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An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah-MP
- An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah-MP
- Gim H.-J.; Park S.K.; Kang M.; Thakuri B.M.; Kim J.; Ho C.-H.
- Ewha Authors
- SCOPUS Author ID
- Issue Date
- Journal Title
- Journal of Advances in Modeling Earth Systems
- vol. 9, no. 4, pp. 1776 - 1794
- land surface model; parameterization; plant allometric growth; plant carbon allocation; temperate forest prediction; vegetation dynamics
- Blackwell Publishing Ltd
- SCIE; SCOPUS
- In the land surface models predicting vegetation growth and decay, representation of the seasonality of land surface energy and mass fluxes largely depends on how to describe the vegetation dynamics. In this study, we developed a new parameterization scheme to characterize allocation of the assimilated carbon to plant parts, including leaves and fine roots. The amount of carbon allocation in this scheme depends on the climatological net primary production (NPP) of the plants. The newly developed scheme is implemented in the augmented Noah land surface model with multiple parameterization options (Noah-MP) along with other biophysical processes related to variations in photosynthetic capacity. The scheme and the augmented biophysical processes are evaluated against tower measurements of vegetation from four forest sites in various regions—two for the deciduous broadleaf and two for the needleleaf evergreen forest. Results from the augmented Noah-MP showed good agreement with the observations and demonstrated improvements in representing the seasonality of leaf area index (LAI), gross primary production (GPP), ecosystem respiration (ER), and latent heat flux. In particular, significant improvements are found in simulating amplitudes and phase shift timing in the LAI seasonal cycle, and the amount of GPP and ER in the growing season. Furthermore, the augmented Noah-MP performed reasonably well in simulating the spatial distributions of LAI, GPP, and NPP in East Asia, consistent with the satellite observations. © 2017. The Authors.
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