Effects of Parameterized Boundary Layer Structure on Hurricane Rapid Intensification in Shear

Effects of Parameterized Boundary Layer Structure on Hurricane Rapid Intensification in Shear
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DOI:
10.1175/mwr-d-18-0010.1
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发表时间:
2019-02
影响因子:
3.2
通讯作者:
Jun A. Zhang;R. Rogers
Jun A. Zhang;R. Rogers
中科院分区:
地球科学2区
文献类型:
--
作者:
Jun A. Zhang;R. Rogers

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本研究利用厄尔飓风 (2010) 的两次回顾性 HWRF 预测,研究了参数化边界层结构在飓风强度变化中的作用,其中垂直涡流扩散率 Km 在物理升级过程中进行了修改。正如在自然界中观察到的那样,厄尔在低 Km 预报中经历了快速强化 (RI),而在高 Km 预报中,在 RI 开始时它会短暂减弱,然后恢复缓慢强化。角动量预算分析表明,Km 调节边界层中角动量的收敛,这是飓风旋转动力学的关键组成部分。减少边界层的 Km 会导致流入和辐合的增强,从而导致低 Km 预报中的深层对流比高 Km 预报中的更强且更对称。低公里预报中的更深、更强、静稳定性较低的飓风涡旋比高公里预报中的切变弹性更强。低公里预报中涡旋倾斜较小,与涡旋倾斜相关的下沉气流减少,从中层到边界层的低熵空气减少,导致边界层不稳定。未来飓风模型的物理升级应考虑这种多尺度相互作用链,以评估其对模型 RI 预测的影响。
This study investigates the role of the parameterized boundary layer structure in hurricane intensity change using two retrospective HWRF forecasts of Hurricane Earl (2010) in which the vertical eddy diffusivity Km was modified during physics upgrades. Earl undergoes rapid intensification (RI) in the low-Km forecast as observed in nature, while it weakens briefly before resuming a slow intensification at the RI onset in the high-Km forecast. Angular momentum budget analysis suggests that Km modulates the convergence of angular momentum in the boundary layer, which is a key component of the hurricane spinup dynamics. Reducing Km in the boundary layer causes enhancement of both the inflow and convergence, which in turn leads to stronger and more symmetric deep convection in the low-Km forecast than in the high-Km forecast. The deeper and stronger hurricane vortex with lower static stability in the low-Km forecast is more resilient to shear than that in the high-Km forecast. With a smaller vortex tilt in the low-Km forecast, downdrafts associated with the vortex tilt are reduced, bringing less low-entropy air from the midlevels to the boundary layer, resulting in a less stable boundary layer. Future physics upgrades in operational hurricane models should consider this chain of multiscale interactions to assess their impact on model RI forecasts.