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Title: Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites

Abstract

The Community Land Model (CLM) is an advanced process-based land surface model that simulates carbon, nitrogen, water vapor and energy exchanges between terrestrial ecosystems and the atmosphere at various spatial and temporal scales. We use observed carbon and water fluxes from five representative Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX) eddy covariance tower sites to systematically evaluate the new version CLM4.5 and old version CLM4.0, and to generate insights that may inform future model developments. CLM4.5 underestimates the annual carbon sink at three forest sites and one alpine grassland site but overestimates the carbon sink of a semi-arid grassland site. The annual carbon sink underestimation for the deciduous-dominated forest site results from underestimated daytime carbon sequestration during summer and overestimated nighttime carbon emission during spring and autumn. Compared to CLM4.0, the bias of annual gross primary production (GPP) is reduced by 24% and 28% in CLM4.5 at two subtropical forest sites. However, CLM4.5 still presents a large positive bias in annual GPP. The improvement in net ecosystem exchange (NEE) is limited, although soil respiration bias decreases by 16%–43% at three forest sites. CLM4.5 simulates lower soil water content in the dry season than CLM4.0 at two grassland sites. Drier soilsmore » produce a significant drop in the leaf area index and in GPP and an increase in respiration for CLM4.5. The new fire parameterization approach in CLM4.5 causes excessive burning at the Changbaishan forest site, resulting in an unexpected underestimation of NEE, vegetation carbon, and soil organic carbon by 46%, 95%, and 87%, respectively. Altogether, our study reveals significant improvements achieved by CLM4.5 compared to CLM4.0, and suggests further developments on the parameterization of seasonal GPP and respiration, which will require a more effective representation of seasonal water conditions and the partitioning of net radiation between sensible and heat fluxes.« less

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2];  [1]; ORCiD logo [2];  [1];  [3];  [4];  [1];  [5];  [6];  [7];  [8];  [1]
  1. Chinese Academy of Sciences (CAS), Beijing (China)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Chinese Academy of Sciences, Guiyang (China)
  4. East China Normal Univ., Shanghai (China)
  5. Chinese Academy of Sciences, Shenyang (China)
  6. Chinese Academy of Sciences, Xining (China)
  7. Chinese Academy of Sciences, Guangzhou (China)
  8. Univ. of Chinese Academy of Sciences, Beijing (China)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1394600
Grant/Contract Number:
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Agricultural and Forest Meteorology
Additional Journal Information:
Journal Volume: 226-227; Journal Issue: C; Journal ID: ISSN 0168-1923
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; Community land model; ChinaFLUX; Eddy covariance; Carbon flux

Citation Formats

Zhang, Li, Mao, Jiafu, Shi, Xiaoying, Ricciuto, Daniel M., He, Honglin, Thornton, Peter E., Yu, Guirui, Li, Pan, Liu, Min, Ren, Xiaoli, Han, Shijie, Li, Yingnian, Yan, Junhua, Hao, Yanbin, and Wang, Huimin. Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites. United States: N. p., 2016. Web. doi:10.1016/j.agrformet.2016.05.018.
Zhang, Li, Mao, Jiafu, Shi, Xiaoying, Ricciuto, Daniel M., He, Honglin, Thornton, Peter E., Yu, Guirui, Li, Pan, Liu, Min, Ren, Xiaoli, Han, Shijie, Li, Yingnian, Yan, Junhua, Hao, Yanbin, & Wang, Huimin. Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites. United States. doi:10.1016/j.agrformet.2016.05.018.
Zhang, Li, Mao, Jiafu, Shi, Xiaoying, Ricciuto, Daniel M., He, Honglin, Thornton, Peter E., Yu, Guirui, Li, Pan, Liu, Min, Ren, Xiaoli, Han, Shijie, Li, Yingnian, Yan, Junhua, Hao, Yanbin, and Wang, Huimin. 2016. "Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites". United States. doi:10.1016/j.agrformet.2016.05.018. https://www.osti.gov/servlets/purl/1394600.
@article{osti_1394600,
title = {Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites},
author = {Zhang, Li and Mao, Jiafu and Shi, Xiaoying and Ricciuto, Daniel M. and He, Honglin and Thornton, Peter E. and Yu, Guirui and Li, Pan and Liu, Min and Ren, Xiaoli and Han, Shijie and Li, Yingnian and Yan, Junhua and Hao, Yanbin and Wang, Huimin},
abstractNote = {The Community Land Model (CLM) is an advanced process-based land surface model that simulates carbon, nitrogen, water vapor and energy exchanges between terrestrial ecosystems and the atmosphere at various spatial and temporal scales. We use observed carbon and water fluxes from five representative Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX) eddy covariance tower sites to systematically evaluate the new version CLM4.5 and old version CLM4.0, and to generate insights that may inform future model developments. CLM4.5 underestimates the annual carbon sink at three forest sites and one alpine grassland site but overestimates the carbon sink of a semi-arid grassland site. The annual carbon sink underestimation for the deciduous-dominated forest site results from underestimated daytime carbon sequestration during summer and overestimated nighttime carbon emission during spring and autumn. Compared to CLM4.0, the bias of annual gross primary production (GPP) is reduced by 24% and 28% in CLM4.5 at two subtropical forest sites. However, CLM4.5 still presents a large positive bias in annual GPP. The improvement in net ecosystem exchange (NEE) is limited, although soil respiration bias decreases by 16%–43% at three forest sites. CLM4.5 simulates lower soil water content in the dry season than CLM4.0 at two grassland sites. Drier soils produce a significant drop in the leaf area index and in GPP and an increase in respiration for CLM4.5. The new fire parameterization approach in CLM4.5 causes excessive burning at the Changbaishan forest site, resulting in an unexpected underestimation of NEE, vegetation carbon, and soil organic carbon by 46%, 95%, and 87%, respectively. Altogether, our study reveals significant improvements achieved by CLM4.5 compared to CLM4.0, and suggests further developments on the parameterization of seasonal GPP and respiration, which will require a more effective representation of seasonal water conditions and the partitioning of net radiation between sensible and heat fluxes.},
doi = {10.1016/j.agrformet.2016.05.018},
journal = {Agricultural and Forest Meteorology},
number = C,
volume = 226-227,
place = {United States},
year = 2016,
month = 7
}

