4.7 Article

Initial Land Use/Cover Distribution Substantially Affects Global Carbon and Local Temperature Projections in the Integrated Earth System Model

期刊

GLOBAL BIOGEOCHEMICAL CYCLES
卷 34, 期 5, 页码 -

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2019GB006383

关键词

ESM; land use; land cover; carbon; climate; uncertainty

资金

  1. US Department of Energy, Office of Science, Office of Biological and Environmental Research [DE-AC02-05CH11231]
  2. E3SM project
  3. Biogeochemistry-Climate Feedbacks Scientific Focus Area project 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 Departme
  4. DOE [DE-AC05-00OR22725, DE-AC05-76RL01830]
  5. National Science Foundation
  6. Office of Science (Biological and Environmental Research) of the US Department of Energy
  7. U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling program
  8. U.S. Department of Energy [DE-AC02-05CH11231]

向作者/读者索取更多资源

Initial land cover distribution varies among Earth system models, an uncertainty in initial conditions that can substantially affect carbon and climate projections. We use the integrated Earth System Model to show that a 3.9 M km(2) difference in 2005 global forest area (9-14% of total forest area) generates uncertainties in initial atmospheric CO2 concentration, terrestrial carbon, and local temperature that propagate through a future simulation following the Representative Concentration Pathway 4.5. By 2095, the initial 6 ppmv uncertainty range increases to 9 ppmv and the initial 26 PgC uncertainty range in terrestrial carbon increases to 33 PgC. The initial uncertainty range in annual average local temperature of -0.74 to 0.96 degrees C persists throughout the future simulation, with a seasonal maximum in Dec-Jan-Feb. These results highlight the importance of accurately characterizing historical land use and land cover to reduce overall initial condition uncertainty.

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