Effects of organic soil in the Noah-MP land-surface model on simulated skin and soil temperature profiles and surface energy exchanges for China

2021 ◽  
Vol 249 ◽  
pp. 105284
Author(s):  
Guo Zhang ◽  
Yueli Chen ◽  
Jianduo Li
Keyword(s):  
Surface Energy ◽  
Soil Temperature ◽  
Land Surface ◽  
Land Surface Model ◽  
Organic Soil ◽  
Surface Model ◽  
Temperature Profiles ◽  
Energy Exchanges

scholarly journals Impacts of snow and organic soils parameterization on North-Eurasian soil temperature profiles simulated by the ISBA land surface model

2015 ◽  
Vol 9 (6) ◽  
pp. 6733-6790
Author(s):  
B. Decharme ◽  
E. Brun ◽  
A. Boone ◽  
C. Delire ◽  
P. Le Moigne ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Temperature ◽  
Soil Properties ◽  
Temperature Profile ◽  
Land Surface ◽  
Snow Depth ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature Profiles

Abstract. In this study we analysed how an improved representation of snowpack processes and soil properties in the multi-layer snow and soil schemes of the ISBA land surface model impacts the simulation of soil temperature profiles over North-Eurasian regions. For this purpose, we refine ISBA's snow layering algorithm and propose a parameterization of snow albedo and snow compaction/densification adapted from the detailed Crocus snowpack model. We also include a dependency on soil organic carbon content for ISBA's hydraulic and thermal soil properties. First, changes in the snowpack parameterization are evaluated against snow depth, snow water equivalent, surface albedo, and soil temperature at a 10 cm depth observed at the Col de Porte field site in the French Alps. Next, the new model version including all of the changes is used over Northern-Eurasia to evaluate the model's ability to simulate the snow depth, the soil temperature profile and the permafrost characteristics. The results confirm that an adequate simulation of snow layering and snow compaction/densification significantly impacts the snowpack characteristics and the soil temperature profile during winter, while the impact of the more accurate snow albedo computation is dominant during the spring. In summer, the accounting for the effect of soil organic carbon on hydraulic and thermal soil properties improves the simulation of the soil temperature profile. Finally, the results confirm that this last process strongly influences the simulation of the permafrost active layer thickness and its spatial distribution.

scholarly journals Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model

2016 ◽  
Vol 10 (2) ◽  
pp. 853-877 ◽  
Author(s):  
Bertrand Decharme ◽  
Eric Brun ◽  
Aaron Boone ◽  
Christine Delire ◽  
Patrick Le Moigne ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Temperature ◽  
Soil Properties ◽  
Temperature Profile ◽  
Land Surface ◽  
Snow Depth ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature Profiles

Abstract. In this study we analyzed how an improved representation of snowpack processes and soil properties in the multilayer snow and soil schemes of the Interaction Soil-Biosphere-Atmosphere (ISBA) land surface model impacts the simulation of soil temperature profiles over northern Eurasian regions. For this purpose, we refine ISBA's snow layering algorithm and propose a parameterization of snow albedo and snow compaction/densification adapted from the detailed Crocus snowpack model. We also include a dependency on soil organic carbon content for ISBA's hydraulic and thermal soil properties. First, changes in the snowpack parameterization are evaluated against snow depth, snow water equivalent, surface albedo, and soil temperature at a 10 cm depth observed at the Col de Porte field site in the French Alps. Next, the new model version including all of the changes is used over northern Eurasia to evaluate the model's ability to simulate the snow depth, the soil temperature profile, and the permafrost characteristics. The results confirm that an adequate simulation of snow layering and snow compaction/densification significantly impacts the snowpack characteristics and the soil temperature profile during winter, while the impact of the more accurate snow albedo computation is dominant during the spring. In summer, the accounting for the effect of soil organic carbon on hydraulic and thermal soil properties improves the simulation of the soil temperature profile. Finally, the results confirm that this last process strongly influences the simulation of the permafrost active layer thickness and its spatial distribution.

scholarly journals The incorporation of an organic soil layer in the Noah-MP Land Surface Model and its evaluation over a Boreal Aspen Forest

2015 ◽  
Vol 15 (20) ◽  
pp. 29265-29302
Author(s):  
L. Chen ◽  
Y. Li ◽  
F. Chen ◽  
A. Barr ◽  
M. Barlage ◽  
...  
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Soil Depth ◽  
Soil Layer ◽  
Land Surface Model ◽  
Organic Soil ◽  
Surface Model ◽  
Field Station ◽  
Aspen Forest ◽  
The Impact

