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dc.date.accessioned2022-05-09T00:55:42Z
dc.date.available2022-05-09T00:55:42Z
dc.date.copyright25 Mar 2022
dc.date.issued2022
dc.identifier.otherMWR-D-21-0148.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285892
dc.description.abstractA valid time shifting (VTS) method is explored for the GSI-based ensemble variational (EnVar) system modified to directly assimilate radar reflectivity at convective scales. VTS is a cost-efficient method to increase ensemble size by including subensembles before and after the central analysis time. Additionally, VTS addresses common time and phase model error uncertainties within the ensemble. VTS is examined here for assimilating radar reflectivity in a continuous hourly analysis system for a case study of 1–2 May 2019. The VTS implementation is compared against a 36-member control experiment (ENS-36), to increase ensemble size (3 × 36 VTS), and as a cost-savings method (3 × 12 VTS), with time-shifting intervals τ between 15 and 120 min. The 3 × 36 VTS experiments increased the ensemble spread, with largest subjective benefits in early cycle analyses during convective development. The 3 × 12 VTS experiments captured analysis with similar accuracy as ENS-36 by the third hourly analysis. Control forecasts launched from hourly EnVar analyses show significant skill increases in 1-h precipitation over ENS-36 out to hour 12 for 3 × 36 VTS experiments, subjectively attributable to more accurate placement of the convective line. For 3 × 12 VTS, experiments with τ ≥ 60 min met and exceeded the skill of ENS-36 out to forecast hour 15, with VTS-3 × 12τ90 maximizing skill. Sensitivity results demonstrate preference to τ = 30–60 min for 3 × 36 VTS and 60–120 min for 3 × 12 VTS. The best 3 × 36 VTS experiments add a computational cost of 45%–67%, compared to the near tripling of costs when directly increasing ensemble size, while best 3 × 12 VTS experiments save about 24%–41% costs over ENS-36.
dc.titleUsing a Cost-Effective Approach to Increase Background Ensemble Member Size within the GSI-Based EnVar System for Improved Radar Analyses and Forecasts of Convective Systems
dc.typeJournal Paper
dc.journal.volume150
dc.journal.issue3
dc.journal.titleMonthly Weather Review
dc.identifier.doi10.1175/MWR-D-21-0148.1
dc.page667–689
dc.treeMonthly Weather Review:;2022:;volume( 150 ):;issue: 003
dc.contenttypeFulltext


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