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25.2. Physical Representation
Is Required: TRUE Type: ENUM Cardinality: 1.N
Physical representation of cloud liquid droplets in the longwave radiation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.radiation.longwave_cloud_liquid.physical_representation')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "cloud droplet number concentration"
# "effective cloud droplet radii"
# "droplet size distribution"
# "liquid water path"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
25.3. Optical Methods
Is Required: TRUE Type: ENUM Cardinality: 1.N
Optical methods applicable to cloud liquid droplets in the longwave radiation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.radiation.longwave_cloud_liquid.optical_methods')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "geometric optics"
# "Mie theory"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
26. Radiation --> Longwave Cloud Inhomogeneity
Cloud inhomogeneity in the longwave radiation scheme
26.1. Cloud Inhomogeneity
Is Required: TRUE Type: ENUM Cardinality: 1.1
Method for taking into account horizontal cloud inhomogeneity | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.radiation.longwave_cloud_inhomogeneity.cloud_inhomogeneity')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "Monte Carlo Independent Column Approximation"
# "Triplecloud"
# "analytic"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
27. Radiation --> Longwave Aerosols
Longwave radiative properties of aerosols
27.1. General Interactions
Is Required: TRUE Type: ENUM Cardinality: 1.N
General longwave radiative interactions with aerosols | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.radiation.longwave_aerosols.general_interactions')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "scattering"
# "emission/absorption"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
27.2. Physical Representation
Is Required: TRUE Type: ENUM Cardinality: 1.N
Physical representation of aerosols in the longwave radiation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.radiation.longwave_aerosols.physical_representation')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "number concentration"
# "effective radii"
# "size distribution"
# "asymmetry"
# "aspect ratio"
# "mixing state"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
27.3. Optical Methods
Is Required: TRUE Type: ENUM Cardinality: 1.N
Optical methods applicable to aerosols in the longwave radiation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.radiation.longwave_aerosols.optical_methods')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "T-matrix"
# "geometric optics"
# "finite difference time domain (FDTD)"
# "Mie theory"
# "anomalous diffraction approximation"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
28. Radiation --> Longwave Gases
Longwave radiative properties of gases
28.1. General Interactions
Is Required: TRUE Type: ENUM Cardinality: 1.N
General longwave radiative interactions with gases | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.radiation.longwave_gases.general_interactions')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "scattering"
# "emission/absorption"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
29. Turbulence Convection
Atmosphere Convective Turbulence and Clouds
29.1. Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview description of atmosphere convection and turbulence | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
30. Turbulence Convection --> Boundary Layer Turbulence
Properties of the boundary layer turbulence scheme
30.1. Scheme Name
Is Required: FALSE Type: ENUM Cardinality: 0.1
Boundary layer turbulence scheme name | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.boundary_layer_turbulence.scheme_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "Mellor-Yamada"
# "Holtslag-Boville"
# "EDMF"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
30.2. Scheme Type
Is Required: TRUE Type: ENUM Cardinality: 1.N
Boundary layer turbulence scheme type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.boundary_layer_turbulence.scheme_type')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "TKE prognostic"
# "TKE diagnostic"
# "TKE coupled with water"
# "vertical profile of Kz"
# "non-local diffusion"
# "Monin-Obukhov similarity"
# "Coastal Buddy Scheme"
# "Coupled with convection"
# "Coupled with gravity waves"
# "Depth capped at cloud base"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
30.3. Closure Order
Is Required: TRUE Type: INTEGER Cardinality: 1.1
Boundary layer turbulence scheme closure order | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.boundary_layer_turbulence.closure_order')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
30.4. Counter Gradient
Is Required: TRUE Type: BOOLEAN Cardinality: 1.1
Uses boundary layer turbulence scheme counter gradient | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.boundary_layer_turbulence.counter_gradient')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# Valid Choices:
# True
# False
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
31. Turbulence Convection --> Deep Convection
Properties of the deep convection scheme
31.1. Scheme Name
Is Required: FALSE Type: STRING Cardinality: 0.1
Deep convection scheme name | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.deep_convection.scheme_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
31.2. Scheme Type
Is Required: TRUE Type: ENUM Cardinality: 1.N
Deep convection scheme type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.deep_convection.scheme_type')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "mass-flux"
# "adjustment"
# "plume ensemble"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
31.3. Scheme Method
Is Required: TRUE Type: ENUM Cardinality: 1.N
Deep convection scheme method | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.deep_convection.scheme_method')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "CAPE"
# "bulk"
# "ensemble"
# "CAPE/WFN based"
# "TKE/CIN based"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
31.4. Processes
Is Required: TRUE Type: ENUM Cardinality: 1.N
Physical processes taken into account in the parameterisation of deep convection | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.deep_convection.processes')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "vertical momentum transport"
# "convective momentum transport"
# "entrainment"
# "detrainment"
# "penetrative convection"
# "updrafts"
# "downdrafts"
# "radiative effect of anvils"
# "re-evaporation of convective precipitation"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
31.5. Microphysics
Is Required: FALSE Type: ENUM Cardinality: 0.N
Microphysics scheme for deep convection. Microphysical processes directly control the amount of detrainment of cloud hydrometeor and water vapor from updrafts | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.deep_convection.microphysics')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "tuning parameter based"
# "single moment"
# "two moment"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
32. Turbulence Convection --> Shallow Convection