Abstract. In this study, the multi-parameterization version of the Noah land-surface model (Noah-MP) was used to investigate the impact of adding a forest-floor organic soil layer on the simulated surface energy and water cycle components at a boreal aspen forest. The test site selected is BERMS Old Aspen Flux (OAS) field station in central Saskatchewan, Canada. The selection of different parameterization schemes for each process within the current Noah-MP model significantly affected the simulation results. The best combination options without incorporating organic soil is referred as the control experiment (CTL). By including an organic-soil parameterization within the Noah-MP model for the first time, the verification results (OGN) against site show significantly improved performance of the model in surface energy fluxes and hydrology simulation due to the lower thermal conductivity and greater porosity of the organic soil. The effects of including an organic soil layer on soil temperature are not uniform throughout the soil depth and year, and those effects are more prominent in summer and in deep soils. For drought years, the OGN simulation substantially modified the partition between direct soil evaporation and vegetation transpiration. For wet years, the OGN simulated latent heat fluxes are similar to CTL except for spring season where OGN produced less evaporation. The impact of the organic soil on sub-surface runoff is substantive with much higher runoff throughout the season.

scholarly journals The incorporation of an organic soil layer in the Noah-MP land surface model and its evaluation over a boreal aspen forest

2016 ◽  
Vol 16 (13) ◽  
pp. 8375-8387 ◽  
Author(s):  
Liang Chen ◽  
Yanping Li ◽  
Fei Chen ◽  
Alan Barr ◽  
Michael Barlage ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Latent Heat ◽  
Land Surface ◽  
Soil Layer ◽  
Land Surface Model ◽  
Organic Soil ◽  
Heat Fluxes ◽  
Surface Model ◽  
The Impact

Abstract. A thick top layer of organic matter is a dominant feature in boreal forests and can impact land–atmosphere interactions. In this study, the multi-parameterization version of the Noah land surface model (Noah-MP) was used to investigate the impact of incorporating a forest-floor organic soil layer on the simulated surface energy and water cycle components at the BERMS Old Aspen site (OAS) field station in central Saskatchewan, Canada. Compared to a simulation without an organic soil parameterization (CTL), the Noah-MP simulation with an organic soil (OGN) improved Noah-MP-simulated soil temperature profiles and soil moisture at 40–100 cm, especially the phase and amplitude (Seasonal cycle) of soil temperature below 10 cm. OGN also enhanced the simulation of sensible and latent heat fluxes in spring, especially in wet years, which is mostly related to the timing of spring soil thaw and warming. Simulated top-layer soil moisture is better in OGN than that in CTL. The effects of including an organic soil layer on soil temperature are not uniform throughout the soil depth and are more prominent in summer. For drought years, the OGN simulation substantially modified the partitioning of water between direct soil evaporation and vegetation transpiration. For wet years, the OGN-simulated latent heat fluxes are similar to CTL except for the spring season when OGN produced less evaporation, which was closer to observations. Including organic soil produced more subsurface runoff and resulted in much higher runoff throughout the freezing periods in wet years.

Adjoint retrieval of prognostic land surface model variables for an NWP model: Assimilation of ground surface temperature

2010 ◽  
Vol 2 (2) ◽  
Author(s):  
Diandong Ren
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Land Surface ◽  
Surface Soil ◽  
Land Surface Model ◽  
Initial Guess ◽  
Surface Model ◽  
Soil Moisture Condition ◽  
Wide Range ◽  
Surface Soil Temperature

AbstractBased on a 2-layer land surface model, a rather general variational data assimilation framework for estimating model state variables is developed. The method minimizes the error of surface soil temperature predictions subject to constraints imposed by the prediction model. Retrieval experiments for soil prognostic variables are performed and the results verified against model simulated data as well as real observations for the Oklahoma Atmospheric Surface layer Instrumentation System (OASIS). The optimization scheme is robust with respect to a wide range of initial guess errors in surface soil temperature (as large as 30 K) and deep soil moisture (within the range between wilting point and saturation). When assimilating OASIS data, the scheme can reduce the initial guess error by more than 90%, while for Observing Simulation System Experiments (OSSEs), the initial guess error is usually reduced by over four orders of magnitude.Using synthetic data, the robustness of the retrieval scheme as related to information content of the data and the physical meaning of the adjoint variables and their use in sensitivity studies are investigated. Through sensitivity analysis, it is confirmed that the vegetation coverage and growth condition determine whether or not the optimally estimated initial soil moisture condition leads to an optimal estimation of the surface fluxes. This reconciles two recent studies.With the real data experiments, it is shown that observations during the daytime period are the most effective for the retrieval. Longer assimilation windows result in more accurate initial condition retrieval, underlining the importance of information quantity, especially for schemes assimilating noisy observations.

scholarly journals The ERA5-Land soil temperature bias in permafrost regions

2020 ◽  
Vol 14 (8) ◽  
pp. 2581-2595 ◽  
Author(s):  
Bin Cao ◽  
Stephan Gruber ◽  
Donghai Zheng ◽  
Xin Li
Keyword(s):  
Soil Temperature ◽  
Land Surface ◽  
Soil Column ◽  
Land Surface Model ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Near Surface ◽  
Warm Bias ◽  
Temperature Bias ◽  
Permafrost Regions

