التفاصيل البيبلوغرافية
| العنوان: |
HiMIC-Monthly: A 1 km high-resolution atmospheric moisture index collection over China, 2003–2020 |
| المؤلفون: |
Hui Zhang, Ming Luo, Wenfeng Zhan, Yongquan Zhao, Yuanjian Yang, Erjia Ge, Guicai Ning, Jing Cong |
| المصدر: |
Scientific Data, Vol 11, Iss 1, Pp 1-14 (2024) |
| بيانات النشر: |
Nature Portfolio, 2024. |
| سنة النشر: |
2024 |
| المجموعة: |
LCC:Science |
| مصطلحات موضوعية: |
Science |
| الوصف: |
Abstract Near-surface atmospheric moisture is a key environmental and hydro-climatic variable that has significant implications for the natural and human systems. However, high-resolution moisture data are severely lacking for fine-scale studies. Here, we develop the first 1 km high spatial resolution dataset of monthly moisture index collection in China (HiMIC-Monthly) over a long period of 2003~2020. HiMIC-Monthly is generated by the light gradient boosting machine algorithm (LightGBM) based on observations at 2,419 weather stations and multiple covariates, including land surface temperature, vapor pressure, land cover, impervious surface proportion, population density, and topography. This collection includes six commonly used moisture indices, enabling fine-scale assessment of moisture conditions from different perspectives. Results show that the HiMIC-Monthly dataset has a good performance, with R2 values for all six moisture indices exceeding 0.96 and root mean square error and mean absolute error values within a reasonable range. The dataset exhibits high consistency with in situ observations over various spatial and temporal regimes, demonstrating broad applicability and strong reliability. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2052-4463 |
| Relation: |
https://doaj.org/toc/2052-4463 |
| DOI: |
10.1038/s41597-024-03230-2 |
| URL الوصول: |
https://doaj.org/article/d65644132bbf4a3e86b466e3178be1e4 |
| رقم الانضمام: |
edsdoj.65644132bbf4a3e86b466e3178be1e4 |
| قاعدة البيانات: |
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