基于微脉冲差分吸收激光雷达的距离分辨热力学廓线全球估计
Global Estimation of Range Resolved Thermodynamic Profiles from MicroPulse Differential Absorption Lidar
AI总结：
本文提出一种完全自包含的微脉冲差分吸收激光雷达热力学廓线估计方法，结合泊松全变分正则化最大似然估计，实现温度、绝对湿度和后向散射比的自洽反演，将温度反演误差降至3 km以下小于2 K并扩展到5 km。
摘要：
我们展示了利用MicroPulse DIAL获取的数据进行热力学廓线估计，使得反演过程完全自包含。唯一的外部输入是安装在仪器上的气象站获得的地表气象变量。该估计器提供温度、绝对湿度和后向散射比的产品，使得激光雷达数据产品与原始观测之间的交叉依赖关系得到考虑，最终产品自洽。本文所述方法应用于一个组合式氧气DIAL、钾HSRL和水汽DIAL系统，该系统工作在两对波长（标称中心为770 nm和828 nm）。我们通过泊松全变分技术进行正则化最大似然估计，以抑制噪声并提高观测距离。与119个无线电探空仪的对比表明，这种新的处理方法改善了温度反演，将3 km高度以下的总误差降低到小于2 K，并将温度反演的最大高度扩展到5 km，误差小于3 K。这项工作的结果明确证明了通过氧气DIAL技术测量温度的潜力，并且进一步表明这可以通过低功率半导体基激光雷达传感器实现。
英文摘要：
We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse DIAL such that the retrieval is entirely self contained. The only external input is surface meteorological variables obtained from a weather station installed on the instrument. The estimator provides products of temperature, absolute humidity and backscatter ratio such that cross dependencies between the lidar data products and raw observations are accounted for and the final products are self consistent. The method described here is applied to a combined oxygen DIAL, potassium HSRL, water vapor DIAL system operating at two pairs of wavelengths (nominally centered at 770 and 828 nm). We perform regularized maximum likelihood estimation through the Poisson Total Variation technique to suppress noise and improve the range of the observations. A comparison to 119 radiosondes indicates that this new processing method produces improved temperature retrievals, reducing total errors to less than 2 K below 3 km altitude and extending the maximum altitude of temperature retrievals to 5 km with less than 3 K error. The results of this work definitively demonstrates the potential for measuring temperature through the oxygen DIAL technique and furthermore that this can be accomplished with low-power semiconductor-based lidar sensors.
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