scholarly journals Lower boundary conditions in Land Surface Models. Effects on the permafrost and the carbon pools

2018 ◽  
Author(s):  
Ignacio Hermoso de Mendoza ◽  
Hugo Beltrami ◽  
Andrew H. MacDougall ◽  
Jean-Claude Mareschal
Keyword(s):  
Heat Flux ◽  
Soil Carbon ◽  
Land Surface ◽  
Lower Boundary ◽  
Surface Model ◽  
Land Surface Models ◽  
Near Surface ◽  
Recent Climate ◽  
Surface Models ◽  
Rcp 8.5

Abstract. Earth System Models (ESMs) use bottom boundaries for their land surface model components which are shallower than the depth reached by surface temperature changes in the centennial time scale associated with recent climate change. Shallow bottom boundaries reflect energy to the surface, which along with the lack of geothermal heat flux in current land surface models, alter the surface energy balance and therefore affect some feedback processes between the ground surface and the atmosphere, such as permafrost and soil carbon stability. To evaluate these impacts, we modified the subsurface model in the Community Land Model version 4.5 (CLM4.5) by setting a non-zero crustal heat flux bottom boundary condition and by increasing the depth of the lower boundary by 300 m. The modified and original land models were run during the period 1901–2005 under the historical forcing and between 2005–2300 under two future scenarios of moderate (RCP 4.5) and high (RCP 8.5) emissions. Increasing the thickness of the subsurface by 300 m increases the heat stored in the subsurface by 72 ZJ (1 ZJ = 1021 J) by year 2300 for the RCP 4.5 scenario and 201 ZJ for the RCP 8.5 scenario (respective increases of 260 % and 217 % relative to the shallow model), reduces the loss of near-surface permafrost between 1901 and 2300 by 1.6 %–1.9 %, and reduces the loss of soil carbon by 1.6 %–3.6 %. Each increase of 0.02 W m−2 of the crustal heat flux increases the temperature at the soil-bedrock frontier by 0.4 ± 0.01 K, which decreases near-surface permafrost area slightly (0.3–0.8 %), but reduces the loss of soil carbon by as much as 1.1 %–5.6 % for the two scenarios.

scholarly journals Lower boundary conditions in land surface models – effects on the permafrost and the carbon pools: a case study with CLM4.5

2020 ◽  
Vol 13 (3) ◽  
pp. 1663-1683 ◽  
Author(s):  
Ignacio Hermoso de Mendoza ◽  
Hugo Beltrami ◽  
Andrew H. MacDougall ◽  
Jean-Claude Mareschal
Keyword(s):  
Heat Flux ◽  
Soil Carbon ◽  
Land Surface ◽  
Lower Boundary ◽  
Surface Model ◽  
Seasonal Temperature ◽  
Land Surface Models ◽  
Near Surface ◽  
Recent Climate ◽  
Surface Models

Abstract. Earth system models (ESMs) use bottom boundaries for their land surface model (LSM) components which are shallower than the depth reached by surface temperature changes in the centennial timescale associated with recent climate change. Shallow bottom boundaries reflect energy to the surface, which along with the lack of geothermal heat flux in current land surface models, alter the surface energy balance and therefore affect some feedback processes between the ground surface and the atmosphere, such as permafrost and soil carbon stability. To evaluate these impacts, we modified the subsurface model in the Community Land Model version 4.5 (CLM4.5) by setting a non-zero crustal heat flux bottom boundary condition uniformly across the model and by increasing the depth of the lower boundary from 42.1 to 342.1 m. The modified and original land models were run during the period 1901–2005 under the historical forcing and between 2005 and 2300 under forcings for two future scenarios of moderate (Representative Concentration Pathway 4.5; RCP4.5) and high (RCP8.5) emissions. Increasing the thickness of the subsurface by 300 m increases the heat stored in the subsurface by 72 ZJ (1 ZJ = 1021 J) by the year 2300 for the RCP4.5 scenario and 201 ZJ for the RCP8.5 scenario (respective increases of 260 % and 217 % relative to the shallow model), reduces the loss of near-surface permafrost area in the Northern Hemisphere between 1901 and 2300 by 1.6 %–1.9 %, reduces the loss of intermediate-depth permafrost area (above 42.1 m depth) by a factor of 3–5.5 and reduces the loss of soil carbon by 1.6 %–3.6 %. Each increase of 20 mW m−2 of the crustal heat flux increases the temperature at 3.8 m (the soil–bedrock interface) by 0.04±0.01 K. This decreases near-surface permafrost area slightly (0.3 %–0.8 %) and produces local differences in initial stable size of the soil carbon pool across the permafrost region, which reduces the loss of soil carbon across the region by as much as 1.1 %–5.6 % for the two scenarios. Reducing subsurface thickness from 42.1 to 3.8 m, used by many LSMs, produces a larger effect than increasing it to 342.1 m, because 3.8 m is not enough to damp the annual signal and the subsurface closely follows the air temperature. We determine the optimal subsurface thickness to be 100 m for a 100-year simulation and 200 m for a simulation of 400 years. We recommend short-term simulations to use a subsurface of at least 40 m, to avoid the perturbation of seasonal temperature propagation.

