GSTDTAP  > 资源环境科学
DOI10.1029/2018WR023247
Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture
Zwieback, S.1; Westermann, S.2; Langer, M.3,4; Boike, J.3,4; Marsh, P.5; Berg, A.1
2019-03-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2019
卷号55期号:3页码:1814-1832
文章类型Article
语种英语
国家Canada; Norway; Germany
英文摘要

Knowledge of soil moisture conditions is important for modeling soil temperatures, as soil moisture influences the thermal dynamics in multiple ways. However, in permafrost regions, soil moisture is highly heterogeneous and difficult to model. Satellite soil moisture data may fill this gap, but the degree to which they can improve permafrost modeling is unknown. To explore their added value for modeling soil temperatures, we assimilate fine-scale satellite surface soil moisture into the CryoGrid-3 permafrost model, which accounts for the soil moisture's influence on the soil thermal properties and the surface energy balance. At our study site in the Canadian Arctic, the assimilation improves the estimates of deeper (>10cm) soil temperatures during summer but not consistently those of the near-surface temperatures. The improvements in the deeper temperatures are strongly contingent on soil type: They are largest for porous organic soils (30%), smaller for thin organic soil covers (20%), and they essentially vanish for mineral soils (only synthetic data available). That the improvements are greatest over organic soils reflects the strong coupling between soil moisture and deeper temperatures. The coupling arises largely from the diminishing soil thermal conductivity with increasing desiccation thanks to which the deeper soil is kept cool. It is this association of dry organic soils being cool at depth that lets the assimilation revise the simulated soil temperatures toward the actually measured ones. In the future, the increasing availability of satellite soil moisture data holds promise for the operational monitoring of soil temperatures, hydrology, and biogeochemistry.


Plain Language Summary We explore whether soil moisture data improve the accuracy with which we can predict the soil temperature profile in cold regions. Knowledge of the temperature conditions is important for monitoring the stability of the terrain, for understanding the response of vegetation and microorganisms, and many other applications. Soil moisture data may be useful in this context because soil moisture influences the thermal dynamics of the soil, but so far, such data have been in short supply. Using novel satellite soil moisture data, we show that soil moisture information does indeed help to improve the estimates of deeper temperatures, at least in organic soils. In the future, the increasing availability of satellite soil moisture data holds promise for the operational monitoring of soil temperatures, hydrology, and biogeochemistry.


英文关键词permafrost soil temperature soil moisture data assimilation remote sensing
领域资源环境
收录类别SCI-E
WOS记录号WOS:000464660000004
WOS关键词LAND-SURFACE MODEL ; THERMAL DYNAMICS ; SATELLITE DATA ; WATER-BALANCE ; TUNDRA ; TEMPERATURES ; SITE ; FLUX ; REPRESENTATION ; WETLAND
WOS类目Environmental Sciences ; Limnology ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/181553
专题资源环境科学
作者单位1.Univ Guelph, Dept Geog, Guelph, ON, Canada;
2.Univ Oslo, Dept Geosci, Oslo, Norway;
3.Ctr Polar & Marine Res, Alfred Wegener Inst Helmholtz, Periglacial Res, Potsdam, Germany;
4.Humboldt Univ, Geog Dept, Berlin, Germany;
5.Wilfrid Laurier Univ, Dept Geog, Waterloo, ON, Canada
推荐引用方式
GB/T 7714
Zwieback, S.,Westermann, S.,Langer, M.,et al. Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture[J]. WATER RESOURCES RESEARCH,2019,55(3):1814-1832.
APA Zwieback, S.,Westermann, S.,Langer, M.,Boike, J.,Marsh, P.,&Berg, A..(2019).Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture.WATER RESOURCES RESEARCH,55(3),1814-1832.
MLA Zwieback, S.,et al."Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture".WATER RESOURCES RESEARCH 55.3(2019):1814-1832.
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