1 00:00:01,320 --> 00:00:03,000 Speaker 1: More extreme weather could be on the way. 2 00:00:03,040 --> 00:00:06,600 Speaker 2: The National Oceanic and Atmospheric Administration is issued in Alnino watch. 3 00:00:06,720 --> 00:00:10,760 Speaker 1: Jez El Nino has become very popular again after forecasters 4 00:00:10,760 --> 00:00:13,760 Speaker 1: with Noah declared its arrival in the Pacific Ocean. 5 00:00:13,880 --> 00:00:14,720 Speaker 3: Some people are now. 6 00:00:14,600 --> 00:00:17,799 Speaker 1: Asking if California is in for another wet winter. 7 00:00:17,800 --> 00:00:20,720 Speaker 2: Almost two weeks into the Atlantic hurricane season and ten 8 00:00:20,800 --> 00:00:23,840 Speaker 2: days since we had the first name storm Arlene, and 9 00:00:23,880 --> 00:00:27,600 Speaker 2: it's official Noah's declaring al Nino is here, yeh. 10 00:00:27,600 --> 00:00:29,760 Speaker 3: If you've been thinking the weather and the effects of 11 00:00:29,840 --> 00:00:35,519 Speaker 3: climate change have been extra volatile lately, droughts, wildfires, you 12 00:00:35,840 --> 00:00:40,360 Speaker 3: name it, well, race yourself, because the arrival of the 13 00:00:40,440 --> 00:00:44,599 Speaker 3: first al Nino in almost four years is expected to 14 00:00:44,640 --> 00:00:47,560 Speaker 3: cause new kinds of upheaval across the globe. 15 00:00:47,760 --> 00:00:49,960 Speaker 1: If we looked at North America, for instance, what you 16 00:00:50,000 --> 00:00:53,000 Speaker 1: would see next winter in the al Nino is you 17 00:00:53,000 --> 00:00:57,560 Speaker 1: would see a wetter, stormier part of the southern United States, 18 00:00:57,560 --> 00:01:01,040 Speaker 1: for instance, and a drier southern tier of Canada. 19 00:01:01,640 --> 00:01:05,920 Speaker 2: Scientists suggesting El Nino causes trillions of dollars in lost 20 00:01:05,959 --> 00:01:09,000 Speaker 2: economic growth could be more expensive cup of coffee, or 21 00:01:09,200 --> 00:01:11,279 Speaker 2: you might be thinking twice about that block of chocolate 22 00:01:11,360 --> 00:01:13,119 Speaker 2: the next time you're in the super market isle. 23 00:01:18,440 --> 00:01:21,560 Speaker 3: I'm West Kasova today on the Big Tag Bloomberg's Brian 24 00:01:21,720 --> 00:01:25,480 Speaker 3: Sullivan and Ben Sharples on what al Nino has in 25 00:01:25,640 --> 00:01:34,119 Speaker 3: store for us. Brian, for the past three years, we've 26 00:01:34,200 --> 00:01:38,760 Speaker 3: been experiencing this global weather pattern known as Lanina. Now 27 00:01:38,800 --> 00:01:42,839 Speaker 3: that's ended and we're about to enter into El Nino again. 28 00:01:42,880 --> 00:01:46,120 Speaker 3: Can you explain to us what an al nino is 29 00:01:46,400 --> 00:01:48,800 Speaker 3: and how it's different from a lanina. 30 00:01:49,600 --> 00:01:52,600 Speaker 1: So al nino is when the surface of the the 31 00:01:52,640 --> 00:01:55,960 Speaker 1: equatorial surface of the Pacific Ocean warms and the atmosphere 32 00:01:56,000 --> 00:01:59,520 Speaker 1: above it reacts to it. And then lannina is when 33 00:01:59,760 --> 00:02:03,240 Speaker 1: most of that area is cooler, and there's also a 34 00:02:03,320 --> 00:02:06,080 Speaker 1: reaction to it. But because of the fact that you 35 00:02:06,160 --> 00:02:09,400 Speaker 1: have warm and cold, you have different reactions in the atmosphere. 36 00:02:09,480 --> 00:02:12,280 Speaker 1: And it's that reaction in the atmosphere that actually changes 37 00:02:12,320 --> 00:02:13,799 Speaker 1: the weather systems around the world. 38 00:02:14,080 --> 00:02:15,079 Speaker 3: And why does that happen. 39 00:02:15,919 --> 00:02:18,720 Speaker 1: Part of it is just simply because the Pacific Ocean 40 00:02:18,800 --> 00:02:22,400 Speaker 1: is so big, as one US government expert told me, 41 00:02:22,639 --> 00:02:25,960 Speaker 1: you know, it's just an accident of geography. The equator 42 00:02:26,880 --> 00:02:29,920 Speaker 1: rotates slower than the rest of the globe. Right, if 43 00:02:29,919 --> 00:02:32,400 Speaker 1: you're at the north pole, then you're spinning around much faster, 44 00:02:32,480 --> 00:02:34,720 Speaker 1: and if you're at the equator, it moves slower. And 45 00:02:34,760 --> 00:02:38,520 Speaker 1: the Pacific Ocean is just so huge that there's enough 46 00:02:38,639 --> 00:02:43,760 Speaker 1: time for those anomalies the warm or cool water to 47 00:02:43,840 --> 00:02:46,480 Speaker 1: pile up in that area and then change the atmosphere 48 00:02:46,480 --> 00:02:46,840 Speaker 1: above it. 49 00:02:47,919 --> 00:02:50,760 Speaker 3: Brian, can you just generally explain what's the weather like 50 00:02:50,800 --> 00:02:53,080 Speaker 3: when you're in an al nino and what's it like 51 00:02:53,120 --> 00:02:54,400 Speaker 3: when you're in a lanninia. 