Abstract. ERA5-Land (ERA5L) is a reanalysis product derived by running the land component of ERA5 at increased resolution. This study evaluates ERA5L soil temperature in permafrost regions based on observations and published permafrost products. We find that ERA5L overestimates soil temperature in northern Canada and Alaska but underestimates it in mid–low latitudes, leading to an average bias of −0.08 ∘C. The warm bias of ERA5L soil is stronger in winter than in other seasons. As calculated from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (<1.89 m) permafrost area. This is thought to be due in part to the shallow soil column and coarse vertical discretization of the land surface model and to warmer simulated soil. The soil temperature bias in permafrost regions correlates well with the bias in air temperature and with maximum snow height. A review of the ERA5L snow parameterization and a simulation example both point to a low bias in ERA5L snow density as a possible cause for the warm bias in soil temperature. The apparent disagreement of station-based and areal evaluation techniques highlights challenges in our ability to test permafrost simulation models. While global reanalyses are important drivers for permafrost simulation, we conclude that ERA5L soil data are not well suited for informing permafrost research and decision making directly. To address this, future soil temperature products in reanalyses will require permafrost-specific alterations to their land surface models.

Effects of Gravel on Energy and Water Transport in the Soil of Qinghai-Tibet Plateau

2020 ◽  
Author(s):  
shihua lyu
Keyword(s):  
Soil Temperature ◽  
Soil Water ◽  
Land Surface ◽  
Land Surface Model ◽  
Thermal Inertia ◽  
Tibet Plateau ◽  
Surface Model ◽  
Gravel Content ◽  
Water Move ◽  
The Mean

&lt;p&gt;According to the shortcomings of the land surface model, the new scheme is developed and applied to the simulating soil process at Madoi and Nagqu. Simulations show that gravel tend to reduce soil water holding capacity and enhance soil hydraulic conductivity, surface infiltration and drainage. As a result, the upper layer of soil mixed with gravel tends to drier due to the soil water move to deeper layer. The mean biases of soil moisture between the simulation and observation reduced by 25- 48% at two sites. Soil thermal conductivity is increased with gravel content and the soil thermal inertia was decreased with gravel content increasing. Therefore the deeper layer temperature of soil containing gravel is rapid response to air temperature change. The mean biases of soil temperature between the simulation and observation reduced by 9.1-25% at two sites. From the simulation results at Madoi and Nagqu, we find that the new scheme performed better than the original scheme in simulating soil temperature and water content and the land model implemented the new scheme is suitable for simulating land process in the QTP.&lt;/p&gt;

scholarly journals The interactions between soil–biosphere–atmosphere (ISBA) land surface model multi-energy balance (MEB) option in SURFEXv8 – Part 2: Introduction of a litter formulation and model evaluation for local-scale forest sites

2017 ◽  
Vol 10 (4) ◽  
pp. 1621-1644 ◽  
Author(s):  
Adrien Napoly ◽  
Aaron Boone ◽  
Patrick Samuelsson ◽  
Stefan Gollvik ◽  
Eric Martin ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Soil Temperature ◽  
Latent Heat ◽  
Land Surface ◽  
Forest Floor ◽  
Land Surface Model ◽  
Local Scale ◽  
Surface Model ◽  
Model Parameters

Abstract. Land surface models (LSMs) need to balance a complicated trade-off between computational cost and complexity in order to adequately represent the exchanges of energy, water and matter with the atmosphere and the ocean. Some current generation LSMs use a simplified or composite canopy approach that generates recurrent errors in simulated soil temperature and turbulent fluxes. In response to these issues, a new version of the interactions between soil–biosphere–atmosphere (ISBA) land surface model has recently been developed that explicitly solves the transfer of energy and water from the upper canopy and the forest floor, which is characterized as a litter layer. The multi-energy balance (MEB) version of ISBA is first evaluated for three well-instrumented contrasting local-scale sites, and sensitivity tests are performed to explore the behavior of new model parameters. Second, ISBA-MEB is benchmarked against observations from 42 forested sites from the global micro-meteorological network (FLUXNET) for multiple annual cycles.It is shown that ISBA-MEB outperforms the composite version of ISBA in improving the representation of soil temperature, ground, sensible and, to a lesser extent, latent heat fluxes. Both versions of ISBA give comparable results in terms of simulated latent heat flux because of the similar formulations of the water uptake and the stomatal resistance. However, MEB produces a better agreement with the observations of sensible heat flux than the previous version of ISBA for 87.5 % of the simulated years across the 42 forested FLUXNET sites. Most of this improvement arises owing to the improved simulation of the ground conduction flux, which is greatly improved using MEB, especially owing to the forest litter parameterization. It is also shown that certain processes are also modeled more realistically (such as the partitioning of evapotranspiration into transpiration and ground evaporation), even if certain statistical performances are neutral. The analyses demonstrate that the shading effect of the vegetation, the explicit treatment of turbulent transfer for the canopy and ground, and the insulating thermal and hydrological effects of the forest floor litter turn out to be essential for simulating the exchange of energy, water and matter across a large range of forest types and climates.

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