USP Electronic Research Repository

Quantile mapping bias correction on Rossby Centre Regional Climate Models for precipitation analysis over Kenya, East Africa

Ayugi, Brian and Tan, Guirong and Ruoyun, Niu and Babaousmail, Hassen and Ojara, Moses and Wido, Hanggoro and Mumo, Lucia and Ngoma, Nadoya and Nooni, Isaac and Ongoma, Victor (2020) Quantile mapping bias correction on Rossby Centre Regional Climate Models for precipitation analysis over Kenya, East Africa. Water, 12 (3). pp. 1-16. ISSN 2073-4441

PDF (Quantile Mapping Bias Correction on Rossby Centre Regional Climate Models for Precipitation Analysis over Kenya, East Africa) - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview


This study uses the quantile mapping bias correction (QMBC) method to correct the bias in five regional climate models (RCMs) from the latest output of the Rossby Center Climate Regional Model (RCA4) over Kenya. The outputs were validated using various scalar metrics such as root-mean-square difference (RMSD), mean absolute error (MAE), and mean bias. The study found that the QMBC algorithm demonstrates varying performance among the models in the study domain. The results show that most of the models exhibit reasonable improvement after corrections at seasonal and annual timescales. Specifically, the European Community Earth-System (EC-EARTH) and Commonwealth Scientific and Industrial Research Organization (CSIRO) models depict remarkable improvement as compared to other models. On the contrary, the Institute Pierre Simon Laplace Model CM5A-MR (IPSL-CM5A-MR) model shows little improvement across the rainfall seasons (i.e., March–May (MAM) and October–December (OND)). The projections forced with bias-corrected historical simulations tallied observed values demonstrate satisfactory simulations as compared to the uncorrected RCMs output models. This study has demonstrated that using QMBC on outputs from RCA4 is an important intermediate step to improve climate data before performing any regional impact analysis. The corrected models may be used in projections of drought and flood extreme events over the study area.

Item Type: Journal Article
Subjects: G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
G Geography. Anthropology. Recreation > GB Physical geography
Q Science > Q Science (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Geography, Earth Science and Environment
Depositing User: Victor Ongoma
Date Deposited: 01 May 2020 01:23
Last Modified: 01 May 2020 01:23

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...