52 00:02:55,280 --> 00:02:57,480 Speaker 1: If we looked at North America, for instance, what you 53 00:02:57,520 --> 00:03:00,760 Speaker 1: would see next winter in the alninia is you would 54 00:03:00,760 --> 00:03:05,320 Speaker 1: see a wetter, stormier part of the southern United States, 55 00:03:05,320 --> 00:03:08,920 Speaker 1: for instance, and a drier southern tier of Canada. That 56 00:03:08,960 --> 00:03:12,320 Speaker 1: would be one example. You would also see drier conditions 57 00:03:12,360 --> 00:03:15,040 Speaker 1: across Brazil where they grow a lot of the coffee. 58 00:03:15,040 --> 00:03:18,200 Speaker 1: You would see drier conditions across Southeast Asia as well 59 00:03:18,240 --> 00:03:21,280 Speaker 1: as South Africa. In La Nina, you kind of get 60 00:03:21,280 --> 00:03:24,480 Speaker 1: the opposite of that. So in La Nina, the southern 61 00:03:24,600 --> 00:03:28,720 Speaker 1: United States, for instance, will be dry. The Pacific Northwest 62 00:03:28,720 --> 00:03:32,240 Speaker 1: and southern Canada will be wet. There'll be drought in 63 00:03:32,360 --> 00:03:36,720 Speaker 1: southern Brazil and Argentina, which has been really plaguing corn 64 00:03:36,800 --> 00:03:40,160 Speaker 1: and soybean crops there for years actually, and then you 65 00:03:40,160 --> 00:03:43,240 Speaker 1: would probably get some wetter conditions in Brazil. So basically 66 00:03:43,320 --> 00:03:47,560 Speaker 1: what you're seeing is shifting of drought and flood back 67 00:03:47,600 --> 00:03:50,640 Speaker 1: and forth. It's just swinging of the pendulum. So if 68 00:03:50,680 --> 00:03:54,160 Speaker 1: you're in drought during in El Nino, the pendulum would 69 00:03:54,200 --> 00:03:56,960 Speaker 1: shift and you would be in flood during La Nina 70 00:03:57,120 --> 00:03:58,080 Speaker 1: or vice versa. 71 00:03:58,680 --> 00:04:02,200 Speaker 3: So even though we some times think of Lianninia as 72 00:04:02,280 --> 00:04:05,680 Speaker 3: the kinder of the two because it's cooler, the weather 73 00:04:05,720 --> 00:04:09,360 Speaker 3: patterns themselves are still really extreme and potentially harmful. 74 00:04:09,840 --> 00:04:12,040 Speaker 1: They can be completely destructive. If you look at the 75 00:04:12,160 --> 00:04:14,920 Speaker 1: drought in California that has gone on for three years 76 00:04:15,000 --> 00:04:17,000 Speaker 1: that was driven largely by Vannina. 77 00:04:17,520 --> 00:04:20,599 Speaker 3: And yet Ben in your story, you rate kind of 78 00:04:20,600 --> 00:04:23,800 Speaker 3: the world is bracing for this new El Nina. Way 79 00:04:24,160 --> 00:04:28,440 Speaker 3: is it considered to be so much more potentially harmful 80 00:04:28,520 --> 00:04:30,720 Speaker 3: than the Li Nina we've all been living through. 81 00:04:31,600 --> 00:04:35,640 Speaker 2: El Nina tends to add more inflationary pressure due to 82 00:04:35,640 --> 00:04:40,080 Speaker 2: to high commodity prices, and higher commodity prices are typically 83 00:04:40,200 --> 00:04:43,960 Speaker 2: due to those droughts and flooding that Brian has touched on. 84 00:04:44,560 --> 00:04:46,719 Speaker 2: There's a wide range of crops that can be impacted. 85 00:04:46,880 --> 00:04:51,560 Speaker 2: We're talking from wheat, corn, rice, coffee, cocoa in West Africa, 86 00:04:51,800 --> 00:04:53,960 Speaker 2: and if they're significant damages to those, you know, it 87 00:04:54,000 --> 00:04:56,560 Speaker 2: could be more expensive cup of coffee, or you might 88 00:04:56,600 --> 00:04:58,640 Speaker 2: be thinking twice about that block of chocolate the next 89 00:04:58,680 --> 00:05:01,400 Speaker 2: time you're in the supermarket. All but when you look 90 00:05:01,440 --> 00:05:06,040 Speaker 2: at where we've come also, we've seen the world is recovering, 91 00:05:06,080 --> 00:05:10,279 Speaker 2: it's trying to regain its footing from the COVID nineteen pandemic. 92 00:05:10,800 --> 00:05:13,280 Speaker 2: In a monthst that, you have the Russian invasion of 93 00:05:13,400 --> 00:05:18,040 Speaker 2: Ukraine and that specifically hit commodities like oil, wheat, corn 94 00:05:18,120 --> 00:05:21,680 Speaker 2: and that sort of stuff. So it's heaping that inflationary 95 00:05:21,760 --> 00:05:24,440 Speaker 2: pressure on top of events that have already come. So 96 00:05:24,440 --> 00:05:27,839 Speaker 2: we're in already in an environment where we're experiencing above 97 00:05:27,880 --> 00:05:31,440 Speaker 2: target inflation in many countries. So el Nina just adds 98 00:05:31,480 --> 00:05:34,560 Speaker 2: that a little bit extra. When countries and economies are 99 00:05:34,560 --> 00:05:35,680 Speaker 2: trying to regain their. 