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Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia

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Title Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia
 
Creator Teshome, Asaminew
Zhang, Jie
Ma, Qianrong
Zebiak, Stephen E
Demissie, Teferi D
Dinku, Tufa
Siebert, Asher
Seid, Jemal
Acharya, Nachiketa
 
Subject ethiopia
ensemble
skill
agriculture
food security
climate change
 
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.
 
Date 2022
2022-01-06T13:56:13Z
2022-01-06T13:56:13Z
 
Type Journal Article
 
Identifier 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.
2160-0422
https://hdl.handle.net/10568/117369
https://doi.org/10.4236/acs.2022.121005
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format 54-73
 
Publisher Scientific Research Publishing, Inc.
 
Source Atmospheric and Climate Sciences