All language subtitles for D D S02E08 El Nino 1080p AMZN WEB-DL DD2 0 H 264-playWEB_track3_[eng]

af Afrikaans
ak Akan
sq Albanian
am Amharic
ar Arabic
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bem Bemba
bn Bengali
bh Bihari
bs Bosnian
br Breton
bg Bulgarian
km Cambodian
ca Catalan
ceb Cebuano
chr Cherokee
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
ee Ewe
fo Faroese
tl Filipino
fi Finnish
fr French
fy Frisian
gaa Ga
gl Galician
ka Georgian
de German
gn Guarani
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hmn Hmong
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ia Interlingua
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
rw Kinyarwanda
rn Kirundi
kg Kongo
ko Korean
kri Krio (Sierra Leone)
ku Kurdish
ckb Kurdish (Soranî)
ky Kyrgyz
lo Laothian
la Latin
lv Latvian
ln Lingala
lt Lithuanian
loz Lozi
lg Luganda
ach Luo
lb Luxembourgish
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mfe Mauritian Creole
mo Moldavian
mn Mongolian
my Myanmar (Burmese)
sr-ME Montenegrin
ne Nepali
pcm Nigerian Pidgin
nso Northern Sotho
no Norwegian
nn Norwegian (Nynorsk)
oc Occitan
or Oriya
om Oromo
ps Pashto
fa Persian
pl Polish
pt-BR Portuguese (Brazil)
pt Portuguese (Portugal)
pa Punjabi
qu Quechua
ro Romanian
rm Romansh
nyn Runyakitara
ru Russian
sm Samoan
gd Scots Gaelic
sr Serbian
sh Serbo-Croatian
st Sesotho
tn Setswana
crs Seychellois Creole
sn Shona
sd Sindhi
si Sinhalese
sk Slovak
sl Slovenian
so Somali
es Spanish
es-419 Spanish (Latin American)
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
tt Tatar
te Telugu
th Thai
ti Tigrinya
to Tonga
lua Tshiluba
tum Tumbuka
tr Turkish
tk Turkmen
tw Twi
ug Uighur
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
wo Wolof
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu
Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:25,800 --> 00:00:28,399 What connects seemingly random events 2 00:00:28,400 --> 00:00:31,559 like floods in the United Kingdom, 3 00:00:31,560 --> 00:00:34,519 droughts in Africa, 4 00:00:34,520 --> 00:00:37,479 wildfires in Canada 5 00:00:37,480 --> 00:00:39,560 and cyclones in the Pacific? 6 00:00:41,680 --> 00:00:43,039 A boy. 7 00:00:43,040 --> 00:00:44,999 "El Niño" in Spanish. 8 00:00:45,000 --> 00:00:47,119 It's the innocent-sounding name 9 00:00:47,120 --> 00:00:49,599 that Peruvian fishermen gave 10 00:00:49,600 --> 00:00:54,119 to a climate phenomenon that regularly devastates our world. 11 00:00:54,120 --> 00:00:56,199 There is no single phenomenon in the world 12 00:00:56,200 --> 00:00:58,319 that can affect global weather patterns 13 00:00:58,320 --> 00:00:59,759 as much as El Niño 14 00:00:59,760 --> 00:01:01,239 and is, therefore, associated 15 00:01:01,240 --> 00:01:04,239 with as many natural disasters as El Niño is. 16 00:01:04,240 --> 00:01:06,359 One major El Niño event 17 00:01:06,360 --> 00:01:12,999 that started in 2015 and which only ended in 2016, 18 00:01:13,000 --> 00:01:15,919 contributed to catastrophic weather events 19 00:01:15,920 --> 00:01:18,159 right across the globe. 20 00:01:18,160 --> 00:01:22,039 El Niño of 2015-16 was one of the major 21 00:01:22,040 --> 00:01:23,919 and most intense El Niños 22 00:01:23,920 --> 00:01:26,999 that we've seen in the historical record. 