Properties of the shallow convection scheme
32.1. Scheme Name
Is Required: FALSE Type: STRING Cardinality: 0.1
Shallow convection scheme name | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.shallow_convection.scheme_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
32.2. Scheme Type
Is Required: TRUE Type: ENUM Cardinality: 1.N
shallow convection scheme type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.shallow_convection.scheme_type')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "mass-flux"
# "cumulus-capped boundary layer"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
32.3. Scheme Method
Is Required: TRUE Type: ENUM Cardinality: 1.1
shallow convection scheme method | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.shallow_convection.scheme_method')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "same as deep (unified)"
# "included in boundary layer turbulence"
# "separate diagnosis"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
32.4. Processes
Is Required: TRUE Type: ENUM Cardinality: 1.N
Physical processes taken into account in the parameterisation of shallow convection | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.shallow_convection.processes')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "convective momentum transport"
# "entrainment"
# "detrainment"
# "penetrative convection"
# "re-evaporation of convective precipitation"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
32.5. Microphysics
Is Required: FALSE Type: ENUM Cardinality: 0.N
Microphysics scheme for shallow convection | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.turbulence_convection.shallow_convection.microphysics')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "tuning parameter based"
# "single moment"
# "two moment"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
33. Microphysics Precipitation
Large Scale Cloud Microphysics and Precipitation
33.1. Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview description of large scale cloud microphysics and precipitation | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.microphysics_precipitation.overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
34. Microphysics Precipitation --> Large Scale Precipitation
Properties of the large scale precipitation scheme
34.1. Scheme Name
Is Required: FALSE Type: STRING Cardinality: 0.1
Commonly used name of the large scale precipitation parameterisation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.microphysics_precipitation.large_scale_precipitation.scheme_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
34.2. Hydrometeors
Is Required: TRUE Type: ENUM Cardinality: 1.N
Precipitating hydrometeors taken into account in the large scale precipitation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.microphysics_precipitation.large_scale_precipitation.hydrometeors')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "liquid rain"
# "snow"
# "hail"
# "graupel"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
35. Microphysics Precipitation --> Large Scale Cloud Microphysics
Properties of the large scale cloud microphysics scheme
35.1. Scheme Name
Is Required: FALSE Type: STRING Cardinality: 0.1
Commonly used name of the microphysics parameterisation scheme used for large scale clouds. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.microphysics_precipitation.large_scale_cloud_microphysics.scheme_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
35.2. Processes
Is Required: TRUE Type: ENUM Cardinality: 1.N
Large scale cloud microphysics processes | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.microphysics_precipitation.large_scale_cloud_microphysics.processes')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "mixed phase"
# "cloud droplets"
# "cloud ice"
# "ice nucleation"
# "water vapour deposition"
# "effect of raindrops"
# "effect of snow"
# "effect of graupel"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36. Cloud Scheme
Characteristics of the cloud scheme
36.1. Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview description of the atmosphere cloud scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36.2. Name
Is Required: FALSE Type: STRING Cardinality: 0.1
Commonly used name for the cloud scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36.3. Atmos Coupling
Is Required: FALSE Type: ENUM Cardinality: 0.N
Atmosphere components that are linked to the cloud scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.atmos_coupling')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "atmosphere_radiation"
# "atmosphere_microphysics_precipitation"
# "atmosphere_turbulence_convection"
# "atmosphere_gravity_waves"
# "atmosphere_solar"
# "atmosphere_volcano"
# "atmosphere_cloud_simulator"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36.4. Uses Separate Treatment
Is Required: TRUE Type: BOOLEAN Cardinality: 1.1
Different cloud schemes for the different types of clouds (convective, stratiform and boundary layer) | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.uses_separate_treatment')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# Valid Choices:
# True
# False
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36.5. Processes
Is Required: TRUE Type: ENUM Cardinality: 1.N
Processes included in the cloud scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.processes')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "entrainment"
# "detrainment"
# "bulk cloud"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36.6. Prognostic Scheme
Is Required: TRUE Type: BOOLEAN Cardinality: 1.1
Is the cloud scheme a prognostic scheme? | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.prognostic_scheme')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# Valid Choices:
# True
# False
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36.7. Diagnostic Scheme
Is Required: TRUE Type: BOOLEAN Cardinality: 1.1
Is the cloud scheme a diagnostic scheme? | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.diagnostic_scheme')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# Valid Choices:
# True
# False
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
36.8. Prognostic Variables
Is Required: FALSE Type: ENUM Cardinality: 0.N
List the prognostic variables used by the cloud scheme, if applicable. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.prognostic_variables')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "cloud amount"
# "liquid"
# "ice"
# "rain"
# "snow"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
37. Cloud Scheme --> Optical Cloud Properties
Optical cloud properties
37.1. Cloud Overlap Method
Is Required: FALSE Type: ENUM Cardinality: 0.1
Method for taking into account overlapping of cloud layers | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.optical_cloud_properties.cloud_overlap_method')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "random"
# "maximum"
# "maximum-random"
# "exponential"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
37.2. Cloud Inhomogeneity
Is Required: FALSE Type: STRING Cardinality: 0.1
