1 00:00:01,040 --> 00:00:05,040 [sound of rushing wind] 2 00:00:05,040 --> 00:00:09,040 3 00:00:09,040 --> 00:00:13,040 Narrator: It was just four years after the Soviet Union had launched Sputnik … 4 00:00:13,040 --> 00:00:17,000 News reel: Today a new moon is in the sky, a 23-inch metal sphere 5 00:00:17,000 --> 00:00:21,000 placed in orbit by a Russian rocket … Narrator: and the space race was 6 00:00:21,000 --> 00:00:25,000 ramping up into full gear. The first weather satellite, 7 00:00:25,000 --> 00:00:29,040 launched on Apr. 1, 1960, TIROS-1, 8 00:00:29,040 --> 00:00:33,000 enabled us to see weather – at least in the form of cloud cover – 9 00:00:33,000 --> 00:00:37,040 across the globe. For the first time – we could see 10 00:00:37,040 --> 00:00:41,040 today’s weather from space, which provided clues about what tomorrow had in store. 11 00:00:41,040 --> 00:00:45,040 With each passing year, we 12 00:00:45,040 --> 00:00:49,000 we gain more confidence in our weather forecasts, 13 00:00:49,000 --> 00:00:53,040 compulsively checking out the hourly forecast before heading out the door, 14 00:00:53,040 --> 00:00:57,040 or scanning weather radar in real time, 15 00:00:57,040 --> 00:01:01,000 or eyeing the 10-day outlook for next weekend’s plans. 16 00:01:01,000 --> 00:01:05,040 Our ability to predict the weather, though still imperfect, 17 00:01:05,040 --> 00:01:09,040 would astound our recent ancestors. 18 00:01:09,040 --> 00:01:13,040 But not that long ago, weather forecasts were much, much murkier, 19 00:01:13,040 --> 00:01:17,040 and recent improvements have made revolutionary contributions 20 00:01:17,040 --> 00:01:21,040 to not just picnics and daily commutes, but farming, 21 00:01:21,040 --> 00:01:25,000 worldwide economics, construction projects, military strategy, 22 00:01:25,000 --> 00:01:29,000 and travel by air and sea. 23 00:01:29,000 --> 00:01:33,040 We talked to pioneers in the field, who in some cases 24 00:01:33,040 --> 00:01:37,040 have lived the lion’s share of the history of modern weather forecasting. 25 00:01:37,040 --> 00:01:41,040 Out of that, we want to share five things, mostly from the US satellite era, 26 00:01:41,040 --> 00:01:45,040 that changed forecasting forever. 27 00:01:45,040 --> 00:01:49,000 But first we’ll start a little further back into the past … 28 00:01:49,000 --> 00:01:53,040 Uccellini: Throughout the history of what is now the National Weather Service, 29 00:01:53,040 --> 00:01:57,040 threats to life has been one of the main drivers 30 00:01:57,040 --> 00:02:01,000 for us to even exist. 31 00:02:01,000 --> 00:02:05,040 The initial organization that started weather services 32 00:02:05,040 --> 00:02:09,040 in the United States was the Signal Corps which took on 33 00:02:09,040 --> 00:02:13,000 the responsibilities to observe weather and be able to provide 34 00:02:13,000 --> 00:02:17,040 indications of what could happen 35 00:02:17,040 --> 00:02:21,000 that afternoon or the next day. 36 00:02:21,000 --> 00:02:25,000 Narrator: After the Civil War, the Great Lakes were a main highway for commerce,
After the Civil War, the Great Lakes were a main highway for commerce, 37 00:02:25,000 --> 00:02:29,000 and ships frequently sank in surprise storms. 38 00:02:29,000 --> 00:02:33,000 Uccellini: Telegraph lines made it possible to get weather information in real time 39 00:02:33,000 --> 00:02:37,040 time that could all be brought together to provide indications of squalls passing over the lakes. 40 00:02:37,040 --> 00:02:41,040 So that's the creation of the Signal Corps. 41 00:02:41,040 --> 00:02:45,040 Then you move forward in time, in 1888, for example, 42 00:02:45,040 --> 00:02:49,000 there were two major blizzards that affected the United States. 43 00:02:49,000 --> 00:02:53,000 Narrator: These blizzards were barely forecast,
