Comparing soil moisture retrievals from SMOS and ASCAT over France

Parrens, Marie; Zakharova, Elena; Lafont, S.; Calvet, J.‐C.; Kerr, Yann H.; Wagner, Wolfgang; Wigneron, Jean‐Pierre

doi:10.5194/hess-16-423-2012

Cited by 79 publications

(45 citation statements)

References 78 publications

(64 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The soil moisture dataset is available online at http://www.ipf.tuwien.ac.at/insitu/. The observations from this network were extensively used for the validation of modelled and satellite-derived soil moisture (Albergel et al, 2008(Albergel et al, , 2010Parrens et al, 2012).…”

Section: Smosmania Stationsmentioning

confidence: 99%

Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry

Zakharova¹,

Calvet²,

Lafont³

et al. 2012

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

Section: Smosmania Stationsmentioning

confidence: 99%

Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry

Zakharova¹,

Calvet²,

Lafont³

et al. 2012

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

“…Previous studies found differences between the spatial structures of modelled and retrieved SSM (Parrens et al, 2012;Polcher et al, 2016). This paper shows that these structures are not consistent also when comparing modelled and observed TBs.…”

Section: Discussionmentioning

confidence: 49%

Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

Barella-Ortiz

Polcher

Rosnay

et al. 2017

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. L-band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM estimates. The work exposed compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The two modelled sets were estimated using a radiative transfer model and state variables from two land-surface models: (i) OR-CHIDEE and (ii) H-TESSEL. The radiative transfer model used is the CMEM.Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations at the moment. Further hypotheses are proposed and will be explored in a forthcoming paper. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies.

show abstract

“…After the rotations, the vertical and horizontal polarised brightness temperatures are averaged into 10 • bins that are centred around the designated angle to enable an incidence angle based analysis. A similar approach was chosen by Parrens et al (2012).…”

Section: Smos Datamentioning

confidence: 99%

“…Examples are Albergel et al (2011), Montzka et al (2011), Parrens et al (2012 and Bircher et al (2012). Albergel et al (2011) and Parrens et al (2012) have shown that there is still potential to improve soil moisture retrievals from SMOS brightness temperatures in southern France. They used calibrated statistical relationships based on reference soil moisture values and additional information like leaf area index (LAI) simulated by a land surface model to produce better soil moisture estimates.…”

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

confidence: 99%

See 1 more Smart Citation

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

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.

show abstract

Comparing soil moisture retrievals from SMOS and ASCAT over France

Cited by 79 publications

References 78 publications

Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry

Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry

Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

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

Contact Info

Product

Resources

About