4.6 Article

Ensemble forecasts of a flood-producing storm: comparison of the influence of model-state perturbations and parameter modifications

期刊

出版社

WILEY
DOI: 10.1002/qj.1951

关键词

convective-scale ensemble forecasting; parameter perturbations; model-state perturbations; flood; Unified Model

资金

  1. National Environment Research Council [NE/E002137/1]
  2. NERC [NE/E002137/1] Funding Source: UKRI
  3. Natural Environment Research Council [NE/E002137/1] Funding Source: researchfish

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High-resolution ensemble simulations (x = 1 km) are performed with the Met Office Unified Model for the Boscastle (Cornwall, UK) flash-flooding event of 16 August 2004. Forecast uncertainties arising from imperfections in the forecast model are analysed by comparing the simulation results produced by two types of perturbation strategy. Motivated by the meteorology of the event, one type of perturbation alters relevant physics choices or parameter settings in the model's parametrization schemes. The other type of perturbation is designed to account for representativity error in the boundary-layer parametrization. It makes direct changes to the model state and provides a lower bound against which to judge the spread produced by other uncertainties. The Boscastle has genuine skill at scales of approximately 60 km and an ensemble spread which can be estimated to within approximate to 10% with only eight members. Differences between the model-state perturbation and physics modification strategies are discussed, the former being more important for triggering and the latter for subsequent cell development, including the average internal structure of convective cells. Despite such differences, the spread in rainfall evaluated at skilful scales is shown to be only weakly sensitive to the perturbation strategy. This suggests that relatively simple strategies for treating model uncertainty may be sufficient for practical, convective-scale ensemble forecasting. Copyright (c) 2012 Royal Meteorological Society and British Crown Copyright, the Met Office

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