An assessment of CyGNSS v3.0 level 1 observables over the ocean
Hammond, Matthew Lee ORCID: https://orcid.org/0000-0002-8918-2351; Foti, Giuseppe ORCID: https://orcid.org/0000-0002-1507-2133; Gommenginger, Christine ORCID: https://orcid.org/0000-0002-6941-1671; Srokosz, Meric ORCID: https://orcid.org/0000-0002-7347-7411. 2021 An assessment of CyGNSS v3.0 level 1 observables over the ocean. Remote Sensing, 13 (17), 3500. https://doi.org/10.3390/rs13173500
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: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). remotesensing-13-03500.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (5MB) | Preview |
Abstract/Summary
Global Navigation Satellite System Reflectometry (GNSS-R) is a rapidly developing Earth observation technology that makes use of signals of opportunity from Global Navigation Satellite Systems that have been reflected off the Earth’s surface. The Cyclone Global Navigation Satellite System (CyGNSS) is a constellation of eight small satellites launched by NASA in 2016, carrying dedicated GNSS-R payloads to measure ocean surface wind speed at low latitudes (±35° North/South). The ESA ECOLOGY project evaluated CyGNSS v3.0 products, which were recently released following various calibration updates. This paper examines the performance of the new calibration by evaluating CyGNSS v3.0 Level-1 Normalised Bistatic Radar Cross Section (NBRCS) and Leading Edge Slope (LES) data from individual CyGNSS units and different GPS transmitters under constant ocean wind conditions. Results indicate that L1 NBRCS from individual CyGNSS units are well inter-calibrated and remarkably stable over time, a significant improvement over previous versions of the products. However, prominent geographical biases reaching over 3 dB are found in NBRCS, linked to factors including the choice of GPS transmitter and the bistatic geometry. L1 LES shows similar anomalies as well as a secondary geographical pattern of biases. These findings provide a basis for further improvement of CyGNSS Level-2 wind products and have wider applicability to improving the calibration of GNSS-R sensors for the remote sensing of non-ocean Earth surfaces.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | https://doi.org/10.3390/rs13173500 |
ISSN: | 2072-4292 |
Date made live: | 23 Feb 2023 14:30 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/534073 |
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