scholarly journals Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

2017 ◽  
Author(s):  
Joe R. Melton ◽  
Reinel Sospedra-Alfonso ◽  
Kelly E. McCusker
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Clustering Analysis ◽  
Clustering Algorithms ◽  
Terrestrial Ecosystem ◽  
Grid Cell ◽  
Moisture Stress ◽  
Ecosystem Model ◽  
Global Scale ◽  
Terrestrial Ecosystem Model

Abstract. We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (ca. 2.8° × 2.8°) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms (OPTICS (Ankerst et al., 1999; Daszykowski et al., 2002) and Sander et al. (2003)) to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures, however differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global scale simulations using a simple grid-mean value.

scholarly journals Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

2017 ◽  
Vol 10 (7) ◽  
pp. 2761-2783 ◽  
Author(s):  
Joe R. Melton ◽  
Reinel Sospedra-Alfonso ◽  
Kelly E. McCusker
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Clustering Analysis ◽  
Clustering Algorithms ◽  
Terrestrial Ecosystem ◽  
Grid Cell ◽  
Moisture Stress ◽  
Ecosystem Model ◽  
Global Scale ◽  
Terrestrial Ecosystem Model

Abstract. We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (approximately 2. 8° × 2. 8°) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms – the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm (Ankerst et al., 1999; Daszykowski et al., 2002) and the algorithm of Sander et al. (2003) – to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures; however, differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant-available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global-scale simulations using a simple grid-mean value.

scholarly journals An improved parameterization of leaf area index (LAI) seasonality in the Canadian Land Surface Scheme (CLASS) and Canadian Terrestrial Ecosystem Model (CTEM) modelling framework

2018 ◽  
Author(s):  
Ali Asaadi ◽  
Vivek K. Arora ◽  
Joe R. Melton ◽  
Paul Bartlett
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Area Index ◽  
Terrestrial Ecosystem Model ◽  
Modelling Framework ◽  
Canadian Land Surface Scheme ◽  
Surface Scheme

Abstract. Leaf area index (LAI) and its seasonal dynamics are key determinants of vegetation productivity in nature and as represented in terrestrial biosphere models seeking to understand land-surface atmosphere flux dynamics and its response to climate change. Non-structural carbohydrates (NSCs) and their seasonal variability are known to play a crucial role in seasonal variation of leaf phenology and growth and functioning of plants. The carbon stored in NSC pools provides a buffer during times when supply and demand of carbon are asynchronous. An example of this role is illustrated when NSCs from previous years are used to initiate leaf onset at the arrival of favourable weather conditions. In this study, we incorporate NSC pools and associated parameterizations of new processes in the modelling framework of the Canadian Land Surface Scheme-Canadian Terrestrial Ecosystem Model (CLASS-CTEM) with an aim to improve the seasonality of simulated LAI. The performance of these new parameterizations is evaluated by comparing simulated LAI and atmosphere-land CO2 fluxes, to their observation-based estimates, at three sites characterized by broadleaf cold deciduous trees selected from the Fluxnet database. Results show an improvement in leaf onset and offset times with about 2 weeks shift towards earlier times during the year in better agreement with observations. These improvements in simulated LAI help to improve the simulated seasonal cycle of gross primary productivity (GPP) and as a result simulated net ecosystem productivity (NEP) as well.

scholarly journals Improving permafrost physics in the coupled Canadian Land Surface Scheme (v.3.6.2) and Canadian Terrestrial Ecosystem Model (v.2.1) (CLASS-CTEM)

2019 ◽  
Vol 12 (10) ◽  
pp. 4443-4467 ◽  
Author(s):  
Joe R. Melton ◽  
Diana L. Verseghy ◽  
Reinel Sospedra-Alfonso ◽  
Stephan Gruber
Keyword(s):  
Land Surface ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Grid Cells ◽  
Land Surface Scheme ◽  
Terrestrial Ecosystem Model ◽  
Model Configuration ◽  
Canadian Land Surface Scheme ◽  
Surface Scheme ◽  
The Impact

