Planetary boundary layer height (PBLH) over the SGP

PBLH is a critical parameter influencing weather phenomena, air quality, and various meteorological processes. However, accurately retrieving PBLH has been a challenging task due to limitations such as coarse temporal resolution and measurement drift in traditional radiosonde observations. To address these limitations, we have devised a lidar-based methodology that capitalizes on a newly developed algorithm for PBLH retrieval. This algorithm demonstrates enhanced capabilities in capturing diurnal fluctuations in PBLH compared to existing lidar-based methods (Su et al., 2020). In addition, we have refined this algorithm specifically for PBLH retrieval under cloudy conditions through a novel scheme (Su et al., 2022). To ensure data reliability, a quality-control process has been implemented to filter out questionable data points. Accompanying the dataset is a quality-control flag for ease of reference. It should be noted that we have assimilated all available radiosonde observations to provide a more robust estimate of PBLH, making the dataset valuable for a variety of related studies. Data for PBLH are collected between 07:00 and 19:00 Local Time and are expressed in meters. In the dataset, a Quality Control (QC) value of 0 signifies valid data. A QC value of -2 denotes data that are "Not a Number" (NaN), indicating missing or non-applicable information. A QC value of 2 flags problematic data that may require further scrutiny.

行星边界层高度（Planetary Boundary Layer Height, PBLH）是影响天气现象、空气质量与各类气象过程的关键参数。然而，传统无线电探空观测存在时间分辨率粗糙、测量漂移等局限，使得精准反演PBLH始终是一项挑战性任务。为破解上述局限，我们研发了一种基于激光雷达（lidar）的反演方法，该方法依托全新开发的PBLH反演算法。相较于现有基于激光雷达的反演方法（Su等，2020），此算法可更精准地捕捉PBLH的日变化波动。此外，我们通过全新方案针对多云场景下的PBLH反演对该算法进行了针对性优化（Su等，2022）。为保障数据可靠性，本数据集已实施质控流程以剔除存疑数据点，并附带质控标记以供便捷参考。需说明的是，我们整合了所有可用的无线电探空观测数据，以提供更稳健的PBLH估算结果，令本数据集可广泛服务于各类相关研究。本数据集的PBLH数据采集于当地时间07:00至19:00，单位为米。数据集中的质控（Quality Control, QC）值为0时代表有效数据；QC值为-2表示数据为"非数值（Not a Number, NaN）"，即缺失或不适用的信息；QC值为2则标记为存在问题的数据，需进一步核查。