1 00:00:03,889 --> 00:00:01,429 laughs 2 00:00:10,730 --> 00:00:03,899 I didn't think I was tired but I think 3 00:00:10,740 --> 00:00:15,550 yeah Frozen granola 4 00:00:20,750 --> 00:00:18,890 I'm Carrie voyevich I'm a research 5 00:00:25,009 --> 00:00:20,760 scientist at Nasa Goddard I'm a project 6 00:00:27,950 --> 00:00:25,019 scientist for NASA snowx 2023 we're here 7 00:00:36,220 --> 00:00:27,960 in Alaska in Fairbanks measuring snow in 8 00:00:36,230 --> 00:00:54,310 [Music] 9 00:01:08,590 --> 00:00:56,100 hold on to your breakfast 10 00:01:14,270 --> 00:01:11,690 we're in creamers field Farmers Loop 11 00:01:16,609 --> 00:01:14,280 research site right now we have three 12 00:01:18,469 --> 00:01:16,619 sites here in Fairbanks and then we have 13 00:01:20,630 --> 00:01:18,479 two sites on the North Slope in the 14 00:01:24,530 --> 00:01:20,640 tundra 15 00:01:26,770 --> 00:01:24,540 the goal for snowx is to improve our 16 00:01:29,690 --> 00:01:26,780 remote sensing capabilities of snow 17 00:01:31,310 --> 00:01:29,700 different properties of snow in 18 00:01:33,170 --> 00:01:31,320 different environments and at different 19 00:01:35,749 --> 00:01:33,180 times of the season 20 00:01:38,990 --> 00:01:35,759 water is so important to the Western U.S 21 00:01:41,630 --> 00:01:39,000 and they've had some snow droughts over 22 00:01:43,609 --> 00:01:41,640 the past decade and so understanding how 23 00:01:45,830 --> 00:01:43,619 much water is stored in the snow is 24 00:01:48,590 --> 00:01:45,840 super important right now that means 25 00:01:50,510 --> 00:01:48,600 either Airborne measurements or sending 26 00:01:52,550 --> 00:01:50,520 people out to make manual measurements 27 00:01:55,249 --> 00:01:52,560 which doesn't cover the entire Western 28 00:01:56,569 --> 00:01:55,259 U.S so what we're hoping is that our 29 00:01:58,730 --> 00:01:56,579 measurements will help us understand 30 00:02:00,830 --> 00:01:58,740 what technology could be used on a 31 00:02:02,510 --> 00:02:00,840 satellite mission that could then 32 00:02:04,630 --> 00:02:02,520 collect measurements over that entire 33 00:02:07,370 --> 00:02:04,640 area 34 00:02:10,669 --> 00:02:07,380 so kind of core measurements take place 35 00:02:12,470 --> 00:02:10,679 at these the pit locations we take very 36 00:02:15,050 --> 00:02:12,480 detailed profile measurements of the 37 00:02:17,990 --> 00:02:15,060 snow in those pits including temperature 38 00:02:20,630 --> 00:02:18,000 and density liquid water content and 39 00:02:23,449 --> 00:02:20,640 then around those plots we're taking 40 00:02:25,190 --> 00:02:23,459 very detailed depth profiles and then 41 00:02:28,130 --> 00:02:25,200 further out from there we're taking just 42 00:02:30,710 --> 00:02:28,140 a lot more depth measurements 43 00:02:33,190 --> 00:02:30,720 all of that is within the flight lines 44 00:02:36,350 --> 00:02:33,200 of the the radar and the lidar 45 00:02:37,850 --> 00:02:36,360 observations so that we can connect what 46 00:02:41,809 --> 00:02:37,860 those observations see with what we 47 00:02:45,470 --> 00:02:43,729 we're headed to Bonanza Creek 48 00:02:47,930 --> 00:02:45,480 experimental 49 00:02:49,430 --> 00:02:47,940 forest and we're gonna do a bunch of pit 50 00:02:50,750 --> 00:02:49,440 measurements out there and depth 51 