Abstract. The Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model (CLASS-CTEM) together form the land surface component of the Canadian Earth System Model (CanESM). Here, we investigate the impact of changes to CLASS-CTEM that are designed to improve the simulation of permafrost physics. Overall, 18 tests were performed, including changing the model configuration (number and depth of ground layers, different soil permeable depth datasets, adding a surface moss layer), and investigating alternative parameterizations of soil hydrology, soil thermal conductivity, and snow properties. To evaluate these changes, CLASS-CTEM outputs were compared to 1570 active layer thickness (ALT) measurements from 97 observation sites that are part of the Global Terrestrial Network for Permafrost (GTN-P), 105 106 monthly ground temperature observations from 132 GTN-P borehole sites, a blend of five observation-based snow water equivalent (SWE) datasets (Blended-5), remotely sensed albedo, and seasonal discharge for major rivers draining permafrost regions. From the tests performed, the final revised model configuration has more ground layers (increased from 3 to 20) extending to greater depth (from 4.1 to 61.4 m) and uses a new soil permeable depths dataset with a surface layer of moss added. The most beneficial change to the model parameterizations was incorporation of unfrozen water in frozen soils. These changes to CLASS-CTEM cause a small improvement in simulated SWE with little change in surface albedo but greatly improve the model performance at the GTN-P ALT and borehole sites. Compared to the GTN-P observations, the revised CLASS-CTEM ALTs have a weighted mean absolute error (wMAE) of 0.41–0.47 m (depending on configuration), improved from >2.5 m for the original model, while the borehole sites see a consistent improvement in wMAE for most seasons and depths considered, with seasonal wMAE values for the shallow surface layers of the revised model simulation of at most 3.7 ∘C, which is 1.2 ∘C more than the wMAE of the screen-level air temperature used to drive the model as compared to site-level observations (2.5 ∘C). Subgrid heterogeneity estimates were derived from the standard deviation of ALT on the 1 km2 measurement grids at the GTN-P ALT sites, the spread in wMAE in grid cells with multiple GTN-P ALT sites, as well as from 35 boreholes measured within a 1200 km2 region as part of the Slave Province Surficial Materials and Permafrost Study. Given the size of the model grid cells (approximately 2.8∘), subgrid heterogeneity makes it likely difficult to appreciably reduce the wMAE of ALT or borehole temperatures much further.

scholarly journals Integrating peatlands into the coupled Canadian Land Surface Scheme (CLASS) v3.6 and the Canadian Terrestrial Ecosystem Model (CTEM) v2.0

2016 ◽  
Vol 9 (8) ◽  
pp. 2639-2663 ◽  
Author(s):  
Yuanqiao Wu ◽  
Diana L. Verseghy ◽  
Joe R. Melton
Keyword(s):  
Land Surface ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Earth System ◽  
Land Surface Scheme ◽  
System Models ◽  
Terrestrial Ecosystem Model ◽  
Canadian Land Surface Scheme ◽  
Surface Scheme ◽  
Earth System Models

Abstract. Peatlands, which contain large carbon stocks that must be accounted for in the global carbon budget, are poorly represented in many earth system models. We integrated peatlands into the coupled Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM), which together simulate the fluxes of water, energy, and CO2 at the land surface–atmosphere boundary in the family of Canadian Earth system models (CanESMs). New components and algorithms were added to represent the unique features of peatlands, such as their characteristic ground floor vegetation (mosses), the slow decomposition of carbon in the water-logged soils and the interaction between the water, energy, and carbon cycles. This paper presents the modifications introduced into the CLASS–CTEM modelling framework together with site-level evaluations of the model performance for simulated water, energy and carbon fluxes at eight different peatland sites. The simulated daily gross primary production (GPP) and ecosystem respiration are well correlated with observations, with values of the Pearson correlation coefficient higher than 0.8 and 0.75 respectively. The simulated mean annual net ecosystem production at the eight test sites is 87 g C m−2 yr−1, which is 22 g C m−2 yr−1 higher than the observed annual mean. The general peatland model compares well with other site-level and regional-level models for peatlands, and is able to represent bogs and fens under a range of climatic and geographical conditions.

scholarly journals Freeze/thaw processes in complex permafrost landscapes of northern Siberia simulated using the TEM ecosystem model: impact of thermokarst ponds and lakes

2014 ◽  
Vol 7 (4) ◽  
pp. 1671-1689 ◽  
Author(s):  
S. Yi ◽  
K. Wischnewski ◽  
M. Langer ◽  
S. Muster ◽  
J. Boike
Keyword(s):  
Water Depth ◽  
Land Surface ◽  
Terrestrial Ecosystem ◽  
Climate Scenario ◽  
Water Layer ◽  
Ecosystem Model ◽  
The Arctic ◽  
Thermal Processes ◽  
Freeze Thaw ◽  
Terrestrial Ecosystem Model

Abstract. Freeze/thaw (F/T) processes can be quite different under the various land surface types found in the complex tundra of the Arctic, such as polygonal tundra (wet center and dry rims), ponds, and thermokarst lakes. Proper simulation of these different processes is essential for accurate prediction of the release of greenhouse gases under a warming climate scenario. In this study we have incorporated the water layer into a dynamic organic soil version of the Terrestrial Ecosystem Model (DOS-TEM), having first verified and validated the model. Results showed that (1) the DOS-TEM was very efficient and its results compared well with analytical solutions for idealized cases, and (2) despite a number of limitations and uncertainties in the modeling, the simulations compared reasonably well with in situ measurements from polygon rims, polygon centers (with and without water), and lakes on Samoylov Island, Siberia, indicating the suitability of the DOS-TEM for simulating the various F/T processes. Sensitivity tests were performed on the effects of water depth and our results indicated that both water and snow cover are very important in the simulated thermal processes, for both polygon centers and lakes. We therefore concluded that the polygon rims and polygon centers (with various maximum water depths) should be considered separately, and that the dynamics of water depth in both polygons and lakes should be taken into account when simulating thermal processes for methane emission studies.

