{"title":"Impacts of initial condition perturbation blending in 10- and 40-member convection-allowing ensemble forecasts","authors":"Aaron Johnson, Xuguang Wang","doi":"10.1175/mwr-d-23-0188.1","DOIUrl":null,"url":null,"abstract":"\nA series of convection-allowing 36-hour ensemble forecasts during the 2018 Spring season are used to better understand the impacts of ensemble configuration and blending different sources of initial condition (IC) perturbation. Ten- and 40-member ensemble configurations are initialized with the multi-scale IC perturbations generated as a product of convective-scale data assimilation (MULTI), and initialized with the MULTI IC perturbations blended with IC perturbations downscaled from coarser resolution ensembles (BLEND). The forecast performance of both precipitation and non-precipitation variables is consistently improved by the larger ensemble size. The benefit of the larger ensemble is largely, but not entirely, due to compensating for under-dispersion in the fixed-physics ensemble configuration. A consistent improvement in precipitation forecast skill results from blending in the 10-member ensemble configuration, corresponding to a reduction in the ensemble calibration error (i.e., reliability component of Brier Score). In the 40-member ensemble configuration, the advantage of blending is limited to the ∼18-22 hour lead times at all precipitation thresholds, and the ∼35-36 hour lead times at the lowest threshold, both corresponding to an improved resolution component of the Brier Score. The advantage of blending in the 40-member ensemble during the diurnal convection maximum of ∼18-22 hour lead times is primarily due to cases with relatively weak synoptic scale forcing while advantages at later lead times beyond ∼30 hours lead time are most prominent on cases with relatively strong synoptic scale forcing. The impacts of blending and ensemble configuration on forecasts of non-precipitation variables is generally consistent with the impacts on the precipitation forecasts.","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Monthly Weather Review","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/mwr-d-23-0188.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
A series of convection-allowing 36-hour ensemble forecasts during the 2018 Spring season are used to better understand the impacts of ensemble configuration and blending different sources of initial condition (IC) perturbation. Ten- and 40-member ensemble configurations are initialized with the multi-scale IC perturbations generated as a product of convective-scale data assimilation (MULTI), and initialized with the MULTI IC perturbations blended with IC perturbations downscaled from coarser resolution ensembles (BLEND). The forecast performance of both precipitation and non-precipitation variables is consistently improved by the larger ensemble size. The benefit of the larger ensemble is largely, but not entirely, due to compensating for under-dispersion in the fixed-physics ensemble configuration. A consistent improvement in precipitation forecast skill results from blending in the 10-member ensemble configuration, corresponding to a reduction in the ensemble calibration error (i.e., reliability component of Brier Score). In the 40-member ensemble configuration, the advantage of blending is limited to the ∼18-22 hour lead times at all precipitation thresholds, and the ∼35-36 hour lead times at the lowest threshold, both corresponding to an improved resolution component of the Brier Score. The advantage of blending in the 40-member ensemble during the diurnal convection maximum of ∼18-22 hour lead times is primarily due to cases with relatively weak synoptic scale forcing while advantages at later lead times beyond ∼30 hours lead time are most prominent on cases with relatively strong synoptic scale forcing. The impacts of blending and ensemble configuration on forecasts of non-precipitation variables is generally consistent with the impacts on the precipitation forecasts.
期刊介绍:
Monthly Weather Review (MWR) (ISSN: 0027-0644; eISSN: 1520-0493) publishes research relevant to the analysis and prediction of observed atmospheric circulations and physics, including technique development, data assimilation, model validation, and relevant case studies. This research includes numerical and data assimilation techniques that apply to the atmosphere and/or ocean environments. MWR also addresses phenomena having seasonal and subseasonal time scales.