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Diagnostic list

In this section you have a list of the available diagnostics, with a small description of each one and a link to the full documentation. To see what options are available for each diagnostic, see generate_jobs documentation.

Remember that diagnostics are specified separated by spaces while options are given separated by commas:

DIAGS = diag1 diag2,option1,option2 diag3

General

The diagnostics from this section are of general use and can be used with any variable you may have. Most of them are meant to help you to solve usual issues that you may have with the data: incorrect metadata, scaled up or down variables, links missing. This section also contains the diagnostic used to calculate the monthly means.

att

Writes a global attributte to all the netCDF files for a given variable. See Attribute

Options:

  1. Variable:
    Variable name
  2. Domain:
    Variable domain
  3. Attributte name:
    Attributte to write
  4. Attribute value:
    Atrribute’s new value. Replace ‘,’ with ‘&;’ and ‘ ‘ with ‘&.’ to avoid parsing errors when processing the diags
  5. Grid = ‘’:
    Variable grid. Only required in case that you want to use interpolated data.

dailymean

Calculates the daily mean for a given variable. See DailyMean

Warning

This diagnostic does not use the frequency configuration from the config file. You must specify the original frequency when calling it.

Options:

  1. Variable:
    Variable name
  2. Domain:
    Variable domain
  3. Original frequency:
    Original frequency to use
  4. Grid = ‘’:
    Variable grid. Only required in case that you want to use interpolated data.

module

Calculates the module for two given variables and stores the result in a third. See Module

Options:

  1. Domain:
    Variables domain
  2. Variable U:
    Variable U name
  3. Variable V:
    Variable V name
  4. Variable Module:
    Variable module name
  5. Grid = ‘’:
    Variable grids. Only required in case that you want to use interpolated data.

monmean

Calculates the monthly mean for a given variable. See MonthlyMean

Warning

This diagnostic does not use the frequency configuration from the config file. You must specify the original frequency when calling it. Otherwise, it will always try to use daily data.

Options:

  1. Variable:
    Variable name
  2. Domain:
    Variable domain
  3. Original frequency = daily:
    Original frequency to use
  4. Grid = ‘’:
    Variable grid. Only required in case that you want to use interpolated data.

relinkall

Regenerates the links created in the monthly_mean, daily_mean, etc folders for all variables See RelinkAll

Options:

This diagnostic has no options

rewrite:

Just rewrites the CMOR output of a given variable. Useful to correct metadata or variable units. See Rewrite

Options:

  1. Variable:
    Variable name
  2. Domain:
    Variable domain
  3. Grid = ‘’:
    Variable grid. Only required in case that you want to use interpolated data.

scale

Scales a given variable using a given scale factor and offset (NEW_VALUE = OLD_VALUE * scale + offset). Useful to correct errors on the data.

See Scale

Options:

  1. Variable:
    Variable name
  2. Domain:
    Variable domain
  3. Scale value:
    Scale factor for the variable
  4. Offset value:
    Value to add to the original value after scaling
  5. Grid = ‘’:
    Variable grid. Only required in case that you want to use interpolated data.
  6. Min limit = NaN:
    If there is any value below this threshold, scale will not be applied
  7. Max limit = NaN:
    If there is any value above this threshold, scale will not be applied
  8. Frequencies = [Default_frequency]:
    List of frequencies (‘-‘ separated) to apply the scale on. Default is the frequency defined globally for all the diagnostics

simdim

Convert i j files to lon lat when there is no interpolation required, i.e. lon is constant over i and lat is constat over j

See SimplifyDimensions

Options:

  1. Domain:
    Variable domain
  2. Variable:
    Variable name
  1. Grid = ‘’:
    Variable grid. Only required in case that you want to use interpolated data.

yearlymean

Calculates the daily mean for a given variable. See YearlyMean

Warning

This diagnostic does not use the frequency configuration from the config file. You must specify the original frequency when calling it.

Options:

  1. Variable:
    Variable name
  2. Domain:
    Variable domain
  3. Original frequency:
    Original frequency to use
  4. Grid = ‘’:
    Variable grid. Only required in case that you want to use interpolated data.

