@article{PAR00012922,
  title = {{C}opula-based downscaling of coarse-scale soil moisture observations with implicit bias correction},
  author = {{V}erhoest, {N}. {E}. {C}. and van den {B}erg, {M}. {J}. and {M}artens, {B}. and {L}ievens, {H}. and {W}ood, {E}. {F}. and {P}an, {M}. and {K}err, {Y}ann and {A}l {B}itar, {A}. and {T}omer, {S}. {K}. and {D}rusch, {M}. and {V}ernieuwe, {H}. and {D}e {B}aets, {B}. and {W}alker, {J}. {P}. and {D}umedah, {G}. and {P}auwels, {V}. {R}. {N}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}oil moisture retrievals, delivered as a {CATDS} ({C}entre {A}val de {T}raitement des {D}onnees {SMOS}) {L}evel-3 product of the {S}oil {M}oisture and {O}cean {S}alinity ({SMOS}) mission, form an important information source, particularly for updating land surface models. {H}owever, the coarse resolution of the {SMOS} product requires additional treatment if it is to be used in applications at higher resolutions. {F}urthermore, the remotely sensed soil moisture often does not reflect the climatology of the soil moisture predictions, and the bias between model predictions and observations needs to be removed. {I}n this paper, a statistical framework is presented that allows for the downscaling of the coarse-scale {SMOS} soil moisture product to a finer resolution. {T}his framework describes the interscale relationship between {SMOS} observations and model-predicted soil moisture values, in this case, using the variable infiltration capacity ({VIC}) model, using a copula. {T}hrough conditioning, the copula to a {SMOS} observation, a probability distribution function is obtained that reflects the expected distribution function of {VIC} soil moisture for the given {SMOS} observation. {T}his distribution function is then used in a cumulative distribution function matching procedure to obtain an unbiased fine-scale soil moisture map that can be assimilated into {VIC}. {T}he methodology is applied to {SMOS} observations over the {U}pper {M}ississippi {R}iver basin. {A}lthough the focus in this paper is on data assimilation apcations, the framework developed could also be used for other purposes where downscaling of coarse-scale observations is required.},
  keywords = {{H}ydrology ; microwave radiometry ; soil moisture ; {ETATS} {UNIS} ; {MISSISSIPI} {BASSIN}},
  booktitle = {},
  journal = {{I}eee {T}ransactions on {G}eoscience and {R}emote {S}ensing},
  volume = {53},
  numero = {6},
  pages = {3507--3521},
  ISSN = {0196-2892},
  year = {2015},
  DOI = {10.1109/tgrs.2014.2378913},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00012922},
}