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Evaluation of WRF planetary boundary layer parameterization schemes for simulation of monsoon depressions over India

机译:WRF行星边界层参数化方案对印度季风萧条的模拟

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This study evaluates the fidelity of five planetary boundary layer (PBL) parameterization schemes in the advanced weather research and forecasting model for simulating monsoon depressions (MDs) over India. Five PBL schemes include; nonlocal first-order medium-range forecasting (MRF) and Yonsei University (YSU); hybrid first-order Asymmetric Convective Model version 2 (ACM2), and local one-and-a-half-order Bougeault-Lacarrere (BouLac) and Mellor-Yamada-Nakanishi-Niino (MYNN2). PBL schemes show significant impact on rainfall along with dynamical and thermodynamical parameters associated with MDs at the surface as well as at the upper levels. MRF simulates a relatively shallower, warmer and drier boundary layer compared to others. Results reveal that strong upper-level divergence and high moisture content within the lower levels are favorable for the occurrence of heavy rain associated with MDs. However, stronger wind shear within the mid-troposphere weakens the system and reduces the rain intensity. Based on the results and keeping the rainfall product in view, it is found that nonlocal PBL schemes (MRF and ACM2) have better forecast skills score than local PBL schemes (BouLac and MYNN2) over the Indian region.
机译:本研究评估了在印度模拟季风萧条(MDS)的先进天气研究和预测模型中五个行星边界层(PBL)参数化方案的保真度。五个PBL计划包括;非本体一阶中等范围预测(MRF)和Yonsi大学(Ysu);混合的一阶非对比对流模型版本2(ACM2)和当地一流的Bougeault-Lacarrere(Boulac)和Mellor-yamada-Nakanishi-Niino(MyNN2)。 PBL方案对降雨的影响显着影响以及与表面上的MDS相关的动态和热力学参数以及上层。与他人相比,MRF模拟相对较浅,更温暖,更干燥的边界层。结果表明,在较低水平内的强大的上层分歧和高水分含量有利于与MD相关的大雨发生。然而,中层内部的风剪得更弱,削弱了系统并降低了雨水强度。根据结果​​并保持降雨产品视图,发现非本地PBL方案(MRF和ACM2)在印度地区的本地PBL方案(Boulac和MyNN2)具有更好的预测技能分数。

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