scholarly journals Assessing the simulated soil hydrothermal regime of the active layer from the Noah-MP land surface model (v1.1) in the permafrost regions of the Qinghai–Tibet Plateau

2021 ◽  
Vol 14 (3) ◽  
pp. 1753-1771
Author(s):  
Xiangfei Li ◽  
Tonghua Wu ◽  
Xiaodong Wu ◽  
Jie Chen ◽  
Xiaofan Zhu ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Snow Cover ◽  
Land Surface ◽  
Tibet Plateau ◽  
Cold Bias ◽  
Surface Model ◽  
Model Parameters ◽  
Hydrothermal Regime ◽  
Qinghai Tibet Plateau ◽  
Permafrost Regions

Abstract. Extensive and rigorous model intercomparison is of great importance before model application due to the uncertainties in current land surface models (LSMs). Without considering the uncertainties in forcing data and model parameters, this study designed an ensemble of 55 296 experiments to evaluate the Noah LSM with multi-parameterization (Noah-MP) for snow cover events (SCEs), soil temperature (ST) and soil liquid water (SLW) simulation, and investigated the sensitivity of parameterization schemes at a typical permafrost site on the Qinghai–Tibet Plateau (QTP). The results showed that Noah-MP systematically overestimates snow cover, which could be greatly resolved when adopting the sublimation from wind and a semi-implicit snow/soil temperature time scheme. As a result of the overestimated snow, Noah-MP generally underestimates ST, which is mostly influenced by the snow process. A systematic cold bias and large uncertainties in soil temperature remain after eliminating the effects of snow, particularly in the deep layers and during the cold season. The combination of roughness length for heat and under-canopy (below-canopy) aerodynamic resistance contributes to resolving the cold bias in soil temperature. In addition, Noah-MP generally underestimates top SLW. The runoff and groundwater (RUN) process dominates the SLW simulation in comparison to the very limited impacts of all other physical processes. The analysis of the model structural uncertainties and characteristics of each scheme would be constructive to a better understanding of the land surface processes in the permafrost regions of the QTP as well as to further model improvements towards soil hydrothermal regime modeling using LSMs.

scholarly journals Assessing the simulated soil thermal regime from Noah-MPLSM v1.1 for near-surface permafrost modeling on the Qinghai-Tibet Plateau

2020 ◽  
Author(s):  
Xiangfei Li ◽  
Tonghua Wu ◽  
Xiaodong Wu ◽  
Xiaofan Zhu ◽  
Guojie Hu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Land Surface ◽  
Stomatal Resistance ◽  
Cold Season ◽  
Canopy Gap ◽  
Tibet Plateau ◽  
Surface Model ◽  
Near Surface ◽  
Qinghai Tibet Plateau

Abstract. Land surface models (LSMs) are effective tools for near-surface permafrost modeling. Extensive and rigorous model inter-comparison is of great importance before application due to the uncertainties in current LSMs. This study designed an ensemble of 6912 experiments to evaluate the Noah land surface model with multi-parameterization (Noah-MP) for soil temperature (ST) simulation, and investigate the sensitivity of parameterization schemes at a typical permafrost site on the Qinghai-Tibet Plateau. The results showed that Noah-MP generally underestimates ST, especially that during the cold season. In addition, the simulation uncertainty is greater in the cold season (October-April) and for the deep soil layers. ST is most sensitive to surface layer drag coefficient (SFC) while largely influenced by runoff and groundwater (RUN). By contrast, the influence of canopy stomatal resistance (CRS) and soil moisture factor for stomatal resistance (BTR) on ST is negligible. With limited impacts on ST simulation, vegetation model (VEG), canopy gap for radiation transfer (RAD) and snow/soil temperature time scheme (STC) are more influential on shallow ST, while super-cooled liquid water (FRZ), frozen soil permeability (INF) and lower boundary of soil temperature (TBOT) have greater impacts on deep ST. Furthermore, an optimal configuration of Noah-MP for permafrost modeling were extracted based on the connectivity between schemes, and they are: table leaf area index with calculated vegetation fraction, Jarvis scheme for CRS, Noah scheme for BTR, BATS model for RUN, Chen97 for SFC, zero canopy gap for RAD, variant freezing-point depression for FRZ, hydraulic parameters defined by soil moisture for INF, ST at 8 m for TBOT, and semi-implicit method for STC. The analysis of the model structural uncertainties and characteristics of each scheme would be constructive to a better understanding of the land surface processes on the QTP and further model improvements towards near-surface permafrost modeling using the LSMs.

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.

scholarly journals A Tiling Approach to Represent Subgrid Snow Variability in Coupled Land Surface–Atmosphere Models

2016 ◽  
Vol 18 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Kjetil Schanke Aas ◽  
Kjersti Gisnås ◽  
Sebastian Westermann ◽  
Terje Koren Berntsen
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Digital Camera ◽  
Cold Bias ◽  
Surface Model ◽  
Surface Energy Fluxes ◽  
Subgrid Scales ◽  
Moisture Fluxes

Abstract A mosaic approach to represent subgrid snow variation in a coupled atmosphere–land surface model (WRF–Noah) is introduced and tested. Solid precipitation is scaled in 10 subgrid tiles based on precalculated snow distributions, giving a consistent, explicit representation of variable snow cover and snow depth on subgrid scales. The method is tested in the Weather Research and Forecasting (WRF) Model for southern Norway at 3-km grid spacing, using the subgrid tiling for areas above the tree line. At a validation site in Finse, the modeled transition time from full snow cover to snow-free ground is increased from a few days with the default snow cover fraction formulation to more than 2 months with the tiling approach, which agrees with in situ observations from both digital camera images and surface temperature loggers. This in turn reduces a cold bias at this site by more than 2°C during the first half of July, with the noontime bias reduced from −5° to −1°C. The improved representation of subgrid snow variation also reduces a cold bias found in the reference simulation on regional scales by up to 0.8°C and increases surface energy fluxes (in particular the latent heat flux), and it resulted in up to 50% increase in monthly (June) precipitation in some of the most affected areas. By simulating individual soil properties for each tile, this approach also accounts for a number of secondary effects of uneven snow distribution resulting in different energy and moisture fluxes in different tiles also after the snow has disappeared.

