1 00:00:03,333 --> 00:00:06,973 DAISY: NASA spends lots of time and resources studying the weather. 2 00:00:06,975 --> 00:00:10,343 And winter weather is particularly important. 3 00:00:10,345 --> 00:00:14,613 That’s why NASA sponsors the History of Winter workshop for teachers... 4 00:00:14,615 --> 00:00:18,083 We’ll take you to a frozen Lake Placid to learn about 5 00:00:18,085 --> 00:00:21,020 the tools that measure the conditions of our coldest season... 6 00:00:21,021 --> 00:00:23,623 Next on Real World. 7 00:00:23,625 --> 00:00:26,891 ? [music] ? 8 00:00:31,096 --> 00:00:34,166 Winter conditions here on earth are very important to 9 00:00:34,168 --> 00:00:36,368 NASA Scientists and engineers. 10 00:00:36,370 --> 00:00:39,371 The agency’s aeronautics mission relies on data 11 00:00:39,373 --> 00:00:41,775 gathered during the coldest part of the year. 12 00:00:41,776 --> 00:00:44,010 They use it to develop systems that will allow 13 00:00:44,011 --> 00:00:47,113 planes to fly better and safer in winter conditions... 14 00:00:48,350 --> 00:00:52,051 The exploration mission studies winter conditions, too. 15 00:00:52,120 --> 00:00:55,088 Data related to harsh winter-like conditions here, 16 00:00:55,090 --> 00:00:58,591 give scientists perspective about other places in the universe... 17 00:00:58,593 --> 00:01:00,826 like the Moon or Mars... 18 00:01:00,828 --> 00:01:03,630 ALLEN LUNSFORD: Now that we’re discovering more closely, 19 00:01:03,631 --> 00:01:06,631 ice on other planets, it’s important to understand their properties. 20 00:01:06,633 --> 00:01:09,535 DAISY: Allen Lunsford is a NASA computer scientist 21 00:01:09,536 --> 00:01:11,938 and History of Winter technologist. 22 00:01:11,940 --> 00:01:15,375 ALLEN: Not only of natural ice, on earth, but ice that 23 00:01:15,376 --> 00:01:18,076 forms in other conditions that you don’t find on earth. 24 00:01:18,078 --> 00:01:20,546 Higher pressures, lower pressures, different 25 00:01:20,548 --> 00:01:23,750 temperature regimes, the same concepts that we learn 26 00:01:23,751 --> 00:01:26,118 here at H.O.W. are the concepts that are used by 27 00:01:26,120 --> 00:01:29,421 scientists to study ice all over the solar system 28 00:01:29,423 --> 00:01:32,191 DAISY: Teachers come to Lake Placid, New York and become 29 00:01:32,193 --> 00:01:35,061 scientists for a week, rolling their sleeves up and 30 00:01:35,063 --> 00:01:38,365 taking a hands on approach to understanding winter. 31 00:01:38,366 --> 00:01:41,466 One of the things these teacher-slash-scientists do 32 00:01:41,468 --> 00:01:45,105 is learn how to measure abiotic conditions of Winter. 33 00:01:45,106 --> 00:01:48,273 Abiotic conditions are all the non-living elements of an 34 00:01:48,275 --> 00:01:51,711 ecosystem, like air and soil, and snow and ice. 35 00:01:51,713 --> 00:01:56,515 At Lake Placid, they use lots of tools for measuring these conditions. 36 00:01:56,516 --> 00:01:59,385 One of the simplest tools to measure ice is called a 37 00:01:59,386 --> 00:02:02,588 thermochron, and teachers at History of Winter 38 00:02:02,590 --> 00:02:05,025 get a lot of use out of this tool. 39 00:02:05,026 --> 00:02:07,126 ALLEN: A thermchron is a little data logger. 40 00:02:07,128 --> 00:02:09,828 It has a clock and a little computer and some memory, so 41 00:02:09,830 --> 00:02:12,598 it keeps track of time and temperature. 42 00:02:12,600 --> 00:02:15,368 It’s really kind of small, compact and rugged. 