1 00:00:00,030 --> 00:00:04,040 Field: So when we look at a global picture of fire, you can see fire everywhere 2 00:00:04,060 --> 00:00:08,060 on all continents. And at some level they're similar 3 00:00:08,080 --> 00:00:12,110 in that it's vegetation that's burning, but the drivers of those can be 4 00:00:12,130 --> 00:00:16,150 very different. In North America, for example, 5 00:00:16,170 --> 00:00:20,180 fires can be started by lightning, by natural factors, by 6 00:00:20,200 --> 00:00:24,230 people, often accidentally, and the explosive fires 7 00:00:24,250 --> 00:00:28,240 there that we see on TV are driven by the variability 8 00:00:28,260 --> 00:00:32,290 in the weather, so high winds at the surface for example. In other 9 00:00:32,310 --> 00:00:36,320 areas, in South America for example, wind-driven fires are less 10 00:00:36,340 --> 00:00:40,450 of an issue. It's primarily related to the land use. So 11 00:00:40,470 --> 00:00:44,470 using fire for land clearing and land preparation. 12 00:00:44,490 --> 00:00:48,530 In those cases, it's getting an accurate picture of the overall dryness 13 00:00:48,550 --> 00:00:52,560 of that area. VO: NASA has a long history of monitoring fire 14 00:00:52,580 --> 00:00:56,620 and smoke using different satellites in the Earth Observing System. Data from the 15 00:00:56,640 --> 00:01:00,720 Global Precipitation Measurement mission, or GPM, and other satellites and 16 00:01:00,740 --> 00:01:04,760 models gives us information on rainfall, temperature and land cover, which 17 00:01:04,780 --> 00:01:08,790 in turn, create a more complete picture of a vegetation fire starting and spreading. 18 00:01:08,810 --> 00:01:12,850 That's the thinking behind the Global Fire Weather Database, the first 19 00:01:12,870 --> 00:01:16,900 globally consistent fire weather dataset for fire researchers and managers. 20 00:01:16,920 --> 00:01:20,970 Field: So the Global Fire Weather Database is designed to get at the 21 00:01:20,990 --> 00:01:25,030 underlying conditions that drive those fires. Really focused 22 00:01:25,050 --> 00:01:29,110 on the meteorological aspect and to be used alongside some 23 00:01:29,130 --> 00:01:33,140 of the other risk factors. As we learn how to make use of the 24 00:01:33,160 --> 00:01:37,180 satellite data in driving these calculations, from GPM in particular, 25 00:01:37,200 --> 00:01:41,200 that can translate into actual operational products used, for example, 26 00:01:41,220 --> 00:01:45,230 by the meteorological services in different countries 27 00:01:45,250 --> 00:01:49,280 for their localized fire weather products. 28 00:01:49,300 --> 00:01:53,310 A good example is in Indonesia, which has a very serious fire problem. 29 00:01:53,330 --> 00:01:57,350 It's all related to land clearing, and one issue there 30 00:01:57,370 --> 00:02:01,460 is that it's happening in very remote regions. And in those places 31 00:02:01,480 --> 00:02:05,490 there's very little data. It's not a data-rich environment, and so you're limited 32 00:02:05,510 --> 00:02:09,510 by the accuracy of the picture you can get. 33 00:02:09,530 --> 00:02:13,560 So in that case, when we use calculations based on GPM data, 34 00:02:13,580 --> 00:02:17,610 it fills in all of those gaps. And we've seen that over 35 00:02:17,630 --> 00:02:21,650 the past couple of years for some of its severe fire episodes 36 00:02:21,670 --> 00:02:25,680 that we get a much better picture of where the dry regions are compared 37 00:02:25,700 --> 00:02:29,730 to where it's very rainy. And those can be very close together 38 00:02:29,750 --> 00:02:33,820 because of how localized rainfall can be in the tropics. 39 00:02:33,840 --> 00:02:37,870 VO: Far away from the tropics, the Global Fire Weather Database is used 40 00:02:37,890 --> 00:02:41,940 to assess risk in Canada. In 2017, abnormally 41 00:02:41,960 --> 00:02:46,010 hot and dry weather, combined with stressed forests, led to severe 42 00:02:46,030 --> 00:02:50,090 fires throughout British Columbia. Through July and August, stretches of high 43 00:02:50,110 --> 00:02:54,130 fire risk in the interior led to periods of extreme fire behavior 44 00:02:54,150 --> 00:02:58,180 and the highest annual recorded burned area for the province. 45 00:02:58,200 --> 00:03:02,210 The impact from these fires isn't just on the ground. Plumes of smoke 46 00:03:02,230 --> 00:03:06,260 can travel and pollute the air beyond the source. Field: In some cases we 47 00:03:06,280 --> 00:03:10,290 can see smoke plumes from Northern Canada transported over the 48 00:03:10,310 --> 00:03:14,320 Atlantic and arriving in Europe. In the most extreme cases, when 49 00:03:14,340 --> 00:03:18,350 those fires are really hot, the smoke from those fires can be 50 00:03:18,370 --> 00:03:22,390 ejected directly into the lower stratosphere. 51 00:03:22,410 --> 00:03:26,440 It's like a small volcano. And then can persist in 52 00:03:26,460 --> 00:03:30,500 the lower stratosphere for months. VO: Fire weather data based on satellites like 53 00:03:30,520 --> 00:03:34,570 GPM continue to help researchers understand the conditions under which those extreme 54 00:03:34,590 --> 00:03:38,610 fire events occur and how things may change over time. 55 00:03:38,630 --> 00:03:40,972