Evaluation of the new irrigation implementation in CTSM

2021 ◽  
Author(s):  
Yi Yao ◽  
Sean Swenson ◽  
David Lawrence ◽  
Danica Lombardozzi ◽  
Inne Vanderkelen ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Near Surface ◽  
Surface Energy Fluxes ◽  
Systems Model ◽  
Surface Models ◽  
Modelling Studies ◽  
Community Earth System Model

<p>Many observational and modelling studies have highlighted the important role that irrigation plays in the terrestrial hydrological and energy cycle. Land surface models are a key tool to study these interactions, underlining the importance of an accurate representation of irrigation in these models. However, most land surface models either ignore irrigation or represent it in a crude way. Here we improve and evaluate the implementation of irrigation in the Community Terrestrial Systems Model (CTSM), the land component of the Community Earth System Model (CESM). In this improvement, we consider three irrigation techniques (flood, sprinkler and drip), which differ in the amount and way of water applied. By combining global maps of the area equipped for irrigation with the distribution of different irrigation techniques, we represent the transient spatial distribution of irrigation techniques. Subsequently, we evaluate the performance of CTSM with the improved irrigation module. Three experiments are conducted: one with irrigation switched off, the second with the original irrigation module and the third with the improved irrigation module implemented. All three outputs are evaluated against observed or remotely sensed land surface energy fluxes and near-surface climate datasets. We anticipate that the results will reveal how our new irrigation schemes improve or reduce the performance of the land surface model.</p>

scholarly journals The Plumbing of Land Surface Models: Benchmarking Model Performance

2015 ◽  
Vol 16 (3) ◽  
pp. 1425-1442 ◽  
Author(s):  
M. J. Best ◽  
G. Abramowitz ◽  
H. R. Johnson ◽  
A. J. Pitman ◽  
G. Balsamo ◽  
...  
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Model Performance ◽  
Land Surface Model ◽  
Shortwave Radiation ◽  
Surface Model ◽  
Land Surface Models ◽  
Downward Shortwave Radiation ◽  
Surface Models ◽  
Physically Based

Abstract The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically based models and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.

scholarly journals Advantages of Analytically Computing the Ground Heat Flux in Land Surface Models

2016 ◽  
Author(s):  
Valentijn R. N. Pauwels ◽  
Edoardo Daly
Keyword(s):  
Thermal Conductivity ◽  
Heat Flux ◽  
Numerical Solution ◽  
Spatial Resolution ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Ground Heat Flux ◽  
Surface Models

