1 00:00:00,000 --> 00:00:04,150 Music 2 00:00:04,170 --> 00:00:08,330 Music 3 00:00:08,350 --> 00:00:12,510 As you can see, it 4 00:00:12,530 --> 00:00:16,690 is snowing pretty good here this morning at the CARE site. Pretty nice, large aggregates, 5 00:00:16,710 --> 00:00:20,890 this is exactly what we're looking for, and 6 00:00:20,910 --> 00:00:25,050 it keeps coming down. 7 00:00:25,070 --> 00:00:29,200 Scientists get really excited over data, and that can really 8 00:00:29,220 --> 00:00:33,350 be enjoyable because you end up having a "nerd 9 00:00:33,370 --> 00:00:37,500 moment," where "Holy cow, this data looks really amazing!" And then 10 00:00:37,520 --> 00:00:41,670 you're kind of like, Wow, should I really get that excited about it? And then you're like, Yes, I 11 00:00:41,690 --> 00:00:45,790 should be because I've traveled all this way to do it. But, you know, those kind of moments are kind 12 00:00:45,810 --> 00:00:49,870 of the most special things that I have as a scientist, where you make these initial 13 00:00:49,890 --> 00:00:53,960 discoveries. Then you get to do the hard work of trying to make sure that they're 14 00:00:53,980 --> 00:00:58,030 making sense, and then publishing your results and sharing them with the community. 15 00:00:58,050 --> 00:01:02,070 16 00:01:02,090 --> 00:01:06,360 I grew up in upstate New York, in one of the snowbelt regions, and 17 00:01:06,380 --> 00:01:10,550 I've always loved precipitation and it's fascinated me, 18 00:01:10,570 --> 00:01:14,720 and that's really focused my career on studying something that's always interested me for a long 19 00:01:14,740 --> 00:01:18,890 period of time. Even going back to elementary school, I was a kid that used to keep a 20 00:01:18,910 --> 00:01:23,080 rain gauge in the back yard and measured precipitation and kept track of it. 21 00:01:23,100 --> 00:01:27,250 And I was always interested in weather, and now I get to live my dream. 22 00:01:27,270 --> 00:01:31,440 And so GPM, when it launches in a few years, is 23 00:01:31,460 --> 00:01:35,610 going to provide really high quality estimates of precipitation in 24 00:01:35,630 --> 00:01:39,800 places where nobody lives, but it's really important for climate 25 00:01:39,820 --> 00:01:43,970 as well as understanding weather forecasting and things like that. I look to 26 00:01:43,990 --> 00:01:48,140 investigate how precipitation changes 27 00:01:48,160 --> 00:01:52,310 in different weather regimes, and so what we want to try to understand 28 00:01:52,330 --> 00:01:56,450 as we go to these higher latitudes--how do the weather systems interact with 29 00:01:56,470 --> 00:02:00,540 precipitation and how well can we measure those things? And part 30 00:02:00,560 --> 00:02:04,630 of that obviously is to go up there and validate these things as well. So another part of my 31 00:02:04,650 --> 00:02:08,730 research is taking measurements from the ground in various places 32 00:02:08,750 --> 00:02:12,780 in the world and try to validate the satellite estimates that we're putting out, and 33 00:02:12,800 --> 00:02:16,820 making sure that they're high quality. I get really excited when we start to 34 00:02:16,840 --> 00:02:21,010 put data together and we make a diagram, and wow, it starts to 35 00:02:21,030 --> 00:02:25,200 make sense. And so that's really what motivates me to kind of 36 00:02:25,220 --> 00:02:29,380 explore, and it's nice that NASA provides this sort of observations 37 00:02:29,400 --> 00:02:33,550 where we can really explore our own planet in a very amazing way. 38 00:02:33,570 --> 00:02:37,710 Music 39 00:02:37,730 --> 00:02:41,900 Rain falling 40 00:02:41,920 --> 00:02:46,070 Rain falling 41 00:02:46,090 --> 00:02:48,549