,880 --> 00:34:55,879
to slow the flow of water.
688
00:34:55,880 --> 00:34:58,199
In one of the worst
hit villages,
689
00:34:58,200 --> 00:35:00,199
Glenridding in Cumbria,
690
00:35:00,200 --> 00:35:03,999
thousands of tons of gravel
were removed from the river,
691
00:35:04,000 --> 00:35:06,479
walls were raised,
and drains improved
692
00:35:06,480 --> 00:35:08,239
to reduce the risk.
693
00:35:08,240 --> 00:35:13,439
The floods themselves actually
cost about £1.6 billion,
694
00:35:13,440 --> 00:35:16,239
and that's
government statistics.
695
00:35:16,240 --> 00:35:20,279
But obviously the-- A lot
of people weren't insured,
696
00:35:20,280 --> 00:35:23,439
so they weren't able to apply
for flood insurance.
697
00:35:23,440 --> 00:35:26,719
The 2015-16 El Niño
698
00:35:26,720 --> 00:35:29,119
was as remarkable for its reach
699
00:35:29,120 --> 00:35:32,359
as for its range
of extreme weather impacts.
700
00:35:32,360 --> 00:35:34,439
Countries across five continents
701
00:35:34,440 --> 00:35:36,239
called states of emergency.
702
00:35:36,240 --> 00:35:39,719
It brings extremes
from both ends of the spectrum,
703
00:35:39,720 --> 00:35:42,119
sometimes both in the same place.
704
00:35:42,120 --> 00:35:44,079
A clear example of this
705
00:35:44,080 --> 00:35:50,359
is the 2015-16 winter in Canada
and the United States.
706
00:35:50,360 --> 00:35:52,719
December 2015
707
00:35:52,720 --> 00:35:58,159
set records
as the mildest in 120 years.
708
00:35:58,160 --> 00:36:01,359
Some places
in the Midwest and East
709
00:36:01,360 --> 00:36:04,919
were as much as nine degrees
Celsius warmer than normal.
710
00:36:04,920 --> 00:36:07,799
Then,
as the new year arrived,
711
00:36:07,800 --> 00:36:09,919
so did the cold.
712
00:36:09,920 --> 00:36:13,279
The east coast
and southern United States
713
00:36:13,280 --> 00:36:16,639
were plunged into well below
average temperatures,
714
00:36:16,640 --> 00:36:18,479
and many saw snow.
715
00:36:18,480 --> 00:36:22,439
But this was only the beginning
of what was to come.
716
00:36:22,440 --> 00:36:27,039
The coastline was soon
to be hit by a giant blizzard.
717
00:36:27,040 --> 00:36:31,639
Between the 20th
and the 22nd of January 2016,
718
00:36:31,640 --> 00:36:36,119
governors of 11 states and
the mayor of Washington, D.C.
719
00:36:36,120 --> 00:36:37,879
declared states of emergency
720
00:36:37,880 --> 00:36:42,759
in anticipation of heavy
snowfall and strong winds.
721
00:36:42,760 --> 00:36:44,999
On Saturday,
the 23rd of January,
722
00:36:45,000 --> 00:36:47,279
Blizzard Jonas hit.
723
00:36:47,280 --> 00:36:49,639
New York City was paralyzed.
724
00:36:49,640 --> 00:36:52,599
The blizzard dropped
69 centimeters of snow
725
00:36:52,600 --> 00:36:54,359
on Central Park.
726
00:36:54,360 --> 00:36:56,159
This was the most snow
the park had seen
727
00:36:56,160 --> 00:36:59,559
since records began in 1869.
728
00:36:59,560 --> 00:37:02,679
Governor Andrew Cuomo
issued a travel ban
729
00:37:02,680 --> 00:37:04,919
for New York City
and Long Island roads
730
00:37:04,920 --> 00:37:06,399
on Saturday afternoon.
731
00:37:06,400 --> 00:37:09,079
Mayor de Blasio
said that drivers
732
00:37:09,080 --> 00:37:12,159
who violated the ban
could be arrested.
733
00:37:12,160 --> 00:37:15,159
Snow fell
even in southern states
734
00:37:15,160 --> 00:37:17,879
that are rarely associated
with white winters.
735
00:37:17,880 --> 00:37:19,839
Georgia and South Carolina
736
00:37:19,840 --> 00:37:24,079
reported as much as
19 centimeters of snow cover.