These blizzards were barely forecast, 44 00:02:53,000 --> 00:02:57,000 and hundreds of people lost their lives. 45 00:02:57,000 --> 00:03:01,000 Uccellini: There was a general push to get the weather services out of the military Signal Corps
There was a general push to get the weather services out of the military Signal Corps 46 00:03:01,000 --> 00:03:05,040 into a civilian agency. And that was probably the last straw 47 00:03:05,040 --> 00:03:09,000 straw for many of those who really wanted this to happen and it became much more emphatic. 48 00:03:09,000 --> 00:03:13,040 Narrator: Then the weather disasters of the 1900s – 
Then the weather disasters of the 1900s – 49 00:03:13,040 --> 00:03:17,040 like the surprise Long Island Express Hurricane in 1938 50 00:03:17,040 --> 00:03:21,040 and a major tornado outbreak in 1974 – 51 00:03:21,040 --> 00:03:25,040 spurred interest in new technologies, 52 00:03:25,040 --> 00:03:29,040 like Doppler radar, that could give a local or regional view of developing weather. 53 00:03:29,040 --> 00:03:33,040 But it was really the view from on high 54 00:03:33,040 --> 00:03:37,040 that brought the world’s weather forecasts together. 55 00:03:37,040 --> 00:03:41,040 [sound of applause.] Not many people know that during John F. Kennedy’s 56 00:03:41,040 --> 00:03:45,040 famous speech to Congress in 1961, 57 00:03:45,040 --> 00:03:49,000 he not only set this audacious goal: 58 00:03:49,000 --> 00:03:53,040 Kennedy: First, I believe that this nation should commit itself to achieving the goal, 59 00:03:53,040 --> 00:03:57,000 before this decade is out, of landing a man on the moon 60 00:03:57,000 --> 00:04:01,000 and returning him safely to the Earth. 61 00:04:01,000 --> 00:04:05,040 Narrator: He also called out for the development of nuclear rocket, and a worldwide system 62 00:04:05,040 --> 00:04:09,000 of communications satellites, and … 63 00:04:09,000 --> 00:04:13,040 Kennedy: Fourth, an additional 75 million dollars – of which 53 million dollars is for the Weather Bureau – 64 00:04:13,040 --> 00:04:17,040 will help give us at the earliest possible time a satellite system 65 00:04:17,040 --> 00:04:21,000 for world-wide weather observation. 66 00:04:21,000 --> 00:04:25,000 Narrator: TIROS-1 and 2 had already launched before the Kennedy speech, 67 00:04:25,000 --> 00:04:29,040 but a long series of TIROS satellites followed after, 68 00:04:29,040 --> 00:04:33,040 which were then complemented by the Nimbus program – a set of satellites 69 00:04:33,040 --> 00:04:37,040 designed not just to take pictures, but to actually measure aspects 70 00:04:37,040 --> 00:04:41,040 of the atmosphere from hundreds of miles away – 71 00:04:41,040 --> 00:04:45,040 including temperature, wind speed, and water vapor. 72 00:04:45,040 --> 00:04:49,040 Scientific progress is often slow, building incrementally. 73 00:04:49,040 --> 00:04:53,040 But sometimes science makes giant leaps, 74 00:04:53,040 --> 00:04:57,040 literally overnight. For the field of weather forecasting 75 00:04:57,040 --> 00:05:01,040 this happened one night in 1969, 76 00:05:01,040 --> 00:05:05,040 just three months before the first humans landed on the moon. 77 00:05:05,040 --> 00:05:09,040 It was the night the team behind the NIMBUS 3 satellite 78 00:05:09,040 --> 00:05:13,000 received their first global set of data. 79 00:05:13,000 --> 00:05:17,040 Smith: We stayed up all night and plotted these data on a map.  80 00:05:17,040 --> 00:05:21,040 Hand plotted them when we got the computer. 81 00:05:21,040 --> 00:05:25,040 Just reams of paper with numbers on them, latitude, longitude, temperature values, 82 00:05:25,040 --> 00:05:29,000 altitude and things. It was pretty exciting 83 00:05:29,000 --> 00:05:33,000 because it looked very real, just like a real weather map. But this just came from the satellite. 