Please use this identifier to cite or link to this item: https://repository.seku.ac.ke/handle/123456789/3872
Full metadata record
DC FieldValueLanguage
dc.contributor.authorOngoma, Victor
dc.contributor.authorChen, Haishan
dc.contributor.authorGao, Chujie
dc.date.accessioned2018-03-07T09:05:05Z
dc.date.available2018-03-07T09:05:05Z
dc.date.issued2018-01
dc.identifier.citationTheoretical and Applied Climatology pp 1–18en_US
dc.identifier.issn0177-798X
dc.identifier.issn1434-4483
dc.identifier.urihttps://link.springer.com/article/10.1007/s00704-018-2392-x#citeas
dc.identifier.urihttp://repository.seku.ac.ke/handle/123456789/3872
dc.descriptionDOI: https://doi.org/10.1007/s00704-018-2392-xen_US
dc.description.abstractThis study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951–2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October–December (OND) and March–May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.en_US
dc.language.isoenen_US
dc.publisherSpringer Viennaen_US
dc.titleEvaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africaen_US
dc.typeArticleen_US
Appears in Collections:School of Agriculture, Environment, Water and Natural Resources Management (JA)

Files in This Item:
File Description SizeFormat 
Ongoma_Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa.pdfAbstract46.55 kBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.