100 00:05:35,560 --> 00:05:40,040 Speaker 3: Footing, Brian, how do they know when an al Ninia 101 00:05:40,120 --> 00:05:42,040 Speaker 3: year is coming or when a lie ninia? What is 102 00:05:42,080 --> 00:05:42,640 Speaker 3: the cycle? 103 00:05:43,520 --> 00:05:47,159 Speaker 1: There is an array of booies that stretch from South 104 00:05:47,200 --> 00:05:50,960 Speaker 1: America all the way across the Pacific Ocean into Indonesia, 105 00:05:51,040 --> 00:05:54,359 Speaker 1: and those are constantly measuring the temperature of the water 106 00:05:54,920 --> 00:05:57,880 Speaker 1: as well as the atmosphere conditions above it. They use 107 00:05:57,960 --> 00:06:01,279 Speaker 1: satellites as well, they have boats that go out there 108 00:06:01,320 --> 00:06:04,120 Speaker 1: and take a look at things. So basically, if they 109 00:06:04,160 --> 00:06:07,680 Speaker 1: start to see a trend in the temperature of the water, 110 00:06:08,160 --> 00:06:11,640 Speaker 1: they start to look for signs in the atmosphere that 111 00:06:11,720 --> 00:06:14,600 Speaker 1: the al Nino or the La Nina cycle may be starting. 112 00:06:14,920 --> 00:06:17,680 Speaker 1: And that's the directions of the winds, for instance, across 113 00:06:17,720 --> 00:06:19,960 Speaker 1: the Pacific Ocean. So if the winds are blowing from 114 00:06:19,960 --> 00:06:24,080 Speaker 1: South America towards Asia, then you're going to get La Nina, 115 00:06:24,080 --> 00:06:26,040 Speaker 1: because that's going to pull the cold water up from 116 00:06:26,040 --> 00:06:28,160 Speaker 1: the depths of the Pacific Ocean and spread it out 117 00:06:28,200 --> 00:06:32,360 Speaker 1: across the equator. And likewise, when al Nino happens, those 118 00:06:32,400 --> 00:06:35,039 Speaker 1: winds get weaker and that allows the sun to just 119 00:06:35,120 --> 00:06:38,279 Speaker 1: bake those waters and the equatorial Pacific and then just 120 00:06:38,279 --> 00:06:40,560 Speaker 1: get hotter and harder and hotter. So there's a lot 121 00:06:40,560 --> 00:06:43,960 Speaker 1: of different signs out there that people are watching constantly. 122 00:06:44,400 --> 00:06:47,279 Speaker 2: If you really want to know if El Nino has hit. 123 00:06:47,920 --> 00:06:51,360 Speaker 2: Just look to the waters off Peru and the anchovy's there. Historically, 124 00:06:51,640 --> 00:06:54,960 Speaker 2: it was a dead giveaway when El Nino was rolling 125 00:06:55,000 --> 00:06:58,440 Speaker 2: in because the anchovy catch was less than what it 126 00:06:58,480 --> 00:07:01,520 Speaker 2: would be in previous years. It's because the anchovies go 127 00:07:01,720 --> 00:07:04,120 Speaker 2: they dive deeper into the cooler waters. They don't like 128 00:07:04,160 --> 00:07:06,280 Speaker 2: the hot waters, and it makes it harder for them 129 00:07:06,279 --> 00:07:09,400 Speaker 2: to the catch. And that became initially as part of 130 00:07:09,440 --> 00:07:12,680 Speaker 2: one of the indicators as to this whole phenomenon that 131 00:07:12,680 --> 00:07:13,440 Speaker 2: we know El Nino. 132 00:07:14,120 --> 00:07:17,640 Speaker 1: So al Nino got its name because this migration of 133 00:07:17,640 --> 00:07:21,720 Speaker 1: the anchovies happened around Christmas time. The fishermen in this 134 00:07:21,920 --> 00:07:25,080 Speaker 1: area noticed that it was happening at Christmas time, so 135 00:07:25,120 --> 00:07:27,960 Speaker 1: they referred to it as al Nino or the little boy. 136 00:07:28,920 --> 00:07:31,280 Speaker 1: The christ child was born on Christmas, and that's where 137 00:07:31,280 --> 00:07:33,720 Speaker 1: it came from. So the opposite, of course is a girl. 138 00:07:33,760 --> 00:07:35,239 Speaker 1: If you have a boy, you have to have a girl. 139 00:07:35,320 --> 00:07:36,600 Speaker 1: And la Nina. 140 00:07:36,760 --> 00:07:40,520 Speaker 3: And how is climate change impacted El Nino or the 141 00:07:40,560 --> 00:07:43,320 Speaker 3: strength of it. How often this cycle occurs. 142 00:07:44,160 --> 00:07:47,920 Speaker 1: So originally, years ago, decades ago, they thought that El 143 00:07:48,000 --> 00:07:51,480 Speaker 1: Nino's would become more common under the climate change regime. 144 00:07:51,560 --> 00:07:54,280 Speaker 1: Under the global warming, because you know, warm ocean, you 145 00:07:54,320 --> 00:07:56,800 Speaker 1: would have more al Nina's. But what they found in 146 00:07:56,880 --> 00:07:59,560 Speaker 1: the last twenty years that there's actually more n Ninia's, 147 00:07:59,680 --> 00:08:02,800 Speaker 1: and there's a lot of academic research going on right 148 00:08:02,880 --> 00:08:05,120 Speaker 1: now is to try to figure out why that's happening. 