Abstract. It is generally accepted that the ground heat flux accounts for a significant fraction of the surface energy balance. In land surface models, the ground heat flux is estimated through a numerical solution of the heat conduction equation. Recent research has shown that this approach introduces errors in the estimation of the energy balance. In this paper, we calibrate a land surface model using a numerical solution of the heat conduction equation with four different vertical spatial resolutions. It is found that the thermal conductivity is the most sensitive parameter to the spatial resolution. More importantly, the thermal conductivity values are directly related to the spatial resolution, thus rendering any physical interpretation of this value irrelevant. The numerical solution is then replaced by an analytical solution. The results of the numerical and analytical solutions are identical when fine spatial and temporal resolutions are used. However, when using resolutions that are typical for land surface models, significant differences are found. When using the analytical solution, the ground heat flux is directly calculated without calculating the soil temperature profile. The calculation of the temperature at each node in the soil profile is thus no longer required, unless the model contains parameters that depend on the soil temperature, which in this study is not the case. The calibration is repeated, and thermal conductivity values independent of the vertical spatial resolution are obtained. The main conclusion of this study is that care must be taken when interpreting land surface model results that have been obtained using numerical ground heat flux estimates. The use of exact analytical solutions is recommended.

scholarly journals Advantages of analytically computing the ground heat flux in land surface models

2016 ◽  
Vol 20 (11) ◽  
pp. 4689-4706 ◽  
Author(s):  
Valentijn R. N. Pauwels ◽  
Edoardo Daly
Keyword(s):  
Thermal Conductivity ◽  
Heat Flux ◽  
Numerical Solution ◽  
Spatial Resolution ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Ground Heat Flux ◽  
Surface Models

Abstract. It is generally accepted that the ground heat flux accounts for a significant fraction of the surface energy balance. In land surface models, the ground heat flux is typically estimated through a numerical solution of the heat conduction equation. Recent research has shown that this approach introduces errors in the estimation of the energy balance. In this paper, we calibrate a land surface model using a numerical solution of the heat conduction equation with four different vertical spatial resolutions. It is found that the thermal conductivity is the most sensitive parameter to the spatial resolution. More importantly, the thermal conductivity values are directly related to the spatial resolution, thus rendering any physical interpretation of this value irrelevant. The numerical solution is then replaced by an analytical solution. The results of the numerical and analytical solutions are identical when fine spatial and temporal resolutions are used. However, when using resolutions that are typical of land surface models, significant differences are found. When using the analytical solution, the ground heat flux is directly calculated without calculating the soil temperature profile. The calculation of the temperature at each node in the soil profile is thus no longer required, unless the model contains parameters that depend on the soil temperature, which in this study is not the case. The calibration is repeated, and thermal conductivity values independent of the vertical spatial resolution are obtained. The main conclusion of this study is that care must be taken when interpreting land surface model results that have been obtained using numerical ground heat flux estimates. The use of exact analytical solutions, when available, is recommended.

scholarly journals Exploring the Sensitivity of Photosynthesis and Stomatal Resistance Parameters in a Land Surface Model

2017 ◽  
Vol 18 (3) ◽  
pp. 897-915 ◽  
Author(s):  
Jennifer L. Jefferson ◽  
Reed M. Maxwell ◽  
Paul G. Constantine
Keyword(s):  
Land Surface ◽  
Stomatal Resistance ◽  
Hydrologic Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Common Land Model ◽  
Surface Models ◽  
Input Parameters ◽  
Rate Of Photosynthesis ◽  
Quantities Of Interest

Abstract Land surface models, like the Common Land Model component of the ParFlow integrated hydrologic model (PF-CLM), are used to estimate transpiration from vegetated surfaces. Transpiration rates quantify how much water moves from the subsurface through the plant and into the atmosphere. This rate is controlled by the stomatal resistance term in land surface models. The Ball–Berry stomatal resistance parameterization relies, in part, on the rate of photosynthesis, and together these equations require the specification of 20 input parameters. Here, the active subspace method is applied to 2100 year-long PF-CLM simulations, forced by atmospheric data from California, Colorado, and Oklahoma, to identify which input parameters are important and how they relate to three quantities of interest: transpiration, stomatal resistance from the sunlit portion of the canopy, and stomatal resistance from the shaded portion. The slope (mp) and intercept (bp) parameters associated with the Ball–Berry parameterization are consistently important for all locations, along with five parameters associated with ribulose bisphosphate carboxylase/oxygenase (RuBisCO)- and light-limited rates of photosynthesis [CO2 Michaelis–Menten constant at 25°C (kc25), maximum ratio of oxygenation to carboxylation (ocr), quantum efficiency at 25°C (qe25), maximum rate of carboxylation at 25°C (vcmx25), and multiplier in the denominator of the equation used to compute the light-limited rate of photosynthesis (wj1)]. The importance of these input parameters, quantified by the active variable weight, and the relationship between the input parameters and quantities of interest vary seasonally and diurnally. Input parameter values influence transpiration rates most during midday, summertime hours when fluxes are large. This research informs model users about which photosynthesis and stomatal resistance parameters should be more carefully selected. Quantifying sensitivities associated with the stomatal resistance term is necessary to better understand transpiration estimates from land surface models.

