Abstract
Abstract. Reliable soil biogeochemical modeling is a prerequisite for credible projections of climate change and associated ecosystem feedbacks. This recognition has called for frameworks that can support flexible and efficient development and application of new or alternative soil biogeochemical modules in Earth system models (ESMs). The the Biogeochemical Transport and Reaction model version 1 (BeTR-v1) code (i.e., CLM4-BeTR) is one such framework designed to accelerate the development and integration of new soil biogeochemistry formulations into ESMs and to analyze structural uncertainty in ESM simulations. With a generic reactive transport capability, BeTR-v1 can represent multiphase (e.g., gaseous, aqueous, and solid), multi-tracer (e.g., nitrate and organic carbon), and multi-organism (e.g., plants, bacteria, and fungi) dynamics. Here, we describe the new version, Biogeochemical Transport and Reaction model version 2 (BeTR-v2), which adopts more robust numerical solvers for multiphase diffusion and advection and coupling between biogeochemical reactions and improves code modularization over BeTR-v1. BeTR-v2 better supports different mathematical formulations in a hierarchical manner by allowing the resultant model be run for a single topsoil layer or a vertically resolved soil column, and it allows the model to be fully coupled with the land component of the Energy Exascale Earth System Model (E3SM). We demonstrate the capability of BeTR-v2 with benchmark cases and example soil biogeochemical (BGC) implementations. By taking advantage of BeTR-v2's generic structure integrated in E3SM, we then found that calibration could not resolve biases introduced by different numerical coupling strategies of plant–soil biogeochemistry. These results highlight the importance of numerically robust implementation of soil biogeochemistry and coupling with hydrology, thermal dynamics, and plants – capabilities that the open-source BeTR-v2 provides. We contend that Earth system models should strive to minimize this uncertainty by applying better numerical solvers.
Highlights
Soil biogeochemical (BGC) modeling is essential for predicting terrestrial ecosystem dynamics in natural and managed lands and is an important component of Earth system models (ESMs) that perform projections and hindcasts of ecosystem–climate feedbacks (e.g., Golaz et al, 2019, Hurrell et al, 2013)
We made better use of the object-oriented programming feature of Fortran 2003 to enable more efficient code sharing among the Fortran modules. All of these are integrated into the Biogeochemical Transport and Reaction model version 2 (BeTR-v2): a platform to accelerate soil BGC model development and enable efficient code and knowledge sharing among ESM BGC components
We found that the BeTR-v2 advection–diffusion solver solutions agreed well with the analytical solutions for both benchmarking cases (Fig. 1)
Summary
Soil biogeochemical (BGC) modeling is essential for predicting terrestrial ecosystem dynamics in natural and managed lands and is an important component of Earth system models (ESMs) that perform projections and hindcasts of ecosystem–climate feedbacks (e.g., Golaz et al, 2019, Hurrell et al, 2013). When the 1-D diffusion equation is solved with central difference in both time and space, the numerical solution approximates a wave equation instead, and this deficiency cannot be fixed by calibration Both types of inference error will contribute to the uncertainty of climate–biogeochemistry feedback simulated by ESMs. For point (3), aqueous environments, such as wetlands, groundwater, rivers, lakes, and oceans, share many biogeochemical processes with soils, but different representations are often used (e.g., early diagenesis in marine sediments vs terrestrial soil organic matter decomposition; Koven et al, 2013; Munhoven, 2021). We made better use of the object-oriented programming feature of Fortran 2003 to enable more efficient code sharing among the Fortran modules All of these are integrated into the Biogeochemical Transport and Reaction model version 2 (BeTR-v2): a platform to accelerate soil BGC model development and enable efficient code and knowledge sharing among ESM BGC components. We describe the improvements that have brought into BeTR-v2 since BeTR-v1 in detail, give some examples based on its integration with the land module of the Energy Exascale Earth System Model (ELM; Burrows et al, 2020), and apply the model to evaluate whether parameter calibration can resolve the uncertainty associated with different numerical implementations
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