149 00:08:05,480 --> 00:08:08,000 Speaker 1: There's a number of interesting things though. If you took 150 00:08:08,480 --> 00:08:13,000 Speaker 1: the water temperature that would demonstrate on Lannina now, that 151 00:08:13,080 --> 00:08:16,520 Speaker 1: would would demonstrate the cool part of the Pacific Ocean now, 152 00:08:16,840 --> 00:08:19,720 Speaker 1: and you went back in time fifty years or sixty years, 153 00:08:20,120 --> 00:08:22,480 Speaker 1: that water would be warm enough to trigger an El 154 00:08:22,560 --> 00:08:25,480 Speaker 1: Nino back in those days. So what you're seeing with 155 00:08:25,560 --> 00:08:28,640 Speaker 1: that example is that the oceans are actually getting warmer 156 00:08:28,720 --> 00:08:31,440 Speaker 1: and warmer and warmer. But al nino and La Nina 157 00:08:31,520 --> 00:08:35,720 Speaker 1: itself doesn't depend on the actual warmth of the water. 158 00:08:35,800 --> 00:08:38,960 Speaker 1: What it depends on is how different the water is 159 00:08:39,000 --> 00:08:42,200 Speaker 1: to each other. So if you get an area that's 160 00:08:42,640 --> 00:08:45,600 Speaker 1: relatively warm in the Pacific Ocean, but it's cooler than 161 00:08:45,600 --> 00:08:47,480 Speaker 1: the water on either side of it, then you will 162 00:08:47,480 --> 00:08:50,040 Speaker 1: get a La Nina. Likewise, if you get a part 163 00:08:50,040 --> 00:08:52,600 Speaker 1: of the Pacific Ocean that's actually quite a bit warmer 164 00:08:52,600 --> 00:08:54,880 Speaker 1: than the water on either side of it, you get 165 00:08:54,920 --> 00:08:57,600 Speaker 1: that al Nino because you need that differential in the 166 00:08:57,600 --> 00:09:00,559 Speaker 1: temperature to really dart the engine and get the things going. 167 00:09:01,840 --> 00:09:05,880 Speaker 3: Then you mentioned earlier about how these forceful weather patterns 168 00:09:05,920 --> 00:09:10,520 Speaker 3: can affect the price of food, the ability to grow crops. 169 00:09:10,679 --> 00:09:14,920 Speaker 3: How have previous al Nino's affected the food supply? 170 00:09:15,760 --> 00:09:18,400 Speaker 2: Crops are vulnerable to the weather. All it takes is 171 00:09:18,640 --> 00:09:21,600 Speaker 2: a little bit of change, a little less rain, and 172 00:09:21,679 --> 00:09:24,280 Speaker 2: you've got a little less Let's say, for example, wheat. 173 00:09:24,679 --> 00:09:27,720 Speaker 2: One of the examples is Australia recently reduced its forecast 174 00:09:27,760 --> 00:09:31,440 Speaker 2: for the nation's wheat harvest and they are predicting that 175 00:09:31,559 --> 00:09:34,640 Speaker 2: is primarily due to lower rainfall due to El Nino, 176 00:09:34,760 --> 00:09:36,920 Speaker 2: So that'll be a lower wheat crop this year, and 177 00:09:36,960 --> 00:09:40,880 Speaker 2: that feeds into the global narrative of supply for wheat. 178 00:09:40,920 --> 00:09:44,520 Speaker 2: For example, there are healthy supplies within sort of the 179 00:09:44,840 --> 00:09:49,520 Speaker 2: European basket, but you get sort of dense in supply. 180 00:09:49,880 --> 00:09:52,920 Speaker 2: El Nino is a reason we spoke about Russia before. 181 00:09:52,960 --> 00:09:56,000 Speaker 2: That was a reason. And incrementally, if you take supply 182 00:09:56,040 --> 00:09:59,840 Speaker 2: out of system, prices rise and that feeds through into inflation. 183 00:10:00,080 --> 00:10:04,000 Speaker 2: It leads feeds into GDP growth from anywhere from Brazil 184 00:10:04,080 --> 00:10:07,280 Speaker 2: to Australia to India, and it has a huge effect. 185 00:10:07,320 --> 00:10:09,760 Speaker 2: I mean, people are repaying a lot of money for 186 00:10:10,080 --> 00:10:12,319 Speaker 2: staples in many areas of the world at the moment. 187 00:10:13,120 --> 00:10:16,800 Speaker 3: Brian. One thing you write also in this story is 188 00:10:16,840 --> 00:10:21,120 Speaker 3: that this spike in heat leads to a huge surge 189 00:10:21,240 --> 00:10:25,319 Speaker 3: in demand for electricity to cool homes and other things. 190 00:10:26,120 --> 00:10:29,800 Speaker 3: How do they anticipate this El Nino is going to 191 00:10:30,080 --> 00:10:33,319 Speaker 3: affect just the power grid and energy. 