Sensitivity Evaluation of Snow Simulation to Multi-parameterization Schemes in the Noah-MP Model
Received date: 2018-11-16
Revised date: 2019-01-22
Online published: 2019-05-27
Supported by
Project supported by the National Natural Science Foundation of China “Study of snow data assimilation based on machine leaning and multi-scale ensemble Kalman Filter” (No. 41671375) and “Study of snow data assimilation based on Bayesian Model averaging and genetic particle filter”(No. 41871251)
On account of the latest community Noah land surface model with multi-parameterization (Noah-MP) schemes and its uncertainty breadth in simulation results being difficult to be determined, this study assessed the sensitivity of snow to physics options using meteorological data from the Altay Station in northern Xinjiang. The Noah-MP physics ensemble simulation with the total number of 13 824 was designed without the consideration of the uncertainties of forcing data and parameters. The natural selection approach was used to analyze the sensitivity of physical processes. Based on the results of sensitivity analysis, the uncertainty of ensemble simulation results was further discussed. The results showed that snow was sensitive to the physical processes of surface-layer exchange coefficient, partitioning precipitation into rainfall and snowfall, lower boundary condition of soil temperature, and first-layer snow or soil temperature time scheme; Uncertainties in multi-parameterization ensemble simulation experiments were mainly from sensitive physical processes under the condition of disregarding uncertainties of forcing data and parameters. After removing the parameterization schemes that notably reduced simulation performance in sensitive physical processes, the uncertainty breadth in ensemble simulations decreased significantly. Finally, an optimal combination group of parameterization schemes for this station was configured.
Yuanhong You , Chunlin Huang , Ying Zhang , Jinliang Hou . Sensitivity Evaluation of Snow Simulation to Multi-parameterization Schemes in the Noah-MP Model[J]. Advances in Earth Science, 2019 , 34(4) : 356 -365 . DOI: 10.11867/j.issn.1001-8166.2019.04.0356
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