期刊
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
卷 131, 期 606, 页码 389-407出版社
ROYAL METEOROLOGICAL SOC
DOI: 10.1256/qj.04.03
关键词
ensemble prediction; probability forecasting; spread-skill relationship
Stochastic parametrization of the effects of unresolved variables is studied in the context of the Lorenz '96 system. These parametrizations are found to produce clear improvements in correspondence between the model and 'true' climatologies; they similarly provide clear improvements in all ensemble forecast verification measures investigated, including accuracy of ensemble means and ensemble probability estimation, and including measures operating on both scalar (each resolved forecast variable evaluated individually) and vector (all forecast variables evaluated simultaneously) predictands. Scalar accuracy measures for non-ensemble (i.e. single integration) forecasts are, however, degraded. The results depend very strongly on both the amplitude (standard deviation) and time-scale of the stochastic forcing, but only weakly on its spatial scale. In general there seems not to be a single clear optimum combination of time-scale and amplitude, but rather there exists a range of combinations producing similar results.
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