192 00:10:33,679 --> 00:10:36,719 Speaker 1: Over the past few years. You've had trouble in California 193 00:10:36,760 --> 00:10:40,360 Speaker 1: and particularly in Texas when this spike and heat comes 194 00:10:40,400 --> 00:10:42,959 Speaker 1: along because it puts taxes to grid. Many of these 195 00:10:42,960 --> 00:10:46,079 Speaker 1: places have a larger percentage of renewable energy online now 196 00:10:46,120 --> 00:10:48,800 Speaker 1: than they had before. So when you get a really 197 00:10:48,880 --> 00:10:53,160 Speaker 1: hot day, when you anticipate that the megawattach is going 198 00:10:53,240 --> 00:10:56,880 Speaker 1: way up, you're going to have to start shifting electricity 199 00:10:56,880 --> 00:10:59,079 Speaker 1: around the grid to make up for that. Now, if 200 00:10:59,120 --> 00:11:01,640 Speaker 1: you have one of these massive heat waves, which you've 201 00:11:01,640 --> 00:11:04,080 Speaker 1: seen for the past few summers in a row, you 202 00:11:04,160 --> 00:11:07,280 Speaker 1: can't really start grabbing electricity from somewhere else because everyone 203 00:11:07,360 --> 00:11:10,160 Speaker 1: is hot. The only way to deal with that in 204 00:11:10,200 --> 00:11:12,600 Speaker 1: a lot of cases is to actually ask people to 205 00:11:12,640 --> 00:11:16,720 Speaker 1: go offline, or you have rolling blackouts, which has happened before, 206 00:11:17,160 --> 00:11:19,880 Speaker 1: or in the extreme cases, the Communist government of China 207 00:11:20,000 --> 00:11:23,440 Speaker 1: actually told people to shut down using electricity and they 208 00:11:23,480 --> 00:11:27,400 Speaker 1: closed factories. So there's a lot of stress on the 209 00:11:27,440 --> 00:11:30,880 Speaker 1: system worldwide when these things happen. And especially if you 210 00:11:31,000 --> 00:11:36,000 Speaker 1: get combination of these stuck weather patterns, these big high 211 00:11:36,040 --> 00:11:38,319 Speaker 1: pressure systems that just sit over an area and they 212 00:11:38,400 --> 00:11:40,280 Speaker 1: bake and bake and bake the place, you're going to 213 00:11:40,320 --> 00:11:43,400 Speaker 1: see a lot more stress on the grid conditions. 214 00:11:43,480 --> 00:11:45,640 Speaker 2: The US is just called an El Nina's we're just 215 00:11:46,040 --> 00:11:49,160 Speaker 2: on the cusp of El Ninyu. And yet across Asia 216 00:11:49,200 --> 00:11:54,600 Speaker 2: we've seen it's hot. It's stifling hot. Countries from Thailand 217 00:11:54,600 --> 00:11:59,000 Speaker 2: to Bangladesh to India have already broaken temperature records. We've 218 00:11:59,040 --> 00:12:03,400 Speaker 2: seen in China the heat is could turning hydropower, so 219 00:12:03,760 --> 00:12:07,520 Speaker 2: that's affecting aluminum output in China. In parts of Vietnam, 220 00:12:07,559 --> 00:12:09,880 Speaker 2: they've also gone into rolling blackouts. And this is already 221 00:12:09,960 --> 00:12:13,800 Speaker 2: this is pre El Nino, and you know El Nino, China, Bangladesh, 222 00:12:13,960 --> 00:12:17,960 Speaker 2: this is the factory of the world. Canon, Apple, Samsung 223 00:12:18,040 --> 00:12:20,720 Speaker 2: all produce various bits and pieces in these areas, and 224 00:12:21,200 --> 00:12:27,320 Speaker 2: they're already facing conditions where there's blackouts in Vietnam, a 225 00:12:27,400 --> 00:12:30,559 Speaker 2: key area for a key manufacturing areas up in the north. 226 00:12:30,960 --> 00:12:33,720 Speaker 2: There are already stresses in the system already, and we 227 00:12:33,840 --> 00:12:36,000 Speaker 2: haven't seen the worst of El Nino yet. 228 00:12:37,000 --> 00:12:40,280 Speaker 3: After the break, Al Nino could stir up a big 229 00:12:40,320 --> 00:12:51,880 Speaker 3: storm for the global economy. Then you mentioned earlier about 230 00:12:51,920 --> 00:12:56,280 Speaker 3: how El Nino can cause a spike in inflation. How 231 00:12:56,320 --> 00:12:59,360 Speaker 3: else does it affect economies? What does it do to 232 00:12:59,400 --> 00:13:02,120 Speaker 3: say gross domestic product are just the general output of 233 00:13:02,160 --> 00:13:02,679 Speaker 3: a country. 234 00:13:03,120 --> 00:13:06,400 Speaker 2: There's been some recent modeling done from Dartmouth scientists suggesting 235 00:13:06,480 --> 00:13:10,400 Speaker 2: El Nino causes trillions of dollars in lost economic growth. 236 00:13:10,440 --> 00:13:13,480 Speaker 2: They've done some modeling on some the bigger El Nino 237 00:13:13,600 --> 00:13:16,559 Speaker 2: events previously in nineteen ninety seven, ninety eight, that was 238 00:13:16,559 --> 00:13:19,120 Speaker 2: a bigger on Inuo event, and they found that it 239 00:13:19,200 --> 00:13:23,000 Speaker 2: set world GDP back by five point seven trillion dollars. 