Synergistic retrievals of ice in high clouds from elastic backscatter lidar, Ku-band radar and submillimeter wave radiometer observations

IF 1.9 4区 地球科学 Q2 ENGINEERING, OCEAN Journal of Atmospheric and Oceanic Technology Pub Date : 2024-01-05 DOI:10.1175/jtech-d-23-0028.1
Mircea Grecu, J. Yorks
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Abstract

In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and sub-millimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of Ice Water Content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments e.g. frequencies, sensitivities, etc. are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, out of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-Means clustering algorithm. In the second step, the IWC profile is estimated using an Ensemble Kalman Smoother (EKS) algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.
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从弹性后向散射激光雷达、Ku 波段雷达和亚毫米波辐射计观测中协同获取高云中的冰量
在本研究中,我们研究了弹性后向散射激光雷达、Ku 波段雷达和亚毫米波辐射计测量在从卫星观测数据中获取冰数据方面的协同作用。通过生成大量冰水含量(IWC)剖面数据集以及模拟激光雷达、雷达和辐射计观测数据,对协同作用进行了分析。仪器的特性(如频率、灵敏度等)是根据大气观测系统(AOS)任务仪器的预期特性设定的。采用暂缓验证方法来评估从三种仪器的各种观测组合中获取的 IWC 剖面图的准确性。具体来说,IWC 和相关观测数据被随机分成两个数据集,一个用于训练,另一个用于评估。训练数据集用于训练检索算法,而评估数据集用于评估检索性能。冰水含量剖面数据集来自云卫星反射率和 CALIOP 激光雷达观测数据。从计算的观测数据中检索冰水含量 IWC 剖面图分两步实现。第一步,从观测数据中估算出 18 个潜在类别中的一个类别,这些类别的特点是冰水含量的垂直分布各不相同。这 18 个类别是根据 k-Means 聚类算法预先确定的。第二步,使用集合卡尔曼平滑器(EKS)算法估算 IWC 剖面,该算法将估算出的类别作为先验信息。研究结果表明,激光雷达、雷达和辐射计观测数据的协同作用在 IWC 剖面的检索中非常重要。不过,应该指出的是,这种协同作用是在理想条件下发现的,要在实践中实现可能还需要更多的工作。与雷达观测数据相比,将激光雷达反向散射观测数据纳入检索过程对检索性能的影响更大。由于冰云对大气辐射过程有重大影响,这项工作与目前为减少气候分析和预测中的不确定性所做的努力有关。
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来源期刊
CiteScore
4.50
自引率
9.10%
发文量
135
审稿时长
3 months
期刊介绍: The Journal of Atmospheric and Oceanic Technology (JTECH) publishes research describing instrumentation and methods used in atmospheric and oceanic research, including remote sensing instruments; measurements, validation, and data analysis techniques from satellites, aircraft, balloons, and surface-based platforms; in situ instruments, measurements, and methods for data acquisition, analysis, and interpretation and assimilation in numerical models; and information systems and algorithms.
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