Ocean

The diagnostics from this section are meant to be used with NEMO variables. Some of them will compute new variables while others just calculate means or sections for variables in the ORCA grid. The interpolation diagnostics are also included here as they are usually used with variables in the ORCA grid.

areamoc

Compute an Atlantic MOC index by averaging the meridional overturning in a latitude band between 1km and 2km or any other index averaging the meridional overturning in a given basin and a given domain. See AreaMoc

Warning

The MOC for the given basin must be calculated previously. Usually, it will suffice to call the ‘moc’ diagnostic earlier in the DIAGS list.

Options:

  1. Min latitude:
    Minimum latitude to compute
  2. Max latitude:
    Maximum latitude to compute
  3. Min depth:
    Minimum depth (in levels)
  4. Max depth:
    Maximum depth (in levels)
  5. Basin = ‘Global’:
    Basin to calculate the diagnostic on.

averagesection

Compute an average of a given zone. The variable MUST be in a regular grid See AverageSection

Options:

  1. Variable:
    Variable to average
  2. Min longitude:
    Minimum longitude to compute
  3. Max longitude:
    Maximum longitude to compute
  4. Min latitude:
    Minimum latitude to compute
  5. Max latitude:
    Maximum latitude to compute
  6. Domain = ocean:
    Variable domain

convectionsites

Compute the intensity of convection in the four main convection sites. See ConvectionSites

Options:

This diagnostic has no options

cutsection

Cuts a meridional or zonal section. See CutSection

Options:

  1. Variable:
    Variable to cut the section on
  2. Zonal:
    If True, calculates a zonal section. If False, it will be a meridional one
  3. Value:
    Reference value for the section
  4. Domain = ocean:
    Variable’s domain

gyres

Compute the intensity of the subtropical and subpolar gyres. See Gyres

Options:

This diagnostic has no options

heatcontent

Compute the total and mean ocean heat content. See HeatContent

Options:

  1. Basin
    Basin to calculate the heat content one
  2. Mixed layer:
    If 1, reduces the compuation to the mixed layer. If -1, excludes the mixed layer from the computations. If 0, no effect.
  3. Min depth:
    Minimum depth for the calculation in levels. If 0, whole depth is used
  4. Max depth:
    Maximum depth for the calculation in levels

heatcontentlayer

Point-wise Ocean Heat Content in a specified ocean thickness. See HeatContentLayer

Options:

  1. Min depth:
    Minimum depth for the calculation in meteres
  2. Max depth:
    Maximum depth for the calculation in meters
  3. Basin = ‘Global’:
    Basin to calculate the heat content on.

interpolate

3-dimensional conservative interpolation to the regular atmospheric grid. It can also be used for 2D (i,j) variables. See Interpolate

Warning

This interpolation requires the pre-generated weights that can be found in ‘/esnas/autosubmit/con_files/weights’. Make sure that they are available for your configuration.

Options:

  1. Target grid:
    New grid for the data
  2. Variable:
    Variable to interpolate
  3. Domain = ocean:
    Variable’s domain
  4. Invert latitude:
    If True, inverts the latitude in the output file.
  5. Original grid = ‘’:
    Source grid to choose. By default this is the original data, but sometimes you will want to use another (for example, the ‘rotated’ one produced by the rotation diagnostic)

interpolateCDO

Bilinear interpolation to a given grid using CDO. See InterpolateCDO

Warning

This interpolation is non-conservative, so treat its output with care. It has the advantage that does not require the pre-generated weights so it can be used when the ‘interp’ diagnostic is not available.

Options:

  1. Variable:
    variable to interpolate
  2. Target grid:
    Variable domain
  3. Domain = ocean:
    Variable’s domain
  4. Mask oceans = True:
    If True, replaces the values in the ocean by NaN. You must only set it to false if, for some reason, you are interpolating an atmospheric or land variable that is stored in the NEMO grid (yes, this can happen, i.e. with tas).
  5. Original grid = ‘’:
    Source grid to choose. By default this is the original data, but sometimes you will want to use another (for example, the ‘rotated’ one produced by the rotation diagnostic)

maskland

Replaces all values excluded by the mask by NaN. See MaskLand

Options:

  1. Domain:
    Variable to mask domain
  2. Variable:
    variable to mask
  3. Cell point = T:
    Cell point where variable is stored. Options: T, U, V, W, F
  4. Original grid = ‘’:
    Source grid to choose. By default this is the original data, but sometimes you will want to use another (for example, the ‘rotated’ one produced by the rotation diagnostic)

maxmoc

Compute an Atlantic MOC index by finding the maximum of the annual mean meridional overturning in a latitude / depth region. Output from this diagnostic will be always in yearly frequency. See MaxMoc

Warning

The MOC for the given basin must be calculated previously. Usually, it will suffice to call the ‘moc’ diagnostic earlier in the DIAGS list.