240 00:13:23,520 --> 00:13:26,000 Speaker 2: The age two eighty three El Nina reduced growth by 241 00:13:26,200 --> 00:13:30,280 Speaker 2: four point one trillion, So it's big. It hurts GDP. 242 00:13:30,440 --> 00:13:33,880 Speaker 2: So you know there you will get the immediate inflationary 243 00:13:33,920 --> 00:13:37,320 Speaker 2: pressure from the high commodity prices that have been damaged 244 00:13:37,400 --> 00:13:39,880 Speaker 2: due to drought to dry conditions, less rainfall, but the 245 00:13:39,920 --> 00:13:42,680 Speaker 2: flow in effect and the hit to GDP is even 246 00:13:42,800 --> 00:13:44,360 Speaker 2: larger than what the immediate effect is. 247 00:13:44,920 --> 00:13:47,640 Speaker 3: So we talked a bit about how El Nino will 248 00:13:47,920 --> 00:13:52,679 Speaker 3: affect energy supplies, in particular electricity. We're starting to see 249 00:13:52,720 --> 00:13:56,760 Speaker 3: Apple and Tesla, which depend on huge amounts of electricity, 250 00:13:56,840 --> 00:14:00,440 Speaker 3: the whole tech sector looking at possible sure, which is 251 00:14:00,480 --> 00:14:05,760 Speaker 3: how are other businesses responding to these potential disruptions caused 252 00:14:05,760 --> 00:14:06,560 Speaker 3: by El Nino. 253 00:14:07,600 --> 00:14:10,400 Speaker 2: Sadly, you know, the winner is fossil fuels. A lot 254 00:14:10,400 --> 00:14:13,400 Speaker 2: of the time, especially in parts of Asia, in hot 255 00:14:13,440 --> 00:14:17,480 Speaker 2: periods in parts of Europe as well, a lot of 256 00:14:17,480 --> 00:14:19,680 Speaker 2: people or a lot of companies have relied on diesel 257 00:14:19,720 --> 00:14:22,360 Speaker 2: generators to make up that power short is, to ensure 258 00:14:22,440 --> 00:14:27,680 Speaker 2: that manufacturing or their production isn't affected by rolling blackouts. 259 00:14:27,760 --> 00:14:31,960 Speaker 2: So again it becomes a world reliant on fossil fuels. 260 00:14:31,960 --> 00:14:35,840 Speaker 2: Diesel generators plug that gap when we start to find 261 00:14:35,880 --> 00:14:38,080 Speaker 2: ourselves losing power due to blackouts. 262 00:14:38,760 --> 00:14:41,800 Speaker 3: Brain we're all seeing these wildfires in Canada. We've seen 263 00:14:41,880 --> 00:14:46,240 Speaker 3: wildfires in recent years spread across the globe. Is there 264 00:14:46,280 --> 00:14:50,720 Speaker 3: a relationship between La Nina, between al Nino and these 265 00:14:50,800 --> 00:14:54,520 Speaker 3: kinds of really big increasing fires and droughts and other 266 00:14:55,040 --> 00:14:56,640 Speaker 3: climate events. 267 00:14:56,880 --> 00:15:00,600 Speaker 1: There definitely are. If you look at the large wildfires, 268 00:15:00,600 --> 00:15:04,400 Speaker 1: for instance, that raked across Australia a few years ago, 269 00:15:04,720 --> 00:15:08,280 Speaker 1: those are directly tried to a drought caused by al Nina. 270 00:15:08,400 --> 00:15:10,720 Speaker 1: If you looked at some of the large wildfires that 271 00:15:10,760 --> 00:15:13,240 Speaker 1: went across the western United States in the last few years, 272 00:15:13,680 --> 00:15:16,920 Speaker 1: those were tied to droughts caused by Li Nina. And 273 00:15:17,320 --> 00:15:21,560 Speaker 1: the fires in Canada, for instance, while not really caused 274 00:15:21,640 --> 00:15:24,640 Speaker 1: by al Nino and Linina, will probably be made worse 275 00:15:24,720 --> 00:15:28,640 Speaker 1: next year because al Nino brings drought to southern Canada. 276 00:15:29,000 --> 00:15:32,120 Speaker 1: You have these parched forests already, they're going to get 277 00:15:32,120 --> 00:15:35,480 Speaker 1: even more dry, and next summer you have lightning strikes, 278 00:15:35,560 --> 00:15:39,200 Speaker 1: you'll have more fires, and it'll just get progressively worse. 279 00:15:40,280 --> 00:15:42,920 Speaker 1: I think the one way to think about the relationship 280 00:15:42,960 --> 00:15:45,920 Speaker 1: between climate and weather is that climate sets the table 281 00:15:45,960 --> 00:15:49,640 Speaker 1: and weather delivers the meal. We get. The extremes coming 282 00:15:50,240 --> 00:15:55,040 Speaker 1: from weather events such as hurricanes or typhoons or heat 283 00:15:55,080 --> 00:15:59,120 Speaker 1: waves or floods or droughts or whatever, they're all made 284 00:15:59,160 --> 00:16:02,000 Speaker 1: worse as the climate gets warmer and warmer and warmer. 285 00:16:02,520 --> 00:16:05,120 Speaker 2: I was talking to a climate scientist about the recent 286 00:16:05,160 --> 00:16:09,400 Speaker 2: heat wave in Asia in April, and he mentioned that 287 00:16:10,080 --> 00:16:13,240 Speaker 2: a heat wave of that severity is typical of what 288 00:16:13,280 --> 00:16:17,120 Speaker 2: we see toward the end of an el Nina, and 289 00:16:17,160 --> 00:16:19,280 Speaker 2: this is happening pre on Nina. So that just gives 290 00:16:19,280 --> 00:16:24,760 Speaker 2: you an understanding of what climate is doing to temperatures 291 00:16:24,840 --> 00:16:27,840 Speaker 2: even without the effects of an al Ninu event. 