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@InProceedings{VanOldenborghCoel:2006:PrSeFo,
               author = "Van Oldenborgh, G. J. and Coelho, Caio Augusto dos Santos",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE/CPTEC)}",
                title = "Probabilistic seasonal forecast verification with the climate 
                         explorer",
            booktitle = "Abstracts...",
                 year = "2006",
         organization = "European Geosciences Union General Assembly 2006.",
             keywords = "*.",
             abstract = "Seasonal climate forecasts are made using multi-model ensembles. 
                         Contrary to climate change projections, the skill of the forecasts 
                         can be verified against observations using old forecasts and 
                         hindcasts. In practice the small number of forecasts (15-45) is a 
                         severe limitation, as the skill depends strongly on the region and 
                         season. We present a web-based system to produce charts and maps 
                         of the skill of operational seasonal forecast systems using a 
                         variety of measures. It is part of the KNMI Climate Explorer 
                         (climexp.knmi.nl), and presently contains data from the ECMWF S2 
                         and NCEP CFS operational forecast systems, as well as the Demeter 
                         research experiment. The verification measures have been developed 
                         in the RCLIM project, and include deterministic measures such as 
                         the ensemble mean correlation, RMSE and MAE, as well as 
                         probabilistic measures such as the Brier Score, its decomposition 
                         into resolution, reliability and uncertainty, and the ROC curve. 
                         These are available both for time series (area-averaged or all 
                         grid points in a region) and as spatial maps. More measures, and 
                         estimates of the uncertainties of the skill scores, are planned. 
                         The verification system allows seasonal forecasters and climate 
                         researchers to quickly explore the predictability of the 
                         short-term climate with current state-of-the-art models.",
  conference-location = "Vienna, Austria",
      conference-year = "2-7 Apr.",
             language = "en",
         organisation = "EGU",
           targetfile = "egu06_climexp.pdf",
        urlaccessdate = "25 jan. 2021"
}


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