Edge Detection Method for Determining Boundary Layer Height Based on Doppler Lidar
Edge Detection Method for Determining Boundary Layer Height Based on Doppler Lidar
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基于多普勒激光雷达确定边界层高度的边缘检测方法
DOI：
10.3390/atmos12091103
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发表时间：
2021-08
期刊：
影响因子：
2.9
通讯作者：
Wang Wei
中科院分区：
文献类型：
--
作者：
Pan Ya'ni;Jin Zhili;Tong Pengfei;Xu Weiwei;Wang Wei
边界层顶部是大气数值模式中的一个重要物理参数，在大气模拟、大气污染防治和气候预报中起着至关重要的作用。传统的利用多普勒激光雷达垂直速度方差(σw2)确定潜伏层的方法可分为方差法和峰值法，由于采用单一阈值，这两种方法依赖于大气条件，从而限制了它们估计昼夜潜伏层的能力。由于边缘检测(ED)能够识别图像的2D梯度，它后来被引入到BLH估计中。ED的一个关键步骤是根据轮廓的峰值自动识别BLH的边缘，从而避免极端大气条件的影响。在2019年3月4日和2019年7月8日的两个日循环中，ED在夜间和极端大气条件下的表现优于方差和峰值方法。将2018-2020年反演的BLHs与同一时间的中性、稳定和对流边界层的无线电探空仪(RS)测量结果进行了比较。ED法获得的相关系数(R：0.4vs.0.05，0.14；0.26vs.RMSE0.10，−0.16；0.35vs.0.01，0.16)和均方根误差(−(Km)：0.58vs.0.82，0.90；0.37vs.1.01，0.50；0.66vs.0.98，0.82)分别高于方差法和峰值法。在NBL、SBL和CBL条件下，ED方法的平均绝对误差(MAE)分别低于方差法和峰值法(MAE(Km)：0.44、0.14、0.50比0.62、0.34、0.64；0.59、0.75、0.74)。在NBL条件下，ED法的平均相对误差低于方差法和峰值法(−8.88%对−18.39%、13.91%)。在标准差下，ED法的相对误差低于方差法，高于峰值法(−为38.64%，−为152.23%；14.02%)。在CBL下，ED法的相对误差低于方差法，高于峰值法(−15.07%vs.2.24%；5.64%)。此外，通过与小波协方差变换(WCT)方法和遥感测量结果的比较，表明ED方法与小波协方差变换(WCT)方法具有相似的性能，甚至更好。在长期分析中，ED得到的日循环和年循环中的每小时和每月的BLHs分别与遥感测量结果高度一致，并获得了最低的标准误差。在年周期中，夏季和秋季的植被覆盖率高于春季和冬季。
The top of the boundary layer, referred to as the planetary boundary layer height (BLH), is an important physical parameter in atmospheric numerical models, which has a critical role in atmospheric simulation, air pollution prevention, and climate prediction. The traditional methods for determining BLHs using Doppler lidar vertical velocity variance (σw2) can be classified into the variance and peak methods, which depend on atmospheric conditions due to their use of a single threshold, hence limiting their ability to estimate diurnal BLHs. Edge detection (ED) was later introduced in BLH estimation due to its ability to identify the 2D gradient of an image. A key step in ED is automatically identifying the edge of BLHs based on the peaks of the profile, hence avoiding the influence of extreme atmospheric conditions. Two cases in the diurnal cycle on 4 March 2019 and 8 July 2019 reveal that ED outperforms both the variance and peak methods in nighttime and extreme atmospheric conditions. The retrieved BLHs from 2018 to 2020 were compared with radiosonde (RS) measurements for the same time at the neutral, stable, and convective boundary layers. The correlation coefficient (R: 0.4 vs. 0.05, 0.14; 0.26 vs. −0.10, −0.16; 0.35 vs. 0.01, 0.16) and root mean square error (RMSE (km): 0.58 vs. 0.82, 0.90; 0.37 vs. 1.01, 0.50; 0.66 vs. 0.98, 0.82) obtained by the ED method were higher and lower than those obtained by the variance and peak methods, respectively. The mean absolute error (MAE) of the ED method under the NBL, SBL, and CBL conditions are lower than the variance and peak methods (MAE (km): 0.44, 0.14, 0.50 vs. 0.62, 0.34, 0.64; 0.59, 0.75, 0.74), respectively. The mean relative error (MRE) of the ED method is lower than the variance and peak methods under the NBL condition (MRE: −8.88% vs. −18.39%, 13.91%). Under the SBL, the MRE of the ED method is lower than the variance method and higher than the peak method (−38.64%, vs. −152.23%; 14.02%). Under the CBL, the MRE of the ED method is lower than the variance method and higher than the peak method (−15.07% vs. 2.24%; 5.64%). In addition, the comparison between ED and wavelet covariance transform (WCT) method and RS measurements showed that the ED method has a similar performance with the WCT method and is even better. In the long-term analysis, the hourly and monthly BLHs in the diurnal and annual cycles, respectively, as obtained by ED, were highly consistent with the RS measurements and obtained the lowest standard error. In the annual cycle, the retrieved BLHs in summer and autumn were higher than those retrieved in spring and winter.
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