Simultaneous Overpass Off Nadir (SOON): A Method for Unified Calibration/Validation across IEOS and GEOSS System of Systems

摘要

The US operates a diverse, evolving constellation of research and operational environmental satellites, principally in polar and geosynchronous orbits. Our current and enhanced future domestic remote sensing capability is complemented by the significant capabilities of our current and potential future international partners. Satellite data users, such as the JSCSDA, are following roadmaps for the relentlessly increased ingest and assimilation of these data feeds, driven by the desire to fulfill the evolving operational requirements of their respective end-user communities. In this analysis, we define "success" through the data customers' "eyes": participating in the sufficient and continuously improving satisfaction of their mission responsibilities. To successfully fuse together observations from multiple simultaneous platforms and sensors into a common, self-consistent, operational environment requires that there exist a unified calibration and validation approach. Here, we consider develop a concept for an integrating framework for absolute accuracy; long-term stability; self-consistency among sensors, platforms, techniques, and observing systems; and validation and characterization of performance. Across all systems, this is a non-trivial problem. NOAA alone sustains > 80 observing platforms, > 800 variables, and > 30K observing data collection points. Simultaneous Nadir Overpasses, or SNO's, provide a proven intercomparison technique: simultaneous, collocated, co-angular measurements. Many systems have off-nadir elements, or effects, that must be calibrated. For these systems, the nadir technique constrains the process. We define the term "SOON," for simultaneous overpass off nadir. We present a target architecture and sensitivity analysis for the affordable, sustainable implementation of a global SOON calibration/validation network that can deliver the much-needed comprehensive, common, self-consistent operational picture in near-real time, at an affordable cost.