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Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

Journal Article · · Geoscientific Model Development (Online)
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [4];  [4];  [5];  [2];  [8];  [4];  [4];  [9];  [10]
  1. California Inst. of Technology (CalTech),Pasadena, CA (United States). Jet Propulsion Lab.; Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Earth and Environmental Sciences Div.
  3. Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique (CERFACS), Toulouse (France)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Climate and Ecosystem Sciences Div.
  5. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Div.
  6. Brookhaven National Lab. (BNL), Upton, NY (United States). Biological, Environmental & Climate Sciences Dept.
  7. Univ. of Texas Rio Grande Valley, Edinburg, TX (United States)
  8. Univ. of Florida, Gainesville, FL (United States). School of Forest Resources and Conservation
  9. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Earth Systems Analysis and Modeling Div.
  10. Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering; Univ. of California, Irvine, CA (United States). Dept. of Earth System Science
+ Show Author Affiliations
Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple “big-leaf” approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1 x 1°. While the photosynthetic capacity parameter (Vc,max25)is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity.
Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Biological and Environmental Research (BER). Climate and Environmental Sciences Division
Grant/Contract Number:
SC0012704; AC02-05CH11231; 89233218CNA000001; AC05-00OR22725
OSTI ID:
1562475
Alternate ID(s):
OSTI ID: 1735738
OSTI ID: 1649090
OSTI ID: 1571627
OSTI ID: 1580929
Report Number(s):
BNL--212083-2019-JAAM
Journal Information:
Geoscientific Model Development (Online), Journal Name: Geoscientific Model Development (Online) Journal Issue: 9 Vol. 12; ISSN 1991-9603
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (2)

Forecasting semi‐arid biome shifts in the Anthropocene journal January 2020
A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996) journal January 2019

Figures / Tables (22)

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