23 00:01:27,000 --> 00:01:31,279 It contributed to the longest coral bleaching ever recorded, 24 00:01:31,280 --> 00:01:33,559 stretching across the oceans 25 00:01:33,560 --> 00:01:38,079 from Florida Keys to the Great Barrier Reef. 26 00:01:38,080 --> 00:01:43,239 Africa, Malawi, Zimbabwe, South Africa, 27 00:01:43,240 --> 00:01:47,519 Mozambique and Ethiopia all suffered devastating drought, 28 00:01:47,520 --> 00:01:52,439 inflicting hunger and disease on millions. 29 00:01:52,440 --> 00:01:54,759 South America struggled to cope 30 00:01:54,760 --> 00:01:58,039 with both drought and extreme storms. 31 00:01:58,040 --> 00:02:01,519 The Pacific Ocean's vulnerable, low-lying islands 32 00:02:01,520 --> 00:02:05,359 were hit by several cyclones, one after the other. 33 00:02:05,360 --> 00:02:07,519 And southeast Asia recorded 34 00:02:07,520 --> 00:02:12,839 the largest emissions of wildfire and smoke ever. 35 00:02:12,840 --> 00:02:15,519 So extensive was El Niño's impact 36 00:02:15,520 --> 00:02:18,559 that it even played a part in major disasters 37 00:02:18,560 --> 00:02:20,959 across Europe. 38 00:02:20,960 --> 00:02:24,879 The United Kingdom was hit by wave after wave 39 00:02:24,880 --> 00:02:29,479 of record-breaking storms and floods. 40 00:02:29,480 --> 00:02:32,519 Floods can kill. Floods annihilate. 41 00:02:32,520 --> 00:02:34,919 They destroy. They're incredibly dangerous. 42 00:02:34,920 --> 00:02:38,159 In this episode of Deadly Disasters, 43 00:02:38,160 --> 00:02:40,479 we will look at this climate phenomenon 44 00:02:40,480 --> 00:02:44,239 that has affected the entire world for millennia. 45 00:02:49,240 --> 00:02:51,359 Our experts will look at some 46 00:02:51,360 --> 00:02:54,439 of the most catastrophic consequences of El Niño, 47 00:02:54,440 --> 00:02:56,759 and its little sister, La Niña. 48 00:02:56,760 --> 00:02:58,239 another climate event 49 00:02:58,240 --> 00:03:02,559 with devastating effects around the globe. 50 00:03:02,560 --> 00:03:04,519 Many of them are immediately felt, 51 00:03:04,520 --> 00:03:09,159 and they cause death and destruction and disruption. 52 00:03:09,160 --> 00:03:12,359 We will examine the differences and similarities 53 00:03:12,360 --> 00:03:15,239 between these two climate-changing incidents. 54 00:03:17,280 --> 00:03:19,359 We will consider how different countries 55 00:03:19,360 --> 00:03:21,159 have managed their impacts, 56 00:03:21,160 --> 00:03:23,839 particularly in the developing world, 57 00:03:23,840 --> 00:03:26,999 where resources can be stretched thin. 58 00:03:27,000 --> 00:03:31,239 Eyewitness reports will tell the human story behind El Niño 59 00:03:31,240 --> 00:03:34,200 and the personal toll these disasters take. 60 00:03:37,920 --> 00:03:43,279 El Niño is a climate phenomenon that happens every few years, 61 00:03:43,280 --> 00:03:46,679 when the waters in the eastern tropical Pacific Ocean 62 00:03:46,680 --> 00:03:48,719 get unusually warm. 63 00:03:48,720 --> 00:03:51,159 Normally, this warm water, 64 00:03:51,160 --> 00:03:53,399 and the rainy conditions it causes, 65 00:03:53,400 --> 00:03:55,559 are in the western Pacific. 66 00:03:55,560 --> 00:03:58,759 There, the sea level is naturally higher. 67 00:03:58,760 --> 00:04:02,799 In fact, normally around 40 to 50 centimeters higher 68 00:04:02,800 --> 00:04:05,759 near Indonesia than Ecuador. 69 00:04:05,760 --> 00:04:08,639 This is, in part, because of strong trade winds 70 00:04:08,640 --> 00:04:11,239 blowing westward across the Pacific. 