This dataset is based on the system physics field of the Global Land Data Assimilation System Version 2 (GLDAS-2) and is calculated using the Noah land surface model. The dataset considers different physical water energy processes, especially snow processes. The evaluation indicates that the dataset is capable of investigating different types of drought at different time scales. The evaluation also indicates that the dataset has sufficient performance to capture drought at different spatial scales. The consideration of snow processes has improved the ability of SZIsnow, and the improvement is significant in snow covered areas such as the Arctic and high-altitude areas such as the Qinghai Tibet Plateau. In addition, the analysis also indicates that the SZIsnow dataset can effectively capture large-scale drought events worldwide. This dataset has high potential for application in drought monitoring, assessment, and information provision, and can also serve as a valuable resource for drought research.
Using numerical models of hydro meteorological variables as source data for calculating drought indices.
Based on the Global Land Data Assimilation System Version 2 (GLDAS-2), the system physical field is calculated using the Noah land surface model.
The data quality is good.
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CSTR:11738.11.NCDC.ZENODO.DB6670.2024
10.12072/ncdc.zenodo.db6670.2024