U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Earth System Estimates
Published: January 23, 2018
Posted: April 09, 2018

Impacts of land cover conversion uncertainty on carbon and Earth system estimates.

The Science
Land cover conversion uncertainty constitutes a 5 ppmv range in estimated 2004 atmospheric CO2 concentration, a range of 2004 terrestrial carbon stock uncertainty that is 80% of net historical CO2 and climate effects on this stock, and over 1 °C range in local surface temperature estimates (1984-2004 average).

The Impact
Global socioeconomic and Earth system modeling efforts, such as phase 5 of the Coupled Model Intercomparison Project (CMIP5), aim to provide understanding of potential Earth system change given scenarios of human economic and agricultural activity. However, only land use scenarios were harmonized across models, with each Earth System Model (ESM) using a unique implementation for Land Use and Land Cover Change (LULCC). As LULCC has both biophysical and biogeochemical effects on the Earth system, different implementations of the same land use scenario can constitute vastly different ESM LULCC scenarios, with corresponding differences in regional and global and climate projections. Thus it is imperative that scenario-based global modeling efforts aim to standardize land use and land cover data to reduce uncertainties.

In order to help people adjust to and lessen the local impacts of global change, international modeling efforts aim to understand global change and its impacts on humans and the environment. Most human activities are on land, such as living, agriculture, and wood harvesting, and these activities both contribute to and are affected by global change. Modeling how these activities change vegetation cover, and subsequently the greater environment, is difficult and highly uncertain, yet crucial to understanding impacts of global change. Here, we estimate an uncertainty in year-2004 global forest cover of 5.1 km2 using one historical agriculture pattern, and corresponding uncertainties of 5ppmv in atmospheric carbon dioxide concentration and greater than 1°C in local surface temperature. The associated uncertainty in land carbon storage is 80% of the estimated additional carbon stored due to historical changes in carbon dioxide concentration and climate, and 124% of the additional carbon attributed to nitrogen deposition. We conclude that future studies of global change and its impacts on humans and the environment need to constrain and reduce land cover uncertainties.

Contacts (BER PM)
Bob Vallario
Integrated Assessment Research

Renu Joseph
Regional and Global Climate Modeling

Dorothy Koch
Earth System Modeling

(PI Contact)
Alan Di Vittorio
Lawrence Berkeley National Laboratory
avdivittorio@lbl.gov (510-486-7798)

This work is supported by the Director, Office of Science, Office of Biological and Environmental Research of the US Department of Energy under Award No. DEAC02-05CH11231 as part of the Integrated Assessment Research and Earth System Modeling Programs and with additional support from the Accelerated Climate Modeling for Energy project. J.Mao and X.Shi are also supported by the Biogeochemistry-Climate Feedbacks Scientific Focus Area project funded through the Regional and Global Climate Modeling Program in the Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the US Department of Energy Office of Science. G. Hurtt and L. Chini gratefully acknowledge the support of NASA-IDS and DOE-SciDAC programs. Oak Ridge National Laboratory is managed by UT-BATTELLE for DOE under contract DE-AC05-00OR22725. This project used resources of the National Energy Research Scientific Computing Center (NERSC), which is a DOE Office of Science user Facility. The CESM project is supported by the National Science Foundation and the Office of Science (Biological and Environmental Research) of the US Department of Energy. The authors also acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation.

Di Vittorio, A.V., J. Mao, X. Shi, L. Chini, G. Hurtt, and W.D. Collins, "Quantifying the effects of historical land cover uncertainty on global carbon and climate estimates." Geophysical Research Letters 45, 974-982, 2018. [DOI:10.1002/2017GL075124]

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Multisector Dynamics (formerly Integrated Assessment)
  • Cross-Cutting: Scientific Computing and SciDAC

Division: SC-23.1 Climate and Environmental Sciences Division, BER


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