Prioritizing forestation based on biogeochemical and local biogeophysical impacts, Windisch et al.

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How to run

Create output data

Always specify in and output paths first as indicated by "SPECIFY IN/OUTPUT PATH" in the code. The main output calculation is performed by 2_full_calc_bgp_v_bgc.py which imports functions from functions.py and depends on output from 1_biomass_potential.py.

Analyse output data

Jupyter Notebook scripts for figure creation and result analysis are prepared in the folder /output_analysis. For proper function the scripts need to be executed from top to bottom as they are separated into loading datasets and figure creation / analysis.

Necessary external datasets

GLC2000 land cover map:

https://cdiac.ess-dive.lbl.gov/epubs/ndp/global_carbon/carbon_documentation.html

As [0,1] masks of:

nonforest: 10<=x<=19 # in code call "nonforest_mask_GLC2000_gte10lte19"
grassland: x=13 # in code call "gra_mask_GLC2000_eq_13"
cropland: 16<=x<=18 # in code call "cro_mask_GLC2000_eq_16_17_18"
shrubland: x=11;x=12;x=15 # in code call "shr_mask_GLC2000_eq_11_12_15"

IPCC Tier 1 biomass:

https://cdiac.ess-dive.lbl.gov/epubs/ndp/global_carbon/carbon_documentation.html

As full dataset and forest specific biomass prepared by multiplying with GLC2000 land cover classes (numbers provided below)

full dataset # in code call "20181023_IPCC_Biomass"

forest specific biomass only
evergreen broadleaf: x=1 # in code call "ebf_biomass"
decideous broadleaf: x=2;x=3 # in code call "dbf_biomass"
evergreen needleleaf: x=4 # in code call "enf_biomass"
decideous needleleaf: x=5 # in code call "dnf_biomass"
other forest types: 6<=x<=9 # in code call "otf_biomass"

Standard deviation of biomass, Erb et al. 2017:

https://www.nature.com/articles/nature25138.

As forest specific biomass prepared by multiplying with GLC2000 land cover classes (numbers provided below)

forest specific biomass only
evergreen broadleaf: x=1 # in code call "ebf_biomass_max/min_1SD"
decideous broadleaf: x=2;x=3 # in code call "dbf_biomass_max/min_1SD"
evergreen needleleaf: x=4 # in code call "enf_biomass_max/min_1SD"
decideous needleleaf: x=5 # in code call "dnf_biomass_max/min_1SD"
other forest types: 6<=x<=9 # in code call "otf_biomass_max/min_1SD"

Soil organic carbon, Sanderman et al. 2017:

https://www.pnas.org/content/114/36/9575.short

full dataset # in code call "SOCS_0_30cm_year_NoLU_10km"

BGP temperature change, Duveiller et al. 2018; Bright et al. 2017:

https://www.nature.com/articles/s41467-017-02810-8
https://www.nature.com/articles/nclimate3250

Duveiller # in code call "D18_LST_IGBPdet"
Bright # in code call "B17_DTS"

Transient (after doubling of CO2) surface temperature ("ts") response to cumulative emissions of +1% CO2 ESM experiments:

Please see method section of the manuscript for detailed information about the experiment setup.

monthly ensemble mean # in code call "mean_ensemble"
monthly ensemble standard deviation # in code call "std_ensemble"

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bgpvbgc's Introduction

Prioritizing forestation based on biogeochemical and local biogeophysical impacts, Windisch et al.

Contact

Citation

How to run

Create output data

Analyse output data

Necessary external datasets

GLC2000 land cover map:

IPCC Tier 1 biomass:

Standard deviation of biomass, Erb et al. 2017:

Soil organic carbon, Sanderman et al. 2017:

BGP temperature change, Duveiller et al. 2018; Bright et al. 2017:

Transient (after doubling of CO2) surface temperature ("ts") response to cumulative emissions of +1% CO2 ESM experiments:

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