Effect of Scattering Angle on Earth Reflectance

Self Cite

In vegetation canopies cross-shading between finite dimensional leaves leads to a peak in reflectance in the retro-illumination direction. This effect is called the hot spot in optical remote sensing. The hotspot region in reflectance of vegetated surfaces represents the most information-rich directions in the angular distribution of canopy reflected radiation. This paper presents a new approach for generating hot spot signatures of equatorial forests from synergistic analyses of multiangle observations from the Multiangle Imaging SpectroRadiometer (MISR) on Terra platform and near backscattering reflectance data from the Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR). A canopy radiation model parameterized in terms of canopy spectral invariants underlies the theoretical basis for joining Terra MISR and DSCOVR EPIC data. The proposed model can accurately reproduce both MISR angular signatures acquired at 10:30 local solar time and diurnal courses of EPIC reflectance (NRMSE < 9%, R2 > 0.8). Analyses of time series of the hot spot signature suggest its ability to unambiguously detect seasonal changes of equatorial forests.

Section: Monitoring Equatorial Forestssupporting

confidence: 88%

“…DSCOVR returned to full operations on March 2, 2020 after the navigation problem had been resolved. After March 2020 the range of phase has substantially increased towards backscattering reaching 2 ° (Lyapustin et al, 2021;Marshak et al, 2021).…”

Section: Data Usedmentioning

confidence: 99%

Vegetation Angular Signatures of Equatorial Forests From DSCOVR EPIC and Terra MISR Observations

Ni¹,

Knyazikhin²,

Sun³

et al. 2021

Self Cite

“…During many seasons, measurements are taken relatively infrequently at those scattering angles from LEO and GEO satellites [e.g., Minnis et al (1998), Figure A1], so DSCOVR's nearly constant scattering angle everywhere on Earth is markedly different from those associated with other satellites. Yet, each scattering angle configuration has its advantages and problems, Marshak et al, 2021).…”

Section: Earth-observing Characteristics Of Dscovrmentioning

confidence: 99%

Lagrange Point Missions: The Key to next Generation Integrated Earth Observations. DSCOVR Innovation

Valero

Marshak

Minnis

2021

Self Cite

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.

“…The changes in DSCOVR viewing geometry directly affect the amount of reflected SW radiation that NISTAR and EPIC receive (Marshak et al, 2021), and require explicit use of the DSCOVR Satellite Ephemeris in the GCM SHS modeling to account for the changing GCM grid-box projected area, as seen from the DSCOVR Satellite perspective. With this explicit SHS modeling in place, the GCM SHS sampled output data are collected with the same Sun-Satellite viewing geometry of Earth as is the case for NISTAR and EPIC observational data.…”

Section: Introductionmentioning

confidence: 99%

“…Given that NISTAR observations of the Earth are from the vicinity of the Lagrangian L1 point, and are near zero phase angle, the expected reflected solar SW flux from the sunlit hemisphere would be near 200 Wm -2 , and the outgoing longwave (OLR) near 240 Wm -2 . However, the NISTAR data are near-backscattered radiances that are sensitive to phase angle variability (Marshak et al, 2021). The NISTAR near-backscattered radiance-to-flux conversion is still an ongoing endeavor.…”

Section: Introductionmentioning

confidence: 99%

Unique NISTAR-Based Climate GCM Diagnostics of the Earth’s Planetary Albedo and Spectral Absorption Through Longitudinal Data Slicing

Lacis

Carlson

Russell

et al. 2022

Self Cite

Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation permit a unique model/data comparison perspective that is not readily available from other satellite data. The key factor is the unique Lissajous orbital viewing geometry from the Lagrangian L1 point, which enables a continuous view of Earth’s sunlit hemisphere. The National Institute of Standards and Technology Advanced Radiometer (NISTAR) is the DSCOVR Mission energy budget instrument, which views the reflected and emitted radiation of the Earth’s sunlit hemisphere by means of single pixel active cavity full-spectrum (Band-A, 0.2–100 μm) and filtered solar wavelength (Band-B, 0.2–4.0 μm; and Band-C, 0.7–4.0 μm) radiometer measurements. An additional solar wavelength photodiode channel (0.3–1.1 μm) provides a calibration reference. The objective of this study is the assessment of climate GCM performance via direct model/data comparisons. Such comparisons are difficult due to quasi-chaotic natural variability present in real-world observational data and in climate GCM simulations. This is where the unique DSCOVR viewing geometry makes possible the longitudinal data slicing methodology for more direct model/data comparison. The key point of the longitudinal slicing approach is that data integration over the entire sunlit hemisphere eliminates the quasi-chaotic meteorological weather-scale noise, while preserving intra-seasonal and planetary-scale variability. The rotation of the Earth that retrieves this climate-style, large-scale longitudinal and seasonal variability. The hemispheric averaging is accomplished automatically in NISTAR measurements with its single-pixel view of the Earth. For climate GCMs, this requires implementing the Sunlit Hemisphere Sampling (SHS) scheme to operate on the GCM run-time output data, utilizing the DSCOVR Satellite Ephemeris data to assure precise viewing geometry between NISTAR measurements and GCM output data, while averaging out the meteorological weather noise. However, GCM generated data are radiative fluxes, while NISTAR (and EPIC) measurements are near-backscattered radiances. Conversing NISTSR measurements into radiative fluxes cannot be accomplished using NISTAR data alone, even with detailed support from conventional satellite data. But the identical viewing geometry of Earth’s sunlit hemisphere, and synergistic analyses of EPIC data make it feasible for this conversion of NISTAR near-backscatter radiances into radiative fluxes.