737
00:37:24,080 --> 00:37:26,159
Louisiana and Mississippi
738
00:37:26,160 --> 00:37:29,439
both reported over
5 centimeters in some areas,
739
00:37:29,440 --> 00:37:33,839
and one town in Alabama
had as much as 9 centimeters.
740
00:37:33,840 --> 00:37:36,199
West Virginia
received the most snow,
741
00:37:36,200 --> 00:37:39,159
getting a whopping
106 centimeters
742
00:37:39,160 --> 00:37:40,999
in the town of Glengary.
743
00:37:41,000 --> 00:37:43,279
Jonas battered the country
744
00:37:43,280 --> 00:37:47,079
with 126 kilometer
per hour gusts,
745
00:37:47,080 --> 00:37:50,999
and sustained winds of up
to 91 kilometers per hour.
746
00:37:51,000 --> 00:37:53,399
By Monday, the 25th of January,
747
00:37:53,400 --> 00:37:55,719
the storm was still
going strong.
748
00:37:55,720 --> 00:37:58,839
Schools all over
the east coast were closed,
749
00:37:58,840 --> 00:38:01,959
as were federal offices
in Washington, D.C.
750
00:38:07,160 --> 00:38:09,519
People were bunkered up
in their homes,
751
00:38:09,520 --> 00:38:11,439
unable to leave.
752
00:38:11,440 --> 00:38:14,199
Hundreds of thousands of people
lost electricity
753
00:38:14,200 --> 00:38:15,799
during the storm.
754
00:38:15,800 --> 00:38:19,999
When the winds finally subsided
and the snow let up,
755
00:38:20,000 --> 00:38:24,439
over 100 million people
had been affected by Jonas.
756
00:38:24,440 --> 00:38:28,839
As many as 13,000 flights
had to be canceled.
757
00:38:28,840 --> 00:38:31,039
And, worst of all,
758
00:38:31,040 --> 00:38:34,079
at least 48 people
had been killed.
759
00:38:34,080 --> 00:38:37,839
Storm Jonas was what is called
a Nor'easter,
760
00:38:37,840 --> 00:38:41,999
a cyclonic storm named after
its northeastern winds.
761
00:38:42,000 --> 00:38:45,799
While Nor'easters can occur
at any time of year,
762
00:38:45,800 --> 00:38:48,919
they are most common
in the winter months.
763
00:38:48,920 --> 00:38:52,439
One notable difference between
a rainstorm and a snowstorm,
764
00:38:52,440 --> 00:38:55,919
is that snow has a tendency
to stick around.
765
00:38:55,920 --> 00:38:58,959
Water runs off,
dries up,
766
00:38:58,960 --> 00:39:01,159
and is absorbed by the ground,
767
00:39:01,160 --> 00:39:04,199
but, unless temperatures
rise above freezing,
768
00:39:04,200 --> 00:39:06,599
snow stays
right where it lands.
769
00:39:06,600 --> 00:39:09,799
This means a lot of work
for cities and communities
770
00:39:09,800 --> 00:39:11,519
to clear the snow off roads,
771
00:39:11,520 --> 00:39:14,039
roofs and vehicles.
772
00:39:14,040 --> 00:39:17,119
It can take days
for even a well-prepared city
773
00:39:17,120 --> 00:39:20,119
to recover use of all roads.
774
00:39:20,120 --> 00:39:25,159
For those not used to snowfall,
the situation is much worse.
775
00:39:33,560 --> 00:39:35,359
Uncharacteristically,
776
00:39:35,360 --> 00:39:38,359
in the 2015-16 El Niño,
777
00:39:38,360 --> 00:39:40,759
Peru wasn't affected.
778
00:39:40,760 --> 00:39:42,759
The year after,
however,
779
00:39:42,760 --> 00:39:46,119
serious rains and floods
struck the country.
780
00:39:46,120 --> 00:39:48,599
Between January
and February 2017,
781
00:39:48,600 --> 00:39:50,679
a region of northern Peru
and Ecuador,
782
00:39:50,680 --> 00:39:51,959
which is a desert region,
783
00:39:51,960 --> 00:39:54,359
received considerable amounts
of rain.
784
00:39:54,360 --> 00:39:56,359
Rivers burst their banks.
785
00:39:56,360 --> 00:39:58,959
Houses were under
a meter or sometimes...
