PU_BGC_diagram

Set of experiment setings and python scripts for plotting diagrams for PU_BGC paper

Updates

• [02/28/2025] cmems_instac_loader.py and config_user.yaml added

List of scripts

• cmems_instac_loader.py to download Global Ocean - Delayed Mode Biogeochemical product with Copernicus Marine Toolbox
• diagram_taylor.py to plot modified Taylor diagram (Note: under development)

Usages

plot sample Taylor diagram

python diagram_taylor.py

check usage of cmems_instac_loader.py

python cmems_instac_loader.py

NOTE: Rewrite config_user.yaml to register your Copernicus Marine credentials before using cmems_instac_loader.py

Experiment Setups

Metrices for PU_BGC BIO_MY diagnosis with model ensemble

• Period: 5 years (e.g., 2017-2021 for ARC MFC)
• Model:
  • MFC BIO MY with data assimilation (CMEMS product)
  • MFC BIO MY without data assimilation (control experiment)
• Model subdomains:
  • ARC MFC Norwegian Sea
  • ARC MFC Greenland Sea
  • ARC MFC Subpolar Gyre
  • other MFCs subdomains (e.g., MED WEST and MED EAST)
• Independent Observations (Reference):
  • CMEMS INSTAC Global Ocean - Delayed Mode Biogeochemical product
    • BGC Argo float data (PF): Chlorophyll-a, BBP/POC, Oxygen, Nitrate
    • Bottle sampled in situ data (BO): Chlorophyll-a, Nitreate, Silicate, Phosphate, Oxygen
• Variables [unit]:
  • 0-100m Nitrate [mmol/m3]
  • 100-400m Nitrate [mmol/m3]
  • 0-100m Phosphate [mmol/m3]
  • 100-400m Phosphate [mmol/m3]
  • 0-100m Silicate [mmol/m3]
  • 100-400m Silicate [mmol/m3]
  • 0-100m Nitrate [mmol/m3]
  • 100-400m Nitrate [mmol/m3]
  • 0-100m Chlorophyll-a [mg/m3]
  • 100-400m Chlorophyll-a [mg/m3]
  • 0-100m POC [mg/m3]
  • 100-400m POC [mg/m3]
  • 0-100m Oxygen [mmol/m3]
  • 100-400m Oxygen [mmol/m3]

Modified Taylor diagram (see Taylor 2005)

Sample modified Taylor diagram creatd by diagram_taylor.py. Data used in the sample plot are bogus. Input data are set of standard deviation, Pearson correlation in sample() specified by

    stdref = 48.491 # reference (observation) standard deviation
    stats = [
        [25.939, 0.385, "ARC NWS"], 
        [29.593, 0.509, "ARC SPG"],
        [33.125, 0.585, "MED EAST"], 
        [35.807, 0.609, "MED WEST"]
    ]
    # [standard deviation, Pearson correlation, label]

Since it does not accept different source of data yet, the code will be modified soon so that data can be imported by YAML file of the form:

datasets:
  - name: "ARC NRW"
    reference_stddev: 48.491
    stddev: 25.939
    correlation: 0.385

  - name: "ARC SPG"
    reference_stddev: 50.123
    stddev: 29.593
    correlation: 0.509

  - name: "MED WST"
    reference_stddev: 45.678
    stddev: 33.125
    correlation: 0.585

  - name: "MED EST"
    reference_stddev: 48.491
    stddev: 29.593
    correlation: 0.509