Nonlinear Forecast Error Growth of Rapidly Intensifying Hurricane Harvey (2017) Examined through Convection-Permitting Ensemble Assimilation of GOES-16 All-Sky Radiances
Nonlinear Forecast Error Growth of Rapidly Intensifying Hurricane Harvey (2017) Examined through Convection-Permitting Ensemble Assimilation of GOES-16 All-Sky Radiances
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DOI：
10.1175/jas-d-19-0279.1
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发表时间：
2020-12
影响因子：
3.1
通讯作者：
M. Minamide;Fuqing Zhang;E. Clothiaux
中科院分区：
文献类型：
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作者：
M. Minamide;Fuqing Zhang;E. Clothiaux
使用循环集合卡尔曼滤波器 (EnKF) 的对流允许初始化、分析和预测来检查飓风哈维 (2017) 快速增强 (RI) 的动态和可预测性，该滤波器吸收了 GOES-16 上高级基线成像仪的全天空红外辐射。 EnKF 分析能够演化出与哈维相关的各种尺度的辐射场，接近于观测到的辐射场，包括与快速增强 (RI) 开始之前分散的单个对流单元相关的辐射场以及在 RI 期间和之后有组织的涡旋尺度对流系统。在超过 3 天的连续同化循环中都是如此。 EnKF 分析初始化的确定性预测捕捉到了哈维飓风发生前 24 小时内迅速增强的强度。为了探索 RI 期间哈维强度的可预测性，进行了集合概率预报和敏感性分析。研究发现，风场或湿气场中的初始扰动会引起显着的集合扩散增长。风和湿气扰动之间的非线性相互作用增加了模拟风和湿气分布的不确定性，并修改了对流活动及其对涡流的反馈，从而进一步限制了哈维强化过程的可预测性。这项研究强调了更好地同时初始化动态和湿度状态变量的重要性，以及卫星全天辐射同化对约束它们及其影响热带气旋 RI 的相关对流活动的潜在贡献。
The dynamics and predictability of the rapid intensification (RI) of Hurricane Harvey (2017) were examined using convection-permitting initialization, analysis, and prediction from a cycling ensemble Kalman filter (EnKF) that assimilated all-sky infrared radiances from the Advanced Baseline Imager on GOES-16. The EnKF analyses were able to evolve the various scales of the radiance fields associated with Harvey close to those observed, including those associated with scattered individual convective cells before the onset of rapid intensification (RI) and the organized vortex-scale convective system during and after RI. This was true for more than 3 days of a continuous assimilation cycling. Deterministic forecasts initialized from the EnKF analyses captured the rapidly deepening intensity of Harvey more than 24 h prior to its onset. To explore the predictability of Harvey’s intensity during RI, ensemble probabilistic forecasts and sensitivity analyses were conducted. It was found that significant ensemble spread growth was induced by initial perturbations individually in either the wind or moisture fields. The nonlinear interactions between wind and moisture perturbations further limited the predictability of the intensification process of Harvey by increasing the uncertainty in the simulated wind and moisture distributions and modifying the convective activity and its feedback on vortex flow. This study highlights both the importance of better initializing the dynamic and moisture state variables simultaneously and the potential contribution of satellite all-sky radiance assimilation on constraining them and their associated convective activity that impacts RI of tropical cyclones.