84 00:05:33,000 --> 00:05:37,000 Nothing else, just the satellite data. 85 00:05:37,000 --> 00:05:41,040 Narrator: When morning came, they brought their weather map to the director of operations 86 00:05:41,040 --> 00:05:45,040 of the National Meteorological Center.  87 00:05:45,040 --> 00:05:49,040 Smith: He says, “Oh my God,” he said, “we've been taking flak from the airlines this morning because we 88 00:05:49,040 --> 00:05:53,040 mis-forecast where the jet stream was going to be. 89 00:05:53,040 --> 00:05:57,000 And our flights to Asia, were not making 90 00:05:57,000 --> 00:06:01,040 their destination … because of the strong headwinds and so on 91 00:06:01,040 --> 00:06:05,000 that we didn't forecast.” And he says, 92 00:06:05,000 --> 00:06:09,000 “Your satellite data shows it. Shows right where it is." 93 00:06:09,000 --> 00:06:13,040 Narrator: The TIROS and Nimbus satellites and other
The TIROS and Nimbus satellites and other 94 00:06:13,040 --> 00:06:17,040 low-orbit satellites that followed, circle round the Earth, 95 00:06:17,040 --> 00:06:21,040 getting different views all the time. But now let’s talk about the view 96 00:06:21,040 --> 00:06:25,000 from ten times higher up. 97 00:06:25,000 --> 00:06:29,040 Mandt: The geostationary program is primarily been a visual imagery program
The geostationary program is primarily been a visual imagery program … 98 00:06:29,040 --> 00:06:33,040 basically flying above the equator at the same rate 99 00:06:33,040 --> 00:06:37,040 as the Earth spins. So to a person on the Earth, it appears that it's stationary, 100 00:06:37,040 --> 00:06:41,040 and what that allows you to do is see the Earth from the same vantage points 101 00:06:41,040 --> 00:06:45,040 continuously. So you could basically take movies. So you can update 102 00:06:45,040 --> 00:06:49,040 the picture every 30 seconds, if you want. 103 00:06:49,040 --> 00:06:53,000 When you loop those, you get a sense of the motion of the weather. 104 00:06:53,000 --> 00:06:57,000 Uccellini: We forget the days where the TV folks
We forget the days where the TV folks 105 00:06:57,000 --> 00:07:01,000 who were talking about a storm being out in the Atlantic couldn't even show where it was, 106 00:07:01,000 --> 00:07:05,000 just that the Hurricane Center is tracking it. Papers have been written about how 107 00:07:05,000 --> 00:07:09,000 the geostationary satellite was probably the most important 108 00:07:09,000 --> 00:07:13,000 observing system with its ground processing in the history 109 00:07:13,000 --> 00:07:17,000 of advancing the Hurricane Center because 110 00:07:17,000 --> 00:07:21,000 it gave them the situational awareness of where that storm was, 111 00:07:21,000 --> 00:07:25,000 where it was going, and the intensity changes 112 00:07:25,000 --> 00:07:29,000 as it was moving in real time. 113 00:07:29,000 --> 00:07:33,000 It was just an amazing eye-opening experience for the Hurricane Center. 114 00:07:33,000 --> 00:07:37,000 Narrator: So geostationary satellites give us, literally, 115 00:07:37,000 --> 00:07:41,000 the big picture. But from a data standpoint, it’s usually been 116 00:07:41,000 --> 00:07:45,000 the low orbit satellites, usually in a polar orbit, 117 00:07:45,000 --> 00:07:49,000 that are the workhorses of the weather fleet. 118 00:07:49,000 --> 00:07:53,000 Mandt: So the polar orbiting satellites compliment the geostationary 
