GSTDTAP  > 地球科学
DOI10.1016/j.atmosres.2019.104808
Gauging the performance of CMIP5 historical simulation in reproducing observed gauge rainfall over Kenya
Mumo, Lucia1,2; Yu, Jinhua1,2
2020-05-15
发表期刊ATMOSPHERIC RESEARCH
ISSN0169-8095
EISSN1873-2895
出版年2020
卷号236
文章类型Article
语种英语
国家Peoples R China
英文摘要

The detrimental impacts of climate change have drawn the interest of many climate scientists toward understanding the past climate for the sake of preparing for the future. The current study evaluates the performance of 12 rainfall models available in Coupled Model Intercomparison Project Phase 5 (CMIP5) in reproducing observed rainfall over Kenya from 1979 to 2005. Several statistical metrics were deployed in quantifying the disparities between CMIP5 models, in situ, and the Global Precipitation Climatology Centre (GPCC v7) rainfall datasets. The results show satisfactory skill of CMIP5 models' in simulating the bimodal rainfall regime despite exhibiting dry (wet) bias during March-May (MAM) and October-November (OND) season, respectively. The models' skills in reproducing the interannual variability is relatively weak. However, majority of the models captures the temporal pattern with reasonable skills in OND than in MAM and annual rainfall. The impacts of Indian Ocean Dipole (IOD) and El Nino southern oscillation (ENSO) are marked in observed OND rains with no significance link in MAM rains. Overall, CMIP5 models' skills in replicating the mean statistics and teleconnection links are relatively weak. Remarkably, the performance of models at different time scale, metrics, simulation of dynamical and teleconnection patterns are inconsistent among models. Nevertheless, based on skill score, the models are listed from top to bottom as; MPI-ESM-MR, CSIRO-MK3-6-0, GISS-E2-R, MRI-CGCM2.3.3, EC-EARTH, MIROC-ESM-CHEM, FGOALS-g2, BCC-CSM1.1-M, HADGEM-AO, CanESM2, GFDL-ESM2G, IPSL-CM5A-MR, and MME model. This study sheds light on the use of statistical metrics and teleconnection pattern to rank CMIP5 models and forms basis on model selection. Model parameterization over tropics is prudent, and bias correction is paramount in future projections and impacts studies.


英文关键词CMIP5 Rainfall Kenya Teleconnections
领域地球科学
收录类别SCI-E
WOS记录号WOS:000525322900012
WOS关键词INDIAN-OCEAN DIPOLE ; AFRICAN SHORT RAINS ; CLIMATE-CHANGE ; EAST-AFRICA ; TROPICAL RAINFALL ; LONG RAINS ; MODEL ; PRECIPITATION ; VARIABILITY ; TEMPERATURE
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/278875
专题地球科学
作者单位1.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Minist Educ, Key Lab Meteorol Disaster, Nanjing 210044, Peoples R China;
2.Nanjing Univ Informat Sci & Technol, Coll Atmospher Sci, Nanjing 210044, Jiangsu, Peoples R China
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Mumo, Lucia,Yu, Jinhua. Gauging the performance of CMIP5 historical simulation in reproducing observed gauge rainfall over Kenya[J]. ATMOSPHERIC RESEARCH,2020,236.
APA Mumo, Lucia,&Yu, Jinhua.(2020).Gauging the performance of CMIP5 historical simulation in reproducing observed gauge rainfall over Kenya.ATMOSPHERIC RESEARCH,236.
MLA Mumo, Lucia,et al."Gauging the performance of CMIP5 historical simulation in reproducing observed gauge rainfall over Kenya".ATMOSPHERIC RESEARCH 236(2020).
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