Bias adjustment of hourly rainfall distributions in WFDE5 reanalysis for hydrological impact studies in Benin (West Africa)

Gridded climate datasets such as satellite and reanalysis products have biases related to the methods used to develop them. This study aims to improve the hourly rainfall distribution of the WFDE5 reanalysis over all grid boxes in Benin, based on bias adjustment through Quantile Mapping (QM). The bias adjusted product (called NEW) was evaluated on an hourly scale, using the percentage and quantity of precipitation events per modality class ([0–1), [1–2), [2–3), [3–4), [4–5) and ≥ 5 mm/h) and the relative mean absolute error (RMAE). On a daily scale, evaluation was based on Pearson correlation and RMAE values using nine extreme precipitation indices. The mean absolute error (MAE) and Mann Kendall trend are sometimes shown. Our result showed that assimilated rainfall from WFDE5 performed well at seasonal scales (RMAE < 15%) but underperformed at the hourly scale (RMAE sometimes > 400%). NEW offers RMAE values generally < 100%, i.e. an almost four-fold reduction in bias. The QM method improves the rainfall distribution, particularly with regard to the percentage of rainfall between 0 and 1 mm/h (WFDE5 = 95.40%, Obs = 97.87% and NEW = 97.83% at the Nalohou station) and the cumulative rainfall quantity greater than 5 mm/h (WFDE5 = 131 mm/year vs. Obs = 880 mm/year and NEW = 790 mm/year at the Nalohou station). The bias adjustment also significantly improved the description of climate extremes in Benin, particularly in terms of bias. At Cotonou station, WFDE5 was associated with an average RMAE of 61% for the nine indices, compared to 33% for NEW. Finally, NEW presents mean values closer to observation data, and can be used for hydrological impact studies in Benin.