GNSS Remote Sensing:Overview and selected recent developments

Ponencia expuesta online en el 8th International Radio Occultation Working Group Meeting (2021) celebrado del 7 al 9 de abrilGround and satellite based GNSS Remote Sensing (GNSS-RS) developed during the recent two decades into a very powerful and versatile tool for Earth System Research. A highlight of these developments is the operational use of spaceborne GNSS Radio Occultation (RO) data from several satellite missions to improve day-by-day global weather predictions. GNSS Remote Sensing is briefly introduced with selected applications. One prominent example is the improvement of regional and global weather forecasts. GNSS signals, reflected from water, ice and land surfaces (GNSS-Reflectometry, GNSS-R) can usefully complement the observation capabilities of GNSS-RO mission and enable versatile additional geophysical applications such as observation of wind speed and precipitation over oceans, which are illustrated. Finally, selected aspects for a comprehensive GNSS based Earth Observation with small satellite constellations are presented

IEEE 4003-2021

27 páginasThe scope of this effort is to develop a standard for data and metadata content arising from spaceborne global navigation satellite system-reflectometry (GNSS-R) missions, which uses GNSS signals as signals of opportunity, as described in “The IEEE SA Working Group on Spaceborne GNSS-R: Scene Study.” In particular, this standard would provide a means for describing: a) The terminology assigned to GNSS-R data and products, such as the product levels. b) The structure and content of the data. This includes, but is not limited to, units of measure, data organization, data description, data encoding, and data storage format. c) The metadata. This includes and is not limited to metadata, methods and algorithms applied to the data, parameters related to the algorithms, citation information, instrument calibration and characterization, and description of the input signals. The purpose of this standard is to provide a set of specifications and recommended practices that can be used to describe any known and future spaceborne GNSS-R data set, allowing users to work with different GNSS-R data sets at the same time. The definition of such standard would also allow any software that uses these data to fully operate and ingest any spaceborne GNSS-R input data as they will conform to the same standard

Evolving ocean monitoring With GNSS-R: promises in surface wind speed and prospects for rain detection

After developing a wind speed retrieval algorithm, derived winds from measurements of UK TechDemoSat-1 (TDS-1), from May 2015 to July 2017, are compared to wind products of Advanced Scatterometer showing a reliable performance, especially during rain events. However, a rain signature in GNSS-R observations, a decrease in the value of the bistatic radar cross section at low winds, is demonstrated, which can potentially enable the technique to detect precipitation over oceans induced by low-to-moderate winds. This phenomenon is investigated and finally characterized as the rain splash effect altering the ocean surface roughness. To improve the quality of derived winds, a machine learning technique is implemented for the wind speed inversion as a geophysical model function. The trained feedforward neural network shows a significant improvement of 17% in the wind speed RMSE compared to the LS approach. In the end, one can conclude that space-borne ocean monitoring is evolving existing products with a potential for novel geophysical applications