Method for taking into account cloud inhomogeneity | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.optical_cloud_properties.cloud_inhomogeneity')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
38. Cloud Scheme --> Sub Grid Scale Water Distribution
Sub-grid scale water distribution
38.1. Type
Is Required: TRUE Type: ENUM Cardinality: 1.1
Sub-grid scale water distribution type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_water_distribution.type')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "prognostic"
# "diagnostic"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
38.2. Function Name
Is Required: TRUE Type: STRING Cardinality: 1.1
Sub-grid scale water distribution function name | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_water_distribution.function_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
38.3. Function Order
Is Required: TRUE Type: INTEGER Cardinality: 1.1
Sub-grid scale water distribution function type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_water_distribution.function_order')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
38.4. Convection Coupling
Is Required: TRUE Type: ENUM Cardinality: 1.N
Sub-grid scale water distribution coupling with convection | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_water_distribution.convection_coupling')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "coupled with deep"
# "coupled with shallow"
# "not coupled with convection"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
39. Cloud Scheme --> Sub Grid Scale Ice Distribution
Sub-grid scale ice distribution
39.1. Type
Is Required: TRUE Type: ENUM Cardinality: 1.1
Sub-grid scale ice distribution type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_ice_distribution.type')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "prognostic"
# "diagnostic"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
39.2. Function Name
Is Required: TRUE Type: STRING Cardinality: 1.1
Sub-grid scale ice distribution function name | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_ice_distribution.function_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
39.3. Function Order
Is Required: TRUE Type: INTEGER Cardinality: 1.1
Sub-grid scale ice distribution function type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_ice_distribution.function_order')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
39.4. Convection Coupling
Is Required: TRUE Type: ENUM Cardinality: 1.N
Sub-grid scale ice distribution coupling with convection | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.cloud_scheme.sub_grid_scale_ice_distribution.convection_coupling')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "coupled with deep"
# "coupled with shallow"
# "not coupled with convection"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
40. Observation Simulation
Characteristics of observation simulation
40.1. Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview description of observation simulator characteristics | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
41. Observation Simulation --> Isscp Attributes
ISSCP Characteristics
41.1. Top Height Estimation Method
Is Required: TRUE Type: ENUM Cardinality: 1.N
Cloud simulator ISSCP top height estimation methodUo | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.isscp_attributes.top_height_estimation_method')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "no adjustment"
# "IR brightness"
# "visible optical depth"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
41.2. Top Height Direction
Is Required: TRUE Type: ENUM Cardinality: 1.1
Cloud simulator ISSCP top height direction | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.isscp_attributes.top_height_direction')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "lowest altitude level"
# "highest altitude level"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
42. Observation Simulation --> Cosp Attributes
CFMIP Observational Simulator Package attributes
42.1. Run Configuration
Is Required: TRUE Type: ENUM Cardinality: 1.1
Cloud simulator COSP run configuration | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.cosp_attributes.run_configuration')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "Inline"
# "Offline"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
42.2. Number Of Grid Points
Is Required: TRUE Type: INTEGER Cardinality: 1.1
Cloud simulator COSP number of grid points | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.cosp_attributes.number_of_grid_points')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
42.3. Number Of Sub Columns
Is Required: TRUE Type: INTEGER Cardinality: 1.1
Cloud simulator COSP number of sub-cloumns used to simulate sub-grid variability | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.cosp_attributes.number_of_sub_columns')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
42.4. Number Of Levels
Is Required: TRUE Type: INTEGER Cardinality: 1.1
Cloud simulator COSP number of levels | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.cosp_attributes.number_of_levels')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
43. Observation Simulation --> Radar Inputs
Characteristics of the cloud radar simulator
43.1. Frequency
Is Required: TRUE Type: FLOAT Cardinality: 1.1
Cloud simulator radar frequency (Hz) | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.radar_inputs.frequency')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
43.2. Type
Is Required: TRUE Type: ENUM Cardinality: 1.1
Cloud simulator radar type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.radar_inputs.type')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "surface"
# "space borne"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
43.3. Gas Absorption
Is Required: TRUE Type: BOOLEAN Cardinality: 1.1
Cloud simulator radar uses gas absorption | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.radar_inputs.gas_absorption')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# Valid Choices:
# True
# False
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
43.4. Effective Radius
Is Required: TRUE Type: BOOLEAN Cardinality: 1.1
Cloud simulator radar uses effective radius | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.radar_inputs.effective_radius')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# Valid Choices:
# True
# False
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
44. Observation Simulation --> Lidar Inputs
Characteristics of the cloud lidar simulator
44.1. Ice Types
Is Required: TRUE Type: ENUM Cardinality: 1.1
Cloud simulator lidar ice type | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.lidar_inputs.ice_types')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "ice spheres"
# "ice non-spherical"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
44.2. Overlap
Is Required: TRUE Type: ENUM Cardinality: 1.N
Cloud simulator lidar overlap | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.observation_simulation.lidar_inputs.overlap')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "max"
# "random"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
45. Gravity Waves
Characteristics of the parameterised gravity waves in the atmosphere, whether from orography or other sources.