71 00:04:11,240 --> 00:04:14,759 They push water toward Asia and Oceania, 72 00:04:14,760 --> 00:04:19,399 where it gathers and creates a slightly tilted ocean surface. 73 00:04:19,400 --> 00:04:22,919 El Niño causes droughts in normally damp areas 74 00:04:22,920 --> 00:04:24,439 in the eastern Pacific, 75 00:04:24,440 --> 00:04:28,039 such as Indonesia and Australia, 76 00:04:28,040 --> 00:04:30,039 while normally drier places, 77 00:04:30,040 --> 00:04:32,039 like South America's west coast, 78 00:04:32,040 --> 00:04:34,479 endure devastating floods. 79 00:04:34,480 --> 00:04:38,479 But it also impacts the global atmospheric circulation. 80 00:04:38,480 --> 00:04:41,199 It can weaken the Indian monsoon, 81 00:04:41,200 --> 00:04:45,040 while bringing heavy rain to the western United States. 82 00:04:46,800 --> 00:04:48,439 We are only just beginning 83 00:04:48,440 --> 00:04:51,239 to understand this powerful phenomenon. 84 00:04:53,000 --> 00:04:54,919 Essentially, El Niño is quite a new science. 85 00:04:54,920 --> 00:04:58,759 El Niño have only really been known about for about 100 years, 86 00:04:58,760 --> 00:05:01,919 and it's only been observed properly for about 40 years, 87 00:05:01,920 --> 00:05:05,039 during which time there's been maybe four big events. 88 00:05:05,040 --> 00:05:07,759 The first recorded scientific discussions 89 00:05:07,760 --> 00:05:10,599 of El Niño were in the 1890s, 90 00:05:10,600 --> 00:05:13,519 between the Lima Geographical Society 91 00:05:13,520 --> 00:05:16,919 and the International Geographic Congress. 92 00:05:16,920 --> 00:05:20,279 But we now know that it stretches at least as far back 93 00:05:20,280 --> 00:05:21,959 as 10,000 years, 94 00:05:21,960 --> 00:05:24,479 to the beginning of the Holocene Epoch, 95 00:05:24,480 --> 00:05:27,319 and the end of the last Ice Age. 96 00:05:27,320 --> 00:05:29,999 We have detected chemical signatures 97 00:05:30,000 --> 00:05:32,839 of increased rainfall and warmer seas 98 00:05:32,840 --> 00:05:36,359 in coral samples and other paleoclimate indicators 99 00:05:36,360 --> 00:05:38,759 since the previous Ice Age. 100 00:05:38,760 --> 00:05:41,119 Climate scientists have also shown 101 00:05:41,120 --> 00:05:43,719 that tree-ring records from North America, 102 00:05:43,720 --> 00:05:45,879 especially from the Southwest, 103 00:05:45,880 --> 00:05:48,559 match the intensity of El Niño events 104 00:05:48,560 --> 00:05:51,559 over the last 1100 years. 105 00:05:51,560 --> 00:05:53,799 These tree rings coincide well 106 00:05:53,800 --> 00:05:57,399 with the 150 year sea surface temperature records 107 00:05:57,400 --> 00:06:00,599 we have from the Pacific. 108 00:06:00,600 --> 00:06:02,399 During El Niño, 109 00:06:02,400 --> 00:06:05,599 the warmer surface temperatures in the eastern Pacific 110 00:06:05,600 --> 00:06:08,439 change the atmospheric circulation. 111 00:06:08,440 --> 00:06:10,719 This causes unusually wet winters 112 00:06:10,720 --> 00:06:15,359 in the southwest United States, and thus wider tree rings. 113 00:06:15,360 --> 00:06:19,439 This research was used to help improve El Niño prediction 114 00:06:19,440 --> 00:06:21,279 in climate models. 115 00:06:21,280 --> 00:06:23,399 Predicting its likely events 116 00:06:23,400 --> 00:06:26,319 over a few months ahead is now normal. 