scholarly journals Evaluation of air–soil temperature relationships simulated by land surface models during winter across the permafrost region

2016 ◽  
Vol 10 (4) ◽  
pp. 1721-1737 ◽  
Author(s):  
Wenli Wang ◽  
Annette Rinke ◽  
John C. Moore ◽  
Duoying Ji ◽  
Xuefeng Cui ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Land Surface ◽  
Snow Depth ◽  
Soil Depth ◽  
Permafrost Region ◽  
Simple Relationship ◽  
Land Surface Models ◽  
Cross Model ◽  
Near Surface ◽  
Surface Models

Abstract. A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C−1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.

scholarly journals Using Cosmic-Ray Neutron Probes in Validating Satellite Soil Moisture Products and Land Surface Models

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1362 ◽  
Author(s):  
Mustafa Berk Duygu ◽  
Zuhal Akyürek
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Cosmic Ray ◽  
Surface Model ◽  
High Temporal Resolution ◽  
Land Surface Models ◽  
Statistical Measures ◽  
Surface Models ◽  
Global Land

Soil moisture content is one of the most important parameters of hydrological studies. Cosmic-ray neutron sensing is a promising proximal soil moisture sensing technique at intermediate scale and high temporal resolution. In this study, we validate satellite soil moisture products for the period of March 2015 and December 2018 by using several existing Cosmic Ray Neutron Probe (CRNP) stations of the COSMOS database and a CRNP station that was installed in the south part of Turkey in October 2016. Soil moisture values, which were inferred from the CRNP station in Turkey, are also validated using a time domain reflectometer (TDR) installed at the same location and soil water content values obtained from a land surface model (Noah LSM) at various depths (0.1 m, 0.3 m, 0.6 m and 1.0 m). The CRNP has a very good correlation with TDR where both measurements show consistent changes in soil moisture due to storm events. Satellite soil moisture products obtained from the Soil Moisture and Ocean Salinity (SMOS), the METOP-A/B Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), Advanced Microwave Scanning Radiometer 2 (AMSR2), Climate Change Initiative (CCI) and a global land surface model Global Land Data Assimilation System (GLDAS) are compared with the soil moisture values obtained from CRNP stations. Coefficient of determination ( r 2 ) and unbiased root mean square error (ubRMSE) are used as the statistical measures. Triple Collocation (TC) was also performed by considering soil moisture values obtained from different soil moisture products and the CRNPs. The validation results are mainly influenced by the location of the sensor and the soil moisture retrieval algorithm of satellite products. The SMAP surface product produces the highest correlations and lowest errors especially in semi-arid areas whereas the ASCAT product provides better results in vegetated areas. Both global and local land surface models’ outputs are highly compatible with the CRNP soil moisture values.

scholarly journals Inter-comparison of two land-surface models applied at different scales and their feedbacks while coupled with a regional climate model

2012 ◽  
Vol 16 (3) ◽  
pp. 1017-1031 ◽  
Author(s):  
F. Zabel ◽  
W. Mauser ◽  
T. Marke ◽  
A. Pfeiffer ◽  
G. Zängl ◽  
...  
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Regional Climate ◽  
Moderate Increase ◽  
Net Radiation ◽  
Land Surface Models ◽  
Near Surface ◽  
Temporal Behaviour ◽  
Surface Models ◽  
The Alps