43 00:02:15,370 --> 00:02:18,170 So you can connect it to a computer and program it to 44 00:02:18,171 --> 00:02:21,941 record the temperature every minute, every two minutes, whatever you like. 45 00:02:21,943 --> 00:02:24,176 It’s rugged enough that you can bury it in the sand or 46 00:02:24,178 --> 00:02:27,146 put it under water or put it in a snow pack, and later 47 00:02:27,148 --> 00:02:29,948 retrieve it, connect it to the computer again, download 48 00:02:29,950 --> 00:02:32,951 the data and then analyze the temperature history 49 00:02:32,953 --> 00:02:35,655 that the thermachron experienced. 50 00:02:35,656 --> 00:02:37,813 DAISY: Here’s an experiment you can do with a thermochron... 51 00:02:37,815 --> 00:02:42,795 Drop it in a glass of water... put the glass in the freezer, and let it freeze. 52 00:02:45,533 --> 00:02:48,901 Then take it out of the freezer, 53 00:02:48,903 --> 00:02:51,905 and let it melt. 54 00:02:51,906 --> 00:02:55,875 This is going to talk a little while. 55 00:02:55,876 --> 00:02:59,178 Once it’s back to room temperature, pull the 56 00:02:59,180 --> 00:03:02,848 thermochron out and check the data on a computer. 57 00:03:02,850 --> 00:03:05,685 ALLEN: That’s a great experiment, to show them the 58 00:03:05,686 --> 00:03:09,721 concept of latent heat, where it’ll start warm and come 59 00:03:09,723 --> 00:03:12,525 down to the freezing point of water, zero degrees and then 60 00:03:12,526 --> 00:03:16,696 it will stay zero for a long time, and as all the water in 61 00:03:16,698 --> 00:03:19,631 that cup freezes, and then once it’s all frozen, 62 00:03:19,633 --> 00:03:23,001 only then does the ice start to get colder and it 63 00:03:23,003 --> 00:03:26,071 will get as cold as the freezer. When you take it out of the freezer, 64 00:03:26,073 --> 00:03:29,075 it’ll get warmer, really quickly, right up to zero, 65 00:03:29,076 --> 00:03:32,178 and then it will stay zero for a long time until all 66 00:03:32,180 --> 00:03:35,048 that ice has melted and then it will get room temperature. 67 00:03:35,050 --> 00:03:38,351 Those little areas there, where it maintains 68 00:03:38,353 --> 00:03:41,053 temperature, even though it’s absorbing heat or 69 00:03:41,055 --> 00:03:44,590 releasing is that latent heat concept. 70 00:03:44,591 --> 00:03:47,560 DAISY: Another Abiotic condition that scientists 71 00:03:47,561 --> 00:03:50,563 want to learn more about is snow. And there are lots of 72 00:03:50,565 --> 00:03:53,031 ways they measure snow at HOW. 73 00:03:53,033 --> 00:03:55,701 TOM ALENA: You actually use what is called a snowboard. 74 00:03:55,703 --> 00:03:59,705 DAISY: Tom Alena is a meteorologist at Talcott Mountain Science Center. 75 00:03:59,706 --> 00:04:03,710 TOM: Not a fancy thing you go downhill snowboarding in. 76 00:04:03,711 --> 00:04:07,813 It’s a piece of plywood, maybe 2x2. You place it on 77 00:04:07,815 --> 00:04:10,383 the surface of the snow before the storm. 78 00:04:10,385 --> 00:04:15,088 And every six hours or so you measure the accumulation on that board. 79 00:04:15,090 --> 00:04:17,856 DAISY: But then you have to reset the board. Cleaning 80 00:04:17,858 --> 00:04:21,426 the accumulated snow off. This is very important. 81 00:04:21,428 --> 00:04:24,096 TOM: The more snow that’s on it, it’s going to compact the 82 00:04:24,098 --> 00:04:26,733 snow so if you went two days after the storm, and just 83 00:04:26,735 --> 00:04:30,003 measured the one measurement, you might have a little less 84 00:04:30,005 --> 00:04:33,171 snow than what really did fall. 85 00:04:33,173 --> 00:04:37,010 DAISY: It’s also important to measure the density of the snow. 86 00:04:37,011 --> 00:04:40,513 TOM: We can calculate using those snow tubes, putting 87 00:04:40,515 --> 00:04:44,583 them on a weight, a certain known volume, with a weight, 88 00:04:44,585 --> 00:04:49,188 grams per cubic centimeter, and we can get densities. 