45.1. Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview description of gravity wave parameterisation in the atmosphere | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
45.2. Sponge Layer
Is Required: TRUE Type: ENUM Cardinality: 1.1
Sponge layer in the upper levels in order to avoid gravity wave reflection at the top. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.sponge_layer')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "Rayleigh friction"
# "Diffusive sponge layer"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
45.3. Background
Is Required: TRUE Type: ENUM Cardinality: 1.1
Background wave distribution | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.background')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "continuous spectrum"
# "discrete spectrum"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
45.4. Subgrid Scale Orography
Is Required: TRUE Type: ENUM Cardinality: 1.N
Subgrid scale orography effects taken into account. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.subgrid_scale_orography')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "effect on drag"
# "effect on lifting"
# "enhanced topography"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
46. Gravity Waves --> Orographic Gravity Waves
Gravity waves generated due to the presence of orography
46.1. Name
Is Required: FALSE Type: STRING Cardinality: 0.1
Commonly used name for the orographic gravity wave scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.orographic_gravity_waves.name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
46.2. Source Mechanisms
Is Required: TRUE Type: ENUM Cardinality: 1.N
Orographic gravity wave source mechanisms | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.orographic_gravity_waves.source_mechanisms')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "linear mountain waves"
# "hydraulic jump"
# "envelope orography"
# "low level flow blocking"
# "statistical sub-grid scale variance"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
46.3. Calculation Method
Is Required: TRUE Type: ENUM Cardinality: 1.N
Orographic gravity wave calculation method | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.orographic_gravity_waves.calculation_method')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "non-linear calculation"
# "more than two cardinal directions"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
46.4. Propagation Scheme
Is Required: TRUE Type: ENUM Cardinality: 1.1
Orographic gravity wave propogation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.orographic_gravity_waves.propagation_scheme')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "linear theory"
# "non-linear theory"
# "includes boundary layer ducting"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
46.5. Dissipation Scheme
Is Required: TRUE Type: ENUM Cardinality: 1.1
Orographic gravity wave dissipation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.orographic_gravity_waves.dissipation_scheme')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "total wave"
# "single wave"
# "spectral"
# "linear"
# "wave saturation vs Richardson number"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
47. Gravity Waves --> Non Orographic Gravity Waves
Gravity waves generated by non-orographic processes.
47.1. Name
Is Required: FALSE Type: STRING Cardinality: 0.1
Commonly used name for the non-orographic gravity wave scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.non_orographic_gravity_waves.name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
47.2. Source Mechanisms
Is Required: TRUE Type: ENUM Cardinality: 1.N
Non-orographic gravity wave source mechanisms | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.non_orographic_gravity_waves.source_mechanisms')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "convection"
# "precipitation"
# "background spectrum"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
47.3. Calculation Method
Is Required: TRUE Type: ENUM Cardinality: 1.N
Non-orographic gravity wave calculation method | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.non_orographic_gravity_waves.calculation_method')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "spatially dependent"
# "temporally dependent"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
47.4. Propagation Scheme
Is Required: TRUE Type: ENUM Cardinality: 1.1
Non-orographic gravity wave propogation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.non_orographic_gravity_waves.propagation_scheme')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "linear theory"
# "non-linear theory"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
47.5. Dissipation Scheme
Is Required: TRUE Type: ENUM Cardinality: 1.1
Non-orographic gravity wave dissipation scheme | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.gravity_waves.non_orographic_gravity_waves.dissipation_scheme')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "total wave"
# "single wave"
# "spectral"
# "linear"
# "wave saturation vs Richardson number"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
48. Solar
Top of atmosphere solar insolation characteristics
48.1. Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview description of solar insolation of the atmosphere | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
49. Solar --> Solar Pathways
Pathways for solar forcing of the atmosphere
49.1. Pathways
Is Required: TRUE Type: ENUM Cardinality: 1.N
Pathways for the solar forcing of the atmosphere model domain | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.solar_pathways.pathways')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "SW radiation"
# "precipitating energetic particles"
# "cosmic rays"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
50. Solar --> Solar Constant
Solar constant and top of atmosphere insolation characteristics
50.1. Type
Is Required: TRUE Type: ENUM Cardinality: 1.1
Time adaptation of the solar constant. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.solar_constant.type')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "fixed"
# "transient"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
50.2. Fixed Value
Is Required: FALSE Type: FLOAT Cardinality: 0.1
If the solar constant is fixed, enter the value of the solar constant (W m-2). | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.solar_constant.fixed_value')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
50.3. Transient Characteristics
Is Required: TRUE Type: STRING Cardinality: 1.1
solar constant transient characteristics (W m-2) | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.solar_constant.transient_characteristics')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
51. Solar --> Orbital Parameters
Orbital parameters and top of atmosphere insolation characteristics
51.1. Type
Is Required: TRUE Type: ENUM Cardinality: 1.1
