@article{fdi:010066939,
  title = {{A}ssimilation of {SMOS} soil moisture and brightness temperature products into a land surface model},
  author = {{L}ievens, {H}. and {D}e {L}annoy, {G}. {J}. {M}. and {A}l {B}itar, {A}. and {D}rusch, {M}. and {D}umedah, {G}. and {F}ranssen, {H}. {J}. {H}. and {K}err, {Y}. and {T}omer, {S}. {K}. and {M}artens, {B}. and {M}erlin, {O}livier and {P}an, {M}. and {R}oundy, {J}. {K}. and {V}ereecken, {H}. and {W}alker, {J}. {P}. and {W}ood, {E}. {F}. and {V}erhoest, {N}. {E}. {C}. and {P}auwels, {V}. {R}. {N}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {S}oil {M}oisture and {O}cean {S}alinity ({SMOS}) mission has the potential to improve the predictive skill of land surface models through the assimilation of its observations. {S}everal alternate products can be distinguished: the observed brightness temperature ({TB}) data at coarse scale, indirect estimates of soil moisture ({SM}) through the inversion of the coarse-scale {TB} observations, and fine-scale soil moisture through the a priori downscaling of coarse-scale soil moisture. {T}he {SMOS} {TB} products include observations over a large range of incidence angles at both {H}- and {V}-polarizations, which allows the merit of assimilating the full set of multi-angular/polarization observations, as opposed to specific sub-sets of observations, to be assessed. {T}his study investigates the performance of various observation scenarios with respect to soil moisture and streamflow predictions in the {M}urray {D}arling {B}asin. {T}he observations are assimilated into the {V}ariable {I}nfiltration {C}apacity ({VIC}) model, coupled to the {C}ommunity {M}icrowave {E}mission {M}odeling ({CMEM}) platform, using the {E}nsemble {K}alman filter. {T}he assimilation of these various observation products is assessed under similar realistic assimilation settings, without optimization, and validated by comparison of the modeled soil moisture and streamflow to in situ measurements across the basin. {T}he best results are achieved from assimilation of the coarse-scale {SM} observations. {T}he reduced improvement using downscaled {SM} is probably due to a lower number of observations, as a result of cloud cover effects on the downscaling method. {T}he assimilation of {TB} was found to be a promising alternative, which led to improvements in soil moisture prediction approaching those of the coarse-scale {SM} assimilation.},
  keywords = {{SMOS} ; {D}ata assimilation ; {S}oil moisture ; {M}ulti-scale ; {B}rightness ; temperature ; {AUSTRALIE}},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {180},
  numero = {{N}o {S}p{\'e}cial},
  pages = {292--304},
  ISSN = {0034-4257},
  year = {2016},
  DOI = {10.1016/j.rse.2015.10.033},
  URL = {https://www.documentation.ird.fr/hor/fdi:010066939},
}