89 00:04:49,190 --> 00:04:52,258 DAISY: Scientists use this information to determine the 90 00:04:52,260 --> 00:04:54,360 snow water equivalent. 91 00:04:54,361 --> 00:04:57,596 This is the amount of water contained within a snow pack. 92 00:04:57,598 --> 00:05:02,835 TOM: A layer of snow... how much water would be if you melted that down. 93 00:05:02,836 --> 00:05:06,371 A good start is 10:1. So ten inches of snow would melt 94 00:05:06,373 --> 00:05:09,308 down to a one inch layer of water. 95 00:05:09,310 --> 00:05:14,513 Cold dry fluffy snow... that could be 2,0 even 30 to One. 96 00:05:14,515 --> 00:05:19,685 The very heavy stuff, sleet is almost 2:1, and ice of 97 00:05:19,686 --> 00:05:23,390 course, would be a one to one. 98 00:05:23,391 --> 00:05:25,958 DAISY: More data about snow density can be recorded 99 00:05:25,960 --> 00:05:28,495 simply by observing the snow flakes. 100 00:05:28,496 --> 00:05:31,865 TOM: If they come out of the cloud base at that point, they are beautiful. 101 00:05:31,866 --> 00:05:35,601 They’re like little glass sculptures. However, if they 102 00:05:35,603 --> 00:05:39,605 continue going through a lot of cloud, the cloud droplets stick to it. 103 00:05:39,606 --> 00:05:44,310 It’s called riming. Those crystals tend to have a lower snow ratio. 104 00:05:44,311 --> 00:05:48,481 Moisture and temperature, very important variables in the cloud. 105 00:05:48,483 --> 00:05:52,885 DAISY: There are a lot of very practical reasons to study snow density. 106 00:05:52,886 --> 00:05:55,955 TOM: It’s very important in watershed resources. 107 00:05:55,956 --> 00:05:58,625 In the western United States where the Sierra Nevada 108 00:05:58,626 --> 00:06:03,261 harbor the entire summer water supply for much of the big cities. 109 00:06:03,263 --> 00:06:06,198 People there, doing core samples all the time in the 110 00:06:06,200 --> 00:06:09,801 snow to look, how deep? How is its density? 111 00:06:09,803 --> 00:06:14,973 And calculate how much water is up there for the spring and early summer melt. 112 00:06:15,941 --> 00:06:20,246 DAISY: Studying snow density can also help predict avalanche dangers. 113 00:06:20,315 --> 00:06:23,148 When snow of different densities get’s layered, 114 00:06:23,150 --> 00:06:26,318 one on top of the other, layers tend to slip. 115 00:06:26,320 --> 00:06:29,888 Especially when you get a layer of low density icy snow. 116 00:06:29,890 --> 00:06:32,425 TOM: That ice layer can really act as a slippery 117 00:06:32,426 --> 00:06:35,395 surface for a brand new snow fall. 118 00:06:35,396 --> 00:06:39,465 That’s usually there where you’d expect slippage. 119 00:06:40,776 --> 00:06:44,236 DAISY: So now you see why it’s important to study about these topics. 120 00:06:44,305 --> 00:06:47,473 But from NASA’s perspective, the best reason to bring 121 00:06:47,475 --> 00:06:50,410 these teachers up here is so they bring back great ideas 122 00:06:50,411 --> 00:06:54,246 to the classroom, teaching kids to grow up thinking like scientists. 123 00:06:54,248 --> 00:06:57,250 And those kids will be the ones who lead NASA forward 124 00:06:57,251 --> 00:07:00,320 through the next generation, and continue exploring our 125 00:07:00,321 --> 00:07:03,055 world and the worlds beyond. 126 00:07:03,056 --> 00:07:07,130 ? 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