Time adaptation of orbital parameters | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.orbital_parameters.type')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "fixed"
# "transient"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
51.2. Fixed Reference Date
Is Required: TRUE Type: INTEGER Cardinality: 1.1
Reference date for fixed orbital parameters (yyyy) | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.orbital_parameters.fixed_reference_date')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
51.3. Transient Method
Is Required: TRUE Type: STRING Cardinality: 1.1
Description of transient orbital parameters | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.orbital_parameters.transient_method')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
51.4. Computation Method
Is Required: TRUE Type: ENUM Cardinality: 1.1
Method used for computing orbital parameters. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.orbital_parameters.computation_method')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "Berger 1978"
# "Laskar 2004"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
52. Solar --> Insolation Ozone
Impact of solar insolation on stratospheric ozone
52.1. Solar Ozone Impact
Is Required: TRUE Type: BOOLEAN Cardinality: 1.1
Does top of atmosphere insolation impact on stratospheric ozone? | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.solar.insolation_ozone.solar_ozone_impact')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# Valid Choices:
# True
# False
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
53. Volcanos
Characteristics of the implementation of volcanoes
53.1. Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview description of the implementation of volcanic effects in the atmosphere | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.volcanos.overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
54. Volcanos --> Volcanoes Treatment
Treatment of volcanoes in the atmosphere
54.1. Volcanoes Implementation
Is Required: TRUE Type: ENUM Cardinality: 1.1
How volcanic effects are modeled in the atmosphere. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.atmos.volcanos.volcanoes_treatment.volcanoes_implementation')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "high frequency solar constant anomaly"
# "stratospheric aerosols optical thickness"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/test-institute-2/cmip6/models/sandbox-3/atmos.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
overwrite links, since v1.5.3 installation does not work properly due to
https://github.com/JuliaLang/julia/issues/38411 | if julia_version=='1.5.3':
julia_version='1.6.0-rc1'
ziplink64bit='https://julialang-s3.julialang.org/bin/winnt/x64/1.6/julia-1.6.0-rc1-win64.zip'
md5link='https://julialang-s3.julialang.org/bin/checksums/julia-1.6.0-rc1.md5'
sha256link='https://julialang-s3.julialang.org/bin/checksums/julia-1.6.0-rc1.sha256'
print(julia_version)
# download checksums
g = request.urlopen(md5link)
md5hashes = g.read().decode()
g.close;
g = request.urlopen(sha256link)
sha256hashes = g.read().decode()
g.close;
# downloading julia (may take 1 minute or 2)
if 'amd64' in sys.version.lower():
julia_zip=ziplink64bit.split("/")[-1]
julia_url=ziplink64bit
else:
julia_zip=ziplink32bit.split("/")[-1]
julia_url=ziplink32bit
hashes=(re.findall(r"([0-9a-f]{32})\s"+julia_zip, md5hashes)[0] , re.findall(r"([0-9a-f]{64})\s+"+julia_zip, sha256hashes)[0])
julia_zip_fullpath = os.path.join(os.environ["WINPYDIRBASE"], "t", julia_zip)
g = request.urlopen(julia_url)
with io.open(julia_zip_fullpath, 'wb') as f:
f.write(g.read())
g.close
g = None
#checking it's there
assert os.path.isfile(julia_zip_fullpath)
# checking the hashes
import hashlib
def give_hash(of_file, with_this):
with io.open(julia_zip_fullpath, 'rb') as f:
return with_this(f.read()).hexdigest()
print (" "*12+"MD5"+" "*(32-12-3)+" "+" "*15+"SHA-256"+" "*(40-15-5)+"\n"+"-"*32+" "+"-"*64)
print ("%s %s %s" % (give_hash(julia_zip_fullpath, hashlib.md5) , give_hash(julia_zip_fullpath, hashlib.sha256),julia_zip))
assert give_hash(julia_zip_fullpath, hashlib.md5) == hashes[0].lower()
assert give_hash(julia_zip_fullpath, hashlib.sha256) == hashes[1].lower()
# will be in env next time
os.environ["JUPYTER"] = os.path.join(os.environ["WINPYDIR"],"Scripts","jupyter.exe")
os.environ["JULIA_HOME"] = os.path.join(os.environ["WINPYDIRBASE"], "t", "julia-"+julia_version)
os.environ["JULIA_EXE_PATH"] = os.path.join(os.environ["JULIA_HOME"], "bin")
os.environ["JULIA_EXE"] = "julia.exe"
os.environ["JULIA"] = os.path.join(os.environ["JULIA_EXE_PATH"],os.environ["JULIA_EXE"])
os.environ["JULIA_PKGDIR"] = os.path.join(os.environ["WINPYDIRBASE"],"settings",".julia")
os.environ["JULIA_DEPOT_PATH"] = os.environ["JULIA_PKGDIR"]
os.environ["JULIA_HISTORY"] = os.path.join(os.environ["JULIA_PKGDIR"],"logs","repl_history.jl")
os.environ["CONDA_JL_HOME"] = os.path.join(os.environ["JULIA_HOME"], "conda", "3")
# move JULIA_EXE_PATH to the beginning of PATH, since a julia installation may be present on the machine
os.environ["PATH"] = os.environ["JULIA_EXE_PATH"] + ";" + os.environ["PATH"]
if not os.path.isdir(os.environ["JULIA_PKGDIR"]):
os.mkdir(os.environ["JULIA_PKGDIR"])
if not os.path.isdir(os.path.join(os.environ["JULIA_PKGDIR"],"logs")):
os.mkdir(os.path.join(os.environ["JULIA_PKGDIR"],"logs"))
if not os.path.isfile(os.environ["JULIA_HISTORY"]):
open(os.environ["JULIA_HISTORY"], 'a').close() # create empty file
# extract the zip archive
import zipfile
try:
with zipfile.ZipFile(julia_zip_fullpath) as z:
z.extractall(os.path.join(os.environ["WINPYDIRBASE"], "t"))
print("Extracted all files")
except:
print("Invalid file")
# delete zip file
os.remove(julia_zip_fullpath) | docs/installing_julia_and_ijulia.ipynb | winpython/winpython_afterdoc | mit |
2 - Initialize Julia , IJulia, and make them link to winpython | # connecting Julia to WinPython (only once, or everytime you move things)
# see the Windows terminal window for the detailed status. This may take
# a minute or two.
import julia
julia.install()
%load_ext julia.magic
info = julia.juliainfo.JuliaInfo.load()
print(info.julia)
print(info.sysimage)
print(info.version_raw)
from julia.api import Julia
jl = Julia(compiled_modules=False)
# sanity check
assert jl.eval("1+2") == 3 | docs/installing_julia_and_ijulia.ipynb | winpython/winpython_afterdoc | mit |
Print julia's versioninfo()
The environment should point to the usb drive and not to C:\ (your local installation of julia maybe...) | jl.eval("using InteractiveUtils")
jl.eval('file = open("julia_versioninfo.txt","w")')
jl.eval("versioninfo(file,verbose=false)")
jl.eval("close(file)")
with open('julia_versioninfo.txt', 'r') as f:
print(f.read())
os.remove('julia_versioninfo.txt') | docs/installing_julia_and_ijulia.ipynb | winpython/winpython_afterdoc | mit |
Install julia Packages | %%julia
using Pkg
Pkg.instantiate()
Pkg.update()