292 00:16:28,600 --> 00:16:31,160 Speaker 3: Brain one thing that happens when we head into the 293 00:16:31,160 --> 00:16:34,600 Speaker 3: summer is the hurricane season starts, and we've seen some 294 00:16:34,720 --> 00:16:38,520 Speaker 3: pretty devastating storms in recent years. How might El Nina 295 00:16:38,560 --> 00:16:39,080 Speaker 3: affect that? 296 00:16:40,000 --> 00:16:44,000 Speaker 1: Almina might actually help the Atlantic hurricane season, simply because 297 00:16:44,240 --> 00:16:47,160 Speaker 1: the changes in the atmosphere bring wind sheer across the 298 00:16:47,200 --> 00:16:50,720 Speaker 1: Atlantic Ocean, the Gulf of Mexico and the Caribbean, which 299 00:16:50,840 --> 00:16:54,200 Speaker 1: will tear apart budding tropical storms and hurricanes that are 300 00:16:54,240 --> 00:16:56,960 Speaker 1: moving into that area. And as you know, I mean 301 00:16:57,440 --> 00:17:00,440 Speaker 1: a storm, a hurricane, or a tropical dorm and the 302 00:17:00,440 --> 00:17:03,400 Speaker 1: Gulf of Mexico can really disrupt energy prices in the 303 00:17:03,480 --> 00:17:07,200 Speaker 1: United States, it can disrupt supplies, it can disrupt production. 304 00:17:07,840 --> 00:17:10,800 Speaker 1: The place where it doesn't help, however, is in the Pacific. 305 00:17:11,240 --> 00:17:14,520 Speaker 1: You've often seen more typhoons in the Pacific Ocean. You 306 00:17:14,600 --> 00:17:17,920 Speaker 1: see them curving up towards Japan more often, so Japan 307 00:17:18,040 --> 00:17:21,119 Speaker 1: may actually be under the gun for some really strong 308 00:17:21,160 --> 00:17:22,600 Speaker 1: typhoons at the end of the summer. 309 00:17:23,480 --> 00:17:34,679 Speaker 3: When we come back to the human cost of Al Nina, 310 00:17:34,840 --> 00:17:37,560 Speaker 3: then one thing we haven't talked about is how it 311 00:17:37,680 --> 00:17:40,280 Speaker 3: just affects people and people's health. 312 00:17:40,840 --> 00:17:44,800 Speaker 2: A big feature of El Nino is is drought, and 313 00:17:44,880 --> 00:17:49,359 Speaker 2: we've seen drought, particularly across Africa, kill a lot of people. 314 00:17:49,760 --> 00:17:54,240 Speaker 2: There was in twenty fifteen sixteen high malnutrition rates, force displacement. 315 00:17:54,600 --> 00:17:57,879 Speaker 2: You had nearly two dozen nations issuing humanitarian appeals of 316 00:17:57,920 --> 00:18:03,399 Speaker 2: more than five billion dollars route and famine, and typically 317 00:18:03,440 --> 00:18:07,159 Speaker 2: in countries that aren't really well equipped to deal with 318 00:18:07,200 --> 00:18:10,440 Speaker 2: these sort of health issues. You know, usually it's poorer 319 00:18:10,520 --> 00:18:13,679 Speaker 2: nations that the feel the bigger brunt of it. We 320 00:18:13,720 --> 00:18:16,240 Speaker 2: touched on it earlier, but you know, the haze and 321 00:18:16,240 --> 00:18:22,080 Speaker 2: the smog from plantations that fires, especially across Indonesia and Malaysia, 322 00:18:22,240 --> 00:18:25,359 Speaker 2: has in the past drifered across the Philippines and across Singapore, 323 00:18:25,520 --> 00:18:28,720 Speaker 2: and more recently twenty nineteen twenty twenty wh hared the 324 00:18:28,720 --> 00:18:32,960 Speaker 2: bushfires in eastern Australia. Now, while that was considered globally 325 00:18:33,119 --> 00:18:36,480 Speaker 2: a week El Nino year, conditions were set for a 326 00:18:36,560 --> 00:18:40,920 Speaker 2: huge bushfire season. We've seen respiratory problems in kids, newborns 327 00:18:40,960 --> 00:18:44,480 Speaker 2: and stuff like that. So public health is also a 328 00:18:44,520 --> 00:18:47,800 Speaker 2: big impact, not only the loss of crops and commodities, 329 00:18:47,840 --> 00:18:50,800 Speaker 2: but public health is a key aspect or a key 330 00:18:50,840 --> 00:18:52,600 Speaker 2: feature of El Nino. 331 00:18:54,520 --> 00:18:58,080 Speaker 3: And then, since this happens cyclically, is there anything that 332 00:18:58,760 --> 00:19:02,080 Speaker 3: governments do to kind of prepare for it so that 333 00:19:02,119 --> 00:19:05,760 Speaker 3: there aren't commodity praise sharks and everybody is suddenly scrambling. 