Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation-fire model SSiB4/TRIFFID-Fire v1.0

Abstract

Abstract. Fire is one of the primary disturbances to the distribution and ecological properties of the world’s major biomes and can influence the surface fluxes and climate through vegetation-climate interactions. This study incorporates a fire model of intermediate complexity to a biophysical model with dynamic vegetation, SSiB4/TRIFFID (The Simplified Simple Biosphere Model coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model). This new model, SSiB4/TRIFFID-Fire, updating fire impact on the terrestrial carbon cycle every 10 days, is then used to simulate the burned area during 1948–2014. The simulated global burned area in 2000–2014 is 471.9 Mha yr−1, close to the estimate, 478.1 Mha yr−1, in Global Fire Emission Database v4s (GFED4s) with a spatial correlation of 0.8. The SSiB4/TRIFFID-Fire reproduces temporal variations of the burned area at monthly to interannual scales. Specifically, it captures the observed decline trend in northern African savanna fire and accurately simulates the fire seasonality in most major fire regions. The simulated fire carbon emission is 2.19 Pg yr−1, slightly higher than the GFED4s (2.07 Pg yr−1). The SSiB4/TRIFFID-Fire is applied to assess long-term fire impact on ecosystem characteristics and surface energy budget by comparing model runs with and without fire (FIRE-ON minus FIRE-OFF). The FIRE-ON simulation reduces tree cover over 6.14 % of the global land surface, accompanied by a decrease in leaf area index and vegetation height by 0.13 m2 m−2 and 1.27 m, respectively. The surface albedo and sensible heat are reduced throughout the year, while latent heat flux decreases in the fire season but increases in the rainy season. Fire results in an increase in surface temperature over most fire regions.

Development of a plant carbon-nitrogen interface coupling framework in a coupled biophysical-ecosystem-biogeochemical model (SSiB5/Triffid/DayCent-SOM v1.0): Its parameterization, implementation, and evaluation

“…PFT coverage is determined by net C availability, competition between species, and disturbance, which includes mortality due to fires, pests, and windthrow. A detailed description and validation of SSiB4/TRIFFID can be found in Zhang et al (2015), Liu et al (2019), and Huang et al (2020). In this study, The DayCent-SOM (see next section) is introduced and coupled with the SSiB5/TRIFFID using the C-N interface coupling framework introduced in this study, which will be discussed in Section 2.2.…”

“…There are different ways to initialize the surface condition for the quasi-equilibrium simulation. Following previous SSiB4/TRIFFID studies (Huang et al, 2020;Liu et al, 2019;Zhang et al, 2015), we set up the initial condition for the run using the SSiB vegetation map and SSiB vegetation table, which are based on ground surveys and satellite-derived information (Dorman and Sellers, 1989;Sellers et al, 1986;Xue et al, 2004;Zhang et al, 2015) with 100% occupation at each grid point for the dominant PFT and zero for other PFTs. We then ran the SSiB4/TRIFFID model with the climate forcing and the atmospheric CO2 concentration at 1948 level for 100 years to reach equilibrium conditions.…”

A plant carbon-nitrogen interface coupling framework in a coupled biophysical-ecosystem-biogeochemical model, SSiB version5/TRIFFID/DayCent-SOM: Its parameterization, implementation, and evaluation

“…PFT coverage is determined by net C availability, competition between species, and disturbance, which includes mortality due to fires, pests, and windthrow. A detailed description and validation of SSiB4/TRIFFID can be found in Zhang et al, (2015), Liu et al, (2019), andHuang et al (2020). In this study, The DayCent-SOM (see next section) is introduced and coupled with the SSiB5/TRIFFID using the C-N interface coupling framework introduced in this study, which will be discussed in Section 4.…”

“…There are different ways to initialize the surface condition for the quasi-equilibrium simulation. Following previous SSiB4/TRIFFID studies (Zhang et al, 2015;Liu et al, 2019;Huang et al, 2020), we set up the initial condition for the run using the SSiB vegetation map and SSiB vegetation table, which are based on ground surveys and satellite-derived information (Dorman & Sellers, 1989;Sellet et al, 1996;Xue et al, 2004;Zhang et al, 2015) with 100% occupation at each grid point for the dominant PFT and zero for other PFTs. We then ran the SSiB4/TRIFFID model with the climate forcing for 100 years to reach equilibrium conditions.…”