Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO2 Flux and its Inter-Annual Variability

Kashif Mahmud, Russell L. Scott, Joel A. Biederman, Marcy E. Litvak, Thomas Kolb, Tilden P. Meyers, Praveena Krishnan, Vladislav Bastrikov, Natasha MacBean

Research output: Contribution to journalArticlepeer-review

Abstract

Drylands occupy ∼40% of the land surface and are thought to dominate global carbon (C) cycle inter-annual variability (IAV). Therefore, it is imperative that global terrestrial biosphere models (TBMs), which form the land component of IPCC earth system models, are able to accurately simulate dryland vegetation and biogeochemical processes. However, compared to more mesic ecosystems, TBMs have not been widely tested or optimized using in situ dryland CO2 fluxes. Here, we address this gap using a Bayesian data assimilation system and 89 site-years of daily net ecosystem exchange (NEE) data from 12 southwest US Ameriflux sites to optimize the C cycle parameters of the ORCHIDEE TBM. The sites span high elevation forest ecosystems, which are a mean sink of C, and low elevation shrub and grass ecosystems that are either a mean C sink or “pivot” between an annual C sink and source. We find that using the default (prior) model parameters drastically underestimates both the mean annual NEE at the forested mean C sink sites and the NEE IAV across all sites. Our analysis demonstrated that optimizing phenology parameters are particularly useful in improving the model's ability to capture both the magnitude and sign of the NEE IAV. At the forest sites, optimizing C allocation, respiration, and biomass and soil C turnover parameters reduces the underestimate in simulated mean annual NEE. Our study demonstrates that all TBMs need to be calibrated for dryland ecosystems before they are used to determine dryland contributions to global C cycle variability and long-term carbon-climate feedbacks.

Original languageEnglish (US)
Article numbere2021JG006400
JournalJournal of Geophysical Research: Biogeosciences
Volume126
Issue number10
DOIs
StatePublished - Oct 2021

Keywords

  • carbon cycle
  • data assimilation
  • drylands
  • terrestrial biosphere modeling

ASJC Scopus subject areas

  • Soil Science
  • Forestry
  • Water Science and Technology
  • Palaeontology
  • Atmospheric Science
  • Aquatic Science
  • Ecology

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