Spatially explicit terrestrial carbon densities for calibrating the carbon cycle in human-Earth system Models

Area of Science:

• Earth System Science
• Climate Modeling
• Ecology

Background:

• Soil and vegetation carbon stocks are crucial components of human-Earth system models.
• These carbon stocks influence land use change emissions and pathways under climate forcing scenarios.
• Accurate carbon stock data is vital for simulating climate change impacts and policy responses.

Purpose of the Study:

• To present reharmonized soil and vegetation carbon density data at high resolution.
• To define statistical carbon states based on carbon distribution within land types.
• To improve the initial conditions for soil and vegetation carbon in human-Earth system models.

Main Methods:

• Reharmonized soil and vegetation carbon densities at 5-arcmin resolution and aggregated to 235 watersheds.
• Categorization of carbon densities across four land use types and 15 land cover types.
• Development of statistical carbon states based on intra-pixel carbon distribution.

Main Results:

• New, high-resolution datasets for soil and vegetation carbon densities are available.
• Statistical carbon states provide a range of possible carbon values for model initialization.
• Implementation in the Global Change Analysis Model (GCAM) demonstrated improved land use responses.

Conclusions:

• The reharmonized carbon density data and statistical states enhance human-Earth system model accuracy.
• Improved land use responses are particularly evident when terrestrial carbon is priced.
• This work provides a valuable resource for climate change research and policy modeling.