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RISS 인기검색어
- 검색키워드
- 저자 : Mohammed Sanusi Shiru (검색결과 3 건)
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Replicability of Annual and Seasonal Precipitation by CMIP5 and CMIP6 GCMs over East Asia
Mohammed Sanusi Shiru,Shamsuddin Shahid,채승택,정은성 대한토목학회 2022 KSCE Journal of Civil Engineering Vol.26 No.4
Global climate models (GCMs) structure is a source of uncertainty in climate change projections. Therefore, evaluation of the performances of GCMs is crucial for development of adaptation and mitigation measures and risk reduction against climate change impacts. This study quantified the performances of 10 GCMs of the Coupled Model Intercomparison Project 5 (CMIP5) and their CMIP6 equivalents in replicating precipitation over East Asia during 1975 – 2005. The CMIP5 and CMIP6 GCMs and their multi-model ensembles (MMEs) were annually and seasonally compared with the Global Precipitation Climatology Centre (GPCC) precipitation. Compromise Programming was used to rank GCMs by aggregating their scores obtained using statistical performance indices. Taylor diagram was used to assess their relative performances and GCMs' ability to replicate seasonal precipitation distribution was evaluated. Results revealed most CMIP6 GCMs' have better replicability of GPCC precipitation than CMIP5 GCMs. The MME mean of the CMIP6 showed better replicability of annual and seasonal GPCC precipitation than that of CMIP5. The CMIP6 MME also showed efficiency in simulating the seasonal precipitation distribution over East Asia. This study indicates improvements of some CMIP5 GCMs in their CMIP6 equivalents over East Asia. Findings from this study can be significant to policy makers and engineers in reducing the uncertainties in prediction of events such as floods and droughts.
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Mohammed Sanusi Shiru,김진혁,정은성 대한토목학회 2022 KSCE Journal of Civil Engineering Vol.26 No.12
This study projects precipitation over East Asia comprising of East China, South Korea, and Japan using ten Global climate models (GCM) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) and their Multi-Model Ensemble (MME). The historical GCMs were assessed using statistical metrics and compromise programming for their abilities in replicating the observed precipitation in order to assess their skills in projecting precipitation relative to the MME. Linear scaling method was used in bias correcting the GCMs using Global Precipitation Climatology Center (GPCC) as reference observed data. Probability density function and mean monthly precipitation of GCMs for the different months over the period 2021 − 2060 and 2061 − 2100 were compared with those of the observed under SSPs 2-45 and 5-85. The study revealed that NorESM2-MM, MRI-ESM2-0, MME and ACCESS-ESM1-5 have the best abilities to replicate the observed precipitation in the area of study. Under SSP 2-45, spatial projections show that the changes in precipitation for 2021 − 2060 are expected to range between -32.0 − 4.0% while those for 2061 − 2100 are -46.7 − 4.4%. Under SSP 5-85, the expected changes in precipitation range from -40 to 6.6% during 2021 to 2060 while the range is -87.3 to 6.6% with the highest decreases expected for CanESM5. The MME projects the changes of -12.0 − 6.6% during this period. The mean monthly precipitations for the different months over 2021 – 2060 and 2061 – 2100 show that while some GCMs project increases in mean monthly precipitation, others projected decreases depending on the months. Study show, no model exhibits the exact features of the observed precipitation. A model’s projection skill may be independent of its ability to replicate the properties of the observed climate. Therefore, there is a need for caution in choosing GCMs for the climate projection. This study suggests the use of the MME or the other models that have closest projections to it for climatic and hydrological studies in the region.
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Joint Modelling of Drought Severity and Duration using Copula Theory: A Case Study of Ghana
Gyamfi Kwame Adutwum,정은성,Mohammed Sanusi Shiru,Shamsuddin Shahid 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.4
Analysing and understanding the occurrence and development of droughts is of great significance in mitigating drought impacts. This study assessed the possible changes in the joint distribution of drought duration and severity in two major cities of Ghana, Accra and Yendi. The duration and severity of droughts, estimated using the Standardized Precipitation Index (SPI), were determined based on run theory. The best-fitted Copula models were used to combine the drought duration and severity to analyse the drought return period. The gamma, lognormal and Weibull distributions were considered to select the marginal distributions for the duration and severity, while the normal, t, Gumbel, Joe, Clayton and Frank copulas to select the best-fit Copula model. Bias corrected climate simulations of six Global Climate Models (GCMs) of the CMIP6 were used to project drought characteristics for the near and far futures. The results showed the Clayton and Frank copulas as the most suitable for fitting the joint distribution of drought duration and severity at Accra and Yendi, respectively. Lognormal and Weibull distributions were the most suitable for the marginal distributions of severity and duration, respectively. The joint return periods of droughts showed almost no change in the future compared to the historical period in Accra with a historical mean of 11.36 and a near and far future mean of 12.26 and 10.30 respectively but significantly reduced return periods in the future in Yendi with a near and far future means of 1.47 and 2.13 respectively compared to a historical mean of 17.40. The drought risks estimated for different future periods can provide useful information in planning, management, and assessing the adequacy of the water structures in the region.
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