The functioning and vulnerability of permafrost are largely determined by near-surface ground ice content. However, high-quality, grid-based ground ice maps for the Northern Hemisphere are currently unavailable. This study presents the first 1-km resolution grid-based ground ice map within 5 m below the permafrost table across the Northern Hemisphere. The map integrates an unprecedentedly amount (1,178 boreholes) of field measurement for volumetric ice content (VIC) and multisource geospatial data, especially paleoclimate, remote sensing data, surficial geology units, using Copula-Embedded Bayesian Model Averaging (COP-BMA) techniques with multiple machine learning models and 200 ensemble simulations. The validation indicates relatively low errors (R2=0.86, RMSE=7.08%VIC, bias=0.02%VIC), while the uncertainty, represented by the 95% prediction interval (PI), is 16.08% ± 3.55%VIC. The map indicates that the total ice storage of near‐surface permafrost across the Northern Hemisphere is approximately 54,600 km3 (47,800–62,300 km³), about twice the value from the International Permafrost Association map. This difference may be due to, but is not limited to, advancements in mapping techniques, the integration of additional measurement data, and improved spatial resolution. High VIC (>80%) is predominantly concentrated in low-lying plains, wetlands, and marshes. In contrast, mountainous regions, including the Qinghai-Xizang Plateau and Mongolian Plateau, exhibit lower VIC, typically ranging from 20% to 40%. The new ground ice map exhibits a spatial pattern that is largely consistent with previous maps while providing enhanced spatial detail. This high-resolution map serves as a benchmark for tracing permafrost changes and assessing impacts on climate, hydrology, ecosystems, and infrastructure in permafrost regions.
| collect place | Northern Hemisphere |
|---|---|
| data size | 1.5 GiB |
| data format | *.tif |
| Coordinate system | WGS84 |
This dataset compiles ground-ice survey data from 1,178 boreholes across the major permafrost regions of North America, Eurasia, and the Qinghai–Xizang Plateau. These records are primarily derived from published literature and geological investigation reports, and represent volumetric ice content within the 5 m interval below the permafrost table. The predictors systematically incorporates key environmental controls on ground-ice formation and preservation, including modern and paleoclimate variables, remote-sensing indicators, topographic factors, and geological and geomorphological information. The dataset is stored in GeoTIFF format, and the file is named T5m_VIC.tif, which represents the volumetric ice content within 5 m below the permafrost table.
This dataset integrates multi-source geospatial data, including paleoclimate and modern climate variables, remote-sensing data, topographic factors, and geological–geomorphological information. It further applies a Copula-embedded Bayesian model averaging (COP-BMA) approach to ensemble the predictions from four machine-learning models—support vector regression, generalized additive regression, random forest, and Light Gradient Boosting Machine (LightGBM)—thereby improving the stability and reliability of the simulation results.
The validation results indicate relatively low model errors (R² = 0.86, RMSE = 7.08% VIC, bias = 0.02% VIC), while the uncertainty derived from the 95% prediction interval (PI) is 16.08 ± 3.55% VIC.
| # | number | name | type |
| 1 | 42525105 | National Natural Science Foundation of China Youth Science Fund Project | |
| 2 | 25JRRA496 | Natural Science Foundation of Gansu Province |
This work is licensed under a
Creative
Commons Attribution 4.0 International License.
| # | title | file size |
|---|---|---|
| 1 | T5m_VIC |
| # | category | title | author | year |
|---|---|---|---|---|
| 1 | paper | Near-surface ground ice map of the Northern Hemisphere | Wang Bingquan, Ran Youhua, Li Xin | 2026 |
Cryosphere underground ice Qinghai Tibet Plateau Arctic machine learning
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