TY - JOUR
T1 - Bias-corrected NASA data for aridity index estimation over tropical climates in Ghana, West Africa
AU - Asilevi, Prince Junior
AU - Dogbey, Felicia
AU - Boakye, Patrick
AU - Aryee, Jeffrey Nii Armah
AU - Yamba, Edmund Ilimoan
AU - Owusu, Stephen Yaw
AU - Peprah, David Kofi
AU - Quansah, Emmanuel
AU - Klutse, Nana Ama Browne
AU - Bentum, John Kwesi
AU - Adjei, Kwaku Amaning
AU - Anornu, Geophrey Kwame
AU - Oduro-Kwarteng, Sampson
AU - Amekudzi, Leonard Kofitse
N1 - Publisher Copyright:
© 2023
PY - 2024/2
Y1 - 2024/2
N2 - Study region: Ghana, West Africa. Study focus: NASA's Prediction of Worldwide Energy Resource (NASA POWER) satellite-based reanalysis products are used for estimating the aridity index (AI) in Ghana, West Africa. The NASA estimates are compared and bias-corrected with temperature-based potential evapotranspiration estimates and rainfall data from 22 synoptic climate stations. The cumulative distribution function (CDF) matching technique was used for bias correction New Hydrological Insights for the region: The results indicated a previous 36% over-estimation of arid conditions in dryland climates and an under-estimation of wetland climate regions by the NASA POWER data compared with the station-based estimation. Post bias-correction, the satellite-based estimates showed substantial improvements, as evidenced by a correlation coefficient of R2 = 0.87. The rectified data suggests that with accurate interpretations and calibrations, satellite-based metrics can play a pivotal role in advancing hydrological studies and water resource management in West Africa Sub-region. This insight underscores the potential of satellite data in augmenting regional hydrological research, establishing a foundation for similar studies in analogous global environments.
AB - Study region: Ghana, West Africa. Study focus: NASA's Prediction of Worldwide Energy Resource (NASA POWER) satellite-based reanalysis products are used for estimating the aridity index (AI) in Ghana, West Africa. The NASA estimates are compared and bias-corrected with temperature-based potential evapotranspiration estimates and rainfall data from 22 synoptic climate stations. The cumulative distribution function (CDF) matching technique was used for bias correction New Hydrological Insights for the region: The results indicated a previous 36% over-estimation of arid conditions in dryland climates and an under-estimation of wetland climate regions by the NASA POWER data compared with the station-based estimation. Post bias-correction, the satellite-based estimates showed substantial improvements, as evidenced by a correlation coefficient of R2 = 0.87. The rectified data suggests that with accurate interpretations and calibrations, satellite-based metrics can play a pivotal role in advancing hydrological studies and water resource management in West Africa Sub-region. This insight underscores the potential of satellite data in augmenting regional hydrological research, establishing a foundation for similar studies in analogous global environments.
KW - Aridity index
KW - Evapotranspiration
KW - NASA POWER
KW - Rainfall
KW - Water resource
UR - https://www.scopus.com/pages/publications/85179928383
U2 - 10.1016/j.ejrh.2023.101610
DO - 10.1016/j.ejrh.2023.101610
M3 - Article
AN - SCOPUS:85179928383
SN - 2214-5818
VL - 51
JO - Journal of Hydrology: Regional Studies
JF - Journal of Hydrology: Regional Studies
M1 - 101610
ER -