scholarly journals Coupling forecast calibration and data‐driven downscaling for generating reliable, high‐resolution, multivariate seasonal climate forecast ensembles at multiple sites

2019 ◽  
Vol 40 (4) ◽  
pp. 2479-2496 ◽  
Author(s):  
Andrew Schepen ◽  
Yvette Everingham ◽  
Quan J. Wang
Keyword(s):  
High Resolution ◽  
Data Driven ◽  
Climate Forecast ◽  
Seasonal Climate Forecast ◽  
Seasonal Climate

scholarly journals Systematic global evaluation of accuracy of seasonal climateforecasts for monthly precipitation of JMA/MRI-CPS2 bycomparing with a statistical system using climate indices

2021 ◽  
Author(s):  
Yuji Masutomi ◽  
Toshichika Iizumi ◽  
Key Oyoshi ◽  
Nobuyuki Kayaba ◽  
Wonsik Kim ◽  
...  
Keyword(s):  
Japan Meteorological Agency ◽  
Climate Indices ◽  
Global Evaluation ◽  
Monthly Precipitation ◽  
Climate Forecast ◽  
Statistical System ◽  
Slow Dynamics ◽  
Seasonal Climate Forecast ◽  
Seasonal Climate

Abstract. In this study, we aimed to evaluate the monthly precipitation forecasts of JMA/MRI-CPS2, a global dynamical seasonal climate forecast (Dyn-SCF) system operated in the Japan Meteorological Agency, by comparing them with the forecasts of a statistical SCF (St-SCF) system using climate indices systematically and globally. Accordingly, we developed a new global St-SCF system using 18 climate indices and compared the monthly precipitation of this system with those of JMA/MRI-CPS2. Consequently, it was found that JMA/MRI-CPS2 forecasts are superior to St-SCFs around the equator (10° S–10° N) even for six-month lead forecasts. For one-month lead forecasts, the accuracy of JMA/MRI-CPS2 forecasts was higher than that of St-SCFs when viewed globally. In contrast, for forecasts made two months or longer in advance, St-SCFs had an advantage in global forecasts. In addition to evaluating the accuracy of JMA/MRI-CPS2 forecasts, the slow dynamics of the ocean and atmosphere, not reproduced by the JMA/MRI-CPS2 system, were determined by comparing the evaluations, and it was concluded that this could contribute to improving Dyn-SCF systems.

scholarly journals Enabling Conditions for Improved Use of Seasonal Climate Forecast in Arid and Semi-Arid Baringo County—Kenya

OALib ◽  
2017 ◽  
Vol 04 (08) ◽  
pp. 1-15 ◽  
Author(s):  
Richard Ochieng ◽  
Charles Recha ◽  
Bockline Omedo Bebe
Keyword(s):  
Climate Forecast ◽  
Seasonal Climate Forecast ◽  
Seasonal Climate ◽  
Semi Arid
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