paper
2018
Climate analysis & attribution
Evaluation or intercomparison of existing models
Classical ML (trees, GP, linear, kernels) Preprint
2018-04-01
008
Apr 2018
Shoji Hashimoto, Kazuki Nanko, Boris Ťupek et al.
Jukuri (Natural Resources Institute Finland (Luke))
Boosted regression trees identify drivers of global soil organic carbon in observations and CMIP5 Earth system models, revealing key mismatches such as clay content and temperature.
Climate analysis & attribution
Data-mining analysis of the global distribution of soil carbon in observational databases and Earth system models
In one sentence. Boosted regression trees identify drivers of global soil organic carbon in observations and CMIP5 Earth system models, revealing key mismatches such as clay content and temperature.
Labels
- Topic
- Climate analysis & attribution
- Type
- Evaluation or intercomparison of existing models
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Global
- Data
- CMIP / climate model output, Other
- Status
- Research
- Identifiers
- OpenAlex:W3116551537
- Added
- 2026-10-22
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