Preprint Article Version 1 This version is not peer-reviewed

Quantile Mapping Bias Correction on Rossby Centre Regional Climate Models for Precipitation Analysis over Kenya, East Africa

Version 1 : Received: 11 January 2020 / Approved: 12 January 2020 / Online: 12 January 2020 (14:18:56 CET)

How to cite: Ayugi, B.; Tan, G.; Niu, R.; Babaousmail, H.; Ojara, M.; Wido, H.; Mumo, L.; Nooni, I.K.; Ongoma, V. Quantile Mapping Bias Correction on Rossby Centre Regional Climate Models for Precipitation Analysis over Kenya, East Africa. Preprints 2020, 2020010119 (doi: 10.20944/preprints202001.0119.v1). Ayugi, B.; Tan, G.; Niu, R.; Babaousmail, H.; Ojara, M.; Wido, H.; Mumo, L.; Nooni, I.K.; Ongoma, V. Quantile Mapping Bias Correction on Rossby Centre Regional Climate Models for Precipitation Analysis over Kenya, East Africa. Preprints 2020, 2020010119 (doi: 10.20944/preprints202001.0119.v1).

Abstract

Accurate assessment and projections of extreme climate events requires the use of climate datasets with no or minimal error. This study uses quantile mapping bias correction (QMBC) method to correct the bias of five Regional Climate Models (RCMs) from the latest output of Rossby Climate Model Center (RCA4) over Kenya, East Africa. 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 demonstrate varying performance among the models in the study domain. The results show that most of the models exhibit significant 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 exemplary improvement as compared to other models. On the contrary, the Institute Pierre Simon Laplace Model CM5A-MR (IPSL-CM5A-MR) model show little improvement across various timescales (i.e. March-April-May (MAM) and October-November-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 prior to performing any regional impact analysis. The corrected models can be used for projections of drought and flood extreme events over the study area. This study analysis is crucial from the sustainable planning for adaptation and mitigation of climate change and disaster risk reduction perspective.

Subject Areas

Quantile Mapping Bias Correction (QMBC); Regional Climate Models (RCMs); Rossby Centre Regional Climate Models (RCA4); Drought; Flood; Kenya

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.