Considering the large simulation bias of the freezing-thawing process from land surface models, an comparative analysis of the freeze-thaw process parameterization schemes based on Noah-MP land surface model are carried out and the simulations of different freeze-thaw process parameterization schemes are verified by observation data. Results show that the Noah-MP land surface model can capture the characteristics of freezing-thawing process. The freeze-thaw process simulation is quite sensitive to the freeze-thaw parameterization scheme. From the freezing phase to the melting phase, the simulated values of the four experimental groups are significantly different. Before the freezing phase and after the melting phase, the simulated values of the four experimental groups are quite consistent.Compared with the super cooled liquid water parameterization scheme, the frozen soil permeability parameterization scheme is more sensitive to the simulation of soil temperature during freezing-thawing period. Different super cooled liquid water parameterization schemes can cause large differences in simulated soil moisture.The simulation of surface energy flux is quite sensitive to the freeze-thaw parameterization scheme.There are significant differences in the simulation values of the surface energy flux by four tests during freezing phase, freezing stability phase and melting phase.
Huolin LIU
,
Zeyong HU
,
Geng HAN
,
Changchun PEI
. Assessment of Freeze-thaw Process Simulation in Qinghai-Tibetan Plateau by Different Parameterization Schemes based on Noah-MP Land Surface Model[J]. Plateau Meteorology, 2020
, 39(1)
: 1
-14
.
DOI: 10.7522/j.issn.1000-0534.2019.00009
[1]Chen F, Mitchell K, Schaake J, al et, 1996. Modeling of land surface evaporation by four schemes and comparison with FIFE observations[J]. Journal of Geophysical Research: Atmospheres, 101(D3): 7251-7268. DOI: 10.1029/95JD02165.
[2]Cheng G, Wu T, 2007. Responses of permafrost to climate change and their environmental significance, Qinghai-Tibet Plateau[J]. Journal of Geophysical Research, 112: F02S03. DOI: 10.1029/2006JF000631.
[3]Flerchinger G N, Saxton K E, 1989. Simultaneous heat and water model of a freezing snow-residue-soil system I. Theory and development[J]. Transactions of the American Society of Agricultural Engineers, 32(2): 565-571.
[4]Jackson T, Schmugge J, Engman E, 1996. Remote sensing applications to hydrology: Soil moisture[J]. Hydrological Science, 41(4): 517-530.
[5]Jorgenson M, Racine C, Walters J, al et, 2001. Permafrost degradation and ecological changes associated with a warming climate in central Alaska[J]. Climatic Change, 48(4): 551-579.
[6]Koren V, Schaake J, Mitchell K, al et, 1999. A parameterization of snowpack and frozen ground intended for NCEP weather and climate models[J]. Journal of Geophysical Research: Atmospheres, 104D16):19569-19585.
[7]Li X, Jin R, Pan X, al et, 2012. Changes in the near-surface soil freeze-thaw cycle on the Qinghai-Tibetan Plateau[J]. International Journal of Applied Earth Observation and Geoinformation, 17: 33-42.
[8]Luo S, Lü S, Zhang Y, 2009. Development and validation of the frozen soil parameterization scheme in Common Land Model[J]. Cold Regions Science and Technology, 55(1): 130-140.
[9]Mahrt L, Pan H, 1984. A two-layer model of soil hydrology[J]. Boundary-Layer Meteorology, 29(1): 1-20.
[10]Niu G Y, Yang Z L, 2006. Effects of frozen soil on snowmelt runoff and soil water storage at a continental scale[J]. Journal of Hydrometeorology, 7(5): 937-952.
[11]Niu G Y, Yang Z L, Mitchell K E, al et, 2011. The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements[J]. Journal of Geophysical Research: Atmospheres, 116: D12109. DOI: 10.1029/2010JD015139.
[12]Wang G, Hu H, Li T, 2009. The influence of freeze-thaw cycles of active soil layer on surface runoff in a permafrost watershed[J]. Journal of Hydrology, 375(3/4): 438-449.
[13]Yang Z L, Niu G Y, Mitchell K E, al et, 2011. The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins[J]. Journal of Geophysical Research: Atmospheres, 116: D12110. DOI: 10.1029/2010JD015140.
[14]陈渤黎, 罗斯琼, 吕世华, 等, 2014. 陆面模式CLM对若尔盖站冻融期模拟性能的检验与对比[J]. 气候与环境研究, 19(5): 649-658.
[15]李燕, 闫加海, 张冬峰, 2018. 青藏高原冬春积雪异常和中国东部夏季降水关系的诊断与模拟[J]. 高原气象, 37(2): 317-324. DOI: 10.7522/j.issn.1000-0534.2017.00040.
[16]李震坤, 武炳义, 朱伟军, 等, 2011. CLM3.0模式中冻土过程参数化的改进及模拟试验[J]. 气候与环境研究, 16(2): 137-48.
[17]刘双, 谢正辉, 高骏强, 等, 2018. 高寒生态脆弱区冻土碳水循环对气候变化的响应—以甘南州为例[J]. 高原气象, 37(5): 1177-1187. DOI: 10.7522/j.issn.1000-0534.2018.00016.
[18]潘保田, 李吉均, 1996. 青藏高原: 全球气候变化的驱动机与放大器—Ⅲ. 青藏高原隆起对气候变化的影响[J]. 兰州大学学报(自然科学版), 32(1): 108-115.
[19]孙少波, 陈报章, 车涛, 等, 2017. 青藏高原季节性冻土湿度模拟及参数优化—以黑河上游为例[J]. 高原气象, 36(3): 643-656. DOI: 10.7522/j.issn.1000-0534.2016.00059.
[20]王奕丹, 胡泽勇, 孙根厚, 等, 2019. 高原季风特征及其与东亚夏季风关系的研究[J]. 高原气象, 38(3): 518-527. DOI: 10.7522/j.issn.1000-0534.2019.00025.
[21]吴青柏, 牛富俊, 2013. 青藏高原多年冻土变化与工程稳定性[J]. 科学通报, 58(2): 115-130.
[22]夏坤, 罗勇, 李伟平, 2011. 青藏高原东北部土壤冻融过程的数值模拟[J].科学通报, 56(22): 1828-1838.
[23]熊建胜, 张宇, 王少影, 等, 2014. CLM4.0土壤水分传输方案改进在青藏高原陆面过程模拟中的效应[J]. 高原气象, 33(2): 323-336. DOI: 10.7522/j.issn.1000-0534.2014.00012.
[24]杨梅学, 姚檀栋, Hirose N, 等, 2006. 青藏高原表层土壤的日冻融循环[J]. 科学通报, 51(16): 1974-1976.
[25]杨淑华, 吴通华, 李韧, 等, 2018. 青藏高原近地表土壤冻融状况的时空变化特征[J]. 高原气象, 37(1): 43-53. DOI: 10.7522/j.issn.1000-0534.2017.00043.
[26]姚闯, 吕世华, 王婷, 等, 2019. 黄河源区多、 少雪年土壤冻融特征分析[J]. 高原气象, 38(3): 474-483. DOI: 10.7522/j.issn.1000-0534.2018.00142.