So the polar orbiting satellites compliment the geostationary … 119 00:07:53,000 --> 00:07:57,000 are basically flying at little over 500 miles up. And when you're at that altitude 120 00:07:57,000 --> 00:08:01,000 you can sense what's in the atmosphere 121 00:08:01,000 --> 00:08:05,000 to a lot higher resolution. And for weather forecasting, 122 00:08:05,000 --> 00:08:09,000 you really want to understand the state of the atmosphere, 123 00:08:09,000 --> 00:08:13,000 primarily temperature and water vapor, and winds. 124 00:08:13,000 --> 00:08:17,000 Twice a day, each satellite is giving a really detailed measurement of the atmosphere 125 00:08:17,000 --> 00:08:21,000 and its state, which is the beginning then to understand 126 00:08:21,000 --> 00:08:25,000 what is the state of the global atmosphere to then project 127 00:08:25,000 --> 00:08:29,000 it forward to produce a weather forecast. 128 00:08:29,000 --> 00:08:33,000 Narrator: The early Nimbus satellites began our legacy of low-orbit data collection,
TSo the early Nimbus satellites began our legacy of low-orbit 129 00:08:33,000 --> 00:08:37,000 but one of the biggest leaps came fromm our ability to measure 130 00:08:37,000 --> 00:08:41,000 literally thousands of different frequencies of energy, representing 131 00:08:41,000 --> 00:08:45,000 an all-weather profile of the atmosphere. 132 00:08:45,000 --> 00:08:49,000 [engine noise] For NASA Goddard Space Flight Center’s Ed Kim, 133 00:08:49,000 --> 00:08:53,000 that all-weather view is never far from his mind. 134 00:08:53,000 --> 00:08:57,000 Kim: I have a vested interest
I have a vested interest 135 00:08:57,000 --> 00:09:01,000 in helping improve weather forecasts. 136 00:09:01,000 --> 00:09:05,000 The hobby of, of flying and the work of improving weather sensors 137 00:09:05,000 --> 00:09:09,000 is a nice combination. They really go hand in hand. 138 00:09:09,000 --> 00:09:13,000 When you're flying around and looking at clouds or looking at weather patterns as you're flying in an airplane, 139 00:09:13,000 --> 00:09:17,000 it's hard not to think about … what a microwave sensor 140 00:09:17,000 --> 00:09:21,000 would see when it's trying to look through that cloud over there to the right.
 141 00:09:21,000 --> 00:09:25,000 So everybody's probably familiar with radio transmissions. 142 00:09:25,000 --> 00:09:29,000 You have a transmitter, you have a receiver, maybe when you were kids you played with walkie-talkies 143 00:09:29,000 --> 00:09:33,000 or you listen to the radio in your car, there's a transmitter somewhere and the receiver is in your car. 144 00:09:33,000 --> 00:09:37,000 Microwaves sounders are just the same thing. 145 00:09:37,000 --> 00:09:41,000 They're just different radio frequencies. So, you might ask well, 146 00:09:41,000 --> 00:09:45,000 what is the receiver receiving? It's actually receiving natural signals 147 00:09:45,000 --> 00:09:49,000 that are emitted by the gases in the atmosphere itself. 148 00:09:49,000 --> 00:09:53,000 All natural objects … 149 00:09:53,000 --> 00:09:57,000 Everything emits a very tiny amount of microwave energy. 150 00:09:57,000 --> 00:10:01,000 And those microwave frequencies happen to allow you to 151 00:10:01,000 --> 00:10:05,000 detect the condition of the atmosphere. And so … 152 00:10:05,000 --> 00:10:09,000 then you can construct the vertical temperature, 153 00:10:09,000 --> 00:10:13,000 we call it a profile, a vertical temperature structure of the atmosphere. 154 00:10:13,000 --> 00:10:17,000 The primary reason that you have both 155 00:10:17,000 --> 00:10:21,000 the microwave and the infrared is that 156 00:10:21,000 --> 00:10:25,000 the microwave sensors, in general, for the most part can, see through clouds. 157 00:10:25,000 --> 00:10:29,000 Just the fact that you could see through the clouds and still figure out the structure of the atmosphere was a gigantic leap forward. 158 00:10:29,000 --> 00:10:33,000 Combined the microwave data and the infrared data 159 00:10:33,000 --> 00:10:37,000 provide that really critical vertical 160 00:10:37,000 --> 00:10:41,000 structure information of the atmosphere to the weather forecasters. 161 00:10:41,000 --> 00:10:45,000 Essentially the most critical information 162 00:10:45,000 --> 00:10:49,000 they need for weather forecasts. 163 00:10:49,000 --> 00:10:53,000 Narrator: So we have a non-stop visual recon of the planet from geostationary satellites, 
