1 00:00:06,446 --> 00:00:09,026 From 2016 to 2019, 2 00:00:09,026 --> 00:00:13,321 meteorologists saw record-breaking heat waves around the globe, 3 00:00:13,321 --> 00:00:16,821 rampant wildfires in California and Australia, 4 00:00:16,821 --> 00:00:21,801 and the longest run of category 5 tropical cyclones on record. 5 00:00:21,801 --> 00:00:26,611 The number of extreme weather events has been increasing for the last 40 years, 6 00:00:26,611 --> 00:00:30,521 and current predictions suggest that trend will continue. 7 00:00:30,521 --> 00:00:34,021 But are these natural disasters simply bad weather? 8 00:00:34,021 --> 00:00:37,451 Or are they due to our changing climate? 9 00:00:37,451 --> 00:00:38,751 To answer this question 10 00:00:38,751 --> 00:00:42,511 we need to understand the differences between weather and climate— 11 00:00:42,511 --> 00:00:48,022 what they are, how we predict them, and what those predictions can tell us. 12 00:00:48,022 --> 00:00:52,078 Meteorologists define weather as the conditions of the atmosphere 13 00:00:52,078 --> 00:00:54,908 at a particular time and place. 14 00:00:54,908 --> 00:00:58,318 Currently, researchers can predict a region’s weather for the next week 15 00:00:58,318 --> 00:01:01,088 with roughly 80% accuracy. 16 00:01:01,088 --> 00:01:05,485 Climate describes a region’s average atmospheric conditions 17 00:01:05,485 --> 00:01:08,685 over periods of a month or more. 18 00:01:08,685 --> 00:01:13,110 Climate predictions can forecast average temperatures for decades to come, 19 00:01:13,110 --> 00:01:17,719 but they can’t tell us what specific weather events to expect. 20 00:01:17,719 --> 00:01:21,775 These two types of predictions give us such different information 21 00:01:21,775 --> 00:01:24,875 because they’re based on different data. 22 00:01:24,875 --> 00:01:26,275 To forecast weather, 23 00:01:26,275 --> 00:01:30,415 meteorologists need to measure the atmosphere’s initial conditions. 24 00:01:30,415 --> 00:01:35,380 These are the current levels of precipitation, air pressure, humidity, 25 00:01:35,380 --> 00:01:40,282 wind speed and wind direction that determine a region’s weather. 26 00:01:40,282 --> 00:01:45,063 Twice every day, meteorologists from over 800 stations around the globe 27 00:01:45,063 --> 00:01:47,983 release balloons into the atmosphere. 28 00:01:47,983 --> 00:01:51,923 These balloons carry instruments called radiosondes, 29 00:01:51,923 --> 00:01:53,444 which measure initial conditions 30 00:01:53,444 --> 00:01:57,284 and transmit their findings to international weather centers. 31 00:01:57,284 --> 00:02:01,014 Meteorologists then run the data through predictive physics models 32 00:02:01,014 --> 00:02:03,954 that generate the final weather forecast. 33 00:02:03,954 --> 00:02:07,394 Unfortunately, there’s something stopping this global web of data 34 00:02:07,394 --> 00:02:09,804 from producing a perfect prediction: 35 00:02:09,804 --> 00:02:13,494 weather is a fundamentally chaotic system. 36 00:02:13,494 --> 00:02:17,807 This means it’s incredibly sensitive and impossible to perfectly forecast 37 00:02:17,807 --> 00:02:21,807 without absolute knowledge of all the system’s elements. 38 00:02:21,807 --> 00:02:23,907 In a period of just ten days, 39 00:02:23,907 --> 00:02:30,015 even incredibly small disturbances can massively impact atmospheric conditions— 40 00:02:30,015 --> 00:02:35,278 making it impossible to reliably predict weather beyond two weeks. 41 00:02:35,278 --> 00:02:39,278 Climate prediction, on the other hand, is far less turbulent. 42 00:02:39,278 --> 00:02:42,498 This is partly because a region’s climate is, by definition, 43 00:02:42,498 --> 00:02:45,398 the average of all its weather data. 44 00:02:45,398 --> 00:02:48,378 But also because climate forecasts ignore 45 00:02:48,378 --> 00:02:50,868 what’s currently happening in the atmosphere, 46 00:02:50,868 --> 00:02:54,128 and focus on the range of what could happen. 47 00:02:54,128 --> 00:02:57,748 These parameters are known as boundary conditions, 48 00:02:57,748 --> 00:03:03,064 and as their name suggests, they act as constraints on climate and weather. 49 00:03:03,064 --> 00:03:07,186 One example of a boundary condition is solar radiation. 50 00:03:07,186 --> 00:03:12,450 By analyzing the precise distance and angle between a location and the sun, 51 00:03:12,450 --> 00:03:16,160 we can determine the amount of heat that area will receive. 52 00:03:16,160 --> 00:03:19,380 And since we know how the sun behaves throughout the year, 53 00:03:19,380 --> 00:03:22,820 we can accurately predict its effects on temperature. 54 00:03:22,820 --> 00:03:25,250 Averaged across years of data, 55 00:03:25,250 --> 00:03:29,742 this reveals periodic patterns, including seasons. 56 00:03:29,742 --> 00:03:34,693 Most boundary conditions have well-defined values that change slowly, if at all. 57 00:03:34,693 --> 00:03:39,401 This allows researchers to reliably predict climate years into the future. 58 00:03:39,401 --> 00:03:41,741 But here’s where it gets tricky. 59 00:03:41,741 --> 00:03:44,421 Even the slightest change in these boundary conditions 60 00:03:44,421 --> 00:03:48,656 represents a much larger shift for the chaotic weather system. 61 00:03:48,656 --> 00:03:53,436 For example, Earth’s surface temperature has warmed by almost 1 degree Celsius 62 00:03:53,436 --> 00:03:56,256 over the last 150 years. 63 00:03:56,256 --> 00:03:58,666 This might seem like a minor shift, 64 00:03:58,666 --> 00:04:02,226 but this 1-degree change has added the energy equivalent 65 00:04:02,226 --> 00:04:06,904 of roughly one million nuclear warheads into the atmosphere. 66 00:04:06,904 --> 00:04:11,545 This massive surge of energy has already led to a dramatic increase 67 00:04:11,545 --> 00:04:15,722 in the number of heatwaves, droughts, and storm surges. 68 00:04:15,722 --> 00:04:21,651 So, is the increase in extreme weather due to random chance, or changing climate? 69 00:04:21,651 --> 00:04:23,001 The answer is that— 70 00:04:23,001 --> 00:04:26,441 while weather will always be a chaotic system— 71 00:04:26,441 --> 00:04:31,782 shifts in our climate do increase the likelihood of extreme weather events. 72 00:04:31,782 --> 00:04:36,820 Scientists are in near universal agreement that our climate is changing 73 00:04:36,820 --> 00:04:40,490 and that human activity is accelerating those changes. 74 00:04:40,490 --> 00:04:41,890 But fortunately, 75 00:04:41,890 --> 00:04:46,253 we can identify what human behaviors are impacting the climate most 76 00:04:46,253 --> 00:04:49,513 by tracking which boundary conditions are shifting. 77 00:04:49,513 --> 00:04:53,840 So even though next month’s weather might always be a mystery, 78 00:04:53,840 --> 00:04:59,120 we can work together to protect the climate for centuries to come.