{ "count": 7, "next": null, "previous": null, "results": [ { "id": 30545, "url": "https://svs.gsfc.nasa.gov/30545/", "result_type": "Hyperwall Visual", "release_date": "2014-11-05T15:00:00-05:00", "title": "Tesso Nilo National Park", "description": "Landsat timeseries of Tesso Nilo National Park || tesso_nilo_1990-2014_9_image_grid_print.jpg (1024x576) [242.3 KB] || tesso_nilo_1990-2014_9_image_grid_web.png (320x180) [115.4 KB] || tesso_nilo_1990-2014_9_image_grid_searchweb.png (320x180) [115.4 KB] || tesso_nilo_1990-2014_9_image_grid_thm.png (80x40) [15.4 KB] || tesso_nilo_1990-2014_9_image_grid.tif (5760x3240) [53.4 MB] || tesso_nilo_1990-2014_9_image_grid.pptx [1.3 MB] || tesso_nilo_1990-2014_9_image_grid.key [35.9 MB] || ", "hits": 25 }, { "id": 4173, "url": "https://svs.gsfc.nasa.gov/4173/", "result_type": "Visualization", "release_date": "2014-09-04T00:00:00-04:00", "title": "GPM Examines East Coast Snow Storm", "description": "On March 17, 2014 the Global Precipitation Measurement (GPM) mission's Core Observatory flew over the East coast's last snow storm of the 2013-2014 winter season. This was also one of the first major snow storms observed by GPM shortly after it was launched on February 27, 2014.The GPM Core Observatory carries two instruments that show the location and intensity of rain and snow, which defines a crucial part of the storm structure – and how it will behave. The GPM Microwave Imager sees through the tops of clouds to observe how much and where precipitation occurs, and the Dual-frequency Precipitation Radar observes precise details of precipitation in 3-dimensions.For forecasters, GPM's microwave and radar data are part of the toolbox of satellite data, including other low Earth orbit and geostationary satellites, that they use to monitor tropical cyclones and hurricanes. The addition of GPM data to the current suite of satellite data is timely. Its predecessor precipitation satellite, the Tropical Rainfall Measuring Mission, is 18 years into what was originally a three-year mission. GPM's new high-resolution microwave imager data and the unique radar data ensure that forecasters and modelers won't have a gap in coverage. GPM is a joint mission between NASA and the Japan Aerospace Exploration Agency. All GPM data products will be released to the public on September 4, 2104. Current and future data sets are available to registered users from NASA Goddard's Precipitation Processing Center website. || ", "hits": 17 }, { "id": 4163, "url": "https://svs.gsfc.nasa.gov/4163/", "result_type": "Visualization", "release_date": "2014-05-29T00:00:00-04:00", "title": "GPM Senses East Coast Snow Storm on March 17th, 2014", "description": "The Global Precipitation Measurement (GPM) Mission is a joint satellite mission between NASA and JAXA. GPM has the capability of differentiating between liquid and frozen precipitation. In this visualization we see a large east coast snow storm through the eyes of GPM. || ", "hits": 16 }, { "id": 4153, "url": "https://svs.gsfc.nasa.gov/4153/", "result_type": "Visualization", "release_date": "2014-03-25T01:00:00-04:00", "title": "GPM/GMI First Light", "description": "Eleven days after the Feb. 27 launch of the Global Precipitation Measurement (GPM) Core Observatory, the two instruments aboard took their first joint images of an interesting precipitation event. On March 10, the Core Observatory passed over an extra-tropical cyclone about 1055 miles (1700 kilometers) due east of Japan's Honshu Island. The storm formed from the collision of a cold front wrapping around a warm front, emerging over the ocean near Okinawa on March 8. It moved northeast over the ocean south of Japan, drawing cold air west-to-east over the land, a typical winter weather pattern that also brought heavy snow over Hokkaido, the northernmost of the four main islands. After the GPM images were taken, the storm continued to move eastward, slowly intensifying before weakening in the central North Pacific.This visualization shows data from the GPM Microwave Imager, which observes different types of precipitation with 13 channels. Scientists analyze that data and then use it to calculate the light to heavy rain rates and falling snow within the storm.For more information on this topic: GPM web siteOther multimedia items related to this story: GPM GMI First Light (#11508) GPM DPR First Light (#11509) || ", "hits": 29 }, { "id": 30163, "url": "https://svs.gsfc.nasa.gov/30163/", "result_type": "Hyperwall Visual", "release_date": "2013-10-17T12:00:00-04:00", "title": "The Seasons of Lake Tahoe", "description": "Perhaps the most familiar change in our changing world is the annual swing of the seasons. This series of images shows the changes around Lake Tahoe, on the border between California and Nevada, from August 27, 2009, to September 7, 2010. Snow, plants, light, and the lake itself all shift in accordance with the seasons. One of the most obvious signals in the Lake Tahoe region is snow, a commodity that draws skiing vacationers. The groomed trails are among the first places to turn white when the first snow arrives in October, and they are among the last places to lose snow in June. Apart from snow cover, the other clear indicator of seasonal change is the lighting. The seasonal shift in light is evident in the shadows that play across the images. During the height of summer, direct light illuminates the mountaintops and valley floors. Moving into the fall, shadows paint the western side of the mountains. By December, shadows dominate, with only eastern mountain faces reflecting bright light. || ", "hits": 22 }, { "id": 20001, "url": "https://svs.gsfc.nasa.gov/20001/", "result_type": "Animation", "release_date": "2003-11-03T12:00:00-05:00", "title": "Sensor Web: Smart Satellites", "description": "Smart Satellites Get a Closer Look - Along with semi-autonomous advancements in the RapidFire system, NASA is testing new integration techniques with the EO-1 spacecraft and its cutting edge ALI instrument. It works like this: when MODIS spots an area on the ground that may indicate fire, advanced software puts out an alert. That message essentially instructs ALI to point itself towards the zone of interest and get a close-up. If the resulting picture from this orbital dance shows risk for fire, the system can alert experts and officials to take action on the ground. The whole process is automated. That makes the observations and analysis fast, and in terms of fire management, speed counts. A system like this has the potential to greatly accelerate notification of potential trouble spots before they can get out of hand. || ", "hits": 8 }, { "id": 1316, "url": "https://svs.gsfc.nasa.gov/1316/", "result_type": "Visualization", "release_date": "2000-12-20T12:00:00-05:00", "title": "EO1/ALI compared to Landsat 7", "description": "This animation shows a zoom down to an area of Alaska, using images of the same area taken by the EO1-ALI instrument and Landsat 7. Landsat is on the left, EO1-ALI is on the right. || a001316_v1.00005_print.png (720x480) [369.2 KB] || compare_pre.jpg (320x238) [10.6 KB] || compare_thm.png (80x40) [5.3 KB] || compare_pre_searchweb.jpg (320x180) [49.8 KB] || a001316_v1.webmhd.webm (960x540) [1.5 MB] || a001316_v1.dv (720x480) [41.2 MB] || a001316_v1.mp4 (640x480) [2.4 MB] || a001316_v2.mp4 (640x480) [2.3 MB] || a001316_v2.dv (720x480) [44.5 MB] || compare.mpg (352x240) [1.4 MB] || ", "hits": 11 } ] }