Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia
In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North Americ...
| Autores principales: | , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Scientific Research Publishing, Inc.
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/117369 |
| _version_ | 1855519674370883584 |
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| author | Teshome, Asaminew Zhang, Jie Ma, Qianrong Zebiak, Stephen E. Demissie, Teferi Dejene Dinku, Tufa Siebert, Asher Ahmed, Jemal Seid Acharya, Nachiketa |
| author_browse | Acharya, Nachiketa Ahmed, Jemal Seid Demissie, Teferi Dejene Dinku, Tufa Ma, Qianrong Siebert, Asher Teshome, Asaminew Zebiak, Stephen E. Zhang, Jie |
| author_facet | Teshome, Asaminew Zhang, Jie Ma, Qianrong Zebiak, Stephen E. Demissie, Teferi Dejene Dinku, Tufa Siebert, Asher Ahmed, Jemal Seid Acharya, Nachiketa |
| author_sort | Teshome, Asaminew |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North American Multi-model Ensemble (NMME) over Ethiopia during the June to September (JJAS) season. The NMME, one of the multi-model seasonal forecasting systems, regularly generates monthly seasonal rainfall forecasts over the globe with 0.5 - 11.5 months lead time. The skill and predictability of seasonal rainfall are assessed using 28 years of hindcast data from the NMME models. The forecast skill is quantified using canonical correlation analysis (CCA) and root mean square error. The results show that the NMME models capture the JJAS seasonal rainfall over central, northern, and northeastern parts of Ethiopia while exhibiting weak or limited skill across western and southwestern Ethiopia. The performance of each model in predicting the JJAS seasonal rainfall is variable, showing greater skill in predicting dry conditions. Overall, the performance of the multi-model ensemble was not consistently better than any single ensemble member. The correlation of observed and predicted seasonal rainfall for the better performing models—GFDL-CM2p5-FLOR-A06, CMC2-CanCM4, GFDL-CM2p5-FLOR-B01 and NASA-GMAO-062012—is 0.68, 0.58, 0.52, and 0.5, respectively. The COLA-RSMAS-CCSM4, CMC1- CanCM3 and NCEP-CFSv2 models exhibit less skill, with correlations less than 0.4. In general, the NMME offers promising skill to predict seasonal rainfall over Ethiopia during the June-September (JJAS) season, motivating further work to assess its performance at longer lead times. |
| format | Journal Article |
| id | CGSpace117369 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Scientific Research Publishing, Inc. |
| publisherStr | Scientific Research Publishing, Inc. |
| record_format | dspace |
| spelling | CGSpace1173692025-12-08T09:54:28Z Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia Teshome, Asaminew Zhang, Jie Ma, Qianrong Zebiak, Stephen E. Demissie, Teferi Dejene Dinku, Tufa Siebert, Asher Ahmed, Jemal Seid Acharya, Nachiketa ethiopia ensemble skill agriculture food security climate change In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North American Multi-model Ensemble (NMME) over Ethiopia during the June to September (JJAS) season. The NMME, one of the multi-model seasonal forecasting systems, regularly generates monthly seasonal rainfall forecasts over the globe with 0.5 - 11.5 months lead time. The skill and predictability of seasonal rainfall are assessed using 28 years of hindcast data from the NMME models. The forecast skill is quantified using canonical correlation analysis (CCA) and root mean square error. The results show that the NMME models capture the JJAS seasonal rainfall over central, northern, and northeastern parts of Ethiopia while exhibiting weak or limited skill across western and southwestern Ethiopia. The performance of each model in predicting the JJAS seasonal rainfall is variable, showing greater skill in predicting dry conditions. Overall, the performance of the multi-model ensemble was not consistently better than any single ensemble member. The correlation of observed and predicted seasonal rainfall for the better performing models—GFDL-CM2p5-FLOR-A06, CMC2-CanCM4, GFDL-CM2p5-FLOR-B01 and NASA-GMAO-062012—is 0.68, 0.58, 0.52, and 0.5, respectively. The COLA-RSMAS-CCSM4, CMC1- CanCM3 and NCEP-CFSv2 models exhibit less skill, with correlations less than 0.4. In general, the NMME offers promising skill to predict seasonal rainfall over Ethiopia during the June-September (JJAS) season, motivating further work to assess its performance at longer lead times. 2022 2022-01-06T13:56:13Z 2022-01-06T13:56:13Z Journal Article https://hdl.handle.net/10568/117369 en Open Access Scientific Research Publishing, Inc. Teshome A, Zhang J, Ma Q, Zebiak SE, Demissie TD, Dinku T, Siebert A, Seid J, Acharya N. 2022. Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia. Atmospheric and Climate Sciences 12(1):54-73. |
| spellingShingle | ethiopia ensemble skill agriculture food security climate change Teshome, Asaminew Zhang, Jie Ma, Qianrong Zebiak, Stephen E. Demissie, Teferi Dejene Dinku, Tufa Siebert, Asher Ahmed, Jemal Seid Acharya, Nachiketa Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia |
| title | Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia |
| title_full | Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia |
| title_fullStr | Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia |
| title_full_unstemmed | Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia |
| title_short | Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia |
| title_sort | skill assessment of north american multi models ensemble nmme for june september jjas seasonal rainfall over ethiopia |
| topic | ethiopia ensemble skill agriculture food security climate change |
| url | https://hdl.handle.net/10568/117369 |
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