geoms_metadata.toml Reference

The geoms_metadata.toml file contains all information on how the Pipeline should generate GEOMS files: which metadata to put in (authors, etc.) and which calibration factors to use.

Example:

# METADATA

[general]
network = "FTIR.COCCON"
affiliation = "TUM.ESM"
pressure_sensor_name = "vaisala-PTB330"

[data]
discipline = "ATMOSPHERIC.CHEMISTRY;REMOTE.SENSING;GROUNDBASED"
group = "EXPERIMENTAL;PROFILE.STATIONARY"
file_version = 1
quality = "Station data."
template = "GEOMS-TE-FTIR-COCCON-001"

[file]
doi = ""
meta_version = "04R088;CUSTOM"
access = "COCCON"
project_id = "COCCON"

[principle_investigator]
name = "Chen;Jia"
email = "jia.chen@tum.de"
affiliation = "Technical University of Munich - Professorship of Environmental Sensing and Modeling;TUM.ESM"
address = "Theresienstr. 90;D-80333 Munich;GERMANY"

[data_originator]
name = "Makowski;Moritz"
email = "moritz.makowski@tum.de"
affiliation = "Technical University of Munich - Professorship of Environmental Sensing and Modeling;TUM.ESM"
address = "Theresienstr. 90;D-80333 Munich;GERMANY"

[data_submitter]
name = "Makowski;Moritz"
email = "moritz.makowski@tum.de"
affiliation = "Technical University of Munich - Professorship of Environmental Sensing and Modeling;TUM.ESM"
address = "Theresienstr. 90;D-80333 Munich;GERMANY"

[locations]
TUM_I = "MUNICH.TUM"
FEL = "MUNICH.FELDKIRCHEN"
GRAE = "MUNICH.GRAEFELFING"
OBE = "MUNICH.OBERSCHLEISSHEIM"
TAU = "MUNICH.TAUFKIRCHEN"
DLR_2 = "MUNICH.DLR_2"
DLR_3 = "MUNICH.DLR_3"

# CALIBRATION FACTORS

[[calibration_factors]]
sensor_id = "ma"
valid_from_datetime = "2019-01-01T00:00:00Z"
valid_to_datetime = "2019-12-31T23:59:59Z"
xco2 = 1.0000
xch4 = 1.0000
xco = 1.0000
xh2o = 1.0000

[[calibration_factors]]
sensor_id = "mb"
valid_from_datetime = "2019-01-01T00:00:00Z"
valid_to_datetime = "2019-12-31T23:59:59Z"
xco2 = 1.0005
xch4 = 1.0005
xco = 1.0005
xh2o = 1.0005

[[calibration_factors]]
sensor_id = "ma"
valid_from_datetime = "2020-01-01T00:00:00Z"
valid_to_datetime = "2024-12-31T23:59:59Z"
xco2 = 1.0010
xch4 = 1.0010
xco = 1.0010
xh2o = 1.0010

---

Metadata

---

general

network

[string]

* required

Used in the filename of the HDF5 file

Examples:

- "FTIR.COCCON"

affiliation

[string]

* required

Used in the filename of the HDF5 file

Examples:

- "TUM.ESM"

pressure_sensor_name

[string]

* required

The value of the HDF5 attribute `SURFACE.PRESSURE_INDEPENDENT_SOURCE`

Examples:

- "young-61302"

- "vaisala-PTB330"

---

data

discipline

[string]

* required

The value of the HDF5 attribute `DATA_DISCIPLINE`

Examples:

- "ATMOSPHERIC.CHEMISTRY;REMOTE.SENSING;GROUNDBASED"

group

[string]

* required

The value of the HDF5 attribute `DATA_GROUP`

Examples:

- "EXPERIMENTAL;PROFILE.STATIONARY"

file_version

[integer]

* required

The value of the HDF5 attribute `DATA_FILE_VERSION`

Examples:

- 1

quality

[string]

* required

The value of the HDF5 attribute `DATA_QUALITY`

Examples:

- "Station data."

template

[string]

* required

The value of the HDF5 attribute `DATA_TEMPLATE`

Examples:

- "GEOMS-TE-FTIR-COCCON-001"

---

file

doi

[string]

* required

The value of the HDF5 attribute `FILE_DOI`

meta_version

[string]

* required

The value of the HDF5 attribute `FILE_META_VERSION`

Examples:

- "04R088;CUSTOM"

access

[string]

* required

The value of the HDF5 attribute `FILE_ACCESS`

Examples:

- "COCCON"

project_id

[string]

* required

The value of the HDF5 attribute `FILE_PROJECT_ID`

Examples:

- "COCCON"

---

principle_investigator

name

[string]

* required

The value of the HDF5 attribute `PI_NAME`/`DO_NAME`/`DS_NAME`

Examples:

- "Makowski;Moritz"

email

[string]

* required

The value of the HDF5 attribute `PI_EMAIL`/`DO_EMAIL`/`DS_EMAIL`

Examples:

- "moritz.makowski@tum.de"

affiliation

[string]

* required

The value of the HDF5 attribute `PI_AFFILIATION`/`DO_AFFILIATION`/`DS_AFFILIATION`

Examples:

- "Technical University of Munich - Professorship of Environmental Sensing and Modeling;TUM.ESM"

address

[string]

* required

The value of the HDF5 attribute `PI_ADDRESS`/`DO_ADDRESS`/`DS_ADDRESS`

Examples:

- "Theresienstr. 90;D-80333 Munich;GERMANY"

---

data_originator

Same schema as the principle_investigator field

---

data_submitter

Same schema as the principle_investigator field

---

locations

Contains: Maps your locations id to the corresponding EVDC location id. It is just an object of strings to strings.

---

Calibration Factors

A list of calibration factor definitions to be applied to the data.

---

calibration_factors[i]

sensor_id

[string]

* required

The sensor id of the sensor for which the calibration factors are valid.

valid_from_datetime

[string]

* required

UTC datetime in format `YYYY-MM-DDTHH:MM:SSZ` or `YYYY-MM-DDTHH:MM:SS+0000`. Non-UTC times are not allowed.

Regex Pattern: "^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(?:Z|\+0000)$"

valid_to_datetime

[string]

* required

UTC datetime in format `YYYY-MM-DDTHH:MM:SSZ` or `YYYY-MM-DDTHH:MM:SS+0000`. Non-UTC times are not allowed.

Regex Pattern: "^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(?:Z|\+0000)$"

xco2

[number]

* required

Calibration factor for carbon dioxide: xco2_cal = xco2_raw * factor

Minimum: 0.001

Maximum: 1000

xch4

[number]

* required

Calibration factor for methane: xch4_cal = xch4_raw * factor

Minimum: 0.001

Maximum: 1000

xco

[number]

* required

Calibration factor for carbon monoxide: xco_cal = xco_raw * factor

Minimum: 0.001

Maximum: 1000

xh2o

[number]

* required

Calibration factor for water vapor: xh2o_cal = xh2o_raw * factor

Minimum: 0.001

Maximum: 1000

---