WEBVTT FILE 1 00:00:00.020 --> 00:00:04.070 [Music, rain] 2 00:00:04.090 --> 00:00:08.100 [rain] Dalia: GPM will help us to understand 3 00:00:08.120 --> 00:00:12.260 precipitation extremes. And this is everything from too much rainfall, such as 4 00:00:12.280 --> 00:00:16.430 flooding in India or Southeast Asia, to too little rainfall 5 00:00:16.450 --> 00:00:20.520 such as drought in the U.S. Southwest. 6 00:00:20.540 --> 00:00:24.670 [music] 7 00:00:24.690 --> 00:00:28.810 Eric: There's about one major flood a day 8 00:00:28.830 --> 00:00:32.920 someplace in the world, so it's not as if it's a rare event. 9 00:00:32.940 --> 00:00:33.040 [rain falling, thunder] 10 00:00:33.060 --> 00:00:37.100 [rain falling, thunder] Big problem is that over much of the world 11 00:00:37.120 --> 00:00:41.190 the in situ data, the gauges, and the measured 12 00:00:41.210 --> 00:00:45.250 precipitation just isn't available. 13 00:00:45.270 --> 00:00:49.300 To predict floods you need to have the data in near real-time. 14 00:00:49.320 --> 00:00:53.320 And so the satellites are 15 00:00:53.340 --> 00:00:57.510 about the only way--GPM is about the only way-- 16 00:00:57.530 --> 00:01:01.570 that this is going to happen. And so we're going to use GPM 17 00:01:01.590 --> 00:01:05.720 rainfall retrievals to go do analyses, do flood forecasting, 18 00:01:05.740 --> 00:01:09.890 and bring climate services, 19 00:01:09.910 --> 00:01:14.050 bring information, to users in these areas. 20 00:01:14.070 --> 00:01:18.240 [music] Dalia: Landslides happen all over the world 21 00:01:18.260 --> 00:01:22.340 in nearly every country, and they cause more economic damage and more fatalities than 22 00:01:22.360 --> 00:01:26.490 people generally think. [rocks falling] The large 23 00:01:26.510 --> 00:01:30.590 majority of landslides around the world are triggered by intense or prolonged rainfall. 24 00:01:30.610 --> 00:01:34.640 [rain falling] A landslide is a general 25 00:01:34.660 --> 00:01:38.690 term, often used for mudslides, debris flows, rock falls, 26 00:01:38.710 --> 00:01:42.720 and usually it's just a mass of rock, earth, and dirt 27 00:01:42.740 --> 00:01:46.770 basically moving down a hillslope. Typical 28 00:01:46.790 --> 00:01:50.870 landslide studies are done at the local scale and they use gauge data. Now this is a problem 29 00:01:50.890 --> 00:01:55.050 in areas of topography where we don't have gauges or radar, in particular 30 00:01:55.070 --> 00:01:59.220 in developing areas where we don't have any information. So satellite data 31 00:01:59.240 --> 00:02:03.410 is really important for understanding where and when this intense rainfall might happen 32 00:02:03.430 --> 00:02:07.570 that could trigger landslides. 33 00:02:07.590 --> 00:02:11.660 [music] 34 00:02:11.680 --> 00:02:15.790 [music] 35 00:02:15.810 --> 00:02:19.940 [music] Tom: In the western U.S. 36 00:02:19.960 --> 00:02:23.960 we deal with drought on a regular basis. It tends to be cyclic. 37 00:02:23.980 --> 00:02:28.050 We'll get two or three dry years and we'll get a few wet years. If somebody 38 00:02:28.070 --> 00:02:32.140 could predict when the dry ones are coming, we'd be a lot better off. 39 00:02:32.160 --> 00:02:36.190 A lot of our water here comes in snow 40 00:02:36.210 --> 00:02:40.240 It accumulates up in the mountains in the wintertime, runs off 41 00:02:40.260 --> 00:02:44.410 in the spring, and that's we use for irrigation in the western U.S. 42 00:02:44.430 --> 00:02:48.600 Wade: Agricultural drought is defined as a lack of 43 00:02:48.620 --> 00:02:52.770 water within the top meter of soil 44 00:02:52.790 --> 00:02:56.940 for adequate crop functionalities, adequate 45 00:02:56.960 --> 00:03:01.120 crop productivity. 46 00:03:01.140 --> 00:03:05.280 And if you're talking about agricultural drought, 47 00:03:05.300 --> 00:03:09.470 probably the biggest error source is the quality of 48 00:03:09.490 --> 00:03:13.650 the precipitation information that you have available. If you have good precipitation 49 00:03:13.670 --> 00:03:17.810 information, you can do a very good job of characterizing drought and often its 50 00:03:17.830 --> 00:03:21.940 subsequent impact on agricultural productivity. 51 00:03:21.960 --> 00:03:26.080 Tom: We do work in research in 52 00:03:26.100 --> 00:03:30.200 determining the water needs of crops and what the impacts on crops are 53 00:03:30.220 --> 00:03:34.290 if you don't have enough water. We're doing this because we 54 00:03:34.310 --> 00:03:38.380 realize that in the western U.S. there will likely be less water available 55 00:03:38.400 --> 00:03:42.440 in the future than there has been in the past, and the farmers need to know how 56 00:03:42.460 --> 00:03:46.490 to respond to that decreasing water supply. 57 00:03:46.510 --> 00:03:50.530 Certainly when we're looking nationwide, the better prediction we have of how much 58 00:03:50.550 --> 00:03:54.600 rain we've been getting and how much is likely to come in the near future 59 00:03:54.620 --> 00:03:58.770 is very, very important. To the extent that we can predict that with satellites, 60 00:03:58.790 --> 00:04:02.800 it's really beneficial. 61 00:04:02.820 --> 00:04:06.930 This isn't just a U.S. problem; it's a global problem. 62 00:04:06.950 --> 00:04:11.010 Many countries of the world are facing the same kind of issues 63 00:04:11.030 --> 00:04:15.070 that we are. And so we expect this information to be able to be used 64 00:04:15.090 --> 00:04:19.190 in the east and the western U.S. and globally. Dalia: We 65 00:04:19.210 --> 00:04:23.260 need accurate and timely rainfall information to understand disasters like 66 00:04:23.280 --> 00:04:27.330 floods, droughts, and landslides. GPM's global 67 00:04:27.350 --> 00:04:31.380 rainfall data will help us to better understand and model these types of disasters 68 00:04:31.400 --> 00:04:35.400 around the world. [Music, whoosh] 69 00:04:35.420 --> 00:04:39.550 [Music] 70 00:04:39.570 --> 00:04:43.580 [Music] 71 00:04:43.600 --> 00:04:43.997