Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm
Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm
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DOI：
10.5194/amt-15-5769-2022
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发表时间：
2022-10
影响因子：
3.8
通讯作者：
G. Stober;A. Liu;A. Kozlovsky;Z. Qiao;A. Kuchař;C. Jacobi;C. Meek;D. Janches;Guiping Liu;M. Tsutsumi;N. Gulbrandsen;S. Nozawa;M. Lester;E. Belova;J. Kero;N. Mitchell
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作者：
G. Stober;A. Liu;A. Kozlovsky;Z. Qiao;A. Kuchař;C. Jacobi;C. Meek;D. Janches;Guiping Liu;M. Tsutsumi;N. Gulbrandsen;S. Nozawa;M. Lester;E. Belova;J. Kero;N. Mitchell
抽象的。流星雷达已成为研究大气动力学的广泛使用的仪器，特别是在70至110公里高度地区。这些系统已被证明能够可靠和连续地测量中间层和低热层的水平风。最近，已经有许多尝试利用镜面反射和/或横向散射流星测量来估计垂直风和垂直风变率。在这项研究中，我们研究了垂直风速估计中潜在的偏差，这些偏差是流星雷达观测几何和散射机制所固有的，我们引入了一个数学去偏过程来缓解这些偏差。该过程使用了基于广义Tikhonov正则化的时空拉普拉斯滤波器。将该算法得到的垂直风场与UA-ICON模式数据进行了比较。这一比较表明，垂直速度分布的统计矩很好地吻合。此外，我们提出了前向散射风偏差的第一个观测指标。这似乎是由于当流星等离子体柱随风漂移时，散射中心沿流星轨迹的明显运动造成的。这一假设通过两个流星雨的辐射映射得到了验证。最后，我们介绍了一种新的反演算法，它提供了一个物理和数学上合理的解决方案，可以从北欧流星雷达群(北欧)和智利流星雷达观测网(秃鹰)等多基地流星雷达网中提取垂直风和风变率。新的反演被称为3DVAR+DIV，并包括其他诊断信息，如水平散度和相对涡度，以确保空间分辨区域中所有3D风的物理一致解。基于这一新算法，我们在2年的时间尺度和空间分辨率上得到了大部分分析数据在w=±1-2m S−1范围内的垂直速度，这与大气环流模式(GCMS)的结果是一致的。
Abstract. Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 km altitude region. These systems have been proven to provide reliable and continuous measurements of horizontal winds in the mesosphere and lower thermosphere. Recently, there have been many attempts to utilize specular and/or transverse scatter meteor measurements to estimate vertical winds and vertical wind variability. In this study we investigate potential biases in vertical wind estimation that are intrinsic to the meteor radar observation geometry and scattering mechanism, and we introduce a mathematical debiasing process to mitigate them. This process makes use of a spatiotemporal Laplace filter, which is based on a generalized Tikhonov regularization. Vertical winds obtained from this retrieval algorithm are compared to UA-ICON model data. This comparison reveals good agreement in the statistical moments of the vertical velocity distributions. Furthermore, we present the first observational indications of a forward scatter wind bias. It appears to be caused by the scattering center's apparent motion along the meteor trajectory when the meteoric plasma column is drifted by the wind. The hypothesis is tested by a radiant mapping of two meteor showers. Finally, we introduce a new retrieval algorithm providing a physically and mathematically sound solution to derive vertical winds and wind variability from multistatic meteor radar networks such as the Nordic Meteor Radar Cluster (NORDIC) and the Chilean Observation Network De meteOr Radars (CONDOR). The new retrieval is called 3DVAR+DIV and includes additional diagnostics such as the horizontal divergence and relative vorticity to ensure a physically consistent solution for all 3D winds in spatially resolved domains. Based on this new algorithm we obtained vertical velocities in the range of w = ± 1–2 m s−1 for most of the analyzed data during 2 years of collection, which is consistent with the values reported from general circulation models (GCMs) for this timescale and spatial resolution.