Comparison of model prediction with measurements of galactic background noise at L-band

Vine, David M. Le; Abraham, Saji; Kerr, Yann H.; Wilson, William J.; Skou, N.; Søbjærg, Sten Schmidl

doi:10.1109/tgrs.2005.853190

Cited by 12 publications

(13 citation statements)

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“…1) Sky Radiation: Estimation of the downwelling celestial sky radiation at L-band that is scattered by the sea surface and sensed by Earth-viewing radiometers (sky glitter) is of particular concern for the remote sensing of SSS [5], [43], [44]. At L-band, this radiation originates from the uniform cosmic microwave background (about 2.7 K), the line emission from hydrogen, and a continuum background [44], [45]. Sea surface scattered sky radiation might hamper the accurate SSS retrievals from spaceborne measurements of upwelling sea surface Tbs at L-band, as the sky-glitter contribution is expected to vary from roughly 2 K to more than 7 K, which is significant with respect to the SSS signature.…”

Section: Contributions From Other Sourcesmentioning

confidence: 99%

Overview of the SMOS Sea Surface Salinity Prototype Processor

Zine

Boutin

Font

et al. 2009

IEEE Trans. Geosci. Remote Sensing

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The L-band interferometric radiometer onboard the Soil Moisture and Ocean Salinity mission will measure polarized brightness temperatures (Tb). The measurements are affected by strong radiometric noise. However, during a satellite overpass, numerous measurements are acquired at various incidence angles at the same location on the Earth's surface. The sea surface salinity (SSS) retrieval algorithm implemented in the Level 2 Salinity Prototype Processor (L2SPP) is based on an iterative inversion method that minimizes the differences between Tb measured at different incidence angles and Tb simulated by a full forward model. The iterative method is initialized with a first-guess surface salinity that is iteratively modified until an optimal fit between the forward model and the measurements is obtained. The forward model takes into account atmospheric emission and absorption, ionospheric effects (Faraday rotation), scattering of celestial radiation by the rough ocean surface, and rough sea surface emission as approximated by one of three models. Potential degradation of the retrieval results is indicated through a flagging strategy. We present results of tests of the L2SPP involving horizontally uniform scenes with no disturbing factors (such as sun glint or land proximity) other than wind-induced surface roughness. Regardless of the roughness model used, the error on the retrieved SSS depends on the location within the swath and ranges from 0.5 psu at the center of the swath to 1.7 psu at the edge, at 35 psu and 15 • C. Dual-polarization (DP) mode provides a better correction for wind-speed (WS) biases than pseudofirst Stokes mode (ST1). For a WS bias of −1 m · s −1 , the corresponding Manuscript

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Section: Contributions From Other Sourcesmentioning

confidence: 99%

Overview of the SMOS Sea Surface Salinity Prototype Processor

Zine

Boutin

Font

et al. 2009

IEEE Trans. Geosci. Remote Sensing

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“…6 left) with ambient and warm targets and 1.5 K (Fig. 6 right) with sky measurements from both the Kernen and Kenaston sites (T Bsky ≈ 5 K from Lemmetyinen et al, 2016;Pellarin et al, 2016;Le Vine et al, 2005). The biases are lower than 0.3 K. For black body targets, only one point gives errors higher than 3 K. This single occurrence is likely associated with an error in recording the black body physical temperature during the stabilitycheck.…”

Section: Radiometer Calibration Results and Instrument Stability Evalmentioning

confidence: 94%

“…The biases are lower than 0.3 K. For black body targets, only one point gives errors higher than 3 K. This single occurrence is likely associated with an error in recording the black body physical temperature during the stabilitycheck. The higher error in the sky measurements could be related to the fact that the sky emission might vary slightly depending upon the observed portion of the sky due to the variability in sky background temperatures measured when the antenna beamwidth crosses the galactic plane (increases by 1-3 K) and due to potential contributions from the sun and moon (Delahaye et al, 2002;Le Vine et al, 2005). Further analysis of these effects will be evaluated in future campaigns.…”

Section: Radiometer Calibration Results and Instrument Stability Evalmentioning

confidence: 99%

“…A three-point calibration procedure using the sky, ambient, and heated warm targets was developed to account for the radiometer's calibration nonlinearity and improve the accuracy over the full range of measured T B . The reference sky T B at L-band was considered to be ≈ 5 K for both polarizations based on previously published data from both measured and modelled sources (Pellarin et al, 2016;Lemmetyinen et al, 2016;Le Vine et al, 2005;Delahaye et al, 2002).…”

Section: Calibration Measurement Procedure/post-processingmentioning

confidence: 99%

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Radio-frequency interference mitigating hyperspectral L-band radiometer

Toose

Roy

Solheim³

et al. 2017

Geosci. Instrum. Method. Data Syst.

