Assimilation of Global Satellite Leaf Area Estimates Reduces Modeled Global Carbon Uptake and Energy Loss by Terrestrial Ecosystems

Andrew M. Fox, Xueli Huo, Timothy J. Hoar, Hamid Dashti, William K. Smith, Natasha MacBean, Jeffrey L. Anderson, Matthew Roby, David J.P. Moore

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Carbon, water and energy exchange between the land and atmosphere controls how ecosystems either accelerate or ameliorate the effect of climate change. However, evaluating improvements to processes controlling carbon cycling, water use and energy exchange in global land surface models (LSMs) remains challenging in part because of persistent model errors in estimating leaf area. Here we evaluate the changes in global carbon, water and energy exchange brought about when a LSM prognostic estimates of leaf area are made consistent with estimates from satellites. This approach achieves two aims; first to quantify the effect of ignoring errors in leaf area index (LAI) on land-atmosphere fluxes and second, to evaluate how closely this LSM replicates fluxes with and without an LAI constraint. We implemented an ensemble Kalman filter with spatiotemporal adaptive inflation to more closely match community land model (CLM5.0) estimates of leaf area to those from the Global Inventory Modeling and Mapping Studies leaf area index (LAI3g) product. We then evaluate the model's estimates of gross primary productivity (GPP) and latent heat flux (LE) against well established global estimates of these fluxes. We find that the model is biased high by 27% relative to the LAI3g product. Moreover, the effect of bias in LAI is substantial for GPP (18%) and LE (6%) and likely to confound efforts to refine processes controlling these fluxes. This data assimilation approach serves as a method to evaluate the efficacy of refinements to flux processes until the processes controlling the dynamics of LAI are better resolved in LSMs.

Original languageEnglish (US)
Article numbere2022JG006830
JournalJournal of Geophysical Research: Biogeosciences
Issue number8
StatePublished - Aug 2022


  • carbon cycle
  • community land model
  • data assimilation
  • leaf area index

ASJC Scopus subject areas

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


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