117 00:06:26,320 --> 00:06:28,959 But our recognition of El Niño 118 00:06:28,960 --> 00:06:32,199 and its impacts is helping us look at our history 119 00:06:32,200 --> 00:06:33,999 with fresh eyes. 120 00:06:34,000 --> 00:06:35,479 For instance, 121 00:06:35,480 --> 00:06:39,839 we know that from 1789 to 1792, 122 00:06:39,840 --> 00:06:43,919 the South Asia monsoon failed many times. 123 00:06:43,920 --> 00:06:46,319 Research suggests the El Niño 124 00:06:46,320 --> 00:06:48,999 influenced a mix of climate anomalies, 125 00:06:49,000 --> 00:06:53,279 and unusual weather led to crop failures in Europe. 126 00:06:53,280 --> 00:06:56,319 This, in turn, became the catalyst 127 00:06:56,320 --> 00:06:59,119 for some of the troubles and desperate anger that, 128 00:06:59,120 --> 00:07:03,519 in 1789, erupted into the French Revolution. 129 00:07:03,520 --> 00:07:07,159 El Niño has been linked to at least three large famines 130 00:07:07,160 --> 00:07:09,599 in the late 19th century. 131 00:07:09,600 --> 00:07:11,519 British and Indian officials 132 00:07:11,520 --> 00:07:13,199 noted that extreme weather 133 00:07:13,200 --> 00:07:15,759 and the collapse of monsoon circulation 134 00:07:15,760 --> 00:07:19,039 resulted in great droughts and floods. 135 00:07:19,040 --> 00:07:22,799 Between 30 to 60 million people died in China, 136 00:07:22,800 --> 00:07:24,639 India and Brazil. 137 00:07:24,640 --> 00:07:27,719 Hundreds of millions endured hunger. 138 00:07:27,720 --> 00:07:30,079 It was only in the 1960s 139 00:07:30,080 --> 00:07:32,719 that scientists definitively linked 140 00:07:32,720 --> 00:07:35,039 the alternating warm and cool patterns 141 00:07:35,040 --> 00:07:36,679 in the Pacific waters 142 00:07:36,680 --> 00:07:39,159 and the atmospheric circulation. 143 00:07:39,160 --> 00:07:44,359 At least 26 El Niños were recorded in the last century. 144 00:07:44,360 --> 00:07:46,999 In 1957-58, 145 00:07:47,000 --> 00:07:49,199 El Niño caused serious damage 146 00:07:49,200 --> 00:07:51,639 to the Californian kelp forests. 147 00:07:51,640 --> 00:07:54,759 It was only in 1982-83 148 00:07:54,760 --> 00:07:58,599 that scientists were able to study a major El Niño 149 00:07:58,600 --> 00:08:00,999 as it was actually taking place. 150 00:08:01,000 --> 00:08:04,479 The unusually warm waters in the Pacific 151 00:08:04,480 --> 00:08:07,919 forced fish to seek out colder waters to survive. 152 00:08:07,920 --> 00:08:09,599 On Christmas Island, 153 00:08:09,600 --> 00:08:11,919 sea birds abandoned their young 154 00:08:11,920 --> 00:08:15,879 to fly over the Pacific desperately searching for food. 155 00:08:15,880 --> 00:08:20,159 Almost a quarter of the fur seal and sea lion populations 156 00:08:20,160 --> 00:08:24,519 off the Peruvian coast starved to death. 157 00:08:24,520 --> 00:08:27,159 Some of the biggest effects on wildlife 158 00:08:27,160 --> 00:08:29,359 that we've known about for the longest with El Niño 159 00:08:29,360 --> 00:08:30,639 is what happens off Peru. 160 00:08:30,640 --> 00:08:32,359 You have deaths of sea birds. 161 00:08:32,360 --> 00:08:34,999 You have deaths of seals, and in some years, 162 00:08:35,000 --> 00:08:38,439 collapses in population of Galapagos penguins. 163 00:08:38,440 --> 00:08:42,439 Indonesia and Australia faced terrible droughts 164 00:08:42,440 --> 00:08:45,359 and Southeast Asia shut down some of its airports 165 00:08:45,360 --> 00:08:50,359 because of the thick plumes of smoke rising from forest fires. 