scholarly journals Novel coupled permafrost-forest model revealing the interplay between permafrost, vegetation, and climate across eastern Siberia

2021 ◽  
Author(s):  
Stefan Kruse ◽  
Simone M. Stuenzi ◽  
Julia Boike ◽  
Moritz Langer ◽  
Josias Gloy ◽  
...  
Keyword(s):  
Global Warming ◽  
Boreal Forest ◽  
Active Layer ◽  
Land Surface ◽  
Coupled Model ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Forest Species ◽  
Forest Model ◽  
Larch Species

Abstract. Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost-vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active-layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics, and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost-multilayer forest land-surface model (CryoGrid), with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. Following parametrization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions, covering a gradient of summergreen forests in the east at Spasskaya Pad to mixed summergreen-evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the south-east of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active-layer thickness (ALT) and soil moisture and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of central Siberia reproducing vegetation patterns making it an excellent tool to disentangle processes driving boreal forest dynamics.

scholarly journals The influence of climate and hydrological variables on opposite anomaly in active-layer thickness between Eurasian and North American watersheds

2013 ◽  
Vol 7 (2) ◽  
pp. 631-645 ◽  
Author(s):  
H. Park ◽  
J. Walsh ◽  
A. N. Fedorov ◽  
A. B. Sherstiukov ◽  
Y. Iijima ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
North American ◽  
Land Surface ◽  
Snow Depth ◽  
The Arctic ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Hydrological Variables ◽  
Permafrost Regions

Abstract. This study not only examined the spatiotemporal variations of active-layer thickness (ALT) in permafrost regions during 1948–2006 over the terrestrial Arctic regions experiencing climate changes, but also identified the associated drivers based on observational data and a simulation conducted by a land surface model (CHANGE). The focus on the ALT extends previous studies that have emphasized ground temperatures in permafrost regions. The Ob, Yenisey, Lena, Yukon, and Mackenzie watersheds are foci of the study. Time series of ALT in Eurasian watersheds showed generally increasing trends, while the increase in ALT in North American watersheds was not significant. However, ALT in the North American watersheds has been negatively anomalous since 1990 when the Arctic air temperature entered into a warming phase. The warming temperatures were not simply expressed to increases in ALT. Since 1990 when the warming increased, the forcing of the ALT by the higher annual thawing index (ATI) in the Mackenzie and Yukon basins has been offset by the combined effects of less insulation caused by thinner snow depth and drier soil during summer. In contrast, the increasing ATI together with thicker snow depth and higher summer soil moisture in the Lena contributed to the increase in ALT. The results imply that the soil thermal and moisture regimes formed in the pre-thaw season(s) provide memory that manifests itself during the summer. The different ALT anomalies between Eurasian and North American watersheds highlight increased importance of the variability of hydrological variables.

Assessing the impact of permafrost-vegetation interaction on treeline dynamics in Siberia with the individual-based, spatially explicit treeline model LAVESI coupled to the permafrost land-surface model CryoGrid

2021 ◽  
Author(s):  
Stefan Kruse ◽  
Simone M. Stünzi ◽  
Moritz Langer ◽  
Julia Boike ◽  
Ulrike Herzschuh
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Coupled Model ◽  
Radiation Budget ◽  
Spatially Explicit ◽  
Surface Model ◽  
Data Set ◽  
Larch Species ◽  
The Individual ◽  
The Impact

<p>Tundra-taiga ecotone dynamics play a relevant role in the global carbon cycle. However, it is rather uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. This knowledge gap stems from the complex permafrost-vegetation interactions, not yet fully understood. Consequently, shedding light on the role of current and future active layer dynamics is crucial for an accurate prediction of treeline dynamics, and thus for aboveground forest biomass and carbon stock developments.</p><p>We make use of a coupled model version combining CryoGrid, a one-dimensional permafrost land-surface model, with LAVESI, an individual-based and spatially explicit forest model for larch species (<em>Larix </em>Mill.) in Siberia. Following a parametrization against an extensive field data set of 100+ forest inventories conducted along the Siberian treeline (97-169° E), we run simulations for the upcoming centuries forced by climatic change scenarios.</p><p>The coupled model setup benefits from the detailed process implementation gained while developing the individual models. Therefore, we can reproduce the energy transfer and thermal regime in permafrost ground as well as the radiation budget, nitrogen and photosynthetic profiles, canopy turbulence, and leaf fluxes, while at the same time, predicting the expected establishment, die-off, and treeline movements of larch forests. In our analyses, we focus on vegetation and permafrost dynamics and reveal the magnitudes of different feedback processes between permafrost, vegetation, and current and future climate in Northern Siberia.</p>

scholarly journals Permafrost temperature and active-layer thickness of Yakutia with 0.5-degree spatial resolution for model evaluation

