Sensitivity Evaluation of Snow Simulation to Multi-parameterization Schemes in the Noah-MP Model

  • Yuanhong You ,
  • Chunlin Huang ,
  • Ying Zhang ,
  • Jinliang Hou
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  • 1. Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
    2. Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
You Yuanhong(1990-), male, Susong County, Anhui Province, Ph.D student. Research areas include land surface simulation and data assimilation. E-mail:youyuanhong@lzb.ac.cn|You Yuanhong(1990-), male, Susong County, Anhui Province, Ph.D student. Research areas include land surface simulation and data assimilation. E-mail:youyuanhong@lzb.ac.cn

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)

Abstract

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.

Cite this article

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

References

1 Walsh J E , Jasperson W H , Ross B . Influence of snow cover and soil moisture on monthly air temperature [J]. Monthly Weather Review, 1985, 113(5): 756-768.
2 Baenett T P , Dumenil L , Schlese U , et al . The effect of Eurasian snow cover on regional and global climate variations [J]. Journal of the Atmospheric Sciences, 1989, 46(5): 661-685.
3 Vernekar A D , Zhou J , Shukla J . The effect of Eurasian snow cover on the Indian monsoon [J]. Journal of Climate, 1995, 8(2): 248-266.
4 Xiao Xiongxin , Zhang Tingjun . Passive microwave remote sensing of snow depth and snow water equivalent: Overview [J]. Advances in Earth Science, 2018, 33(6): 590-605.
4 肖雄新,张廷军 . 基于被动微波遥感的积雪深度和雪水当量反演研究进展[J]. 地球科学进展,2018,33(6):590-605.
5 Wang Jian , Che Tao , Li Zhen , et al . Investigation on snow characteristics and their distribution in China [J]. Advances in Earth Science, 2018, 33(1): 12-26.
5 王建,车涛,李震,等 . 中国积雪特性及分布调查[J]. 地球科学进展,2018,33(1):12-26.
6 Verbunt M , Gurtz J , Jasper K , et al . The hydrological role of snow and glaciers in alpine river basins and their distributed modeling [J]. Journal of Hydrology, 2003, 282(14): 36-55.
7 Parrish M A , Moradkhani H , DeChant C M . Toward reduction of model uncertainty: Integration of Bayesian model averaging and data assimilation [J]. Water Resources Research, 2012, 48: W03519.
8 Zhang G , Chen F , Gan Y J . Assessing uncertainties in the Noah-MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign [J]. Journal of Geophysical Research Atmospheres, 2016, 121(16): 9 576-9 596.
9 Yang Z L , Niu G Y , Mitchell K E . The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over globalriver basins [J]. Journal of Geophysical Research Atmospheres, 2011, 116: D12110.
10 Gao Y H , Li K , Chen F , et al . Assessing and improving Noah-MP land model simulations for the central Tibetan Plateau [J]. Journal of Geophysical Research Atmospheres, 2015, 120(18): 9 258-9 278.
11 Cai X T , Yang Z L , David C H , et al . Hydrological evaluation of the Noah-MP land surface model for the Mississippi River Basin[J]. Journal of Geophysical Research—Atmospheres, 2014, 119(1): 23-38.
12 Niu G Y , Yang Z L , Mitchell E , et al . The community Noah land surface model with multi-parameterization options (Noah-MP):1. Model description andevaluation with local-scale measurements [J]. Journal of Geophysical Research Atmospheres, 2011, 116(D12). DOI:10.1029/2010JD015140.
13 Zheng D H , Van Der Velde R , Su Z B , et al . Assessment of Noah land surface model with various runoff parameterizations over a Tibetan river [J]. Journal of Geophysical Research Atmospheres, 2017, 122(3): 1 488-1 504.
14 Fang Y H , Zhang X N , Niu G Y , et al . Study of the spatiotemporal characteristics of meltwater contribution to the total runoff in the Upper Changjiang River Basin [J]. Water, 2017, 9(3): 165.
15 Ma Yuan , Li Hongyi , Zhang Pu , et al . The improvement of using gamma-ray detect snow water equivalent [J]. Remote Sensing Technology and Application, 2017, 32(1): 57-63.
15 马媛,李弘毅,张璞,等 .利用伽马射线探测雪水当量方法的改进[J]. 遥感技术与应用, 2017, 32(1): 57-63.
16 Chen F , Mitchell K , Schaake J , et al . Modeling of land-surface evaporation by four schemes and comparison with FIFE observations [J]. Journal of Geophysical Research—Atmospheres, 1996, 101(D3): 7 251-7 268.
17 Chen F , Janjic Z , Mitchell K . Impact of atmospheric surface layer parameterization in the new land-surface scheme of the NCEP mesoscale Eta numerical model [J]. Boundary-Layer Meteorology, 1997, 85(3): 391-421.
18 Chen F , Dudhia J . Coupling an advanced land surface hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity [J]. Monthly Weather Review, 2001, 129(4): 569-585.
19 Ek M B , Mitchell K E , Lin Y , et al . Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model [J]. Journal of Geophysical Research Atmospheres, 2003, 108(D22): 1-16.
20 Niu G Y , Yang Z L , Dickinson R E , et al . Development of a simple groundwater model for use in climate models and evaluation with gravity recovery and climate experiment data [J]. Journal of Geophysical Research Atmospheres, 2007, 112: D07103.
21 Dickinson R E , Shaikh M , Bryant R , et al . Interactive canopies for a climate model [J]. Journal of Climate, 1998, 11(11): 2 823-2 836.
22 Shangguan W , Dai Y J , Liu B Y , et al . A soil particle-size distribution dataset for regional land and climate modelling in China [J]. Geoderma, 2012, 171: 85-91.
23 Chen F , Barlage M , Tewari M , et al . Modeling seasonal snowpack evolution in the complex terrain and forested Colorado Headwaters region: A modelinter-comparison study [J]. Journal of Geophysical Research Atmospheres, 2014, 119(24): 13 795-13 819.
24 Xia Y L , Sheffield J , Ek M B , et al . Evaluation of multi-model simulated soil moisture in NLDAS-2 [J]. Journal of Hydrology, 2014, 512: 107-125.
25 Hong S , Yu X , Park S K , et al . Assessing optimal set of implemented physical parameterization schemes in a multi-physics land surface model using genetic algorithm [J]. Geoscientific Model Development, 2014, 7: 2 517-2 529.
26 Niu G Y , Yang Z L . Effects of frozen soil on snowmelt runoff and soil water storage at a continental scale [J]. Journal of Hydrometeorology, 2006, 7(5): 937-952.
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