MIRAS Calibration and Performance: Results From the SMOS In-Orbit Commissioning Phase

Corbella, I.; Torres, F.; Duffo, N.; González-Gambau, Verónica; Pablos, Míriam; Duran, Israel; Martín-Neira, Manuel

doi:10.1109/tgrs.2010.2102769

Cited by 81 publications

(44 citation statements)

References 24 publications

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“…Indeed, tests performed with CATDS CEC-IFREMER products show peak-topeak amplitudes of SSS TIW signals much lower than the ones shown in this paper. SMOS SSS is not used before June 2010 due to the variable configurations for testing the functionalities of the instrument and low-level procedures for data acquisition and handling during In-Orbit Commissioning Phase [Corbella et al, 2011].…”

Section: Data Description and Methodsmentioning

confidence: 99%

SMOSSea Surface Salinity signals of tropical instability waves

Yin

Boutin

Reverdin

et al. 2014

J. Geophys. Res. Oceans

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Section: Data Description and Methodsmentioning

confidence: 99%

SMOSSea Surface Salinity signals of tropical instability waves

Yin

Boutin

Reverdin

et al. 2014

J. Geophys. Res. Oceans

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“…The T B data are georeferenced at an Equal-Area Scalable Earth (EASE) Northern Hemisphere grid (Brodzik and Knowles, 2002) of 25 km on the side. The radiometric accuracy of individual T B observations from SMOS is ∼ 2 K at boresight, and it increases on the extended alias-free field of view (Corbella et al, 2011). Proceeding from L1B data, though computationally more demanding than the more traditional L1C data products, has several benefits.…”

Section: Introductionmentioning

confidence: 99%

New methodology to estimate Arctic sea ice concentration from SMOS combining brightness temperature differences in a maximum-likelihood estimator

et al. 2017

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Abstract. Monitoring sea ice concentration is required for operational and climate studies in the Arctic Sea. Technologies used so far for estimating sea ice concentration have some limitations, for instance the impact of the atmosphere, the physical temperature of ice, and the presence of snow and melting. In the last years, L-band radiometry has been successfully used to study some properties of sea ice, remarkably sea ice thickness. However, the potential of satellite Lband observations for obtaining sea ice concentration had not yet been explored.In this paper, we present preliminary evidence showing that data from the Soil Moisture Ocean Salinity (SMOS) mission can be used to estimate sea ice concentration. Our method, based on a maximum-likelihood estimator (MLE), exploits the marked difference in the radiative properties of sea ice and seawater. In addition, the brightness temperatures of 100 % sea ice and 100 % seawater, as well as their combined values (polarization and angular difference), have been shown to be very stable during winter and spring, so they are robust to variations in physical temperature and other geophysical parameters. Therefore, we can use just two sets of tie points, one for summer and another for winter, for calculating sea ice concentration, leading to a more robust estimate.After analysing the full year 2014 in the entire Arctic, we have found that the sea ice concentration obtained with our method is well determined as compared to the Ocean and Sea Ice Satellite Application Facility (OSI SAF) dataset. However, when thin sea ice is present (ice thickness 0.6 m), the method underestimates the actual sea ice concentration.Our results open the way for a systematic exploitation of SMOS data for monitoring sea ice concentration, at least for specific seasons. Additionally, SMOS data can be synergistically combined with data from other sensors to monitor panArctic sea ice conditions.

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“…The nominal internal PMS calibration uses the NIR measurement as a secondary calibration standard, which is in turn calibrated using the sky, including the values of front-end losses (L 1 ) adjusted to correct for drifts [8]. To compensate the distribution network unbalance, a correction using the so-called "CAS factors" was introduced in the processing [9]. A new set of these factors must be computed only once whenever there is a change in MIRAS operation (for example switching components from nominal to redundant).…”

Section: Power Gain Calibrationmentioning

confidence: 99%

The MIRAS “all-licef” calibration mode

Corbella

González-Gambau²,

Torres

et al. 2016

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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Since each of the individual elements of the MIRAS array is a total power radiometer, the zero-spacing visibility can be obtained by the average of all the corresponding antenna temperatures. The main advantage of this option with respect to using the NIR measurements is that amplitude calibration is more consistent between zero-spacing visibility and the rest. On the other hand, total power radiometers are not usually as stable as noise injection radiometers, so a small loose of stability could be expected. Preliminary results show, however, similar performance.Peer ReviewedPostprint (author's final draft

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MIRAS Calibration and Performance: Results From the SMOS In-Orbit Commissioning Phase

Cited by 81 publications

References 24 publications

SMOSSea Surface Salinity signals of tropical instability waves

SMOSSea Surface Salinity signals of tropical instability waves

New methodology to estimate Arctic sea ice concentration from SMOS combining brightness temperature differences in a maximum-likelihood estimator

The MIRAS “all-licef” calibration mode

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