Friday, 28 July 2017
Atrium (Hyatt Regency Baltimore)
Climate prediction information is of great value at regions where societal and economic sectors are more vulnerable to climate variability. That is the case of mid-summer drought (MSD) in the Mesoamerican region, where agriculture and water management can be strongly dependent on subseasonal to seasonal climate variations. MSD is typically observed during July and August and it is characterized by a relative-minimum in summer precipitation at locations with a bi-modal precipitation distribution. Based on the post-processing of the Climate Forecast System Version 2 forecasts, a prediction scheme at sub-seasonal scale is proposed for MSD using CFSv2 forecasts in real-time; in addition, CFSv2 hindcasts (1999-2010) allowed bias estimation for the region of interest. A daily gridded observed dataset derived from stations of the Mexican Meteorological Service (SMN) is used for validating predictions. The scheme produces forecasts in anomalies but also evaluates probabilities of exceeding a given threshold. Decision-makers are particularly interested in guidance on the likelihood, magnitude, and impacts of MSD and often demand details on its onset, ending, intensity and spatial distribution, though current MSD forecast in the region is provided as non-systematic, qualitative and multi-format. In context with the Global Framework for Climate Services, a climate product -a result from synthesizing science and climatic data- is distinguished from a climate service -climatic information prepared and submitted to respond to specific user needs-. Therefore, insights into additional features of predictions are explored (perception, timeliness, availability, flexibility) so that the MSD prediction scheme can be turned into an operational climate service.
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