101
Development of a global data server using downscaling techniques to produce high-resolution, long-range, hourly forecast data

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Monday, 24 January 2011
Development of a global data server using downscaling techniques to produce high-resolution, long-range, hourly forecast data
Holly C. Hassenzahl, Weather Central, LP, Madison, WI; and B. A. Wilt, C. Johnson, R. Runnheim, R. Arb, A. Rice, M. Thomas, B. J. Good, D. Graham, and N. R. Keene

Poster PDF (624.6 kB)

At Weather Central, LLC it is crucial to stay on the cutting edge of operational atmospheric modeling, while meeting the multi-faceted needs of customers throughout the world. To meet these needs, Weather Central began developing a revolutionary data server that would produce high resolution, hourly forecast data for any location in the world. In tandem, downscaling techniques were being developed and applied to the company's proprietary weather model, Super MicroCast . In order for the data server to supply hourly, long-range forecasts across the globe, Weather Central has applied downscaling techniques to the Grid 004 GFS model (hours 0-180) and the Grid 003 GFS Ensemble (hours 186-384). The downscaler reads the necessary GFS variables then statistically interpolates them across time and space in order to produce 0.25 degree, hourly forecasts from the 3-hour and 6-hour time steps of the GFS and GFS Ensemble, respectively. From these GFS variables, a suite of Weather Central data products is created for use in the global data server.

In key locations where very high resolution forecasts are needed, such as the continential United States, Europe and Asia, hourly forecast variables from a Super MicroCast model of 12 km resolution are downscaled to a resolution of 1 km, out to 60 hours. High-resolution datasets of land usage and elevation are taken into account in the downscaling process, greatly improving forecast accuracy in these regions. Accuracy is further achieved for surface temperature by applying MOS correctors to the 1 km temperature data in order to correct any systemic model biases. Beyond 60 hours, blending techniques are performed on almost all model variables to transition smoothly from the 1 km resolution short-range model to the longer-range GFS model of lower resolution. Blending also occurs for the transition between the GFS and GFS Ensemble beyond 180 hours.

Weather Central recently launched the DataCloud API allowing users to programmatically access the real-time updating weather datasets provided by the global data server. When a user requests a forecast for a specific latitude and longitude, the data server determines which model forecast to return according to the highest resolution data available for that site. The API returns the forecast in xml or image-tile format, per the user's request. This session will feature a detailed discussion of the Weather Central global data server followed by a brief discussion of the DataCloud API.