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- Author or Editor: P. Malguzzi x
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Abstract
Since November 1999, the hydrostatic meteorological Bologna Limited-Area Model (BOLAM) has been running operationally at the National Observatory of Athens. The assessment of the model forecast skill during the 2-yr period included (a) calculation of the root-mean-square errors (model vs gridded analyses) of geopotential height and temperature at 850 and 500 hPa, (b) evaluation of the model's quantitative precipitation forecast skill for the most important events, and (c) evaluation of the model skill in the prediction of surface winds in comparison with buoy observations. Comparison of the verification results with those provided in the literature showed that BOLAM has a high forecast skill, even for precipitation, which is the most difficult parameter to forecast. Especially for precipitation, the comparison between coarse (∼21 km) and fine (∼6.5 km) grid spacing forecasts showed that for the low and medium precipitation amounts, the finer-grid forecasts are not as good as the coarse-grid forecasts. For the large precipitation amounts, the calculated statistical scores provide only little support of the idea that the fine-grid forecasts are better than those of the coarse grid because the fine-grid forecasts give better scores only for the quantity bias and the mean absolute error.
Abstract
Since November 1999, the hydrostatic meteorological Bologna Limited-Area Model (BOLAM) has been running operationally at the National Observatory of Athens. The assessment of the model forecast skill during the 2-yr period included (a) calculation of the root-mean-square errors (model vs gridded analyses) of geopotential height and temperature at 850 and 500 hPa, (b) evaluation of the model's quantitative precipitation forecast skill for the most important events, and (c) evaluation of the model skill in the prediction of surface winds in comparison with buoy observations. Comparison of the verification results with those provided in the literature showed that BOLAM has a high forecast skill, even for precipitation, which is the most difficult parameter to forecast. Especially for precipitation, the comparison between coarse (∼21 km) and fine (∼6.5 km) grid spacing forecasts showed that for the low and medium precipitation amounts, the finer-grid forecasts are not as good as the coarse-grid forecasts. For the large precipitation amounts, the calculated statistical scores provide only little support of the idea that the fine-grid forecasts are better than those of the coarse grid because the fine-grid forecasts give better scores only for the quantity bias and the mean absolute error.
