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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 30 Jun 2020

Submitted as: model evaluation paper | 30 Jun 2020

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This preprint is currently under review for the journal GMD.

Assessing the simulated soil thermal regime from Noah-MPLSM v1.1 for near-surface permafrost modeling on the Qinghai-Tibet Plateau

Xiangfei Li1,2, Tonghua Wu1, Xiaodong Wu1, Xiaofan Zhu1, Guojie Hu1, Ren Li1, Yongping Qiao1, Cheng Yang1,2, Junming Hao1,2, Jie Ni1,2, and Wensi Ma1,2 Xiangfei Li et al.
  • 1Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of CryosphericScience, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China

Abstract. Land surface models (LSMs) are effective tools for near-surface permafrost modeling. Extensive and rigorous model inter-comparison is of great importance before application due to the uncertainties in current LSMs. This study designed an ensemble of 6912 experiments to evaluate the Noah land surface model with multi-parameterization (Noah-MP) for soil temperature (ST) simulation, and investigate the sensitivity of parameterization schemes at a typical permafrost site on the Qinghai-Tibet Plateau. The results showed that Noah-MP generally underestimates ST, especially that during the cold season. In addition, the simulation uncertainty is greater in the cold season (October-April) and for the deep soil layers. ST is most sensitive to surface layer drag coefficient (SFC) while largely influenced by runoff and groundwater (RUN). By contrast, the influence of canopy stomatal resistance (CRS) and soil moisture factor for stomatal resistance (BTR) on ST is negligible. With limited impacts on ST simulation, vegetation model (VEG), canopy gap for radiation transfer (RAD) and snow/soil temperature time scheme (STC) are more influential on shallow ST, while super-cooled liquid water (FRZ), frozen soil permeability (INF) and lower boundary of soil temperature (TBOT) have greater impacts on deep ST. Furthermore, an optimal configuration of Noah-MP for permafrost modeling were extracted based on the connectivity between schemes, and they are: table leaf area index with calculated vegetation fraction, Jarvis scheme for CRS, Noah scheme for BTR, BATS model for RUN, Chen97 for SFC, zero canopy gap for RAD, variant freezing-point depression for FRZ, hydraulic parameters defined by soil moisture for INF, ST at 8 m for TBOT, and semi-implicit method for STC. The analysis of the model structural uncertainties and characteristics of each scheme would be constructive to a better understanding of the land surface processes on the QTP and further model improvements towards near-surface permafrost modeling using the LSMs.

Xiangfei Li et al.

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Xiangfei Li et al.

Data sets

Forcings and results of Noah-MP ensemble simulation at TGL station X. Li

Xiangfei Li et al.


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Latest update: 22 Sep 2020
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Short summary
This paper conducted an ensemble simulation of 6912 scheme combinations at a typical permafrost site on the QTP. The general performance of Noah-MP for soil temperature is assessed and the sensitivities of parameterization schemes at different depth were investigated. Then, we further explored the interactions between the most influential schemes and configured an optimal combination based on the connections between schemes.
This paper conducted an ensemble simulation of 6912 scheme combinations at a typical permafrost...