2013 ◽  
Vol 5 (2) ◽  
pp. 305-310 ◽  
Author(s):  
C. Beer ◽  
A. N. Fedorov ◽  
Y. Torgovkin
Keyword(s):  
Layer Thickness ◽  
Spatial Resolution ◽  
Active Layer ◽  
Land Surface ◽  
Grid Cell ◽  
Active Layer Thickness ◽  
East Siberia ◽  
Permafrost Temperature ◽  
Surface Models ◽  
The Mean

Abstract. Based on the map of landscapes and permafrost conditions in Yakutia (Merzlotno-landshaftnaya karta Yakutskoi0 ASSR, Gosgeodeziya SSSR, 1991), rasterized maps of permafrost temperature and active-layer thickness of Yakutia, East Siberia were derived. The mean and standard deviation at 0.5-degree grid cell size are estimated by assigning a probability density function at 0.001-degree spatial resolution. The gridded datasets can be accessed at the PANGAEA repository (doi:10.1594/PANGAEA.808240). Spatial pattern of both variables are dominated by a climatic gradient from north to south, and by mountains and the soil type distribution. Uncertainties are highest in mountains and in the sporadic permafrost zone in the south. The maps are best suited as a benchmark for land surface models which include a permafrost module.

scholarly journals Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India

2014 ◽  
Vol 18 (10) ◽  
pp. 4223-4238 ◽  
Author(s):  
G. M. Tsarouchi ◽  
W. Buytaert ◽  
A. Mijic
Keyword(s):  
Growth Model ◽  
Land Surface ◽  
Coupled Model ◽  
Crop Growth ◽  
Original Model ◽  
Surface Model ◽  
Strong Impact ◽  
Crop Growth Model ◽  
Mean Error ◽  
The Impact

Abstract. Land-Surface Models (LSMs) are tools that represent energy and water flux exchanges between land and the atmosphere. Although much progress has been made in adding detailed physical processes into these models, there is much room left for improved estimates of evapotranspiration fluxes, by including a more reasonable and accurate representation of crop dynamics. Recent studies suggest a strong land-surface–atmosphere coupling over India and since this is one of the most intensively cultivated areas in the world, the strong impact of crops on the evaporative flux cannot be neglected. In this study we dynamically couple the LSM JULES with the crop growth model InfoCrop. JULES in its current version (v3.4) does not simulate crop growth. Instead, it treats crops as natural grass, while using prescribed vegetation parameters. Such simplification might lead to modelling errors. Therefore we developed a coupled modelling scheme that simulates dynamically crop development and parametrized it for the two main crops of the study area, wheat and rice. This setup is used to examine the impact of inter-seasonal land cover changes in evapotranspiration fluxes of the Upper Ganges River basin (India). The sensitivity of JULES with regard to the dynamics of the vegetation cover is evaluated. Our results show that the model is sensitive to the changes introduced after coupling it with the crop model. Evapotranspiration fluxes, which are significantly different between the original and the coupled model, are giving an approximation of the magnitude of error to be expected in LSMs that do not include dynamic crop growth. For the wet season, in the original model, the monthly Mean Error ranges from 7.5 to 24.4 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 5.4–11.6 mm month−1. For the dry season, in the original model, the monthly Mean Error ranges from 10 to 17 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 2.2–3.4 mm month−1. The new modelling scheme, by offering increased accuracy of evapotranspiration estimations, is an important step towards a better understanding of the two-way crops–atmosphere interactions.

scholarly journals Integration of nitrogen dynamics into the Noah-MP land model v1.1 for climate and environmental predictions

