CR 47:57-75 (2011)  -  DOI: https://doi.org/10.3354/cr00949

ABSTRACT: Provision of seasonal climate predictions is envisioned to be a major component of the intended expansion of climate services. This paper focuses on the research basis for seasonal climate prediction, with emphasis on the needed broad professional development. Use is made of a 3-step interdisciplinary framework that previously was proposed to maximize the societal value of seasonal climate prediction schemes. Those steps involve: (1) identification of the human activities most impacted by climate variability, (2) determination of how affected regional economies can adjust or change to capitalize on the availability of skillful climate predictions, and (3) use of results from the required interdisciplinary research to develop climate prediction schemes that have maximum societal value. Consideration of these steps stresses the need for daily meteorological data and appropriate sets of ‘impacts’ data (e.g. for agriculture, water resources, public health, energy), the importance of conceptualizing and modeling the management decisions involved in those sectors (especially coupling of economic and biological/physical process models), and the necessity for the climate research community to initiate and sustain collaboration with specialists from these other scientific areas. The strong El Niño control on US winter precipitation illustrates the potential for such impact-related guidance to maximize seasonal climate prediction value. This theme is developed further by emphasizing methodologies and re-assessing results for 2 recent strongly contrasting climate research projects, which documented the influence of (1) winter temperature on US residential natural gas consumption and (2) the Intertropical Front (ITF) latitude on rainfall in the West African Sudan-Sahel zone. For each of these regional climate situations, the above 3-step framework is used to assess the seasonal prediction potential and associated professional development needs.

KEY WORDS: Seasonal climate prediction · Professional development · Daily meteorological data · Impacts data · Interdisciplinary modeling

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Cite this article as: Lamb PJ, Timmer RP, Lélé MI (2011) Professional development for providers of seasonal climate prediction. Clim Res 47:57-75. https://doi.org/10.3354/cr00949 Export citation Share:    Facebook - - linkedIn