Wednesday, 13 January 2016
Hall D/E ( New Orleans Ernest N. Morial Convention Center)
Radiosondes, balloon-borne meteorological sensors used to profile the atmosphere, are essential input data streams for numerical weather prediction models and are used for climate research. However, radiosonde programs are costly to maintain, in particular in the remote regions of the Arctic, where only 40 of approximately 1000 routine global launches are made. The climate of this data-sparse region is poorly understood and forecast data assimilation procedures are designed for global applications. Thus, observations may be rejected from the data assimilation because they are too far from the model expectations. For the most cost-efficient deployment of resources and to improve forecasting, analyses of the effectiveness of individual radiosonde programs are necessary. Here, we evaluate how radiosondes launched twice daily (0 and 12 UTC) from Summit Station, Greenland, (72.58⁰N, 38.48⁰W, 3210 masl) influence the European Centre for Medium Range Weather Forecasting (ECMWF) operational forecasts from June 2013 through May of 2015. A statistical analysis is conducted to determine the impact of the observations on the forecast model and meteorological regimes that the model fails to reproduce. High assimilation rates are found for temperature, u-wind, v-wind, and mixing ratio. The lowest assimilation rates are found near the surface, possibly due to biases in the representation of the temperature inversion by ECMWF at Summit. Consequently, assimilation rates are lowest in the boundary-layer during winter when strong temperature inversions are frequently observed. Our findings benefit the scientific community who uses this information for climatological analysis of the Greenland Ice Sheet, and thus further analysis is warranted.
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