Abstract. The cube root of the energy dissipation rate (EDR), as a standard reporting metric of atmospheric turbulence, is estimated using 1-Hz quick access recorder data from Korean-based national air carriers with two different types of aircraft [Boeing 737 (B737) and B777], archived for 12 months from January to December 2012. Various EDRs are estimated using zonal, meridional, and derived vertical wind components, and the derived equivalent vertical gust (DEVG). Wind-based EDRs are estimated by (i) second-order structure function (EDR1), (ii) power spectral density (PSD), considering the Kolmogorov’s -5/3 dependence (EDR2), and (iii) maximum-likelihood estimation using the von Kármán spectral model (EDR3). DEVG-based EDRs are obtained mainly by vertical acceleration with different conversions to EDR using (iv) the lognormal mapping technique (EDR4) and (v) the predefined parabolic relationship between the observed EDR and DEVG (EDR5). For the EDR1, second-order structure functions are computed for zonal, meridional, and vertical wind within the defined inertial subrange. For the EDR2 and EDR3, individual PSDs for each wind component are computed using the Fast Fourier Transform over every 2-minute time window. Then, two EDR estimates are computed separately by employing the Kolmogorov-scale slope (EDR2) or prescribed von Kármán wind model (EDR3) within the inertial subrange. The resultant EDR estimates from five different methods follow a lognormal distribution reasonably well, which satisfies the fundamental characteristics of atmospheric turbulence. Statistics (mean and standard deviation) of log-scale EDRs are somewhat different from those found in a previous study using a higher frequency (10 Hz) of in situ aircraft data in the United States, likely due to different sampling rates, aircraft types, and locations. Finally, five EDR estimates capture well the intensity and location of three strong turbulence cases that are relevant to clear-air turbulence (CAT), mountain wave turbulence (MWT), and convectively induced turbulence (CIT), with different characteristics of the observed EDRs: 1) zonal (vertical) wind-based EDRs are stronger in the CAT (CIT) case, while MWT has a peak of EDRs in both zonal and vertical wind-based EDRs, and 2) the CAT and MWT cases occurred by large-scale (synoptic-scale) forcing have more variations in EDRs before and after the incident, while the CIT case triggered by smaller mesoscale convective cell has an isolated peak of EDR.

中文翻译：

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使用 1Hz 商用飞机快速访问记录器 (QAR) 数据导出的能量耗散率的特征

摘要。能量耗散率 (EDR) 的立方根，作为大气湍流的标准报告指标，使用来自韩国国家航空公司的 1-Hz 快速访问记录器数据进行估计，该数据来自具有两种不同类型的飞机 [波音 737 (B737)和 B777]，从 2012 年 1 月到 12 月存档 12 个月。使用纬向、经向和派生垂直风分量以及派生等效垂直阵风 (DEVG) 估计各种 EDR。基于风的 EDR 由 (i) 二阶结构函数 (EDR1)、(ii) 功率谱密度 (PSD) 估计，考虑到 Kolmogorov 的 -5/3 依赖性 (EDR2)，以及 (iii) 最大似然估计使用von Kármán 光谱模型 (EDR3)。基于 DEVG 的 EDR 主要通过垂直加速度获得，并使用 (iv) 对数正态映射技术 (EDR4) 和 (v) 观察到的 EDR 和 DEVG (EDR5) 之间的预定义抛物线关系转换为 EDR。对于 EDR1，在定义的惯性子范围内为纬向、经向和垂直风计算二阶结构函数。对于 EDR2 和 EDR3，使用快速傅立叶变换在每 2 分钟的时间窗口内计算每个风分量的单独 PSD。然后，通过在惯性子范围内采用 Kolmogorov 尺度斜率 (EDR2) 或规定的 von Kármán 风模型 (EDR3)，分别计算两个 EDR 估计值。来自五种不同方法的结果 EDR 估计值符合对数正态分布，满足大气湍流的基本特征。对数尺度 EDR 的统计数据（均值和标准差）与之前在美国使用更高频率 (10 Hz) 现场飞机数据的研究中发现的数据略有不同，这可能是由于不同的采样率、飞机类型、和地点。最后，五个 EDR 估计值很好地捕获了与晴空湍流 (CAT)、山波湍流 (MWT) 和对流诱导湍流 (CIT) 相关的三个强湍流案例的强度和位置，具有不同的观测 EDR 特征: 1) 在 CAT (CIT) 情况下，基于纬向（垂直）风的 EDR 更强，而 MWT 在纬向和垂直基于风的 EDR 中都具有 EDR 峰值，