%%julia
# add useful packages. Again, this may take a while...
Pkg.add("IJulia")
Pkg.add("Plots")
Pkg.add("Interact")
Pkg.add("Compose")
Pkg.add("SymPy")
using Compose
using SymPy
using IJulia
using Plots | docs/installing_julia_and_ijulia.ipynb | winpython/winpython_afterdoc | mit |
Fix the kernel.json to allow arbitrary drive letters and modify the env.bat
the path to kernel.jl is hardcoded in the kernel.json file
this will cause trouble, if the drive letter of the usb drive changes
use relative paths instead
rewrite kernel.json and delete the one created from IJulia.jl Package | kernel_path = os.path.join(os.environ["WINPYDIRBASE"], "settings", "kernels", "julia-"+julia_version[0:3])
assert os.path.isdir(kernel_path)
with open(os.path.join(kernel_path,"kernel.json"), 'r') as f:
kernel_str = f.read()
new_kernel_str = kernel_str.replace(os.environ["WINPYDIRBASE"].replace("\\","\\\\"),"{prefix}\\\\..")
print(new_kernel_str)
with open(os.path.join(kernel_path,"kernel.json"), 'w') as f:
f.write(new_kernel_str)
# add JULIA env variables to env.bat
inp_str = r"""
rem ******************
rem handle Julia {0} if included
rem ******************
if not exist "%WINPYDIRBASE%\t\julia-{0}\bin" goto julia_bad_{0}
set JULIA_PKGDIR=%WINPYDIRBASE%\settings\.julia
set JULIA_DEPOT_PATH=%JULIA_PKGDIR%
set JULIA_EXE=julia.exe
set JULIA_HOME=%WINPYDIRBASE%\t\julia-{0}
set JULIA_HISTORY=%JULIA_PKGDIR%\logs\repl_history.jl
:julia_bad_{0}
""".format(julia_version)
# append to env.bat
with open(os.path.join(os.environ["WINPYDIRBASE"],"scripts","env.bat"), 'a') as file :
file.write(inp_str) | docs/installing_julia_and_ijulia.ipynb | winpython/winpython_afterdoc | mit |
Introduction
Machine learning literature makes heavy use of probabilistic graphical models
and bayesian statistics. In fact, state of the art (SOTA) architectures, such as
[variational autoencoders][vae-blog] (VAE) or [generative adversarial
networks][gan-blog] (GAN), are intrinsically stochastic by nature. To
wholesomely understand research in this field not only do we need a broad
knowledge of mathematics, probability, and optimization but we somehow need
intuition about how these concepts are applied to real world problems. For
example, one of the most common applications of deep learning techniques is
vision. We may want to classify images or generate new ones. Most SOTA
techniques pose these problems in a probabilistic framework. We frequently see
things like $p(\mathbf{x}|\mathbf{z})$ where $\mathbf{x}$ is an image and
$\mathbf{z}$ is a latent variable. What do we mean by the probability of an
image? What is a latent variable, and why is it necessary[^Bishop2006] to pose
the problems this way?
Short answer, it is necessary due to the inherent uncertainty of our universe.
In this case, uncertainty in image acquisition can be introduced via many
sources, such as the recording apparatus, the finite precision of our
measurements, as well as the intrinsic stochasticity of the process being
measured. Perhaps the most important source of uncertainty we will consider is
due to there being sources of variability that are themselves unobserved.
Probability theory provides us with a framework to reason in the presence of
uncertainty and information theory allows us to quantify uncertainty. As we
elluded earlier the field of machine learning makes heavy use of both, and
this is no coincidence.
Representations
How do we describe a face? The word "face" is a symbol and this symbol means
different things to different people. Yet, there is enough commonality between
our interpretations that we are able to effectively communicate with one
another using the word. How is that? What are the underlying features of faces
that we all hold common? Why is a simple smiley face clip art so obviously
perceived as a face? To make it more concrete, why are two simple ellipses
decorated underneath by a short curve so clearly a face, while an eye lid,
lower lip, one ear and a nostril, not?
Insert Image of Faces
Left: Most would likely agree, this is clearly a face. Middle:
With nearly all of the details removed, a mere two circles and
curve are enough to create what the author still recognizes
as a face. Right: Does this look like a face to you? An ear,
nostril, eyelid, and lip do not seem to convey a face as clearly
as the eyes and the mouth do. We will quantify this demonstration
shortly.
Features, or representations, are built on the idea that characteristics of the
symbol "face" are not a property of any one face. Rather, they only arise from
the myriad of things we use the symbol to represent. In other words, a
particular face is not ascribed meaning by the word "face" - the word "face"
derives meaning from the many faces it represents. This suggests that facial
characteristics can be described through the statistical properties of all
faces. Loosely speaking, these underlying statistical characteristics are what
the machine learning field often calls latent variables.
