@article{fdi:010095474,
  title = {{R}eliability assessment of 15 gridded rainfall datasets for the construction of a daily high-resolution reanalysis across {S}enegal for agroclimatic applications},
  author = {{M}bengue, {A}. and {S}ultan, {B}enjamin and {F}aniriantsoa, {R}. and {N}diaye, {O}. and {D}iongue-{N}iang, {A}. and {S}atg{\'e}, {F}r{\'e}d{\'e}ric and {D}iop, {M}. {L}. and {N}diaye, {D}. and {K}onte, {O}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his study focuses on developing a new high-resolution gridded rainfall dataset for {S}enegal, essential for supporting rainfed agriculture, which is sensitive to climate variability. {G}iven the limited number of rain gauges, the research evaluates 15 publicly available gridded rainfall datasets ({P} datasets) against data from 21 stations of the {S}enegalese {N}ational {M}eteorological {S}ervice ({ANACIM}) over a 17-yr period (2005-21). {T}he evaluation employs several agroclimatic indices, including the onset and cessation of rain, duration of the rainy season, and extreme events. {T}he findings reveal that the reliability of {P} datasets varies significantly based on the metrics used. {F}or total rainfall, {A}frican {R}ainfall {C}limatology, rithm, version 2 ({RFE}v2) emerged as the most reliable datasets, with {ERA}5 achieving the highest {K}ling-{G}upta efficiency ({KGE}) value of 0.81 at daily scale. {I}n terms of agroclimatic parameters, {ARC}2, {CHIRPS}, and {RFE}v2 excelled in accurately representing the start ({KGE} >= 0.45) and end ({KGE} >= 0.39) dates of the rainy season. {H}owever, {P} datasets generally overestimate rainfall events and struggle with identifying dry spells. {T}he newly constructed merged dataset ({M} dataset) demonstrated over 100% improvement in correlation for daily estimates and significant bias reductions: 99.19% for {ARC}2, 80% for {CHIRPS}, and 90.57% for {RFE}v2. {T}his research provides critical insights for selecting appropriate datasets to enhance climate information for agricultural decision-making in {S}enegal.},
  keywords = {{C}limatology ; {S}atellite observations ; {S}urface observations ; {D}ata assimilation ; {R}eanalysis data ; {SENEGAL}},
  booktitle = {},
  journal = {{J}ournal of {A}pplied {M}eteorology and {C}limatology},
  volume = {64},
  numero = {11},
  pages = {1561--1583},
  ISSN = {1558-8424},
  year = {2025},
  DOI = {10.1175/jamc-d-24-0238.1},
  URL = {https://www.documentation.ird.fr/hor/fdi:010095474},
}