scholarly journals The Interactions between Soil-Biosphere-Atmosphere (ISBA) land surface model Multi-Energy Balance (MEB) option in SURFEX – Part 2: Model evaluation for local scale forest sites

2016 ◽  
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 the Surface Biosphere Atmosphere (ISBA) land surface model has recently been developed which explicitly solves the transfer of energy and water from the upper canopy and the forest floor which is characterized as a litter layer. The so-called 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 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.

scholarly journals Gravel Parameterization Scheme and Verification Using BCC_CSM

2021 ◽  
Author(s):  
yue xu ◽  
Shihua Lyu ◽  
Yaomig Ma ◽  
Shaobo Zhang ◽  
Cuili Ma ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Interaction Model ◽  
Northwest China ◽  
Tibet Plateau ◽  
Surface Model ◽  
Wind Fields ◽  
Simulation Performance ◽  
Simulation Results ◽  
Qinghai Tibet Plateau

Abstract The soil in China contains an abundance of gravels, but it is poorly described in land surface models. To solve this problem, the Beijing Climate Center Atmosphere–Vegetation Interaction Model (BCC_AVIM), which is a land surface model with the gravel parameterization, is coupled to the Beijing Climate Center System Model (BCC_CSM). The simulation ability of BCC_CSM for China using the gravel parameterization is evaluated by comparing the simulation results using original and new schemes with the observed data. The results show that the annual average surface temperature simulated with the new scheme is more consistent with the observation in terms of the spatial distribution, and the simulation results in Southwest China, Northwest China and the Qinghai-Tibet Plateau are significantly improved, especially in summer. In the perspective of the area-averaged variables, the situation of more precipitation simulated using the original scheme is improved except for summer. The high-level and low-level wind fields simulated by BCC_CSM have a significant improvement in the Qinghai-Tibet Plateau. In general, this gravel parameterization is more suitable for areas with the high gravel content, and it improves the simulation performance of BCC_CSM in some areas of China.

Underestimated snow density in ERA5-Land as a cause for warm bias of soil temperature over permafrost regions

2021 ◽  
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 ◽  
Snow Density ◽  
Near Surface ◽  
Warm Bias ◽  
Permafrost Regions

&lt;div&gt; &lt;p&gt;ERA5 is the latest generation atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). ERA5-Land (ERA5L) is derived by running the land component of ERA5, Tiled ECMWF Scheme for Surface Exchanges over Land with a revised land surface hydrology (HTESSEL), at an increased resolution of 0.1&amp;#176;. 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&amp;#8211;low latitudes, leading to a near-zero overall bias (&amp;#8722;0.08 &amp;#730;C). The warm bias of ERA5L soil is more pronounced in winter than in other seasons. As calculated from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (&lt; 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.&lt;/p&gt; &lt;p&gt;The soil temperature bias in permafrost regions correlates well with the bias in air temperature and with snow height. A review of the ERA5L snow parameterization in the code and a simulation example comparison with permafrost-specific processes rich model (GEOtop) both point to an error in snow metamorphism of HTESSEL leading 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.&lt;/p&gt; &lt;p&gt;&lt;/p&gt;&lt;/div&gt;

scholarly journals From Standard Weather Stations to Virtual Micro-Meteorological Towers in Ungauged Sites: Modeling Tool for Surface Energy Fluxes, Evapotranspiration, Soil Temperature, and Soil Moisture Estimations

2021 ◽  
Vol 13 (7) ◽  
pp. 1271
Author(s):  
Jorge A. Celis ◽  
Hernan A. Moreno ◽  
Jeffrey B. Basara ◽  
Renee A. McPherson ◽  
Michael Cosh ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Land Surface ◽  
Root Zone ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Parameters ◽  
Energy Fluxes ◽  
Ungauged Sites ◽  
Modis Imagery ◽  
Weather Stations

One of the benefits of training a process-based, land surface model is the capacity to use it in ungauged sites as a complement to standard weather stations for predicting energy fluxes, evapotranspiration, and surface and root-zone soil temperature and moisture. In this study, dynamic (i.e., time-evolving) vegetation parameters were derived from remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and coupled with a physics-based land surface model (tin-based Real-time Integrated Basin Simulator (tRIBS)) at four eddy covariance (EC) sites in south-central U.S. to test the predictability of micro-meteorological, soil-related, and energy flux-related variables. One cropland and one grassland EC site in northern Oklahoma, USA, were used to tune the model with respect to energy fluxes, soil temperature, and moisture. Calibrated model parameters, mostly related to the soil, were then transferred to two other EC sites in Oklahoma with similar soil and vegetation types. New dynamic vegetation parameter time series were updated according to MODIS imagery at each site. Overall, the tRIBS model captured both seasonal and diurnal cycles of the energy partitioning and soil temperatures across all four stations, as indicated by the model assessment metrics, although large uncertainties appeared in the prediction of ground heat flux, surface, and root-zone soil moisture at some stations. The transferability of previously calibrated model parameters and the use of MODIS to derive dynamic vegetation parameters enabled rapid yet reasonable predictions. The model was proven to be a convenient complement to standard weather stations particularly for sites where eddy covariance or similar equipment is not available.

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