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  • Here, the vast forests and natural areas of the Pacific Northwest comprise one of the most productive ecosystems in the northern hemisphere. The heterogeneous landscape of Oregon poses a particular challenge to ecosystem models. We present a framework using a scaling factor Bayesian inversion to improve the modeled atmosphere-biosphere exchange of carbon dioxide. Observations from 5 CO/CO 2 towers, eddy covariance towers, and airborne campaigns were used to constrain the Community Land Model CLM4.5 simulated terrestrial CO 2 exchange at a high spatial and temporal resolution (1/24°, 3-hourly). To balance aggregation errors and the degrees of freedom in the inversemore » modeling system, we applied an unsupervised clustering approach for the spatial structuring of our model domain. Data from flight campaigns were used to quantify the uncertainty introduced by the Lagrangian particle dispersion model that was applied for the inversions. The average annual statewide net ecosystem productivity (NEP) was increased by 32% to 29.7 TgC per year by assimilating the tropospheric mixing ratio data. The associated uncertainty was decreased by 28.4% to 29%, on average over the entire Oregon model domain with the lowest uncertainties of 11% in western Oregon. The largest differences between posterior and prior CO 2 fluxes were found for the Coast Range ecoregion of Oregon that also exhibits the highest availability of atmospheric observations and associated footprints. In this area, covered by highly productive Douglas-fir forest, the differences between the prior and posterior estimate of NEP averaged 3.84 TgC per year during the study period from 2012 through 2014.« less
  • Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less
  • Land surface models are useful tools to quantify contemporary and future climate impact on terrestrial carbon cycle processes, provided they can be appropriately constrained and tested with observations. Stable carbon isotopes of CO 2 offer the potential to improve model representation of the coupled carbon and water cycles because they are strongly influenced by stomatal function. Recently, a representation of stable carbon isotope discrimination was incorporated into the Community Land Model component of the Community Earth System Model. Here, we tested the model's capability to simulate whole-forest isotope discrimination in a subalpine conifer forest at Niwot Ridge, Colorado, USA. Wemore » distinguished between isotopic behavior in response to a decrease of δ 13C within atmospheric CO 2 (Suess effect) vs. photosynthetic discrimination (Δ canopy), by creating a site-customized atmospheric CO 2 and δ 13C of CO 2 time series. We implemented a seasonally varying V cmax model calibration that best matched site observations of net CO 2 carbon exchange, latent heat exchange, and biomass. The model accurately simulated observed δ 13C of needle and stem tissue, but underestimated the δ 13C of bulk soil carbon by 1–2 ‰. The model overestimated the multiyear (2006–2012) average Δ canopy relative to prior data-based estimates by 2–4 ‰. The amplitude of the average seasonal cycle of Δ canopy (i.e., higher in spring/fall as compared to summer) was correctly modeled but only when using a revised, fully coupled A n −  g s (net assimilation rate, stomatal conductance) version of the model in contrast to the partially coupled A n −  g s version used in the default model. The model attributed most of the seasonal variation in discrimination to A n, whereas interannual variation in simulated Δ canopy during the summer months was driven by stomatal response to vapor pressure deficit (VPD). The model simulated a 10 % increase in both photosynthetic discrimination and water-use efficiency (WUE) since 1850 which is counter to established relationships between discrimination and WUE. The isotope observations used here to constrain CLM suggest (1) the model overestimated stomatal conductance and (2) the default CLM approach to representing nitrogen limitation (partially coupled model) was not capable of reproducing observed trends in discrimination. These findings demonstrate that isotope observations can provide important information related to stomatal function driven by environmental stress from VPD and nitrogen limitation. Future versions of CLM that incorporate carbon isotope discrimination are likely to benefit from explicit inclusion of mesophyll conductance.« less
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