SMOS Validation and the COSMOS Campaigns

Delwart, Steven; Bouzinac, Catherine; Wursteisen, P.; Berger, Michael; Drinkwater, Mark R.; Martín-Neira, Manuel; Kerr, Yann H.

doi:10.1109/tgrs.2007.914811

Cited by 65 publications

(46 citation statements)

References 40 publications

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“…Other studies rely either on ground-based or airborne radiometer This study aims at assessing how coupled land surface and radiative transfer models can contribute to the validation and analysis of passive microwave remote-sensing data. It is conducted in the highly instrumented Vils test site in the Upper Danube Catchment in southern Germany that has been used as a major SMOS cal/val test site since 2007 (Delwart et al, 2008). Different extensive field campaigns have taken place here that, amongst others, delivered time series of point-like soil moisture station measurements.…”

Section: F Schlenz Et Al: Analysis Of Smos Brightness Temperature Amentioning

confidence: 99%

“…They cover more than 60 % of the area. Based on previous studies (Strasser et al, 1999;Bach and Mauser, 2003;Loew, 2008), this test site has carefully been chosen and used for SMOS calibration and validation (cal/val) studies since 2007 (Delwart et al, 2008). The test site has been instrumented with seven soil moisture profile stations that have been measured between 2007 and 2011.…”

Section: Study Area and In Situ Datamentioning

confidence: 99%

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Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany

Schlenz¹,

Dall'Amico²,

Mauser³

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract. Soil Moisture and Ocean Salinity (SMOS) L1c brightness temperature and L2 optical depth data are analysed with a coupled land surface (PROMET) and radiative transfer model (L-MEB). The coupled models are validated with ground and airborne measurements under contrasting soil moisture, vegetation and land surface temperature conditions during the SMOS Validation Campaign in May and June 2010 in the SMOS test site Upper Danube Catchment in southern Germany. The brightness temperature root-meansquared errors are between 6 K and 9 K. The L-MEB parameterisation is considered appropriate under local conditions even though it might possibly be further optimised. SMOS L1c brightness temperature data are processed and analysed in the Upper Danube Catchment using the coupled models in 2011 and during the SMOS Validation Campaign 2010 together with airborne L-band brightness temperature data. Only low to fair correlations are found for this comparison (R between 0.1-0.41). SMOS L1c brightness temperature data do not show the expected seasonal behaviour and are positively biased. It is concluded that RFI is responsible for a considerable part of the observed problems in the SMOS data products in the Upper Danube Catchment. This is consistent with the observed dry bias in the SMOS L2 soil moisture products which can also be related to RFI. It is confirmed that the brightness temperature data from the lower SMOS look angles and the horizontal polarisation are less reliable. This information could be used to improve the brightness temperature data filtering before the soil moisture retrieval. SMOS L2 optical depth values have been compared to modelled data and are not considered a reliable source of information about vegetation due to missing seasonal behaviour and a very high mean value. A fairly strong correlation between SMOS L2 soil moisture and optical depth was found (R = 0.65) even though the two variables are considered independent in the study area. The value of coupled models as a tool for the analysis of passive microwave remote-sensing data is demonstrated by extending this SMOS data analysis from a few days during a field campaign to a longer term comparison.

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Section: F Schlenz Et Al: Analysis Of Smos Brightness Temperature Amentioning

confidence: 99%

Section: Study Area and In Situ Datamentioning

confidence: 99%

Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany

Schlenz¹,

Dall'Amico²,

Mauser³

et al. 2012

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

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“…Actually, it was also found that the length of the tail of the waveform (cut of the DDM for Doppler shift equal to 0 Hz) at 1/e was also highly correlated to the sea state. These results have also been used in COSMOS-OS data [78] to improve the salinity retrievals [79]. The experiment conditions are those of Figure 5, and results are shown in Figure 20: blue dots represent the retrieved salinity without any correction, green dots represent the retrieved salinity with the GNSS-R-derived correction, and the red dots are, as a reference for the error introduced by the retrieval algorithm, the SSS retrieved from the flat sea model and the ground-truth measurements.…”

Section: Application To Sea State Correctionmentioning

confidence: 99%

Review of the CALIMAS Team Contributions to European Space Agency’s Soil Moisture and Ocean Salinity Mission Calibration and Validation

et al. 2012

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This work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoring.

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“…Several surface-based and airborne L-band radiometers have been in operation for calibration and validation algorithm development activities during the pre-and post-launch periods for SMOS, Aquarius, and SMAP (Misra et al, 2013;Pardé et al, 2011;Delwart et al, 2008;Rautiainen et al, 2008). With this in mind, a hyperspectral L-band radiometer system was developed by Radiometrics Corporation © , Boulder, CO, and delivered to Environment and Climate Change Canada's (ECCC) Climate Research Division in 2010, that has the capability to detect broadband RFI and mitigate narrowband RFI over an expanded bandwidth with high frequency resolution, in a package that can be easily mounted on both tower and airborne platforms.…”

Section: Introductionmentioning

confidence: 99%

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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SMOS Validation and the COSMOS Campaigns

Cited by 65 publications

References 40 publications

Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany

Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany

Review of the CALIMAS Team Contributions to European Space Agency’s Soil Moisture and Ocean Salinity Mission Calibration and Validation

Radio-frequency interference mitigating hyperspectral L-band radiometer

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