WEBVTT FILE 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