Probability of an Image
Most images are contaminated with noise that must be addressed. At the
highest level, we have noise being added to the data by the imaging device. The
next level of uncertainty comes as a consequence of discretization.
Images in reality are continuous but in the process of imaging we only measure
certain points along the face. Consider for example a military satellite
tracking a vehicle. If one wishes to predict the future location of the van,
the prediction is limited to be within one of the discrete cells that make up
its measurements. However, the true location of the van could be anywhere
within that grid cell. There is also intrinsic stochasticity at the atomic
level that we ignore. The fluctuations taking place at that scale are assumed
to be averaged out in our observations.
The unobserved sources of variability will be our primary focus. Before we
address that, let us lay down some preliminary concepts. We are going to assume
that there exists some true unknown process that determines what faces look
like. A dataset of faces can then be considered as a sample of this process at
various points throughout its life. This suggests that these snapshots are a
outputs of the underlying data generating process. Considering the many
sources of uncertainty outlined above, it is natural to describe this process
as a probability distribution. There will be many ways to interpret the data as
a probability, but we will begin by considering any one image to be the result
of a data generating distribution, $P_{data}(\mathbf{x})$. Here $\mathbf{x}$ is considered to be
an image of a face with $n$ pixels. So $P_{data}$ is a joint distribution over
each pixel of the frame with a probability density function (pdf),
$p_{data}(x_1,x_2,\dots,x_n)$.
To build intuition about what $p_{data}(\mathbf{x})$ is and how it relates to
the assumed data generating process, we will explore a simple example. Take an
image with only 2 pixels... [$x_1$,$x_2$] where both $x_1$ and $x_2$ are in
[0,1]. Each image can be considered as a two dimensional point, in
$\mathbb{R}^2$. All possible images would occupy a square in the 2 dimensional
plane. An example of what this might look like can be seen in Figure
\ref{fig:images_in_2dspace} on page \pageref{fig:images_in_2dspace}. Any one
point inside the unit square would represent an image. For example the image
associated with the point $(0.25,0.85)$ is shown below. | x1 = np.random.uniform(size=500)
x2 = np.random.uniform(size=500)
fig = plt.figure();
ax = fig.add_subplot(1,1,1);
ax.scatter(x1,x2, edgecolor='black', s=80);
ax.grid();
ax.set_axisbelow(True);
ax.set_xlim(-0.25,1.25); ax.set_ylim(-0.25,1.25)
ax.set_xlabel('Pixel 2'); ax.set_ylabel('Pixel 1'); plt.savefig('images_in_2dspace.pdf') | mpfi/probability blog post.ipynb | mathnathan/notebooks | mit |
Any one point inside the unit square would represent an image. For example the image associated with the point $(0.25,0.85)$ is shown below. | im = [(0.25, 0.85)]
plt.imshow(im, cmap='gray',vmin=0,vmax=1)
plt.tick_params(
axis='both', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
left='off',
right='off'
)
plt.xticks([])
plt.yticks([])
plt.xlabel('Pixel 1 = 0.25 Pixel 2 = 0.85')
plt.savefig('sample_2dspace_image.pdf') | mpfi/probability blog post.ipynb | mathnathan/notebooks | mit |
Now consider the case where there is some
process correlating the two variables. This
would be similar to their being some rules behind
the structure of faces. We know, that this must be
the case because if it weren't then faces would
be created randomly and we would not see the
patterns that was do. In
this case, the pixels would be correlated in
some manner due to the mechanism driving the
construction of faces. In this simple case,
let's consider a direct correlation of the
form $x_1 = \frac{1}{2} \cos(2\pi x_2)+\frac{1}{2}+\epsilon$
where $\epsilon$ is a noise term coming from
a low variability normal distribution
$\epsilon \sim N(0,\frac{1}{10})$. We see
in Figure \ref{fig:structured_images_in_2dspace}
on page \pageref{fig:structured_images_in_2dspace}
that in this case, the images plotted
in two dimensions resulting from this
relationship form a distinct pattern. | x1 = lambda x2: 0.5*np.cos(2*np.pi*x2)+0.5
x2 = np.linspace(0,1,200)
eps = np.random.normal(scale=0.1, size=200)
fig = plt.figure();
ax = fig.add_subplot(1,1,1);
ax.scatter(x2,x1(x2)+eps, edgecolor='black', s=80);
ax.grid();
ax.set_axisbelow(True);
ax.set_xlim(-0.25,1.25); ax.set_ylim(-0.25,1.25); plt.axes().set_aspect('equal')
ax.set_xlabel('Pixel 2'); ax.set_ylabel('Pixel 1'); plt.savefig('structured_images_in_2dspace.pdf') | mpfi/probability blog post.ipynb | mathnathan/notebooks | mit |
We will refer to the structure suggested by
the two dimensional points as the 'manifold'.
This is a common practice when analyzing images.
A 28 by 28 dimensional image will be a point in
784 dimensional space. If we are examining
images with structure, various images of the
number 2 for example, then it turns out that
these images will form a manifold in 784
dimensional space. In most cases, as is the
case in our contrived example, this manifold
exists in a lower dimensional space than that
of the images themselves. The goal is to 'learn'
this manifold. In our simple case we can describe
the manifold as a function of only 1 variable
$$f(t) = <t,\frac{1}{2} \cos(2\pi t)+\frac{1}{2}>$$
This is what we would call the underlying data
generating process. In practice we usually
describe the manifold in terms of a probability
distribution. We will refer to the data
generating distribution in our example as
$p_{test}(x_1, x_2)$. Why did we choose a
probability to describe the manifold created
by the data generating process? How might this
probability be interpreted?
