DataCloud forecast data is driven by the company's proprietary forecast model, Super MicroCast™. Short-range model domains have been established over key locations like the continental United States, Europe, the Middle East, India and Indonesia, where hourly forecast variables are produced by a parent model of 12 km, then statistically downscaled to a resolution of 1 km, out to 60 hours. To achieve hourly, long-range forecasts worldwide, Weather Central has applied its downscaling techniques to the GFS 004 model (hours 0-180) and the GFS 003 Ensemble (hours 186-384). GFS variables are statistically downscaled across both time and space in order to produce 12 km hourly forecasts out to 384 hours. From the aforementioned models, an extensive suite of Weather Central data products is created for worldwide use in DataCloud. Beyond 60 hours, blending techniques are performed on almost all model variables to transition smoothly from the 1 km short-range models to the 12 km long-range model.
Users can programmatically access the real-time updating weather datasets provided by DataCloud, through the DataCloud API. The API delivers this data in xml, image-tile, or shape format per the user's request. In the case of forecast data, DataCloud dynamically determines which model forecast to deliver according to the highest resolution data available for the specified latitude, longitude and time. Once the data is received, it can be quickly processed and displayed to meet the user's needs, whether they be broadcast, mobile, internet or otherwise. This session will feature a detailed discussion of the Weather Central DataCloud technology, rapid-response architecture, and API.
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