786
00:39:58,960 --> 00:40:00,799
sometimes two meters of water.
787
00:40:00,800 --> 00:40:03,999
This resulted in considerable
destruction to infrastructure
788
00:40:04,000 --> 00:40:06,359
and property and fatalities.
789
00:40:06,360 --> 00:40:08,639
And this is
particularly difficult
790
00:40:08,640 --> 00:40:10,199
for the region to deal with
791
00:40:10,200 --> 00:40:11,999
when you consider
that it's a region
792
00:40:12,000 --> 00:40:15,319
that often receives just a few
millimeters of rainfall
793
00:40:15,320 --> 00:40:16,919
or no rainfall at ll.
794
00:40:16,920 --> 00:40:18,279
And suddenly, it received
795
00:40:18,280 --> 00:40:20,199
several tens of centimeters
of rainfall
796
00:40:20,200 --> 00:40:21,959
in a very short period
of time.
797
00:40:21,960 --> 00:40:23,479
The wet weather was caused
798
00:40:23,480 --> 00:40:25,119
by a warming of the ocean
799
00:40:25,120 --> 00:40:27,519
off the coast of Peru
and Ecuador.
800
00:40:27,520 --> 00:40:31,359
The locals referred to it
as an El Niño.
801
00:40:31,360 --> 00:40:34,279
But the rest of the world
remained unaffected.
802
00:40:34,280 --> 00:40:38,279
This illustrates just
how limited our understanding
803
00:40:38,280 --> 00:40:41,799
of the El Niño Southern
Oscillation system is.
804
00:40:41,800 --> 00:40:45,199
Scientists across the world
can't always agree
805
00:40:45,200 --> 00:40:48,439
on what is and what isn't
an El Niño.
806
00:41:07,960 --> 00:41:11,839
Some of Peru's poorest
were most severely hit.
807
00:41:11,840 --> 00:41:15,719
Many had set up home
in gulches and canyons
808
00:41:15,720 --> 00:41:19,279
that opened from the mountains
onto the coast.
809
00:41:19,280 --> 00:41:20,959
Dry for years,
810
00:41:20,960 --> 00:41:23,959
they suddenly turned
into raging torrents,
811
00:41:23,960 --> 00:41:28,199
engulfing and sweeping away
whole shanty towns.
812
00:41:54,120 --> 00:41:56,759
The rains also washed rubbish,
813
00:41:56,760 --> 00:41:59,199
chemicals and metals from towns,
814
00:41:59,200 --> 00:42:02,839
mines and farms
into the Pacific Ocean.
815
00:42:02,840 --> 00:42:07,559
Warm coastal waters drove out
schools of Peruvian anchovies,
816
00:42:07,560 --> 00:42:10,319
depriving birds
of their main food supply
817
00:42:10,320 --> 00:42:12,839
and forcing them
to hunt elsewhere.
818
00:42:12,840 --> 00:42:15,359
Two thirds
of the Guanay cormorants
819
00:42:15,360 --> 00:42:18,679
on the south-central coast
abandoned their nests.
820
00:42:18,680 --> 00:42:21,479
On top of the effect
on the ecosystem,
821
00:42:21,480 --> 00:42:23,999
losing the birds
reduced the guano,
822
00:42:24,000 --> 00:42:26,319
which is still mined
in the area.
823
00:42:26,320 --> 00:42:30,359
Tourists in Machu Picchu
were stranded by mudslides
824
00:42:30,360 --> 00:42:33,119
and had to be airlifted
to safety.
825
00:42:33,120 --> 00:42:36,319
Peru's 2017 El Niño event
826
00:42:36,320 --> 00:42:39,359
was one of the most costly
disasters to hit Peru
827
00:42:39,360 --> 00:42:41,999
since 1997-98.
828
00:42:59,800 --> 00:43:02,999
It underlined again
how unpredictable
829
00:43:03,000 --> 00:43:07,079
and ill-prepared we were to
deal with its chaotic effects.
830
00:43:07,080 --> 00:43:10,799
The recovery from that
can take a very long time,
831
00:43:10,800 --> 00:43:13,239
particularly in relation
to investments,
832
00:43:13,240 --> 00:43:15,119
in rebuilding infrastructure,
833
00:43:15,120 --> 00:43:17,239
so roads and bridges and so on,
834
00:43:17,240 --> 00:43:19,959
to get the money
to be able to recover
835
00:43:19,960 --> 00:43:21,519
and rebuild that infrastructure
836
00:43:21,520 --> 00:43:24,639
can take a poor country
an extremely long time.
