Representing nitrogen phosphorus and carbon interactions in the
Representing nitrogen, phosphorus, and carbon interactions in the E 3 SM Land Model: Development and global benchmarking Scientific Achievement • • • We developed a new carbon-nitrogen-phosphorus land model (ELMv 1 -ECA) integrated in the E 3 SM earth system model. We benchmarked the simulated present-day carbon cycle using the Internationa Land Model Benchmarking package (ILAMB). We documented model performance and identified necessary future improvements. Significance and Impact Figure 1. Illustration of Energy Exascale Earth System Model (E 3 SM) Land Model version 1‐Equilibrium Chemistry Approximation (ELMv 1‐ECA) major features: (1) prognostic leaf N and P content directly coupled to leaf level CO 2 sequestration; (2) multiple ‐consumer competition network for soil nutrients including NH 4+, NO 3‐, and POx; and (3) dynamic carbon allocation for leaf, stem, and root Zhu Q. , W. Riley, J. Tang, N. Collier, F. Hoffman, X. Yang, G. Bisht. “Representing Nitrogen, Phosphorus, and Carbon Interactions in the E 3 SM Land Model: Development and Global Benchmarking” Journal of Advances in Modeling Earth Systems (2019) https: //doi. org/10. 1029/2018 MS 001571 Modeling C/N/P dynamics is an important step towards better predicting and understanding future climate. In this study, we present a new land model that mechanistically simulates terrestrial ecosystem C/N/P processes and evaluate the model against multiple large-scale datasets. We demonstrate the novelty of the model and show that the model significantly outperforms its predecessor versions Research Details We introduce a new approach to model multi-nutrient (nitrogen (N), phosphorus (P)) limitations in the Energy Exascale Earth System Model (E 3 SM) Land Model version 1 (ELMv 1 -ECA), grounded on (1) advances in representing multipleconsumer, multiple-nutrient competition; (2) a generic dynamic allocation scheme based on water, N, P, and light availability; (3) flexible plant CNP stoichiometry; (4) prognostic treatment of N and P constraints on several carbon cycle processes; and (5) global datasets of plant physiological traits. Compared with predecessor versions, ELMv 1 -ECA better predicts global-scale gross primary productivity, ecosystem respiration, leaf area index, vegetation biomass, soil carbon stocks, evapotranspiration, N 2 O emissions, and NO 3 - leaching.
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