@article{fdi:010074766,
  title = {{A}ssessment of ground-reference data and validation of the {H}-{SAF} precipitation products in {B}razil},
  author = {do {A}maral, {L}. {M}. {C}. and {B}arbieri, {S}. and {V}ila, {D}. and {P}uca, {S}. and {V}ulpiani, {G}. and {P}anegrossi, {G}. and {B}iscaro, {T}. and {S}ano, {P}. and {P}etracca, {M}. and {M}arra, {A}. {C}. and {G}osset, {M}arielle and {D}ietrich, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he uncertainties associated with rainfall estimates comprise various measurement scales: from rain gauges and ground-based radars to the satellite rainfall retrievals. {T}he quality of satellite rainfall products has improved significantly in recent decades; however, such algorithms require validation studies using observational rainfall data. {F}or this reason, this study aims to apply the {H}-{SAF} consolidated radar data processing to the {X}-band radar used in the {CHUVA} campaigns and apply the well established {H}-{SAF} validation procedure to these data and verify the quality of {EUMETSAT} {H}-{SAF} operational passive microwave precipitation products in two regions of {B}razil ({V}ale do {P}araiba and {M}anaus). {T}hese products are based on two rainfall retrieval algorithms: the physically based {B}ayesian {C}loud {D}ynamics and {R}adiation {D}atabase ({CDRD} algorithm) for {SSMI}/{S} sensors and the {P}assive microwave {N}eural network {P}recipitation {R}etrieval algorithm ({PNPR}) for cross-track scanning radiometers ({AMSU}-{A}/{AMSU}-{B}/{MHS} sensors) and for the {ATMS} sensor. {T}hese algorithms, optimized for {E}urope, {A}frica and the {S}outhern {A}tlantic region, provide estimates for the {MSG} full disk area. {F}irstly, the radar data was treated with an overall quality index which includes corrections for different error sources like ground clutter, range distance, rain-induced attenuation, among others. {D}ifferent polarimetric and non-polarimetric {QPE} algorithms have been tested and the {V}ulpiani algorithm (hereafter, {R}-q2{V}u15) presents the best precipitation retrievals when compared with independent rain gauges. {R}egarding the results from satellite-based algorithms, generally, all rainfall retrievals tend to detect a larger precipitation area than the ground-based radar and overestimate intense rain rates for the {M}anaus region. {S}uch behavior is related to the fact that the environmental and meteorological conditions of the {A}mazon region are not well represented in the algorithms. {D}ifferently, for the {V}ale do {P}araiba region, the precipitation patterns were well detected and the estimates are in accordance with the reference as indicated by the low mean bias values.},
  keywords = {rain gauges ; radar ; quality indexes ; satellite rainfall retrievals ; validation ; {BRESIL}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {10},
  numero = {11},
  pages = {art. 1743 [24 p.]},
  ISSN = {2072-4292},
  year = {2018},
  DOI = {10.3390/rs10111743},
  URL = {https://www.documentation.ird.fr/hor/fdi:010074766},
}