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The primary objective of the National Aeronautics and Space Administration (NASA) Surface Biology and Geology (SBG) mission is to measure biological, physical, chemical, and mineralogical features of the Earth's surface, realizing a key conceptual component of the envisioned NASA Earth System Observatory (ESO). SBG is planned to launch as a two‐platform mission in the late 2020s, the first of the ESO satellites. Targeted science and applications objectives based on observations of the Earth's SBG helped to define the mission architecture and instrument capabilities for the SBG mission concept. These objectives further drove the need for enabling change detection and trending of surface biological and geological features. These needs implied fundamental calibration goals to achieve the necessary science data quality characteristics. To meet those goals, calibration and validation pre‐launch and on‐orbit methods formed a basis of the calibration and validation concept, including the combined use of on‐board references, vicarious techniques, and routine lunar imaging. International collaboration with space agencies in other countries, an important feature of the recommended SBG mission architecture, uncovered and emphasized the need for inter‐calibration techniques that underscored the importance of collaborative instrument characterization data sharing and the use of common calibration references that are International System of Units (SI) traceable in pre‐launch and post‐launch on orbit calibration mission phases. International collaboration through the use of terrestrial and aquatic networks on six continents for vicarious calibration and validation activities will further assure necessary science data quality while in orbit. Plain Language Summary: The NASA Surface Biology and Geology (SBG) mission will measure biological, physical, chemical, and mineralogical features of the Earth's surface. Targeted science and applications objectives helped to define the mission architecture and instrument capabilities for the SBG mission concept. These objectives also defined the need to detect changes and trends in biological and geological process on the face of the Earth. To meet these needs and objectives required fundamental calibration and validation concepts to achieve the necessary science data quality characteristics. These concepts included methods and resources used before and after launch. International collaboration with space agencies in other countries, an important feature of the recommended SBG mission architecture, also revealed the need for strong collaboration between agencies. This includes maintaining commonality in terminology, methods, algorithms and references and through the shared use of surface measurement networks on six continents. Key Points: Overviews cal/val ideas recommended for the Surface Biology and Geology (SBG) mission, with some consideration for collaborating with multiple contemporary missionsLooks at approaches to inter‐calibration of multiple Earth orbiting sensorsSurveys what cal/val resources and techniques are currently available or may be available to the SBG mission later in this decade [ABSTRACT FROM AUTHOR]

Monitoring the flow of radiative energy at top of atmosphere (TOA) is essential for understanding Earth’s climate and how it is changing with time. The determination of TOA global net radiation budget using broadband nonscanner instruments has received renewed interest recently due to advances in both instrument technology and the availability of small satellite platforms. The use of such instruments for monitoring Earth’s radiation budget was attempted in the past from satellite missions such as the Nimbus-7 and the Earth Radiation Budget Experiment (ERBE). This paper discusses the important lessons learned from the operation of the ERBE nonscanner instrument and the production of the ERBE nonscanner TOA radiation budget data set that have direct relevance to current nonscanner instrument efforts. [ABSTRACT FROM AUTHOR]

The NOAA-9 Earth Radiation Budget Experiment (ERBE) scanner measured broadband shortwave, longwave, and total radiances from February 1985 through January 1987. These scanner radiances are reprocessed using the more recent Clouds and the Earth's Radiant Energy System (CERES) unfiltering algorithm. The scene information, including cloud properties, required for reprocessing is derived using Advanced Very High Resolution Radiometer (AVHRR) data on board NOAA-9, while no imager data were used in the original ERBE unfiltering. The reprocessing increases the NOAA-9 ERBE scanner unfiltered longwave radiances by 1.4%-2.0% during daytime and 0.2%-0.3% during nighttime relative to those derived from the ERBE unfiltering algorithm. Similarly, the scanner unfiltered shortwave radiances increase by ~1% for clear ocean and land and decrease for all-sky ocean, land, and snow/ice by ~1%. The resulting NOAA-9 ERBE scanner unfiltered radiances are then compared with NOAA-9 nonscanner irradiances by integrating the ERBE scanner radiance over the nonscanner field of view. The comparison indicates that the integrated scanner radiances are larger by 0.9% for shortwave and 0.7% smaller for longwave. A sensitivity study shows that the one-standard-deviation uncertainties in the agreement are ±2.5%, ±1.2%, and ±1.8% for the shortwave, nighttime longwave, and daytime longwave irradiances, respectively. The NOAA-9 and ERBS nonscanner irradiances are also compared using 2 years of data. The comparison indicates that the NOAA-9 nonscanner shortwave, nighttime longwave, and daytime longwave irradiances are 0.3% larger, 0.6% smaller, and 0.4% larger, respectively. The longer observational record provided by the ERBS nonscanner plays a critical role in tying the CERES-like NOAA-9 ERBE scanner dataset from the mid-1980s to the present-day CERES scanner data record. [ABSTRACT FROM AUTHOR]

Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results. [ABSTRACT FROM PUBLISHER]