So we have a non-stop visual recon of the planet from geostationary satellites, 164 00:10:53,000 --> 00:10:57,000 and highly detailed atmospheric measurements from polar orbiters. 165 00:10:57,000 --> 00:11:01,000 But … all that data coming down 166 00:11:01,000 --> 00:11:05,000 wouldn’t mean much without the quantum leaps in computing power 167 00:11:05,000 --> 00:11:09,000 we’ve seen over this time period, and the massive amounts of work 168 00:11:09,000 --> 00:11:13,000 that have gone into creating computer models of weather and our atmosphere. 169 00:11:13,000 --> 00:11:17,000 One of the pioneers in this field 170 00:11:17,000 --> 00:11:21,000 is Eugenia Kalnay, who after escaping 171 00:11:21,000 --> 00:11:25,000 a brutal crackdown on academia in Argentina, 172 00:11:25,000 --> 00:11:29,000 became the first woman to graduate from MIT in meteorology, 173 00:11:29,000 --> 00:11:33,000 and has possibly the most often cited paper in all of the Earth sciences. 174 00:11:33,000 --> 00:11:37,000 One of her major fields of study has been the ensemble forecast – 175 00:11:37,000 --> 00:11:41,000 basically comparing bits of forecast model information 176 00:11:41,000 --> 00:11:45,000 against each other to figure out what’s working and what’s not. 177 00:11:45,000 --> 00:11:49,000 Kalnay: This method allows you to determine 
This method allows you to determine 178 00:11:49,000 --> 00:11:53,000 whether each observation is good or bad. 179 00:11:53,000 --> 00:11:57,000 If it helps the forecast or it makes it worse. 180 00:11:57,000 --> 00:12:01,000 And I realized that we could do that with 181 00:12:01,000 --> 00:12:05,000 every observation and determine whether it was 182 00:12:05,000 --> 00:12:09,000 beneficial or detrimental, we could take away 183 00:12:09,000 --> 00:12:13,000 the detrimental observations and only use the beneficial ones. 184 00:12:13,000 --> 00:12:17,000 And that improved the forecast quite a lot – 185 00:12:17,000 --> 00:12:21,000 substantially. 186 00:12:21,000 --> 00:12:25,000 Not not just a little bit that you cannot see, 187 00:12:25,000 --> 00:12:29,000 but for eight days, the forecast is better. 188 00:12:29,000 --> 00:12:33,000 So that I feel, I feel 189 00:12:33,000 --> 00:12:37,000 very happy about that result. 190 00:12:37,000 --> 00:12:41,000 Narrator: Before the ensemble, she says, the National Weather Service 
Before the ensemble, she says, the National Weather Service 191 00:12:41,000 --> 00:12:45,000 would calculate a forecast for 15 days, but only show 192 00:12:45,000 --> 00:12:49,000 three days to the public. But in the 1980s, we made a major leap. 193 00:12:49,000 --> 00:12:53,000 Kalnay: That was the first time that the human forecasters 194 00:12:53,000 --> 00:12:57,000 there make a forecast for five days because 195 00:12:57,000 --> 00:13:01,000 they show that all the ensemble forecast were similar. 196 00:13:01,000 --> 00:13:05,000 The TV meteorologists immediately, 197 00:13:05,000 --> 00:13:09,000 some, the most advanced of them, 198 00:13:09,000 --> 00:13:13,000 immediately realized that they could give 199 00:13:13,000 --> 00:13:17,000 forecast much longer than three days. 200 00:13:17,000 --> 00:13:21,000 Narrator: So now we have the data, and we have the computers and the models to run on them – 201 00:13:21,000 --> 00:13:25,000 but that still doesn’t do us any good if we can’t get the data down from the satellites, 202 00:13:25,000 --> 00:13:29,000 processed, and then out to the people who need it. 203 00:13:29,000 --> 00:13:33,000 Mandt: We're sitting here at the NSOF building. It's really the operation center