2015 ◽  
Vol 8 (5) ◽  
pp. 4113-4153 ◽  
Author(s):  
X. Cai ◽  
Z.-L. Yang ◽  
J. B. Fisher ◽  
X. Zhang ◽  
M. Barlage ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Net Primary Productivity ◽  
Assessment Tool ◽  
Land Surface Model ◽  
Coupled Model ◽  
Nitrogen Dynamics ◽  
Surface Model ◽  
Meteorological Model ◽  
Environmental Models

Abstract. Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long-term Ecological Research site within the U.S. Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of the carbon and water cycles (e.g., net primary productivity and evapotranspiration). The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

scholarly journals An improved representation of physical permafrost dynamics in the JULES land surface model

2015 ◽  
Vol 8 (1) ◽  
pp. 715-759 ◽  
Author(s):  
S. Chadburn ◽  
E. Burke ◽  
R. Essery ◽  
J. Boike ◽  
M. Langer ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Active Layer ◽  
Land Surface ◽  
Climate Models ◽  
Surface Soil ◽  
Active Layer Thickness ◽  
Mean Square ◽  
Near Surface ◽  
Soil Temperatures

Abstract. It is important to correctly simulate permafrost in global climate models, since the stored carbon represents the source of a potentially important climate feedback. This carbon feedback depends on the physical state of the permafrost. We have therefore included improved physical permafrost processes in JULES, which is the land-surface scheme used in the Hadley Centre climate models. The thermal and hydraulic properties of the soil were modified to account for the presence of organic matter, and the insulating effects of a surface layer of moss were added, allowing for fractional moss cover. We also simulate a higher-resolution soil column and deeper soil, and include an additional thermal column at the base of the soil to represent bedrock. In addition, the snow scheme was improved to allow it to run with arbitrarily thin layers. Point-site simulations at Samoylov Island, Siberia, show that the model is now able to simulate soil temperatures and thaw depth much closer to the observations. The root mean square error for the near-surface soil temperatures reduces by approximately 30%, and the active layer thickness is reduced from being over 1 m too deep to within 0.1 m of the observed active layer thickness. All of the model improvements contribute to improving the simulations, with organic matter having the single greatest impact. A new method is used to estimate active layer depth more accurately using the fraction of unfrozen water. Soil hydrology and snow are investigated further by holding the soil moisture fixed and adjusting the parameters to make the soil moisture and snow density match better with observations. The root mean square error in near-surface soil temperatures is reduced by a further 20% as a result.

scholarly journals Coupling a groundwater model with a land surface model to improve water and energy cycle simulation

2012 ◽  
Vol 9 (1) ◽  
pp. 1163-1205 ◽  
Author(s):  
W. Tian ◽  
X. Li ◽  
X.-S. Wang ◽  
B. X. Hu
Keyword(s):  
Groundwater Flow ◽  
Land Surface ◽  
Flow Model ◽  
Land Surface Model ◽  
Coupled Model ◽  
Subsurface Water ◽  
Surface Model ◽  
Groundwater Flow Model ◽  
Groundwater Model ◽  
Depth Zone

Abstract. The water and energy cycles interact, making them generally closely related. Land surface models (LSMs) can describe the water and energy cycles of the land surface, but their description of the subsurface water processes is oversimplified, and lateral groundwater flow is ignored. Groundwater models (GWMs) well describe the dynamic movement of subsurface water flow, but they cannot depict the physical mechanism of the evapotranspiration (ET) process in detail. In this study, a coupled model of groundwater with simple biosphere (GWSiB) is developed based on the full coupling of a typical land surface model (SiB2) and a three-dimensional variably saturated groundwater model (AquiferFlow). In this model, the infiltration, ET and energy transfer are simulated by SiB2 via the soil moisture results given by the groundwater flow model. The infiltration and ET results are applied iteratively to drive the groundwater flow model. The developed model is then applied to study water cycle processes in the middle reaches of the Heihe River Basin in the northwest of China. The model is validated through data collected at three stations in the study area. The stations are located in a shallow groundwater depth zone, a deeper groundwater depth zone and an agricultural irrigation area. The study results show that the coupled model can well depict the land surface and groundwater interaction and can more comprehensively and accurately simulate the water and energy cycles compared with uncoupled models.

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