@article{fdi:010090120,
  title = {{R}eliability of gridded temperature datasets to monitor surface air temperature variability over {B}olivia},
  author = {{S}atg{\'e}, {F}r{\'e}d{\'e}ric and {P}illco, {R}. and {M}olina-{C}arpio, {J}. and {M}ollinedo, {P}. {P}. and {B}onnet, {M}. {P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}ix gridded temperature datasets ({T}-datasets) were evaluated for the first time over the {S}outh {A}merican continent, through the case study of {B}olivia, by comparing them with temperature records acquired from 82 meteorological stations spanning the 1995-2010 period. {T}he comparisons were carried out at the daily time step considering different seasons (annual scale, austral summer and austral winter) and regions ({A}mazon, {L}a {P}lata and {A}ltiplano basins). {O}verall, the climate hazards group infrared temperature with stations ({CHIRTS}) and the climate prediction centre ({CPC}) {T}-datasets provided the most reliable mean daily temperature ({T}-mean) and also described well the temporal variability of minimum and maximum daily temperature estimates ({T}-n and {T}-x). {T}-mean, {T}-n and {T}-x trends were analysed over the 1983-2016 period to observe temperature temporal evolution across the three regions. {D}espite some general agreements between the trends ({T}-mean, {T}-x and {T}-n), large discrepancies are also observed. {I}t was found that {CPC} overestimates and {CHIRTS} underestimates mean temperature trends and that {CPC} ({CHIRTS}) was better than {CHIRTS} ({CPC}) to estimate {T}-x ({T}-n) trends, both in magnitude and space. {F}urthermore, opposing trends (i.e., warming and cooling) are described by {CPC} and {CHIRTS} for some specific regions, which call into question their reliability for such analyses. {T}hese findings highlight the need to validate gridded temperature products with reliable ground data for the regions under study, particularly if they have a wide elevation range.},
  keywords = {{B}olivia ; gridded temperature datasets ; reliability ; temperature trends ; {BOLIVIE}},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {C}limatology},
  volume = {[{E}arly access]},
  numero = {},
  pages = {[16 p.]},
  ISSN = {0899-8418},
  year = {2023},
  DOI = {10.1002/joc.8200},
  URL = {https://www.documentation.ird.fr/hor/fdi:010090120},
}