An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah‐MP

Abstract

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.

A Systematic Evaluation of Noah‐MP in Simulating Land‐Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States

“…This may be caused by the Noah‐MP's scheme of carbon allocation to shoot and root, which probably allocates too much assimilated carbon into shoots in spring, accelerating the plants' carbon uptake through photosynthesis (Niu et al, ). Such biases may be alleviated by modifying the carbon allocation scheme (Gim et al, ), refining the temperature limitation (or heat stress) (Schaefer et al, ) as well as introduction of nitrogen limitation (Cai et al, ; Stöckli et al, ).…”

“…This suggests that the dynamic vegetation model in Noah‐MP should be improved to rigorously represent the carbon partitioning into shoot and root, root dynamics, and the feedbacks to photosynthesis. Progresses in refining carbon allocation schemes (Gim et al, ), applying the temperature limitation on photosynthesis (Schaefer et al, ), and introducing the nitrogen limitation (Cai et al, ; Stöckli et al, ) will facilitate simulations of both carbon and water fluxes across multiple scales. Noah‐MP is capable of reproducing the monthly TWSA over most of 18 HUC2 regions (10 regions have NSE values >0.6 at a monthly scale) except those severely affected by either anthropogenic activities including irrigation and impoundments or significant water storage changes over water bodies. Adding the lake water storage changes of the Michigan Lake with an area of 57,756 km 2 to the simulated TWSA reduces the modeling biases in the Great Lakes region to a large extent.…”

On the Representativeness of UTOPIA Land Surface Model for Creating a Database of Surface Layer, Vegetation and Soil Variables in Piedmont Vineyards, Italy

“…Latent heat fluxes have also been analyzed in [2] over forest sites, showing that LHF exhibited distinct seasonal changes and that the modeled values resulted to be overestimated before the initiation of the growing season. Also, UTOPIA LHF values exhibit an overestimation of maxima for all the different boundary conditions.…”

“…These kinds of models can simulate hydro-energetic and gas exchange processes in the layer including atmosphere, soil, and vegetation. Recent studies demonstrate that the accuracy of land surface processes diagnosed by land surface models can be further improved by considering specific aspects of vegetation growth, such as vegetation structure parameterizations [1] and LAI (Leaf Area Index) seasonality [2].…”

Climate change over the high-mountain versus plain areas: Effects on the land surface hydrologic budget in the Alpine area and northern Italy

“…Recent studies 10 demonstrate that the land surface processes diagnosed by land surface models are sensitive to vegetation dynamics and variations, and that their accuracy can be further improved by considering various aspects of vegetation effects in the subgrid-scale parameterizations (e.g., Park and Park, 2016;Gim et al, 2017). Moreover, the model uncertainties can be significantly reduced by optimal estimation of the parameter values in the schemes (e.g., Lee et al, 2006;Yu et al, 2013) and/or seeking for an optimized set among multiple-physics optional schemes (e.g., Hong et al, 2014Hong et al, , 2015.…”