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Building National and Specialised Climate Services

  • John Bellow
  • Abdalah Mokssit
  • Jim O'Brien
  • Rachid Sebbari
Conference paper
Part of the NATO Science Series book series (NAIV, volume 82)

Beneficial application of information, whether this information is based on historical data or on predictions, is the ultimate objective of any climate service. The definitive measure of success of a climate service is in the value that climate information imparts in its final use. In earlier parts of this book we have examined the science of seasonal to interannual prediction itself, whereas here we are exploring the ways in which that information might be used. By contrast with the scope for the earlier sections of the book the possible issues to be considered here are substantial, and beyond any capability to provide a fully comprehensive treatment. In the previous chapter, there was an examination of structural and institutional issues requiring serious consideration in the establishment of climate services, whereas in this chapter and the following one there is a restricted, of necessity, review of some current activities in the field. It should be stressed that all examples in these two chapters follow the end-to-end model for applications rather than the integrated approach, a presentation consistent with the prevailing on-the-ground situation at the time of writing; in due course the balance between the two models may change. The two examples in this Chapter both relate to the building of climate services, in the first case by a Meteorological Service for a range of prospective users, and in the second by a University providing services mainly to the agriculture and forestry sectors. Developing world countries are frequently well-placed geographically to benefit from the maximum prediction skills available, and in the first section the full process taken by the Moroccan Meteorological Service to develop climate services to support planning for agriculture and water, including at high government levels, is described; thus in this example there are multiple users at different decision levels. A commercial approach for agriculture and forestry is described in the second section, where the potential user base is broad with a wide range of requirements that cannot be serviced on a one-to-one basis, and therefore less personal communication processes, in this case built around the Internet, are needed.

Keywords

North Atlantic Oscillation Index Seasonal Forecast Climate Information Climate Forecast Seasonal Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media B.V 2008

Authors and Affiliations

  • John Bellow
    • 1
  • Abdalah Mokssit
    • 2
  • Jim O'Brien
    • 1
  • Rachid Sebbari
    • 2
  1. 1.Florida State UniversityLynnwoodUSA
  2. 2.Direction de la Météorologie NationaleFace Préfecture Hay HassaniMorocco

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