Technical description of version 4.5 of the Community Land Model (CLM)

Oleson, Keith W.; Lawrence, Mark G.; Bonan, Bertrand; Drewniak, Beth; Huang, Maoyi; Koven, D.; Levis, Samuel; Li, Fang; Riley, J. Paul; Subin, M.; Swenson, Sean; Thornton, E. B.; Bozbiyik, Anil; Fisher, Rosie A.; Heald, L.; Kluzek, Erik; Lamarque, Jean‐François; Lawrence, J. R.; Leung, Ruby; Lipscomb, William; Muszala, P.; Ricciuto, M.; Sacks, J. R.; Sun, Yeneng; Tang, Jinyun; Yang, Zong‐Liang

doi:10.5065/d6rr1w7m

Cited by 198 publications

(167 citation statements)

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“…Radiation-based approaches typically operate at relatively larger scales (~1 km 2 ) but are limited by the resolution of the analytical instrument being used (250 m for the moderate-resolution imaging spectroradiometer [MODIS]), the climate data products used to convert satellite observations into NPP (~111 km 2 or 1°for the MODIS algorithm), and assumptions about biome-level parameterization of vegetation photosynthetic capacity that determine the relationship between satellite-derived indices and biomass production rates, among others. Finally, biogeochemical models simulate C cycling processes at the global scale and generate relatively coarse spatial resolution estimates (>1°in the Community Land Model [CLM]) [Lawrence et al, 2011;Oleson et al, 2013] and also use approximations that apply mean biome-level photosynthesis and C allocation schemes. However, because the three approaches produce NPP estimates in different ways (Figure 1a), they offer a unique and valuable opportunity to assess patterns of tropical NPP via intercomparison.…”

Section: Approaches Commonly Used To Estimate Npp In Tropical Forestsmentioning

confidence: 99%

“…The Community Land Model (CLM) is the terrestrial component of the Community Earth System Model [Lawrence et al, 2011] and represents many of the biophysical and biogeochemical processes that are critical to ecosystem function. Here, we used an uncoupled run of CLM v. 4.5 BGC [Oleson et al, 2013;Koven et al, 2013] where historical precipitation, solar radiation, atmospheric conditions (CRUNCEP version 3.1 1901(CRUNCEP version 3.1 -2009 [Viovy, 2011], transient land cover change [Lawrence and Chase, 2007;Lawrence et al, 2012;Oleson et al, 2013], and CO 2 concentrations were provided to the model, and CLM estimated all water, C, and nitrogen (N) components of the global terrestrial ecosystem at ~1°resolution. In CLM, each grid cell is divided into land units that include vegetation, lakes, urban areas, glaciers, and crops.…”

Section: Biogeochemical Model-based Estimates: Clm 45 Bgcmentioning

confidence: 99%

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A comparison of plot‐based satellite and Earth system model estimates of tropical forest net primary production

Cleveland

Taylor

Chadwick

et al. 2015

Global Biogeochemical Cycles

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Net primary production (NPP) by plants represents the largest annual flux of carbon dioxide (CO 2 ) from the atmosphere to the terrestrial biosphere, playing a critical role in the global carbon (C) cycle and the Earth's climate. Rates of NPP in tropical forests are thought to be among the highest on Earth, but debates about the magnitude, patterns, and controls of NPP in the tropics highlight uncertainty in our understanding of how tropical forests may respond to environmental change. Here, we compared tropical NPP estimates generated using three common approaches: (1) field-based methods scaled from plot-level measurements of plant biomass, (2) radiation-based methods that model NPP from satellite-derived radiation absorption by plants, (3) and biogeochemical model-based methods. For undisturbed tropical forests as a whole, the three methods produced similar NPP estimates (i.e.,~10 Pg C yr À1). However, the three different approaches produced vastly different patterns of NPP both in space and through time, suggesting that our understanding of tropical NPP is poor and that our ability to predict the response of NPP in the tropics to environmental change is limited. To address this shortcoming, we suggest the development of an expanded, high-density, permanent network of sites where NPP is continuously evaluated using multiple approaches. Well-designed NPP megatransects that include a high-density plot network would significantly increase the accuracy and certainty in the observed rates and patterns of tropical NPP and improve the reliability of Earth system models used to predict NPP-carbon cycle-climate interactions into the future.

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Section: Approaches Commonly Used To Estimate Npp In Tropical Forestsmentioning

confidence: 99%

Section: Biogeochemical Model-based Estimates: Clm 45 Bgcmentioning

confidence: 99%

A comparison of plot‐based satellite and Earth system model estimates of tropical forest net primary production

Cleveland

Taylor

Chadwick

et al. 2015

Global Biogeochemical Cycles

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“…Fundamentally, this ecohydrological model is an integration of different components from the Soil and Water Assessment Tool (SWAT) (Neitsch et al, 2011;Arnold et al, 2012) and the Community Land Model version 4.5 (CLM4.5) (Oleson et al, 2013) (Fig. 1).…”

Section: General Description Of the Ecohydrological Modelmentioning

confidence: 99%

“…The subsurface hydrological modules, primarily the soil water movement, adopted the 1-D Richards' equation. It is solved numerically following the finite difference scheme used in CLM4.5 (Oleson et al, 2013).…”

Section: General Description Of the Ecohydrological Modelmentioning

confidence: 99%

Modelling the artificial forest (<i>Robinia pseudoacacia</i> L.) root–soil water interactions in the Loess Plateau, China

Luo

Sun

et al. 2022

Hydrol. Earth Syst. Sci.