837
00:43:24,640 --> 00:43:26,679
If El Niño's erratic nature
838
00:43:26,680 --> 00:43:28,719
was not difficult enough
to deal with,
839
00:43:28,720 --> 00:43:31,159
the phenomenon
has a twin sister,
840
00:43:31,160 --> 00:43:32,919
La Niña.
841
00:43:32,920 --> 00:43:35,239
La Niña is the opposite,
842
00:43:35,240 --> 00:43:39,079
the cold phase of the El Niño
Southern Oscillation.
843
00:43:39,080 --> 00:43:41,199
It happens when sea surface
temperatures
844
00:43:41,200 --> 00:43:44,759
in the central Pacific Ocean
fall below normal.
845
00:43:44,760 --> 00:43:46,639
In the United States,
846
00:43:46,640 --> 00:43:51,039
a La Niña winter means more
rain in the Pacific Northwest,
847
00:43:51,040 --> 00:43:55,359
short spells of below-average
temperatures in the Northeast,
848
00:43:55,360 --> 00:43:57,999
and generally dry
and mild conditions
849
00:43:58,000 --> 00:44:00,279
for the southern states.
850
00:44:00,280 --> 00:44:02,239
Whilst an El Niño can spark
851
00:44:02,240 --> 00:44:05,159
streams of moisture
into California,
852
00:44:05,160 --> 00:44:07,559
a La Niña winter stops storms
853
00:44:07,560 --> 00:44:10,159
from delivering snow and rain
to the region,
854
00:44:10,160 --> 00:44:12,679
leading to droughts.
855
00:44:12,680 --> 00:44:15,599
Western Canada
and the Northwest
856
00:44:15,600 --> 00:44:19,559
suffer the most from storms
during a La Niña winter.
857
00:44:19,560 --> 00:44:22,159
La Niña makes winters
in the Northeast
858
00:44:22,160 --> 00:44:24,479
extremely unpredictable.
859
00:44:24,480 --> 00:44:29,239
They can range from colder and
drier to milder and stormier.
860
00:44:29,240 --> 00:44:33,599
La Niña also creates perfect
conditions for cyclone systems
861
00:44:33,600 --> 00:44:35,719
over the Atlantic.
862
00:44:35,720 --> 00:44:38,279
Lasting from 10 to 12 months,
863
00:44:38,280 --> 00:44:40,799
La Niña does not
always develop
864
00:44:40,800 --> 00:44:43,159
immediately after an El Niño.
865
00:44:43,160 --> 00:44:47,119
However, evidence suggests
that strong El Niños
866
00:44:47,120 --> 00:44:50,239
are more likely
to turn into La Niñas.
867
00:44:50,240 --> 00:44:53,639
Quite regularly,
you will find that an area
868
00:44:53,640 --> 00:44:55,319
that was affected
by an El Niño
869
00:44:55,320 --> 00:44:59,239
is then immediately affected by
the La Niña that comes after it.
870
00:44:59,240 --> 00:45:01,719
Having an El Niño and La Niña
year in quick succession
871
00:45:01,720 --> 00:45:03,239
can be devastating
for a country,
872
00:45:03,240 --> 00:45:05,839
particularly countries that are
poorly resourced,
873
00:45:05,840 --> 00:45:07,519
poorer countries.
874
00:45:07,520 --> 00:45:10,719
Alarmingly, La Niña years
875
00:45:10,720 --> 00:45:13,159
have clearly shown
greater average annual losses
876
00:45:13,160 --> 00:45:17,159
in comparison to El Niño
and neutral phases.
877
00:45:17,160 --> 00:45:21,119
Much of the increase in losses
during a La Niña year
878
00:45:21,120 --> 00:45:24,279
is due to tropical cyclones
making landfall
879
00:45:24,280 --> 00:45:27,319
more frequently in
the Atlantic Ocean basin
880
00:45:27,320 --> 00:45:30,799
and increased flooding
across the Asia Pacific.
881
00:45:30,800 --> 00:45:34,479
It is believed there have now
been three "super El Niños"
882
00:45:34,480 --> 00:45:37,119
in just over three decades,
883
00:45:37,120 --> 00:45:39,839
suggesting these "super El Niños"
884
00:45:39,840 --> 00:45:42,759
might start occurring
once every 10 years,
885
00:45:42,760 --> 00:45:45,439
instead of once every 20.
