@article{Zwieback-2019-Improving,
title = "Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture",
author = "Zwieback, Simon and
Westermann, Sebastian and
Langer, Moritz and
Boike, Julia and
Marsh, Philip and
Berg, Aaron",
journal = "Water Resources Research, Volume 55, Issue 3",
volume = "55",
number = "3",
year = "2019",
publisher = "American Geophysical Union (AGU)",
url = "https://gwf-uwaterloo.github.io/gwf-publications/G19-195001",
doi = "10.1029/2018wr023247",
pages = "1814--1832",
abstract = "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 ({\textgreater}10 cm) 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.",
}
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<abstract>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 (\textgreater10 cm) 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.</abstract>
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%0 Journal Article
%T Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture
%A Zwieback, Simon
%A Westermann, Sebastian
%A Langer, Moritz
%A Boike, Julia
%A Marsh, Philip
%A Berg, Aaron
%J Water Resources Research, Volume 55, Issue 3
%D 2019
%V 55
%N 3
%I American Geophysical Union (AGU)
%F Zwieback-2019-Improving
%X 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 (\textgreater10 cm) 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.
%R 10.1029/2018wr023247
%U https://gwf-uwaterloo.github.io/gwf-publications/G19-195001
%U https://doi.org/10.1029/2018wr023247
%P 1814-1832
Markdown (Informal)
[Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture](https://gwf-uwaterloo.github.io/gwf-publications/G19-195001) (Zwieback et al., GWF 2019)
ACL
- Simon Zwieback, Sebastian Westermann, Moritz Langer, Julia Boike, Philip Marsh, and Aaron Berg. 2019. Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture. Water Resources Research, Volume 55, Issue 3, 55(3):1814–1832.
