727 research outputs found

    Can GNSS reflectometry detect precipitation over oceans?

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    For the first time, a rain signature in Global Navigation Satellite System Reflectometry (GNSS‐R) observations is demonstrated. Based on the argument that the forward quasi‐specular scattering relies upon surface gravity waves with lengths larger than several wavelengths of the reflected signal, a commonly made conclusion is that the scatterometric GNSS‐R measurements are not sensitive to the surface small‐scale roughness generated by raindrops impinging on the ocean surface. On the contrary, this study presents an evidence that the bistatic radar cross section σ0 derived from TechDemoSat‐1 data is reduced due to rain at weak winds, lower than ≈ 6 m/s. The decrease is as large as ≈ 0.7 dB at the wind speed of 3 m/s due to a precipitation of 0–2 mm/hr. The simulations based on the recently published scattering theory provide a plausible explanation for this phenomenon which potentially enables the GNSS‐R technique to detect precipitation over oceans at low winds

    First results of a GNSS-R experiment from a stratospheric balloon over boreal forests

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    The empirical results of a global navigation satellite systems reflectometry (GNSS-R) experiment onboard the Balloon EXperiments for University Students (BEXUS) 17 stratospheric balloon performed north of Sweden over boreal forests show that the power of the reflected signals is nearly independent of the platform height for a high coherent integration time T-c = 20 ms. This experimental evidence shows a strong coherent component in the forward scattered signal, as compared with the incoherent component, that allows to be tracked. The bistatic coherent reflectivity is also evaluated as a function of the elevation angle, showing a decrease of similar to 6 dB when the elevation angle increases from 35. to 70 degrees. The received power presents a clearly multimodal behavior, which also suggests that the coherent scattering component may be taking place in different forest elements, i.e., soil, canopy, and through multiple reflections canopy-soil and soil-trunk. This experiment has provided the first GNSS-R data set over boreal forests. The evaluation of these results can be useful for the feasibility study of this technique to perform biomass monitoring that is a key factor to analyze the carbon cycle.Peer ReviewedPostprint (author's final draft

    The Eddy Experiment: accurate GNSS-R ocean altimetry from low altitude aircraft

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    During the Eddy Experiment, two synchronous GPS receivers were flown at 1 km altitude to collect L1 signals and their reflections from the sea surface for assessment of altimetric precision and accuracy. Wind speed (U10) was around 10 m/s, and SWH up to 2 m. A geophysical parametric waveform model was used for retracking and estimation of the lapse between the direct and reflected signals with a 1-second precision of 3 m. The lapse was used to estimate the SSH along the track using a differential model. The RMS error of the 20 km averaged GNSS-R absolute altimetric solution with respect to Jason-1 SSH and a GPS buoy measurement was of 10 cm, with a 2 cm mean difference. Multipath and retracking parameter sensitivity due to the low altitude are suspected to have degraded accuracy. This result provides an important milestone on the road to a GNSS-R mesoscale altimetry space mission.Comment: All Starlab authors have contributed significantly; the Starlab Author list has been ordered randoml

    Impact of rain, swell, and surface currents on the electromagnetic bias in GNSS-Reflectometry

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    The assessment of the electromagnetic (EM) bias is required to predict the performance of upcoming global navigation satellite systems-reflectometry (GNSS-R) altimetry systems, and its impact in data assimilation climate studies. In previous studies, the EM bias in bistatic GNSS-R altimetry (L-band) was numerically estimated for a wind-driven sea surface height spectrum, including the time-domain variability. In the present study, spectral models for the rain, swell, and surface currents are used to compute a perturbed wind-driven sea surface height spectrum, from which a perturbed three-dimensional (3-D) time-evolving wind-driven sea surface height is computed. The generated sea surface is then illuminated by a right hand circular polarization (RHCP) L-band EM wave, and the wave scattered from each facet is computed from each facet using the physical optics (PO) method under the Kirchhoff approximation (KA). Finally, the EM bias is computed numerically as the height of each patch times the forward-scattering coefficient, divided by the average of the forward-scattering coefficient. The impact of rain on the EM bias is a moderate decrease (in magnitude) due to the damping of the large gravity waves, which is more significant as the wind speed increases. The impact of swell is a small increase (in magnitude) mostly due to the change of the local incidence angles. The impact of currents can be either a moderate increase or decrease (in magnitude), depending on the sense of the current with respect to the wind, due to a change in the surface roughness.Peer ReviewedPostprint (author's final draft

    Sensing Ocean, Ice and Land Reflected Signalsfrom Space: Results from the UK-DMC GPS Reflectometry Experiment

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    The use of Global Navigation Satellite System (GNSS) signals reflected from the Earth\u27s surface has progressed from its beginnings in the early 1990\u27s to a demonstrated practical linkage of measurements to geophysical characteristics of ocean, ice and land surfaces. A pioneering space-based experiment was carried on the UK-DMC satellite launched in September of 2003. The GPS receiver on the satellite was modified to accommodate a downward (nadir) pointing medium gain antenna and to send sampled IF data to a solid-state data recorder [1]. Since its launch it has been successfully used to target and detect specular reflections of GPS signals after scattering from the Earth\u27s oceans, ice sheetsand land surfaces. All data collections under a wide range of conditions have revealed reflected signals, including signals reflected off the ocean under reasonably rough ocean conditions. This demonstrates convincingly that GNSS Reflectometry (or GNSS Bistatic Radar) is a valid future technology for space based Earth remote sensing, even when using modest antenna gain configurations such as that deployed on the UK-DMC low Earth orbiting satellite. This paper presents a summary of the signals collected from over the ocean, and an examination of the signal relationship to the ocean wind and wave conditions is presented. The preliminary results from ice and land surfaces reflection analysis are also described. Reprinted with permission from The Institute of Navigation (http://ion.org/) and The Proceedings of the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation, (pp. 1679-1685). Fairfax, VA: The Institute of Navigation

    The GNSS-R Eddy Experiment II: L-band and Optical Speculometry for Directional Sea-Roughness Retrieval from Low Altitude Aircraft

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    We report on the retrieval of directional sea-roughness (the full directional mean square slope, including MSS, direction and isotropy) through inversion of Global Navigation Satellite System Reflections (GNSS-R) and SOlar REflectance Speculometry (SORES)data collected during an experimental flight at 1000 m. The emphasis is on the utilization of the entire Delay-Doppler Map (for GNSS-R) or Tilt Azimuth Map (for SORES) in order to infer these directional parameters. Obtained estimations are analyzed and compared to Jason-1 measurements and the ECMWF numerical weather model.Comment: Proceedings from the 2003 Workshop on Oceanography with GNSS Reflections, Barcelona, Spain, 200

    GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

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    The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version
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