166 00:08:50,360 --> 00:08:53,479 El Niño is associated with extreme weather 167 00:08:53,480 --> 00:08:56,799 and natural disasters in many, many countries in the world. 168 00:08:56,800 --> 00:08:58,479 In Spanish, 169 00:08:58,480 --> 00:09:02,599 "El Niño" translates as "The Child" or "The Boy." 170 00:09:02,600 --> 00:09:05,399 The name was given by Peruvian fishermen 171 00:09:05,400 --> 00:09:08,199 who noticed the occasional warming of the ocean 172 00:09:08,200 --> 00:09:09,839 around December 173 00:09:09,840 --> 00:09:13,519 and made the connection to Christmas and Jesus. 174 00:09:13,520 --> 00:09:15,839 El Niño and La Niña, 175 00:09:15,840 --> 00:09:18,439 which translates to "The Girl," 176 00:09:18,440 --> 00:09:20,199 are opposite phases 177 00:09:20,200 --> 00:09:24,439 of the El Niño Southern Oscillation cycle of ENSO. 178 00:09:24,440 --> 00:09:27,879 ENSO is the name for the temperature variations 179 00:09:27,880 --> 00:09:30,359 between the ocean and atmosphere 180 00:09:30,360 --> 00:09:32,359 in the Equatorial Pacific. 181 00:09:32,360 --> 00:09:38,039 El Niño is the warm and La Niña the cold phase of the ENSO. 182 00:09:38,040 --> 00:09:40,159 El Niño is officially declared 183 00:09:40,160 --> 00:09:43,159 if the eastern tropical Pacific's surface temperature 184 00:09:43,160 --> 00:09:48,359 rises half a degree centigrade above the long-term average. 185 00:09:48,360 --> 00:09:54,279 One of the most severe El Niño events was in 1997-98, 186 00:09:54,280 --> 00:09:56,639 when the Pacific heated up remarkably, 187 00:09:56,640 --> 00:10:00,479 by more than three degrees centigrade. 188 00:10:00,480 --> 00:10:02,599 The effects of climate change 189 00:10:02,600 --> 00:10:06,159 on the cycle are not yet fully established. 190 00:10:06,160 --> 00:10:08,679 Some scientists believe climate change 191 00:10:08,680 --> 00:10:12,239 will make ENSO events more frequent and intense. 192 00:10:12,240 --> 00:10:15,399 If right, it is likely that the economic, 193 00:10:15,400 --> 00:10:18,039 environmental and societal impacts 194 00:10:18,040 --> 00:10:20,999 will only get more extreme. 195 00:10:21,000 --> 00:10:23,639 The three most deadly El Niños, 196 00:10:23,640 --> 00:10:26,199 1982-83, 197 00:10:26,200 --> 00:10:31,119 1997-98 and 2015-16 198 00:10:31,120 --> 00:10:32,639 were not just because 199 00:10:32,640 --> 00:10:34,559 of the scale of the chaos they wreaked. 200 00:10:34,560 --> 00:10:37,039 But also because of how unpredictable 201 00:10:37,040 --> 00:10:38,559 their effects were. 202 00:10:38,560 --> 00:10:40,599 It is not certain what tips 203 00:10:40,600 --> 00:10:43,639 the unstable Pacific Ocean atmosphere system 204 00:10:43,640 --> 00:10:45,639 into El Niño, 205 00:10:45,640 --> 00:10:50,239 but a weakening of normal trade winds that blow west is key. 206 00:10:50,240 --> 00:10:53,799 For instance, in 2014, 207 00:10:53,800 --> 00:10:57,439 a large group of very strong thunderstorms over Indonesia 208 00:10:57,440 --> 00:10:59,399 may have been the trigger. 209 00:10:59,400 --> 00:11:03,159 An upwelling or upward movement of ocean water 210 00:11:03,160 --> 00:11:06,879 can mix upper and lower levels of seawater together. 