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Abstract. Plant root–soil water interactions are fundamental to vegetation–water relationships. Soil water availability and distribution impact the temporal–spatial dynamics of roots and vice versa. In the Loess Plateau (LP) of China, where semi-arid and arid climates prevail and deep loess soil dominates, drying soil layers (DSLs) have been extensively reported in artificial forestland. While the underlying mechanisms that cause DSLs remain unclear, they hypothetically involve root–soil water interactions. Although available root growth models are weak with respect to simulating the rooting depth, this study addresses the hypothesis of the involvement of root–soil water interactions in DSLs using a root growth model that simulates both the dynamic rooting depth and fine-root distribution, coupled with soil water, based on cost–benefit optimization. Evaluation of field data from an artificial black locust (Robinia pseudoacacia L.) forest site in the southern LP positively proves the model's performance. Further, a long-term simulation, forced by a 50-year climatic data series with varying precipitation, was performed to examine the DSLs. The results demonstrate that incorporating the dynamic rooting depth into the current root growth models is necessary to reproduce soil drying processes. The simulations revealed that the upper boundary of the DSLs fluctuates strongly with infiltration events, whereas the lower boundary extends successively with increasing rooting depth. Most infiltration was intercepted by the top 2.0 m layer, which was the most active zone of infiltration and root water uptake. Below this, the percentages of fine roots (5.0 %) and water uptake (6.2 %) were small but caused a persistently negative water balance and consequent DSLs. Therefore, the proposed root–water interaction approach succeeded in revealing the intrinsic properties of DSLs; their persistent extension and the lack of an opportunity for recovery from the drying state may adversely affect the implementation of artificial afforestation in this region as well as in other regions with similar climates and soils.

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“…The coupling of FLake with all these LSMs showed strong benefits in the climate and weather simulations. In addition, the LISS model based on the Hostetler model is used in the CLM land component of the CESM climatic model developed by the NCAR institute (Oleson et al, 2013) and in the ELM land model based on the same core of CESM as BCC-AVIM, (Golaz et al, 2019) and NorESM2 (Seland et al, 2020). The LISS model is also implemented in LM4 which is the land component of the GFDL ESM (Milly et al, 2014) and in the land component CLASS of the Canadian ESM (Martynov et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model

Bernus

Ottlé

2022

Preprint

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Abstract. The freshwater 1-D FLake lake model was coupled to the ORCHIDEE land surface model to simulate lake energy balance at the global scale. A multi-tile approach has been chosen to allow the modelling of various types of lakes within the ORCHIDEE grid cell. The different categories have been defined according to lake depth which is the most influential parameter of FLake, but other properties could be considered in the future. Several depth parameterization strategies have been compared, differing by the way to aggregate the depth of the subgrid lakes, i.e., arithmetical, geometrical, harmonical mean and median. Five atmospheric reanalysis datasets available at 0.5° or 0.25° resolution, have been used to force the model and assess model systematic errors. Simulations have been performed, evaluated and intercompared against observations of lake water temperatures provided by the GloboLakes database over about 1000 lakes and ice phenology derived from the Global Lake and River Ice Phenology database. The results highlighted the large impact of the atmospheric forcing on the lake energy budget simulations and the improvements brought by the highest resolution products (ERA5 and E2OFD). The median of the Root Square Mean Errors (RMSE) calculated at global scale range between 3.2 K and 2.7 K among the forcings, CRUJRA and ERA5 leading respectively to the best and worst results. Depth parameterization strategy appeared to be less influent, with RMSE differences less than 0.1 K for the four aggregation scenarios tested. The simulation of ice phenology presented systematic errors whatever the forcing used and the depth parameterization. Freezing onset was shown to be the less sensitive to forcing and depth parameterization with median of the errors ranging between 10 and 14 days. Larger errors were observed on the simulation of the end of the freezing period significantly influenced by the atmospheric forcing used. Such errors already highlighted in previous works, could be the result of deficiencies in the modeling of snow/ice parameterization processes. Various pathways are drawn to improve the model results, including the use of remote sensing data to better constrain the lake radiative parameters (albedo and extinction coefficient) as well as the lake depth thanks to the recent and forthcoming high resolution satellite missions.

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Technical description of version 4.5 of the Community Land Model (CLM)

Cited by 198 publications

References 0 publications

A comparison of plot‐based satellite and Earth system model estimates of tropical forest net primary production

A comparison of plot‐based satellite and Earth system model estimates of tropical forest net primary production

Modelling the artificial forest (<i>Robinia pseudoacacia</i> L.) root–soil water interactions in the Loess Plateau, China

Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model

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Technical description of version 4.5 of the Community Land Model (CLM)

Cited by 198 publications

References 0 publications

A comparison of plot‐based satellite and Earth system model estimates of tropical forest net primary production

A comparison of plot‐based satellite and Earth system model estimates of tropical forest net primary production

Modelling the artificial forest (&lt;i&gt;Robinia pseudoacacia&lt;/i&gt; L.) root–soil water interactions in the Loess Plateau, China

Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model

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Modelling the artificial forest (<i>Robinia pseudoacacia</i> L.) root–soil water interactions in the Loess Plateau, China