Land Group v2.0 Experiments Plan

Owned by Forrest M. Hoffman (Unlicensed)
Last updated: Nov 03, 2015
4 min read

Simulation Experiments

  • Point simulations

    • Representative sites

    • Super sites

    • Fluxnet sites

  • Manipulation experiments

    • Litter addition

    • Fertilization experiments

    • FACE

    • Warming experiments

  • Partially coupled global simulations

  • Fully coupled regional simulations

  • Fully Coupled global simulations

Experimental Design

  • Focus of experiments should be to:
    1. diagnose/quantify the strength and distribution of model biases,
    2. improve answers to the v1 questions, and
    3. investigate new science questions or hypotheses.
  • Model experiments should be designed to highlight/test/exercise new V2 features:
    • Demonstrate utility of topographic downscaling
    • Explore lateral subsurface processes
    • Test new hydrological processes with thermal physics and transport
    • Test explicit microbial model, wetland hydrology & biogeochemistry, nutrient storage and transport, alternative nutrient cycling approaches, and dynamic vegetation
    • Investigate agricultural impacts on different crop types
    • Address land use change questions through scenario testing
  • We should establish a plan and a schedule to assure we can accomplish all of the experiments we would like to do.
  • For V1 BGC experiments, we borrowed the Historical + RCP 8.5 simulation protocol with alternative atmospheric CO2 coupling (RAD, BGC, FULL) from CMIP5.
  • For V1 Water Cycle experiment, we eliminated experiments for topographic downscaling, which was not fully implemented in v1.

 Biogeochemistry Experiments

The primary focus is to understand and quantify future century-scale changes in land (and ocean) carbon storage and fluxes. Simulations that would achieve this goal could be:

  • idealized experiments to separate and quantify the sensitivity of land (and ocean) carbon cycle to changes in climate and atmospheric CO2,
  • historical experiments to evaluate model performance and investigate the potential for observational constraints on future projects,
  • future scenario experiments to quantify future changes in carbon storage and hence the atmospheric CO2 concentration and related climate change for given CO2 emissions trajectories.

Proposed coupled experiments for the high-throughput model include:

  1. Idealized experiments designed to quantify carbon cycle feedback sensitivities
    1. Idealized 1% per year CO2, BGC coupling, C-driven, constant N-dep, aerosols, CH4 and other GHGs, no crops or LUC or management (140 y)
    2. Idealized 1% per year CO2, RAD coupling, C-driven, constant N-dep, aerosols, CH4 and other GHGs, no crops or LUC or management (140 y)
    3. Idealized 1% per year CO2, FULL coupling, C-driven, constant N-dep, aerosols, CH4 and other GHGs, no crops or LUC or management (140 y)
  2. Idealized experiments designed to quantify the influence of nutrient cycles on carbon cycle feedback sensitivities
    1. Idealized 1% per year CO2, BGC coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, no crops or LUC or management (140 y)
    2. Idealized 1% per year CO2, RAD coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, no crops or LUC or management (140 y)
    3. Idealized 1% per year CO2, FULL coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, no crops or LUC or management (140 y)
  3. Pre-industrial control experiment to quantify residual drift in climate and biogeochemical cycles
    1. 500–1000 y control, C-driven, constant N-dep, aerosols, CH4 and other GHGs, no crops or LUC or management (500–1000 y)
  4. Historical experiments designed to evaluate model performance and investigate emergent constraints
    1. Historical CO2, BGC coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (165 y)
    2. Historical CO2, RAD coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (165 y)
    3. Historical CO2, FULL coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (165 y)
    4. Historical CO2, BGC coupling, E-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (165 y)
    5. Historical CO2, RAD coupling, E-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (165 y)
    6. Historical CO2, FULL coupling, E-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (165 y)
  5. Future scenario experiments to quantify future changes in carbon cycle storage for given CO2 emission trajectories
    1. SSP5-8.5 to 2100, BGC coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (85 y)
    2. SSP5-8.5 to 2100, RAD coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (85 y)
    3. SSP5-8.5 to 2100, FULL coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (85 y)
    4. SSP5-8.5 to 2100, BGC coupling, E-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (85 y)
    5. SSP5-8.5 to 2100, RAD coupling, E-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (85 y)
    6. SSP5-8.5 to 2100, FULL coupling, E-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (85 y)
  6. Extension of future scenario experiments to quantify non-linear carbon cycle feedbacks, strengthening of biogeophysical & biogeochemical feedbacks, and shifting strength of ocean and land feedbacks
    1. SSP-8.5 to 2300, BGC coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (200 y)
    2. SSP-8.5 to 2300, RAD coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (200 y)
    3. SSP-8.5 to 2300, FULL coupling, C-driven, increasing N-dep, aerosols, CH4 and other GHGs, dynamic crops and LUC and management (200 y)

Water Cycle Experiments

To continue to explore the role of processes and parameterizations influencing river flow and fresh water supply, we will systematically explore the sensitivity of atmospheric and surface water budgets simulated in river basins to improvements in the ACME model by isolating the effects of

  • resolution
  • treatments of clouds and aerosols,
  • subgrid orographic effects,
  • surface/subsurface hydrology,
  • human activities (including water management), and
  • ocean–atmosphere interactions.

For V2, the focus will be on investigating subgrid orographic effects, riverine biogeochemistry (including outflow to the oceans), lateral subsurface hydrology, human water management.

Cryosphere Experiments