211 00:11:06,880 --> 00:11:09,959 This brings cool and nutrient-rich water 212 00:11:09,960 --> 00:11:13,119 from the bottom of the ocean to the warmer surface. 213 00:11:13,120 --> 00:11:17,119 There, it supports large populations of phytoplankton, 214 00:11:17,120 --> 00:11:21,399 zooplankton, fish, and fish-eating seabirds. 215 00:11:21,400 --> 00:11:23,159 Every few years, 216 00:11:23,160 --> 00:11:27,839 normal upwelling in the Pacific Ocean is affected by ENSO. 217 00:11:27,840 --> 00:11:29,839 During an ENSO, 218 00:11:29,840 --> 00:11:33,439 the trade winds that blow from east to west weaken. 219 00:11:33,440 --> 00:11:36,639 This allows the warmer waters of the western Pacific 220 00:11:36,640 --> 00:11:39,919 to move towards the western coast of South America. 221 00:11:39,920 --> 00:11:43,159 This suppresses the normal upwellings of cold, 222 00:11:43,160 --> 00:11:45,359 nutrient-rich water. 223 00:11:45,360 --> 00:11:47,759 The marine food chain is disrupted. 224 00:11:47,760 --> 00:11:52,759 Warm waters force fish down to colder, deeper water. 225 00:11:52,760 --> 00:11:56,359 Seals suffer as they lose their food source. 226 00:11:56,360 --> 00:11:59,199 In the same way, the fishing economies 227 00:11:59,200 --> 00:12:03,719 of countries such as Peru and Ecuador are also hit. 228 00:12:03,720 --> 00:12:05,839 We are still trying to work out 229 00:12:05,840 --> 00:12:10,359 the relationship between El Niño and climate change. 230 00:12:10,360 --> 00:12:11,839 What will happen to El Niños 231 00:12:11,840 --> 00:12:13,839 under climate change, global warming, 232 00:12:13,840 --> 00:12:15,999 is a question that many people ask. 233 00:12:16,000 --> 00:12:17,599 Some studies are suggesting 234 00:12:17,600 --> 00:12:20,159 there may be an increase in frequency and intensity, 235 00:12:20,160 --> 00:12:23,239 but other studies suggest that that may not be the case. 236 00:12:23,240 --> 00:12:26,199 So at the moment, there isn't a strong consensus 237 00:12:26,200 --> 00:12:28,079 about future behavior. 238 00:12:28,080 --> 00:12:30,879 But the global system is changing 239 00:12:30,880 --> 00:12:32,479 because of global warming, 240 00:12:32,480 --> 00:12:34,479 so we're very likely to see a change 241 00:12:34,480 --> 00:12:37,399 in the patterns of El Niño. 242 00:12:37,400 --> 00:12:40,439 We know that a rise in global temperatures 243 00:12:40,440 --> 00:12:43,999 leads to an increase in sea surface temperatures. 244 00:12:46,880 --> 00:12:50,079 This is what sparks the El Niño phenomenon. 245 00:12:50,080 --> 00:12:53,839 The relationship between El Niño and a change in climate 246 00:12:53,840 --> 00:12:55,999 is somewhat cyclical. 247 00:12:56,000 --> 00:12:58,999 Oceans act as carbon sinks: 248 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. 250 00:13:03,760 --> 00:13:08,919 And carbon dioxide dissolves more easily in colder waters. 251 00:13:08,920 --> 00:13:10,759 During El Niño, 252 00:13:10,760 --> 00:13:13,719 sea surface temperatures increase. 253 00:13:13,720 --> 00:13:16,999 This causes less CO2 to be dissolved. 254 00:13:17,000 --> 00:13:20,839 The result is more carbon dioxide in the atmosphere, 255 00:13:20,840 --> 00:13:22,879 which causes global warming, 256 00:13:22,880 --> 00:13:26,319 which in turn leads to the climate changing. 257 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

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.