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DOI10.3390/rs15020455
Spatiotemporal Variations of Soil Temperature at 10 and 50 cm Depths in Permafrost Regions along the Qinghai-Tibet Engineering Corridor
Jiao, Mengdi; Zhao, Lin; Wang, Chong; Hu, Guojie; Li, Yan; Zhao, Jianting; Zou, Defu; Xing, Zanpin; Qiao, Yongping; Liu, Guangyue; Du, Erji; Xiao, Minxuan; Hou, Yingxu
发表日期2023
EISSN2072-4292
卷号15期号:2
英文摘要Soil temperature plays an essential role in the permafrost thermal state and degradation process. Especially the soil temperatures at 10 cm and 50 cm depths in the active layer, which are much easier to be observed in situ, have great effects on the surface water cycles and vegetation, and could be used as the upper boundary for permafrost models to simulate the thermal state of the permafrost and active layer thicknesses. However, due to the limitations of the observation data, there are still large uncertainties in the soil temperature data, including at these two depths, in the permafrost region of Qinghai-Tibet Plateau (QTP). In this study, we evaluated and calibrated the applicability of four daily shallow soil temperature datasets (i.e., MERRA-2, GLDAS-Noah, ERA5-Land, and CFSR) by using the in situ soil temperature data from eight observation sites from 2004 to 2018 in the permafrost region along the Qinghai-Tibet Engineering Corridor. The results revealed that there were different uncertainties for all four sets of reanalysis data, which were the largest (Bias = -2.44 degrees C) in CFSR and smallest (Bias= -0.43 degrees C) in GLDAS-Noah at depths of 10 cm and 50 cm. Overall, the reanalysis datasets reflect the trends of soil temperature, and the applicability of reanalysis data at 50 cm depth is better than at 10 cm depth. Furthermore, the GLDAS-Noah soil temperatures were recalibrated based on our observations using multiple linear regression and random forest models. The accuracy of the corrected daily soil temperature was significantly improved, and the RMSE was reduced by 1.49 degrees C and 1.28 degrees C at the depth of 10 cm and 50 cm, respectively. The random forest model performed better in the calibration of soil temperature data from GLDAS-Noah. Finally, the warming rates of soil temperature were analyzed, which were 0.0994 degrees C/a and 0.1005 degrees C/a at 10 cm and 50 cm depth from 2004 to 2018, respectively.
关键词Qinghai-Tibet corridorreanalysis datasoil temperaturedata correctionwarming rate
英文关键词PLATEAU; REANALYSIS; VEGETATION; DATASET; MOISTURE; CLIMATE
WOS研究方向Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000927091700001
来源期刊REMOTE SENSING
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/282773
作者单位Nanjing University of Information Science & Technology; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Jiao, Mengdi,Zhao, Lin,Wang, Chong,et al. Spatiotemporal Variations of Soil Temperature at 10 and 50 cm Depths in Permafrost Regions along the Qinghai-Tibet Engineering Corridor[J],2023,15(2).
APA Jiao, Mengdi.,Zhao, Lin.,Wang, Chong.,Hu, Guojie.,Li, Yan.,...&Hou, Yingxu.(2023).Spatiotemporal Variations of Soil Temperature at 10 and 50 cm Depths in Permafrost Regions along the Qinghai-Tibet Engineering Corridor.REMOTE SENSING,15(2).
MLA Jiao, Mengdi,et al."Spatiotemporal Variations of Soil Temperature at 10 and 50 cm Depths in Permafrost Regions along the Qinghai-Tibet Engineering Corridor".REMOTE SENSING 15.2(2023).
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