Global Soil Moisture Dataset From a Multitask Model (GSM3)

Description GSM3 (Global Soil Moisture from a Multitask Model, v1.0) is a daily, 9 km global soil moisture dataset spanning 2015–2020. It was generated using a multitask deep learning model that simultaneously learns from multiple soil moisture networks worldwide, enabling robust generalization across diverse climatic and land cover conditions. The dataset and methodology are described in detail in the companion paper below. If you use this dataset, please cite the paper: Liu, J., Hughes, D., Rahmani, F., Lawson, K., and Shen, C.: Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats, Geoscientific Model Development, 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, 2023. Interactive Viewer Explore the dataset in your browser (no download required): https://jayhydro.github.io/gsm3-viewer/ Data Specification Shortname: GSM3Longname: Global Soil Moisture Dataset From a Multitask ModelVersion: 1.0Format: GeoTIFFSpatial Coverage: GlobalTemporal Coverage: 2015-01-01 to 2020-12-31File Size: ~10.3 MB per fileData ResolutionSpatial: 9-kmTemporal: DailyCoordinate Reference System (CRS): EPSG:6933 - WGS 84 / NSIDC EASE-Grid 2.0 Global