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| DOI | 10.5194/essd-16-1-2024 |
| A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS | |
| 发表日期 | 2024 |
| ISSN | 1866-3508 |
| EISSN | 1866-3516 |
| 起始页码 | 16 |
| 结束页码 | 1 |
| 卷号 | 16期号:1 |
| 英文摘要 | The planetary boundary layer (PBL) is the lowermost part of the troposphere that governs the exchange of momentum, mass and heat between surface and atmosphere. To date, the radiosonde measurements have been extensively used to estimate PBL height (PBLH); suffering from low spatial coverage and temporal resolution, the radiosonde data are incapable of providing a diurnal description of PBLH across the globe. To fill this data gap, this paper aims to produce a temporally continuous PBLH dataset during the course of a day over the global land by applying machine learning algorithms to integrate high-resolution radiosonde measurements, ERA5 reanalysis, and the Global Land Data Assimilation System (GLDAS) product. This dataset covers the period from 2011 to 2021 with a temporal resolution of 3 h and a horizontal resolution of 0.25 degrees x 0.25 degrees . The radiosonde dataset contains around 180 million profiles over 370 stations across the globe. The machine learning model was established by taking 18 parameters derived from ERA5 reanalysis and GLDAS as input variables, while the PBLH biases between radiosonde observations and ERA5 reanalysis were used as the learning targets. The input variables were presumably representative regarding the land properties, near-surface meteorological conditions, terrain elevations, lower tropospheric stabilities, and solar cycles. Once a state-of-the-art model had been trained, the model was then used to predict the PBLH bias at other grids across the globe with parameters acquired or derived from ERA5 and GLDAS. Eventually, the merged PBLH can be taken as the sum of the predicted PBLH bias and the PBLH retrieved from ERA5 reanalysis. Overall, this merged high-resolution PBLH dataset was globally consistent with the PBLH retrieved from radiosonde observations in terms of both magnitude and spatiotemporal variation, with a mean bias of as low as - 0.9 m. The dataset and related codes are publicly available at 10.5281/zenodo.6498004 (Guo et al., 2022), and are of significance for a multitude of scientific research endeavors and applications, including air quality, convection initiation, climate, and climate change, to name but a few. |
| 语种 | 英语 |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences |
| WOS类目 | Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences |
| WOS记录号 | WOS:001173377600001 |
| 来源期刊 | EARTH SYSTEM SCIENCE DATA
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/303996 |
| 作者单位 | China Meteorological Administration; Chinese Academy of Meteorological Sciences (CAMS); China University of Geosciences; East China Normal University; Huazhong Agricultural University; Tsinghua University; China Meteorological Administration; China University of Mining & Technology; China Meteorological Administration |
| 推荐引用方式 GB/T 7714 | . A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS[J],2024,16(1). |
| APA | (2024).A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS.EARTH SYSTEM SCIENCE DATA,16(1). |
| MLA | "A merged continental planetary boundary layer height dataset based on high-resolution radiosonde measurements, ERA5 reanalysis, and GLDAS".EARTH SYSTEM SCIENCE DATA 16.1(2024). |
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