Abstract
A new perspective for studying Earth processes has been soundly demonstrated by the Deep Space Climate Observatory (DSCOVR) mission. For the past 6 years, the first Earth-observing satellite orbiting at the Lagrange 1 (L1) point, the DSCOVR satellite has been viewing the planet in a fundamentally different way compared to all other satellites. It is providing unique simultaneous observations of nearly the entire sunlit face of the Earth at a relatively high temporal resolution. This capability enables detailed coverage of evolving atmospheric and surface systems over meso- and large-scale domains, both individually and as a whole, from sunrise to sunset, under continuously changing illumination and viewing conditions. DSCOVR’s view also contains polar regions that are only partially seen from geostationary satellites (GEOs). To exploit this unique perspective, DSCOVR instruments provide multispectral imagery and measurements of the Earth’s reflected and emitted radiances from 0.2 to 100 µm. Data from these sensors have been and continue to be utilized for a great variety of research involving retrievals of atmospheric composition, aerosols, clouds, ocean, and vegetation properties; estimates of surface radiation and the top-of-atmosphere radiation budget; and determining exoplanet signatures. DSCOVR’s synoptic and high temporal resolution data encompass the areas observed during the day from low Earth orbiting satellites (LEOs) and GEOs along with occasional views of the Moon. Because the LEO and GEO measurements can be easily matched with simultaneous DSCOVR data, multiangle, multispectral datasets can be developed by integrating DSCOVR, LEO, and GEO data along with surface and airborne observations, when available. Such datasets can open the door for global application of algorithms heretofore limited to specific LEO satellites and development of new scientific tools for Earth sciences. The utility of the integrated datasets relies on accurate intercalibration of the observations, a process that can be facilitated by the DSCOVR views of the Moon, which serves as a stable reference. Because of their full-disc views, observatories at one or more Lagrange points can play a key role in next-generation integrated Earth observing systems.
Highlights
Satellite remote sensing of the Earth has long relied on instruments aboard platforms in either low-Earth orbits (LEO, ∼500–2000 km altitude) or geostationary orbits (GEO, at ∼36,000 km)
The instruments on Deep Space Climate Observatory (DSCOVR) are providing for the first time, synoptic, simultaneous mesoscale and large-scale spatial coverage of the Earth at high temporal-resolution from sunrise to sunset with periodic plain views of the sunlit polar regions, as well as the Moon, which serves as a spectro-radiometric calibration reference
The results of the DSCOVR-generated research to date are by themselves the validation of the scientific concepts that first motivated the original Triana mission
Summary
Satellite remote sensing of the Earth has long relied on instruments aboard platforms in either low-Earth orbits (LEO, ∼500–2000 km altitude) or geostationary orbits (GEO, at ∼36,000 km). Data from airborne and surface instruments, as well as active instruments such as lidars and microwave imagers on FIGURE 10 | Example diagram of a potential future integrated Earth observational system showing some LEO (cyan), GEO (magenta), and Lagrange point (white) satellites, and the Moon. The temporal resolution and broad coverage have great potential for a variety of synergistic and complementary studies that could yield improved and new products To facilitate those studies, Yi et al (2001) proposed the development of a comprehensive dataset consisting of observations from LEOs and GEOs attached to time and space-matched EPIC footprints. An ALO is accomplished by employing the solar wind to maintain the orbit, which aligns the satellite above either of the poles, providing continuous GEO-like coverage of those regions at azimuth angles greatly different from those at L1 (Lazzarra et al, 2011)
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