Abstract. Downstream models are often used in order to study regional impacts of climate and climate change on the land surface. For this purpose, they are usually driven offline (i.e., 1-way) with results from regional climate models (RCMs). However, the offline approach does not allow for feedbacks between these models. Thereby, the land surface of the downstream model is usually completely different to the land surface which is used within the RCM. Thus, this study aims at investigating the inconsistencies that arise when driving a downstream model offline instead of interactively coupled with the RCM, due to different feedbacks from the use of different land surface models (LSM). Therefore, two physically based LSMs which developed from different disciplinary backgrounds are compared in our study: while the NOAH-LSM was developed for the use within RCMs, PROMET was originally developed to answer hydrological questions on the local to regional scale. Thereby, the models use different physical formulations on different spatial scales and different parameterizations of the same land surface processes that lead to inconsistencies when driving PROMET offline with RCM output. Processes that contribute to these inconsistencies are, as described in this study, net radiation due to land use related albedo and emissivity differences, the redistribution of this net radiation over sensible and latent heat, for example, due to different assumptions about land use impermeability or soil hydraulic reasons caused by different plant and soil parameterizations. As a result, simulated evapotranspiration, e.g., shows considerable differences of max. 280 mm yr−1. For a full interactive coupling (i.e., 2-way) between PROMET and the atmospheric part of the RCM, PROMET returns the land surface energy fluxes to the RCM and, thus, provides the lower boundary conditions for the RCM subsequently. Accordingly, the RCM responses to the replacement of the LSM with overall increased annual mean near surface air temperature (+1 K) and less annual precipitation (−56 mm) with different spatial and temporal behaviour. Finally, feedbacks can set up positive and negative effects on simulated evapotranspiration, resulting in a decrease of evapotranspiration South of the Alps a moderate increase North of the Alps. The inconsistencies are quantified and account for up to 30% from July to Semptember when focused to an area around Milan, Italy.

scholarly journals A new dataset of soil carbon and nitrogen stocks and profiles from an instrumented Greenlandic fen designed to evaluate land-surface models

2020 ◽  
Vol 12 (4) ◽  
pp. 2365-2380
Author(s):  
Xavier Morel ◽  
Birger Hansen ◽  
Christine Delire ◽  
Per Ambus ◽  
Mikhail Mastepanov ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Greenhouse Gas ◽  
Land Surface ◽  
High Water Content ◽  
Land Surface Models ◽  
Carbon And Nitrogen ◽  
Soil Carbon And Nitrogen ◽  
C Cycle ◽  
Surface Models ◽  
Carbon And Nitrogen Stocks

Abstract. Arctic and boreal peatlands play a major role in the global carbon (C) cycle. They are particularly efficient at sequestering carbon because their high water content limits decomposition rates to levels below their net primary productivity. Their future in a climate-change context is quite uncertain in terms of carbon emissions and carbon sequestration. Nuuk fen is a well-instrumented Greenlandic fen with monitoring of soil physical variables and greenhouse gas fluxes (CH4 and CO2) and is of particular interest for testing and validating land-surface models. But knowledge of soil carbon stocks and profiles is missing. This is a crucial shortcoming for a complete evaluation of models, as soil carbon is one of the primary drivers of CH4 and CO2 soil emissions. To address this issue, we measured, for the first time, soil carbon and nitrogen density, profiles and stocks in the Nuuk peatland (64∘07′51′′ N, 51∘23′10′′ W), colocated with the greenhouse gas measurements. Measurements were made along two transects, 60 and 90 m long and with a horizontal resolution of 5 m and a vertical resolution of 5 to 10 cm, using a 4 cm diameter gouge auger. A total of 135 soil samples were analyzed. Soil carbon density varied between 6.2 and 160.2 kg C m−3 with a mean value of 50.2 kg C m−3. Mean soil nitrogen density was 2.37 kg N m−3. Mean soil carbon and nitrogen stocks are 36.3 kg C m−2 and 1.7 kg N m−2. These new data are in the range of those encountered in other arctic peatlands. This new dataset, one of very few in Greenland, can contribute to further development of joint modeling of greenhouse gas emissions and soil carbon and nitrogen in land-surface models. The dataset is open-access and available at https://doi.org/10.1594/PANGAEA.909899 (Morel et al., 2019b).

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