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RSS FeedsRemote Sensing, Vol. 15, Pages 1663: Study of Ionospheric Bending Angle and Scintillation Profiles Derived by GNSS Radio-Occultation with MetOp-A Satellite (Remote Sensing)

 
 

20 march 2023 05:34:59

 
Remote Sensing, Vol. 15, Pages 1663: Study of Ionospheric Bending Angle and Scintillation Profiles Derived by GNSS Radio-Occultation with MetOp-A Satellite (Remote Sensing)
 


In this work, a dedicated campaign by MetOp-A satellite is conducted to monitor the ionosphere based on radio-occultation (RO) measurements provided by the onboard GNSS (Global Navigation Satellite System) Receiver for Atmospheric Sounding (GRAS). The main goal is to analyze the capabilities of the collected data to represent the bending angle and scintillation profiles of the ionosphere. We compare the MetOp-A products with those generated by other RO missions and explore the spatial/temporal distributions sensed by the MetOp-A campaign. Validation of dual frequency bending angles at the RO tangent points, S4 index, and Rate of the Total electron content Index (ROTI) is performed against independent products from Fengyun-3D and FORMOSAT-7/COSMIC-2 satellites. Our main findings constitute the following: (1) bending angle profiles from MetOp-A agree well with Fengyun-3D measurements; (2) bending angle distributions show a typical S-shape variation along the altitudes; (3) signatures of the sporadic E-layer and equatorial ionization anomaly crests are observed by the bending angles; (4) sharp transitions are observed in the bending angle profiles above ~200 km due to the transition of the daytime/nighttime in addition to the transition of the bottom-side/top-side; and (5) sporadic E-layer signatures are observed in the S4 index distributions by MetOp-A and FORMOSAT-7/COSMIC-2, with expected differences in magnitudes between the GPS (Global Positioning System) L1 and L2 frequencies.


 
111 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 15, Pages 1662: An Aftershock Deletion Method Based on Fault Buffer Zone (Remote Sensing)
Remote Sensing, Vol. 15, Pages 1664: CRSNet: Cloud and Cloud Shadow Refinement Segmentation Networks for Remote Sensing Imagery (Remote Sensing)
 
 
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