A soil temperature dataset based on random forest in the Three River Source Region
Abstract Changes in soil temperature (ST) in the Three River Source Region (TRSR) significantly influence regional climate, ecology, and hydrological processes. However, existing models and reanalysis data exhibit considerable deviations in ST due to limitations in physical processes and parameteriz...
Saved in:
| Main Authors: | Xiaoqing Tan, Siqiong Luo, Hongmei Li, Zhuoqun Li, Qingxue Dong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04910-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Trend Analysis of High-Resolution Soil Moisture Data Based on GAN in the Three-River-Source Region During the 21st Century
by: Zhuoqun Li, et al.
Published: (2024-11-01) -
Variations of soil thermal conductivity in the Three-River Source Region, Qinghai‒Xizang Plateau
by: Jia Liu, et al.
Published: (2025-06-01) -
SMRFR: A global multilayer soil moisture dataset generated using Random Forest from multi-source data
by: Yuhan Liu, et al.
Published: (2025-07-01) -
Simulation of Land Surface Temperature in Northern China by Three Soil Thermal Conductivity Models
by: Yulong REN, et al.
Published: (2022-10-01) -
Climatological Evaluation of Three Assimilation and Reanalysis Datasets on Soil Moisture over the Tibetan Plateau
by: Yinghan Sang, et al.
Published: (2024-11-01)