Learning the actual distribution turns out to
be a difficult task. Here we will use a
common non parametric technique for describing
distributions, the histogram. Looking at a
histogram of the images, or two dimensional points,
will give us insight into the structure of the
distribution from which they came. Notice here
though that the histogram merely describes the
distribution, we do not know what it is. | from matplotlib.colors import LogNorm
x2 = np.random.uniform(size=100000)
eps = np.random.normal(scale=0.1, size=100000)
hist2d = plt.hist2d(x2,x1(x2)+eps, bins=50, norm=LogNorm())
plt.xlim(0.0,1.0); plt.ylim(-0.3,1.3); plt.axes().set_aspect('equal')
plt.xlabel('Pixel 2'); plt.ylabel('Pixel 1')
plt.colorbar();
plt.savefig('histogram_of_structured_images.pdf') | mpfi/probability blog post.ipynb | mathnathan/notebooks | mit |
Document Table of Contents
1. Key Properties --> Model
2. Key Properties --> Variables
3. Key Properties --> Seawater Properties
4. Key Properties --> Resolution
5. Key Properties --> Tuning Applied
6. Key Properties --> Key Parameter Values
7. Key Properties --> Assumptions
8. Key Properties --> Conservation
9. Grid --> Discretisation --> Horizontal
10. Grid --> Discretisation --> Vertical
11. Grid --> Seaice Categories
12. Grid --> Snow On Seaice
13. Dynamics
14. Thermodynamics --> Energy
15. Thermodynamics --> Mass
16. Thermodynamics --> Salt
17. Thermodynamics --> Salt --> Mass Transport
18. Thermodynamics --> Salt --> Thermodynamics
19. Thermodynamics --> Ice Thickness Distribution
20. Thermodynamics --> Ice Floe Size Distribution
21. Thermodynamics --> Melt Ponds
22. Thermodynamics --> Snow Processes
23. Radiative Processes
1. Key Properties --> Model
Name of seaice model used.
1.1. Model Overview
Is Required: TRUE Type: STRING Cardinality: 1.1
Overview of sea ice model. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.seaice.key_properties.model.model_overview')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/ec-earth-consortium/cmip6/models/ec-earth3-cc/seaice.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
1.2. Model Name
Is Required: TRUE Type: STRING Cardinality: 1.1
Name of sea ice model code (e.g. CICE 4.2, LIM 2.1, etc.) | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.seaice.key_properties.model.model_name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/ec-earth-consortium/cmip6/models/ec-earth3-cc/seaice.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
2. Key Properties --> Variables
List of prognostic variable in the sea ice model.
2.1. Prognostic
Is Required: TRUE Type: ENUM Cardinality: 1.N
List of prognostic variables in the sea ice component. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.seaice.key_properties.variables.prognostic')
# PROPERTY VALUE(S):
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "Sea ice temperature"
# "Sea ice concentration"
# "Sea ice thickness"
# "Sea ice volume per grid cell area"
# "Sea ice u-velocity"
# "Sea ice v-velocity"
# "Sea ice enthalpy"
# "Internal ice stress"
# "Salinity"
# "Snow temperature"
# "Snow depth"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/ec-earth-consortium/cmip6/models/ec-earth3-cc/seaice.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
3. Key Properties --> Seawater Properties
Properties of seawater relevant to sea ice
3.1. Ocean Freezing Point
Is Required: TRUE Type: ENUM Cardinality: 1.1
Equation used to compute the freezing point (in deg C) of seawater, as a function of salinity and pressure | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.seaice.key_properties.seawater_properties.ocean_freezing_point')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# Valid Choices:
# "TEOS-10"
# "Constant"
# "Other: [Please specify]"
# TODO - please enter value(s)
| notebooks/ec-earth-consortium/cmip6/models/ec-earth3-cc/seaice.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
3.2. Ocean Freezing Point Value
Is Required: FALSE Type: FLOAT Cardinality: 0.1
If using a constant seawater freezing point, specify this value. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.seaice.key_properties.seawater_properties.ocean_freezing_point_value')
# PROPERTY VALUE:
# Set as follows: DOC.set_value(value)
# TODO - please enter value(s)
| notebooks/ec-earth-consortium/cmip6/models/ec-earth3-cc/seaice.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
4. Key Properties --> Resolution
Resolution of the sea ice grid
4.1. Name
Is Required: TRUE Type: STRING Cardinality: 1.1
This is a string usually used by the modelling group to describe the resolution of this grid e.g. N512L180, T512L70, ORCA025 etc. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.seaice.key_properties.resolution.name')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/ec-earth-consortium/cmip6/models/ec-earth3-cc/seaice.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
4.2. Canonical Horizontal Resolution
Is Required: TRUE Type: STRING Cardinality: 1.1
Expression quoted for gross comparisons of resolution, eg. 50km or 0.1 degrees etc. | # PROPERTY ID - DO NOT EDIT !
DOC.set_id('cmip6.seaice.key_properties.resolution.canonical_horizontal_resolution')
# PROPERTY VALUE:
# Set as follows: DOC.set_value("value")
# TODO - please enter value(s)
| notebooks/ec-earth-consortium/cmip6/models/ec-earth3-cc/seaice.ipynb | ES-DOC/esdoc-jupyterhub | gpl-3.0 |
Subsets and Splits