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Data · dataset · 2026

Matrix approach to accelerate spin-up of CLM5

Listed in National Center for Atmospheric Research

Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes.

Description

Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin-up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles.

This study introduces a new Semi-Analytical Spin-Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin-up to reach the same steady state.

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Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin-up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin-up on site and globally in comparison with other spin-up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.

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Atmospheric sciences 69%
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National Center for Atmospheric Researchbf5330ae-2768-4308-8c8c-7579e4379fb313 d agoJSON v1
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concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
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