334 00:19:06,160 --> 00:19:08,919 Speaker 2: I mean, governments can stockpile, they can put themselves in 335 00:19:08,920 --> 00:19:12,840 Speaker 2: a position where they adequately have adequate stocks, but I 336 00:19:12,840 --> 00:19:15,320 Speaker 2: mean that can only go so far the world. The 337 00:19:15,320 --> 00:19:18,160 Speaker 2: globe will get stretched very very quickly when commodities are 338 00:19:18,440 --> 00:19:21,119 Speaker 2: especially hit across all across the world and you have 339 00:19:21,200 --> 00:19:23,680 Speaker 2: various events, the caveat there being. It all depends on 340 00:19:23,720 --> 00:19:26,359 Speaker 2: the severity of the Old Nino. But we are already 341 00:19:26,400 --> 00:19:29,639 Speaker 2: seeing countries like Australia reducing that they're there forecast harvest 342 00:19:29,920 --> 00:19:33,480 Speaker 2: for wheat. We've also got Thailand they usually plant two 343 00:19:33,520 --> 00:19:36,000 Speaker 2: types of rice crop. They're only planting one this time around, 344 00:19:36,200 --> 00:19:38,640 Speaker 2: so they put preparations in place as best they can, 345 00:19:38,720 --> 00:19:40,919 Speaker 2: but there's only so much you can do depending on 346 00:19:40,960 --> 00:19:42,400 Speaker 2: the well brain. 347 00:19:42,520 --> 00:19:45,120 Speaker 3: You mentioned at least one good possible thing that could 348 00:19:45,119 --> 00:19:48,919 Speaker 3: come of El Nino, which could possibly break up hurricanes 349 00:19:48,960 --> 00:19:51,600 Speaker 3: in the Atlantic. Are there any other possible benefits, like 350 00:19:51,600 --> 00:19:54,560 Speaker 3: a reason why maybe we should welcome an al Nino 351 00:19:54,640 --> 00:19:56,679 Speaker 3: instead of just being kind of terrified about it. 352 00:19:57,359 --> 00:20:00,600 Speaker 1: California has suffered under drug for the last few years. 353 00:20:00,880 --> 00:20:03,000 Speaker 1: It was actually reversed a little bit this winter. But 354 00:20:03,200 --> 00:20:06,760 Speaker 1: Annel Nino, for instance, would actually help California stay out 355 00:20:06,800 --> 00:20:09,320 Speaker 1: of drought for the coming year. And there are other 356 00:20:09,400 --> 00:20:13,159 Speaker 1: areas such as the crop growing areas of Argentina and Brazil. 357 00:20:13,280 --> 00:20:16,280 Speaker 1: Southern Brazil, they were in drought which was driving up 358 00:20:16,320 --> 00:20:18,879 Speaker 1: corn prices, which was driving up souybean prices. Well, they 359 00:20:18,920 --> 00:20:21,960 Speaker 1: should get more water this year, they should be fine, 360 00:20:22,520 --> 00:20:24,760 Speaker 1: the crop should be fine, yields should go up. So 361 00:20:24,800 --> 00:20:27,760 Speaker 1: there are benefits to this in various parts of the world. 362 00:20:29,640 --> 00:20:32,800 Speaker 3: And how long should we expect this cycle to last 363 00:20:33,119 --> 00:20:36,120 Speaker 3: until once again it flip flops and we're back with 364 00:20:36,760 --> 00:20:37,360 Speaker 3: La Nina. 365 00:20:38,040 --> 00:20:42,160 Speaker 1: Usually they start breaking up sometime around March April May. 366 00:20:42,760 --> 00:20:46,520 Speaker 1: You'll see them. They'll peak between December January February, and 367 00:20:46,520 --> 00:20:48,720 Speaker 1: then they'll start to break up in March April May. 368 00:20:49,359 --> 00:20:52,600 Speaker 1: The ocean will return to a neutral state and then 369 00:20:52,800 --> 00:20:55,840 Speaker 1: the cycle may start again. Usually you don't get too 370 00:20:55,880 --> 00:20:58,400 Speaker 1: El Nino's in a row. It's more common to get 371 00:20:58,400 --> 00:21:00,760 Speaker 1: two La Nina's in a row. In recent years we 372 00:21:00,800 --> 00:21:03,160 Speaker 1: actually had three Lindon News in a row. So there's 373 00:21:03,200 --> 00:21:04,119 Speaker 1: a good example of that. 374 00:21:05,240 --> 00:21:07,920 Speaker 3: Brian Ben, thanks so much for coming on the show, 375 00:21:08,119 --> 00:21:11,600 Speaker 3: Thanks for having me, Thanks for listening to us here 376 00:21:11,600 --> 00:21:14,120 Speaker 3: at The Big Take. It's a daily podcast from Bloomberg 377 00:21:14,160 --> 00:21:18,440 Speaker 3: and iHeartRadio. For more shows from iHeartRadio, visit the iHeartRadio app, 378 00:21:18,600 --> 00:21:21,879 Speaker 3: Apple Podcasts, or wherever you listen. And we'd love to 379 00:21:21,920 --> 00:21:24,920 Speaker 3: hear from you. Email us questions or comments to Big 380 00:21:24,960 --> 00:21:28,879 Speaker 3: Take at Bloomberg dot net. The supervising producer of The 381 00:21:28,880 --> 00:21:32,920 Speaker 3: Big Take is Vicky Ergolina. Our senior producer is Catherine Fink. 382 00:21:33,320 --> 00:21:38,120 Speaker 3: Federica Romannello is our producer. Our associate producer is zeneb Sidiki. 383 00:21:38,560 --> 00:21:41,879 Speaker 3: Hil de Garcia is our engineer. Our original music was 384 00:21:41,880 --> 00:21:45,760 Speaker 3: composed by Leo Sidron. I'm wes Kasova. We'll be back 385 00:21:45,800 --> 00:21:48,680 Speaker 3: on Monday with another big take. Have a great weekend.