00:02:53,990 --> 00:02:50,760 measurements where we characterize 52 00:02:56,150 --> 00:02:54,000 snowpack in different locations and that 53 00:02:58,850 --> 00:02:56,160 will be used for ground Truth for the 54 00:03:02,570 --> 00:02:58,860 air Airborne flights and instruments 55 00:03:05,449 --> 00:03:02,580 that we have flying over the same area 56 00:03:07,190 --> 00:03:05,459 about minus 20 Fahrenheit here right now 57 00:03:09,770 --> 00:03:07,200 and I'm continuing to put on clothes 58 00:03:13,550 --> 00:03:09,780 because I just got out of the truck and 59 00:03:17,110 --> 00:03:13,560 that was pretty warm and I'm changing 60 00:03:20,630 --> 00:03:17,120 body temperature very quickly 61 00:03:23,350 --> 00:03:20,640 and I'm with the USDA natural resources 62 00:03:25,970 --> 00:03:23,360 conservation service we actually are 63 00:03:28,190 --> 00:03:25,980 tasked with making water supply 64 00:03:30,470 --> 00:03:28,200 forecasts for the entire Western United 65 00:03:33,229 --> 00:03:30,480 States we have about 600 different 66 00:03:35,750 --> 00:03:33,239 watersheds that we model and deliver 67 00:03:39,770 --> 00:03:35,760 seasonal runoff forecasts for the reason 68 00:03:42,770 --> 00:03:39,780 why we look at snow density is so that 69 00:03:45,830 --> 00:03:42,780 if you have a given snowpack five feet 70 00:03:48,649 --> 00:03:45,840 tall the amount of water when you melt 71 00:03:50,449 --> 00:03:48,659 it all down could be close to one glass 72 00:03:52,369 --> 00:03:50,459 full of water or it could be more like 73 00:03:53,990 --> 00:03:52,379 three gallons we gotta do these 74 00:03:55,490 --> 00:03:54,000 measurements in the field because even 75 00:03:57,770 --> 00:03:55,500 though there's a lot of technology that 76 00:03:59,930 --> 00:03:57,780 allow us to look at it from a satellite 77 00:04:03,229 --> 00:03:59,940 or a Global Perspective they have 78 00:04:05,089 --> 00:04:03,239 various ranges of accuracy and so doing 79 00:04:08,570 --> 00:04:05,099 it in the field is one of the most 80 00:04:12,530 --> 00:04:10,850 at this site we measure that snow water 81 00:04:15,530 --> 00:04:12,540 equivalent so the snow water equivalence 82 00:04:18,170 --> 00:04:15,540 is the amount of snow you have in one 83 00:04:22,310 --> 00:04:18,180 spot if you melted it into water so it's 84 00:04:25,010 --> 00:04:22,320 the snow water equivalent and that's the 85 00:04:26,450 --> 00:04:25,020 the fundamental Holy Grail parameter 86 00:04:28,550 --> 00:04:26,460 that we're after if we knew how much 87 00:04:30,290 --> 00:04:28,560 water was spatially distributed over the 88 00:04:34,550 --> 00:04:30,300 entire planet that would allow us to 89 00:04:37,430 --> 00:04:34,560 forecast spring runoff much better 90 00:04:39,430 --> 00:04:37,440 all right water resources are just so 91 00:04:42,230 --> 00:04:39,440 critical especially out west 92 00:04:44,030 --> 00:04:42,240 and I think it's really cool to try to 93 00:04:47,390 --> 00:04:44,040 do the science to figure out how much 94 00:04:48,890 --> 00:04:47,400 water we have looking at the snow depths 95 00:04:51,710 --> 00:04:48,900 or the height of the snow from the 96 00:04:53,629 --> 00:04:51,720 ground I'm putting my ruler in the same 97 00:04:55,550 --> 00:04:53,639 spot we took the other measurement so 98 