Matrix Approach to Accelerate Spin-Up of CLM5

Cuijuan Liao, Xingjie Lu, Yuanyuan Huang, Feng Tao, David M. Lawrence, Charles D. Koven, Keith W. Oleson, William R. Wieder, Erik Kluzek, Xiaomeng Huang, Yiqi Luo

Research output: Contribution to journalArticlepeer-review

Abstract

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

Original languageEnglish (US)
Article numbere2023MS003625
JournalJournal of Advances in Modeling Earth Systems
Volume15
Issue number8
DOIs
StatePublished - Aug 2023
Externally publishedYes

Keywords

  • carbon cycle
  • spin-up
  • terrestrial biogeochemistry model

ASJC Scopus subject areas

  • Global and Planetary Change
  • Environmental Chemistry
  • General Earth and Planetary Sciences

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