We're sitting here at the NSOF building. It's really the operation center 204 00:13:33,000 --> 00:13:37,000 for all of our NOAA satellites. So, behind me you can see the floor 205 00:13:37,000 --> 00:13:41,000 where not only do we fly the geostationary satellites, the polar orbiting satellites, 206 00:13:41,000 --> 00:13:45,000 including JPSS-1 which is now called NOAA-20. 207 00:13:45,000 --> 00:13:49,000 The primary purpose of this building then is to fly 208 00:13:49,000 --> 00:13:53,000 the satellites and then take the data from those satellites and process it 209 00:13:53,000 --> 00:13:57,000 and be able to put out the products for the nation. 210 00:13:57,000 --> 00:14:01,000 The data that flows from all of the satellites produces a lot of the products 211 00:14:01,000 --> 00:14:05,000 that are used in the weather forecasting that everybody sort of uses 212 00:14:05,000 --> 00:14:09,000 every day and may not really understand where it's coming from. 213 00:14:09,000 --> 00:14:13,000 But this is the heart and soul of what the nation gets for weather forecasting. 214 00:14:13,000 --> 00:14:17,000 The nice thing about working in this business is we know it's helping people, it's helping people over the world. 215 00:14:17,000 --> 00:14:21,000 And all the countries of the world collaborate very well together 216 00:14:21,000 --> 00:14:25,000 in sharing this data because it's all of mutual benefit. 217 00:14:25,000 --> 00:14:29,000 Narrator: But the getting those forecasts out is still not the end of the line. 
But the getting those forecasts out is still not the end of the line. 218 00:14:29,000 --> 00:14:33,000 In emergency weather situations, the right people have to get the right information to make critical decisions. 219 00:14:33,000 --> 00:14:37,000 Uccellini: Well, one of the new areas 
Well, one of the new areas 220 00:14:37,000 --> 00:14:41,000 that the Weather Service is fully engaged in 221 00:14:41,000 --> 00:14:45,000 is the idea that making a forecast and a warning 222 00:14:45,000 --> 00:14:49,000 is not good enough. 223 00:14:49,000 --> 00:14:53,000 And there's a whole range of decision makers, there's organized decision makers, government agencies 224 00:14:53,000 --> 00:14:57,000 at the federal, state, and local levels, all work together to save lives and property. 225 00:14:57,000 --> 00:15:01,000 And then you've got individuals, everybody with a cell phone now 226 00:15:01,000 --> 00:15:05,000 is a decision maker. They can download all this stuff 227 00:15:05,000 --> 00:15:09,000 and decide whether they're going to evacuate or not, right? 228 00:15:09,000 --> 00:15:13,000 So we're into human factors now. We're into social science. So this combination of physical and social science 229 00:15:13,000 --> 00:15:17,000 science is really a big deal for us in … how we meet the needs 230 00:15:17,000 --> 00:15:21,000 of the emergency management community. 231 00:15:21,000 --> 00:15:25,000 If we all want to get down to societal benefits, this is what we've got to do. 232 00:15:25,000 --> 00:15:29,000 We've embarked on this over the last six, seven, eight years 233 00:15:29,000 --> 00:15:33,000 and it's starting, it’s starting to work. 234 00:15:33,000 --> 00:15:37,000 The part of the mission to protect life and property is really the driver, 235 00:15:37,000 --> 00:15:41,000 it's what brings people to work every day 236 00:15:41,000 --> 00:15:47,605 and we’re certainly dedicated to that mission.