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Abstract. Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers. These spaceborne radiometers operate within the protected passive remote sensing and radio-astronomy frequency allocation of 1400-1427 MHz but nonetheless are still subjected to frequent RFI intrusions. We present a unique surfacebased and airborne hyperspectral 385 channel, dual polarization, L-band Fourier transform, RFI-detecting radiometer designed with a frequency range from 1400 through ≈ 1550 MHz. The extended frequency range was intended to increase the likelihood of detecting adjacent RFI-free channels to increase the signal, and therefore the thermal resolution, of the radiometer instrument. The external instrument calibration uses three targets (sky, ambient, and warm), and validation from independent stability measurements shows a mean absolute error (MAE) of 1.0 K for ambient and warm targets and 1.5 K for sky. A simple but effective RFI removal method which exploits the large number of frequency channels is also described. This method separates the desired thermal emission from RFI intrusions and was evaluated with synthetic microwave spectra generated using a Monte Carlo approach and validated with surface-based and airborne experimental measurements.

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“…Ground test calibration procedures are used before and after every salinity mapping flight. During the ground test calibrations, we use the "cold sky" as one target and assume it to be 5.5 K following [10]. Care must be taken to ensure that the PLMR does not point at a section of the sky that is occupied by the sun, the moon, or the galaxy.…”

Section: A Specifications Of Plmr and Ground Test 1) Specifications mentioning

confidence: 99%

Evaluation of a New Airborne Microwave Remote Sensing Radiometer by Measuring the Salinity Gradients Across the Shelf of the Great Barrier Reef Lagoon

Wang

Heron

Prytz

et al. 2007

IEEE Trans. Geosci. Remote Sensing

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Abstract-Over the last ten years, some operational airborne remote sensing systems have become available for mapping surface salinity over large areas in near real time. A new dualpolarized Polarimetric L-band Multibeam Radiometer (PLMR) has been developed to improve accuracy and precision when compared with previous instrument generations. This paper reports on the first field evaluation of the performance of the PLMR by measuring salinity gradients in the central Great Barrier Reef. Before calibration, the raw salinity values of the PLMR and conductivity-temperature-depth (CTD) differed by 3-6 psu. The calibration, which uses in situ salinity data to remove long-term drifts in the PLMR as well as environmental effects such as surface roughness and radiation from the sky and atmosphere, was carried out by equating the means of the PLMR and CTD salinity data over a subsection of the transect, after which 85% of the salinity values between the PLMR and CTD are within 0.1 psu along the complete transect. From offshore to inshore across the shelf, the PLMR shows an average cross-shelf salinity increase of about 0.4 psu and a decrease of 2 psu over the inshore 20 km at −19• S (around Townsville) and −18 • S (around Lucinda), respectively. The average cross-shelf salinity increase was 0.3 psu for the offshore 100 km over all transects. These results are consistent with the in situ CTD results. This survey shows that PLMR provided an effective method of rapidly measuring the surface salinity in near real time when a calibration could be made.Index Terms-Great Barrier Reef (GBR), microwave radiometer, remote sensing, sea surface salinity. Y. Wang is with the College of Marine Geoscience, Ocean University of China, Qingdao 266100, China, and also with the Marine Geophysical Laboratory, James Cook University, Townsville, Qld. 4811, Australia (e-mail: yonghong.wang@jcu.edu.au; yonghongw@ouc.edu.cn).M. L. Heron and P. V. Ridd are with the AIMS@JCU and Marine Geo-

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Comparison of model prediction with measurements of galactic background noise at L-band

Cited by 12 publications

References 20 publications

Overview of the SMOS Sea Surface Salinity Prototype Processor

Overview of the SMOS Sea Surface Salinity Prototype Processor

Radio-frequency interference mitigating hyperspectral L-band radiometer

Evaluation of a New Airborne Microwave Remote Sensing Radiometer by Measuring the Salinity Gradients Across the Shelf of the Great Barrier Reef Lagoon

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