scholarly journals Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model

2017 ◽  
Author(s):  
Bakr Badawy ◽  
Saroja Polavarapu ◽  
Dylan B. A. Jones ◽  
Feng Deng ◽  
Michael Neish ◽  
...  
Keyword(s):  
Land Surface ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Terrestrial Ecosystem ◽  
Forecast Model ◽  
Ecosystem Model ◽  
Co2 Fluxes ◽  
Meteorological Forcing ◽  
Terrestrial Ecosystem Model ◽  
Atmospheric Transport Model

Abstract. The Canadian Land Surface Scheme and the Canadian Terrestrial Ecosystem Model (CLASS-CTEM) together form the land surface component in the family of Canadian Earth System Models (CanESM). Here, CLASS-CTEM is coupled to Environment and Climate Change Canada (ECCC)'s weather and greenhouse gas forecast model (GEM-MACH-GHG) to consistently model atmosphere-land exchange of CO2. The coupling between the land and the atmospheric transport model ensures consistency between meteorological forcing of CO2 fluxes and CO2 transport. The procedure used to spin up carbon pools for CLASS-CTEM for multi-decadal simulations needed to be significantly altered to deal with the limited availability of consistent meteorological information from a constantly changing operational environment in the GEM-MACH-GHG model. Despite the limitations in the spin up procedure, the simulated fluxes obtained by driving the CLASS-CTEM model with meteorological forcing from GEM-MACH-GHG were comparable to those obtained from CLASS-CTEM when it is driven with standard meteorological forcing (CRU-NCEP). This is due to the similarity of the two meteorological datasets in terms of temperature and radiation. However notable discrepancies in the seasonal variation and spatial patterns of precipitation estimates, especially in the tropics, were reflected in the estimated carbon fluxes, as they significantly affected the magnitude of the vegetation productivity and, to a lesser extent, the seasonal variations in carbon fluxes. Nevertheless, the simulated fluxes based on the meteorological forcing from the GEM-MACH-GHG model are within the range of other estimates from bottom-up or top-down approaches. Indeed, when simulated fluxes obtained by driving the CLASS-CTEM model with meteorological data from the GEM-MACH-GHG model are used as prior estimates for an atmospheric CO2 inversion analysis using the adjoint of the GEOS-Chem model, the retrieved CO2 flux estimates are comparable to those obtained from other systems in terms of the global budget and the total flux estimates for the northern extratropical regions, which have good observational coverage. In data poor regions, as expected, differences in the retrieved fluxes due to the prior fluxes become apparent, but fall within the uncertainty bounds based on multi-inversion analyses. The coupling of CLASS-CTEM to an atmospheric transport model with carbon assimilation capabilities also provides insights into the limitations of CLASS-CTEM simulated CO2 fluxes through comparisons of simulated atmospheric CO2 with observations at selected flask stations. This capability can be used to continually assess and improve the terrestrial ecosystem modules of the CLASS-CTEM model.

scholarly journals CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance

2019 ◽  
Author(s):  
Joe R. Melton ◽  
Vivek K. Arora ◽  
Eduard Wisernig-Cojoc ◽  
Christian Seiler ◽  
Matthew Fortier ◽  
...  
Keyword(s):  
Open Source ◽  
Land Surface ◽  
Terrestrial Ecosystem ◽  
Ecosystem Model ◽  
Model Framework ◽  
Land Surface Scheme ◽  
Terrestrial Ecosystem Model ◽  
Community Model ◽  
Canadian Land Surface Scheme ◽  
Surface Scheme

Abstract. Recent reports by the Global Carbon Project highlight large uncertainties around land surface processes such as land use change, strength of CO2 fertilization, nutrient limitation and supply, and response to variability in climate. Process-based land surface models are well-suited to address these complex and emerging global change problems, but will require extensive development and evaluation. The coupled Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model (CLASS-CTEM) framework has been under continuous development by Environment and Climate Change Canada since 1987. As the open-source model of code development has revolutionized the software industry, scientific software is experiencing a similar evolution. Given the scale of the challenge facing land surface modellers, and the benefits of open-source, or community model, development, we have transitioned CLASS-CTEM from an internally developed model to an open-source community model, which we call the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) v. 1.0. CLASSIC contains many technical features specifically designed to encourage community use including software containerization for serial and parallel simulations, extensive benchmarking software and data (Automated Model Benchmarking; AMBER), self-documenting code, community standard formats for model inputs and outputs, amongst others. Here we evaluate and benchmark CLASSIC against 31 FLUXNET sites where the model has been tailored to the site-level conditions and driven with observed meteorology. Future versions of CLASSIC will be developed using AMBER and these initial benchmark results to evaluate model performance over time. CLASSIC remains under active development and the code, site-level benchmarking data, software container and AMBER are freely available for community use.

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