Warning

This diagnostic can only be computed for full years. It will discard incomplete years and only compute the index in those with the full 12 months available.

Options:

  1. Min latitude:
    Minimum latitude to compute
  2. Max latitude:
    Maximum latitude to compute
  3. Min depth:
    Minimum depth (in levels)
  4. Max depth:
    Maximum depth (in levels)
  5. Basin = ‘Global’:
    Basin to calculate the diagnostic on.

mixedlayerheatcontent

Compute mixed layer heat content. See MixedLayerHeatContent

Options:

This diagnostic has no options

mixedlayersaltcontent

Compute mixed layer salt content. See MixedLayerSaltContent

Options:

This diagnostic has no options

moc

Compute the MOC for oceanic basins. Required for ‘areamoc’ and ‘maxmoc’ See Moc

Options:

This diagnostic has no options

mxl

Compute the mixed layer depth. See Mxl

Options:

This diagnostic has no options

psi

Compute the barotropic stream function. See Psi

Options:

This diagnostic has no options

regmean

Computes the mean value of the field (3D, weighted). For 3D fields, a horizontal mean for each level is also given. If a spatial window is specified, the mean value is computed only in this window. See RegionMean

Options:

  1. Domain:
    Variable domain
  2. Variable:
    Variable to average
  3. Grid_point:
    NEMO grid point used to store the variable: T, U, V …
  4. Basin = Global:
    Basin to compute
  5. Save 3d = True:
    If True, it also stores the average per level
  6. Min depth:
    Minimum depth to compute in levels. If -1, average from the surface
  7. Max depth:
    Maximum depth to compute in levels. If -1, average to the bottom
  8. Variance = False:
    If True, it also stores the variance
  9. Original grid = ‘’:
    Source grid to choose. By default this is the original data, but sometimes you will want to use another (for example, the ‘rotated’ one produced by the rotation diagnostic)

rotate

Rotates the given variables See Rotation

Options:

  1. Variable u:
    Variable’s u component
  2. Variable v:
    Variable’s u component
  3. Domain = ocean:
    Variable domain:
  4. Executable = /home/Earth/jvegas/pyCharm/cfutools/interpolation/rotateUVorca:
    Path to the executable that will compute the rotation

Warning

This default executable has been compiled for ORCA1 experiments. For other resolutions you must use other executables compiled ad-hoc for them

siasiesiv

Compute the sea ice extent , area and volume in both hemispheres or a specified region. See Siasiesiv

Options:

  1. Basin = ‘Global’:
    Basin to restrict the computation to.

vgrad

Calculates the gradient between two levels in a 3D ocean variable. See VerticalGradient

Options:

  1. Variable:
    Variable to compute
  2. Upper level = 1:
    Upper level. Will be used as the reference to compute the gradient
  3. Lower level = 2:
    Lower level.

verticalmean

Chooses vertical level in ocean, or vertically averages between 2 or more ocean levels. See VerticalMean

Options:

  1. Variable:
    Variable to average
  2. Min depth = -1:
    Minimum level to compute. If -1, average from the surface
  3. Max depth:
    Maximum level to compute. If -1, average to the bottom

verticalmeanmeters

Averages vertically any given variable. See VerticalMeanMeters

Options:

  1. Variable:
    Variable to average
  2. Min depth = -1:
    Minimum depth to compute in meters. If -1, average from the surface
  3. Max depth:
    Maximum depth to compute in meters. If -1, average to the bottom

Statistics

climpercent

Calculates the specified climatological percentile of a given variable. See ClimatologicalPercentile

Options:

  1. Domain:
    Variable’s domain
  2. Variable:
    Variable to compute diagnostic on
  3. Leadtimes:
    Leadtimes to compute
  4. Bins:
    Number of bins to use to discretize the variable

monpercent

Calculates the specified monthly percentile of a given variable. See MonthlyPercentile

Options:

  1. Domain:
    Variable’s domain
  2. Variable:
    Variable to compute diagnostic on
  3. Percentiles:
    List of requested percentiles (‘-‘ separated)