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Improvements in WRF simulation skills of southeastern United States summer rainfall: physical parameterization and horizontal resolution

机译:美国东南部夏季降雨的WRF模拟技能的改进:物理参数化和水平分辨率

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摘要

Realistic regional climate simulations are important in understanding the mechanisms of summer rainfall in the southeastern United States (SE US) and in making seasonal predictions. In this study, skills of SE US summer rainfall simulation at a 15-km resolution are evaluated using the weather research and forecasting (WRF) model driven by climate forecast system reanalysis data. Influences of parameterization schemes and model resolution on the rainfall are investigated. It is shown that the WRF simulations for SE US summer rainfall are most sensitive to cumulus schemes, moderately sensitive to planetary boundary layer schemes, and less sensitive to microphysics schemes. Among five WRF cumulus schemes analyzed in this study, the Zhang-McFarlane scheme outperforms the other four. Further analysis suggests that the superior performance of the Zhang-McFarlane scheme is attributable primarily to its capability of representing rainfall-triggering processes over the SE US, especially the positive relationship between convective available potential energy and rainfall. In addition, simulated rainfall using the Zhang-McFarlane scheme at the 15-km resolution is compared with that at a 3-km convection-permitting resolution without cumulus scheme to test whether the increased horizontal resolution can further improve the SE US rainfall simulation. Results indicate that the simulations at the 3-km resolution do not show obvious advantages over those at the 15-km resolution with the Zhang-McFarlane scheme. In conclusion, our study suggests that in order to obtain a satisfactory simulation of SE US summer rainfall, choosing a cumulus scheme that can realistically represent the convective rainfall triggering mechanism may be more effective than solely increasing model resolution. © 2014 Springer-Verlag Berlin Heidelberg.
机译:现实的区域气候模拟对于了解美国东南部(SE US)夏季降雨的机制和做出季节预测非常重要。在这项研究中,使用由气候预测系统重新分析数据驱动的天气研究和预测(WRF)模型,评估了美国东南部15 km分辨率的夏季降雨模拟的技能。研究了参数化方案和模型分辨率对降雨的影响。结果表明,美国东南部夏季降水的WRF模拟对积云方案最敏感,对行星边界层方案最敏感,而对微物理学方案不那么敏感。在本研究中分析的五个WRF积云方案中,Zhang-McFarlane方案优于其他四个。进一步的分析表明,Zhang-McFarlane方案的优越性能主要归因于其代表美国东南部降雨触发过程的能力,尤其是对流可用势能与降雨之间的正相关关系。此外,将使用Zhang-McFarlane方案在15 km分辨率下的模拟降雨与在3 km允许对流的分辨率(无积云方案)下的模拟降雨进行了比较,以测试增加的水平分辨率是否可以进一步改善SE US降雨模拟。结果表明,使用Zhang-McFarlane方案,在3 km分辨率下的模拟与15 km分辨率下的模拟相比,没有显示出明显的优势。总之,我们的研究表明,为了获得令人满意的美国东南部夏季降雨模拟,选择一种可以实际表示对流降雨触发机制的积算方案可能比仅增加模型分辨率更为有效。 ©2014施普林格出版社柏林海德堡。

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    Li L; Li W; Jin J;

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