00:04:57,950 --> 00:04:55,560 that we can have two data sets and I 99 00:04:59,570 --> 00:04:57,960 also then look up and note if we have 100 00:05:02,450 --> 00:04:59,580 canopy 101 00:05:05,150 --> 00:05:02,460 um kind of covering the surface we're 102 00:05:07,550 --> 00:05:05,160 intercepting the surface because that's 103 00:05:09,530 --> 00:05:07,560 an important note for our pilots who are 104 00:05:15,110 --> 00:05:09,540 looking over and trying to measure the 105 00:05:20,629 --> 00:05:17,629 the part of snow eggs we are conducting 106 00:05:23,749 --> 00:05:20,639 these Airborne experiments collecting 107 00:05:25,670 --> 00:05:23,759 activate path to microwave radar later 108 00:05:29,450 --> 00:05:25,680 and we are only one part of the tall 109 00:05:32,270 --> 00:05:29,460 effort you see the uh lines on the down 110 00:05:34,370 --> 00:05:32,280 below lots of lines I think that's 111 00:05:35,810 --> 00:05:34,380 essentially the handiwork of the ground 112 00:05:38,510 --> 00:05:35,820 crew 113 00:05:42,370 --> 00:05:38,520 and to validate measurements First 114 00:05:47,330 --> 00:05:44,870 my name is betsu I'm from Mr God at 115 00:05:49,790 --> 00:05:47,340 space flight center I am the pi for the 116 00:05:52,129 --> 00:05:49,800 swissar instrument it's called snow 117 00:05:54,290 --> 00:05:52,139 watery coolant synthetic aperture radar 118 00:05:56,029 --> 00:05:54,300 radiometer it's very similar to have a 119 00:05:58,790 --> 00:05:56,039 batch transmits sounds waves as it's 120 00:06:00,590 --> 00:05:58,800 flying around and then listens to The 121 00:06:03,170 --> 00:06:00,600 Echoes trying to make sense of the world 122 00:06:04,550 --> 00:06:03,180 the three-dimensional world around it we 123 00:06:06,710 --> 00:06:04,560 do the same thing with just the 124 00:06:08,270 --> 00:06:06,720 microwave so our waves travel at the 125 00:06:10,610 --> 00:06:08,280 speed of light they come back to the 126 00:06:12,770 --> 00:06:10,620 antenna we collect them and we process 127 00:06:14,390 --> 00:06:12,780 those Echoes to make sense of the 3D 128 00:06:16,550 --> 00:06:14,400 World 129 00:06:18,230 --> 00:06:16,560 it is in conjunction with the grounds 130 00:06:20,749 --> 00:06:18,240 measurements that the field teams are 131 00:06:22,790 --> 00:06:20,759 doing they're digging snow pits and 132 00:06:25,249 --> 00:06:22,800 collecting other snow observations for 133 00:06:29,210 --> 00:06:25,259 this to validate what this radar and 134 00:06:34,330 --> 00:06:31,370 we are walking to our snow pits and the 135 00:06:38,270 --> 00:06:34,340 tower radar instruments it's super cool 136 00:06:41,749 --> 00:06:38,280 the surface temperature was minus 34 35 137 00:06:45,170 --> 00:06:41,759 Celsius this morning I'm so cool to say 138 00:06:52,070 --> 00:06:47,890 foreign 139 00:06:57,770 --> 00:06:54,830 the radar sensor and so we'll compare 140 00:06:59,450 --> 00:06:57,780 this with the ongoing flights of this 141 00:07:01,309 --> 00:06:59,460 campaign the sensor is particularly 142 00:07:03,770 --> 00:07:01,319 suitable for deep snow or some of the 143 00:07:05,570 --> 00:07:03,780 other techniques are likely much more 144 00:07:07,490 --> 00:07:05,580 suitable for shallow snow so this is 145 00:07:10,610 --> 00:07:07,500 very complementary 146 00:07:12,710 --> 00:07:10,620 so this will take half an hour to finish 147 00:07:15,650 --> 00:07:12,720 so we do four of those transects so this 148 00:07:17,689 --> 00:07:15,660 takes two hours so they want to test 149 00:07:19,550 --> 00:07:17,699 instruments and all these different snow 150 00:07:20,830 --> 00:07:19,560 environments to make sure that they work 151 00:07:25,309 --> 00:07:20,840 globally 152 00:07:28,610 --> 00:07:25,319 Alaska offers a perfect snow to do this 153 00:07:31,070 --> 00:07:28,620 type of test we have arboreal forest and 154 00:07:34,070 --> 00:07:31,080 Arctic Thunder is very different it's 155 00:07:37,309 --> 00:07:34,080 generally shallow but it's much harder a 156 00:07:39,589 --> 00:07:37,319 lot of wind blown features and the 157 00:07:42,710 --> 00:07:39,599 variability is amazing so it was a very 158 00:07:45,550 --> 00:07:42,720 different types of snow and it's 159 00:07:47,930 --> 00:07:45,560 important to see that the 160 00:07:50,689 --> 00:07:47,940 instruments for remote sensing 161 00:07:54,110 --> 00:07:50,699 measurement of snow they do work well in 162 00:07:57,529 --> 00:07:54,120 in this differential environments it is 163 00:08:00,589 --> 00:07:57,539 a massive effort in terms of like 164 00:08:02,150 --> 00:08:00,599 Community participation we would never 165 00:08:04,610 --> 00:08:02,160 have all these measurements on the 166 00:08:06,409 --> 00:08:04,620 ground if our crews were smaller so the 167 00:08:08,270 --> 00:08:06,419 fact that we can get so many people in 168 00:08:11,930 --> 00:08:08,280 one place to take measurements is really 169 00:08:16,550 --> 00:08:14,749 the team has become really close it so 170 00:08:18,710 --> 00:08:16,560 it takes a lot of camaraderie and a lot 171 00:08:20,450 --> 00:08:18,720 of people pitching in you cannot stand 172 00:08:22,430 --> 00:08:20,460 on your heels and watch what's going on 173 00:08:27,570 --> 00:08:22,440 out here everybody has to pitch in and 174 00:08:33,170 --> 00:08:29,390 [Music] 175 00:08:35,510 --> 00:08:33,180 working out in these conditions is is 176 00:08:38,029 --> 00:08:35,520 just physically demanding it's super 177 00:08:41,329 --> 00:08:38,039 cold here in the Boreal forest 178 00:08:42,709 --> 00:08:41,339 snow was very light and fluffy and we 179 00:08:45,230 --> 00:08:42,719 were trumping around in the woods on 180 00:08:47,810 --> 00:08:45,240 snowshoes I mean really in the woods off 181 00:09:00,490 --> 00:08:47,820 Trail and it was just very physically 182 00:09:06,470 --> 00:09:04,130 I am amazed at how how much data was 183 00:09:07,750 --> 00:09:06,480 collected you are an incredible group of 184 00:09:10,420 --> 00:09:07,760 people 185 00:09:11,630 --> 00:09:10,430 this was this was super 186 00:09:15,650 --> 00:09:11,640 [Music] 187 00:09:18,050 --> 00:09:15,660 just a super opportunity and a really 188 00:09:19,850 --> 00:09:18,060 great experience to be part of so I 189 00:09:21,650 --> 00:09:19,860 appreciate all of the hard work and it 190 00:09:23,150 --> 00:09:21,660 was not easy I heard somebody say like 191 00:09:27,829 --> 00:09:23,160 wow you guys work really hard for this 192 00:09:33,300 --> 00:09:28,370 um 193 00:09:36,920 --> 00:09:35,700 [Music] 194 00:09:38,640 --> 00:09:36,930 [Applause] 195 00:09:41,590 --> 00:09:38,650 [Music]