Recently, more advanced synchronous global-scale satellite observations, the Soil Moisture Active Passive enhanced Level 3 (SMAP L3) soil moisture product and the Orbiting Carbon Observatory 2 (OCO-2) solar-induced chlorophyll fluorescence (SIF) product, provide an opportunity to improve the simulations of both water and carbon cycles in land surface modeling. This study introduces a mechanistic representation of SIF to the Simplified Simple Biosphere Model version 4 (SSiB4) coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (TRIFFID). This newly developed model with the observed satellite data indicates that introducing dynamic processes can lead to substantial improvement in global carbon flux simulation. In the SSiB4/TRIFFID/SIF, four critical soil and vegetation parameters–B parameter, soil hydraulic conductivity at saturation (Ks), wilting point, and maximum Rubisco carboxylation rate (Vmax)–were identified through numerical sensitivity experiments. Among the four parameters, the B parameter has the most significant effects on both soil moisture and SIF simulations. With the optimized B parameter, both soil moisture and SIF simulations were improved substantially, with especially significant improvement for shrubs. The Ks and wilting point also affect both soil moisture and SIF but with reduced magnitude. The Vmax directly affects photosynthesis, and its modification can substantially improve the SIF simulation of needleleaf trees and C3 grasses. With all four calibrated parameters based on SMAP L3 and OCO-2 data, the root-mean-squared error (RMSE) of soil moisture and SIF simulations decreased from 0.076 to 0.063 m3/m3 and from 0.143 to 0.117 W/m2/μm/sr, respectively.

Plant and microbial nitrogen (N) dynamics and nitrogen availability regulate the photosynthetic capacity and capture, allocation, turnover of carbon (C) in terrestrial ecosystem. It is important to adequately represent plant N processes in land surface models. In this study, a plant C-N framework was developed by coupling a biophysical and dynamic land surface processes model, SSiB4/TRIFFID, with a soil organic matter cycling model, DayCent-SOM, to fully incorporate N regulations to investigate the impact of N on plant growth and C cycling. To incorporate the N limitation in the coupled system, the parameterization for dynamic C/N ratios for each plant functional type (PFT) was developed first. Then, after accounting for plant/soil N-cycling, when available N is less than demand, N would restrict the plant growth, reducing the net primary productivity (NPP), but also impact plant respiration rates and phenology. The improvements of the newly-developed model, the SSiB5/TRIFFID/DayCent-SOM, was preliminary verified at three flux tower sites with different PFTs. Furthermore, several offline global simulations were conducted from 1948 to 2007 to predict the long-term mean vegetation distribution and terrestrial C cycling, and the results are evaluated with satellite-derived observational data. The sensitivity of the terrestrial C cycle to N processes is also assessed. In general, new model can better reproduce observed emergent properties, including gross primary productivity (GPP), leaf area index (LAI), and respiration. The main improvements occur in tropical Africa and boreal regions, accompanied by a decrease of the bias in global GPP and LAI by 16.3% and 27.1%, respectively.

It is important to adequately represent plant nitrogen (N) biogeochemistry and its respective processes in land surface models. Thus far, various N representations in models lead to uncertainty in estimating model responses to global warming. Through plant and microbial N dynamics, nitrogen availability regulates the capture, allocation, turnover of carbon (C), and photosynthetic capacity. In this study, to fully incorporate these N regulations, we have developed a plant C-N framework by coupling a biophysical and dynamic land model, SSiB4/TRIFFID, with a soil organic matter cycling model, DayCent-SOM, to simulate the impact of nitrogen on the plant growth and C cycling. To incorporate the N limitation in the coupled system, we first developed the parameterization for the C/N ratios. Then, after accounting for daily plant/soil N-cycling, N will not only limit the plant growth when not sufficient, causing the net primary productivity (NPP) to be down-regulated, but will also impact plant respiration rates and phenology. Using this newly-developed model named SSiB5/TRIFFID/DayCent-SOM, we conduct several simulations from 1948 to 2007 to predict the global vegetation distribution and terrestrial C cycling, and the results are evaluated with satellite-derived observational data. The sensitivity of the terrestrial C cycle to N processes is also assessed. In general, the coupled model can better reproduce observed emergent properties, including gross primary productivity (GPP), NPP, leaf area index (LAI), and respiration. The main improvement occurs in tropical Africa and boreal regions, accompanied by a decrease of the bias in global GPP and LAI by 16.3% and 27.1%, respectively.