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This study contributes to a broader effort of institutions toward improving seasonal forecasts over southern Africa. The primary objective is to understand where global models show shortcomings in their simulations, and how this impacts on their seasonal forecast skill. It is proposed that the skill of a model in simulating natural climate variability is an appropriate metric for a model s potential skill in seasonal forecasting. Thus the study investigates the performance of two global models in simulating the regional processes in relation to the processes variability, and how this is…mehr

Produktbeschreibung
This study contributes to a broader effort of institutions toward improving seasonal forecasts over southern Africa. The primary objective is to understand where global models show shortcomings in their simulations, and how this impacts on their seasonal forecast skill. It is proposed that the skill of a model in simulating natural climate variability is an appropriate metric for a model s potential skill in seasonal forecasting. Thus the study investigates the performance of two global models in simulating the regional processes in relation to the processes variability, and how this is related to their forecast skill. The study significantly provides more insight into models ability to simulate the general circulation features that modulate rainfall and temperature, and the relationship of rainfall with global SST. This study therefore provides useful information for modellers, forecasters, and climate researchers on the global models used in the study.
Autorenporträt
Nana Ama Kum Browne holds a PhD in Climatology. Her research interest is in Climate variability and Climate Change. She is a lecturer at the Department of Physics, University of Cape Coast, Ghana. She is a coordinator of Outreach programs and Education at the Ghana Space Science and Technology Center in Ghana.