886
00:45:47,760 --> 00:45:50,999
El Niño,
and its twin sister, La Niña,
887
00:45:51,000 --> 00:45:52,839
are a strong reminder
888
00:45:52,840 --> 00:45:56,519
to communities vulnerable
to changing weather patterns.
889
00:45:56,520 --> 00:45:59,759
They are going to need
longer-term help adapting.
890
00:45:59,760 --> 00:46:03,639
The UN has warned
that humanitarian disasters
891
00:46:03,640 --> 00:46:06,839
are to be expected
with climate change.
892
00:46:06,840 --> 00:46:09,439
We can see how the effects
of El Niño
893
00:46:09,440 --> 00:46:11,199
can combine
with climate change
894
00:46:11,200 --> 00:46:14,479
most starkly
in the Pacific Islands.
895
00:46:14,480 --> 00:46:17,959
Although the relationship
between El Niño and drought
896
00:46:17,960 --> 00:46:20,119
in the region is well known,
897
00:46:20,120 --> 00:46:23,799
it remains unclear
how global warming might alter
898
00:46:23,800 --> 00:46:26,880
the El Niño phenomenon
in the future.
899
00:46:30,800 --> 00:46:34,559
The islands' residents
are deeply anxious.
900
00:46:34,560 --> 00:46:37,079
Rising sea levels
are already swallowing
901
00:46:37,080 --> 00:46:39,039
the little land
they have.
902
00:46:39,040 --> 00:46:41,559
They also threaten
water supplies,
903
00:46:41,560 --> 00:46:44,559
as the waves that can make
groundwater saline
904
00:46:44,560 --> 00:46:47,079
become more frequent.
905
00:46:47,080 --> 00:46:49,359
It is rainfall's variability,
906
00:46:49,360 --> 00:46:51,039
not average rains,
907
00:46:51,040 --> 00:46:53,159
that mainly drive
drought here.
908
00:46:53,160 --> 00:46:58,599
And the main source
of variability is El Niño.
909
00:46:58,600 --> 00:47:01,599
The study of the El Niño
Southern Oscillation
910
00:47:01,600 --> 00:47:04,319
is a relatively
new field of research.
911
00:47:04,320 --> 00:47:07,999
We are still struggling to
understand its unpredictability
912
00:47:08,000 --> 00:47:11,279
and how we can mitigate
its effects.
913
00:47:11,280 --> 00:47:13,719
Our forecasting
is based on data
914
00:47:13,720 --> 00:47:16,279
gathered over a quarter
of a century ago.
915
00:47:16,280 --> 00:47:20,039
More recent research
and satellite data
916
00:47:20,040 --> 00:47:23,719
suggests that the impact
of El Niño Southern Oscillation
917
00:47:23,720 --> 00:47:27,719
is much wider
than originally believed.
918
00:47:27,720 --> 00:47:31,519
Europe, Africa, Asia
and North America
919
00:47:31,520 --> 00:47:33,759
are all likely to have
been affected
920
00:47:33,760 --> 00:47:36,199
in ways we hadn't realized:
921
00:47:36,200 --> 00:47:39,439
air temperatures, rains,
922
00:47:39,440 --> 00:47:41,359
and in North
and South America,
923
00:47:41,360 --> 00:47:45,560
significant impacts across
a larger area than we thought.
924
00:47:48,000 --> 00:47:51,199
Factors like climate change
are only likely to increase
925
00:47:51,200 --> 00:47:55,759
El Niño Southern Oscillation's
unpredictability.
926
00:47:55,760 --> 00:47:58,119
El Niño and La Niña
927
00:47:58,120 --> 00:48:02,159
are challenging governments
and international organizations
928
00:48:02,160 --> 00:48:05,079
to consider and build
this unpredictability
929
00:48:05,080 --> 00:48:07,199
into their planning.
930
00:48:07,200 --> 00:48:10,519
We still grapple to understand
the full impact
931
00:48:10,520 --> 00:48:12,999
of El Niño's
Southern Oscillation.
932
00:48:13,000 --> 00:48:17,999
The only certainty seems to be
the misery and devastation
933
00:48:18,000 --> 00:48:19,800
brought in its wake.
78499
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