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DOI | 10.1175/JAS-D-17-0332.1 |
Ensemble Spread Grows More Rapidly in Higher-Resolution Simulations of Deep Convection | |
Weyn, Jonathan A.; Durran, Dale R. | |
2018-10-01 | |
发表期刊 | JOURNAL OF THE ATMOSPHERIC SCIENCES
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ISSN | 0022-4928 |
EISSN | 1520-0469 |
出版年 | 2018 |
卷号 | 75期号:10页码:3331-3345 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Idealized ensemble simulations of mesoscale convective systems (MCSs) with horizontal grid spacings of 1, 1.4, and 2 km are used to analyze the influence of numerical resolution on the rate of growth of ensemble spread in convection-resolving numerical models. The ensembles are initialized with random phases of 91-km-wavelength moisture perturbations that are captured with essentially identical accuracy at all resolutions. The rate of growth of ensemble variance is shown to systematically increase at higher resolution. The largest horizontal wavelength at which the perturbation kinetic energy (KE) grows to at least 50% of the background kinetic energy spectrum is also shown to grow more rapidly at higher resolution. The mechanism by which the presence of smaller scales accelerates the upscale growth of KE is clear-cut in the smooth-saturation Lorenz-Rotunno-Snyder (ssLRS) model of homogeneous surface quasigeostrophic turbulence. Comparing the growth of KE from the MCS ensemble simulations to that in the ssLRS model suggests interactions between perturbations at small scales, where KE is not yet completely saturated, and somewhat larger scales, where KE is clearly unsaturated, are responsible for the faster growth rate of ensemble variance at finer resolution. These results provide some empirical justification for the use of deep-convection-related stochastic parameterization schemes to reduce the problem of underdispersion in coarser-resolution ensemble prediction systems. |
英文关键词 | Ensembles Mesoscale forecasting Numerical weather prediction forecasting |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000443221100002 |
WOS关键词 | ATMOSPHERIC PREDICTABILITY ; MESOSCALE PREDICTABILITY ; PARAMETERIZING ENSEMBLES ; MODEL UNCERTAINTIES ; PREDICTION SYSTEMS ; SCALES ; SPECTRA ; ECMWF ; BUTTERFLIES ; MOTION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/29388 |
专题 | 地球科学 |
作者单位 | Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA |
推荐引用方式 GB/T 7714 | Weyn, Jonathan A.,Durran, Dale R.. Ensemble Spread Grows More Rapidly in Higher-Resolution Simulations of Deep Convection[J]. JOURNAL OF THE ATMOSPHERIC SCIENCES,2018,75(10):3331-3345. |
APA | Weyn, Jonathan A.,&Durran, Dale R..(2018).Ensemble Spread Grows More Rapidly in Higher-Resolution Simulations of Deep Convection.JOURNAL OF THE ATMOSPHERIC SCIENCES,75(10),3331-3345. |
MLA | Weyn, Jonathan A.,et al."Ensemble Spread Grows More Rapidly in Higher-Resolution Simulations of Deep Convection".JOURNAL OF THE ATMOSPHERIC SCIENCES 75.10(2018):3331-3345. |
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