Analysis

The Analysis module provides in-situ computation of diagnostic fields from the ocean model state during a simulation. Analysis fields are computed on the fly at user-specified frequencies and written to output streams, eliminating the need to store large volumes of raw model output for offline post-processing.

In the initial delivery, analysis is configured through pre-defined bundled AnalysisGroups such as GlobalStats. These bundles provide convenient shorthands for commonly-used analysis patterns and are configured entirely through the YAML input file. Future updates will add user-defined composable operator chains for fully customizable analysis, though the capability of using pre-defined bundled groups will persist as convenient defaults.

Background

The Analysis module supports two output modes:

• Temporal reduction: Time-averaged output over a specified period (e.g., daily or monthly means). Fields are accumulated each timestep; the reduction is finalized and written at the end of each period. Temporal reduction is configured with the ReductionPeriod parameter. A reduction period may span a restart: the mid-period accumulation state (the partial sum and sample count) is checkpointed in the restart file and restored on continuation, so the final average is identical to an uninterrupted run. There is no requirement that the reduction period divide evenly into the restart interval.

• Instantaneous output: Snapshots of analysis fields written at specified frequencies (e.g., every 6 hours). Instantaneous output is configured with the SnapshotPeriod parameter.

Sampling interval for temporal reductions

The SamplingInterval parameter set the temporal reduction accumulation cadence. The values dt and timestep are accepted as keys to accumulate a sample on every model timestep. Setting SamplingInterval to one of the accepted forms below instead collects samples at a coarser cadence, so the time average is formed from fewer, evenly-spaced samples. This is the in-model equivalent of MPAS-Ocean’s driver-level compute_interval for the time_series_stats analysis member.

SamplingInterval accepts three forms, distinguished by suffix:

Form	Example	Meaning
TimeInterval units	6hour	a fixed time interval between samples
Timestep count	4steps	every 4 model timesteps
Samples per period	8perPeriod	8 evenly-spaced samples per reduction period

Behavior and constraints:

• Omitted/empty: sample every timestep.

• Phasing: the first sample falls one SamplingInterval after the start of each reduction period (samples at PeriodStart + n*SamplingInterval).

• Snap-to-step: like all model alarms, sampling fires on the first timestep at or after each target time. A SamplingInterval that is not a whole multiple of the timestep therefore snaps to the next step, giving a bounded sub-timestep phase error (zero when the interval is a timestep multiple).

• Samples per period: <n>perPeriod divides a period given in days or shorter units into n equal intervals. Months vary in length, so for a period given in months or years n must divide the number of months, as in 3perPeriod for 1Year; otherwise use a fixed interval such as 1day.

• Period-divisibility (required): the reduction period must be evenly divisible by the sampling interval, so the simple count-mean remains an unbiased estimate of the time average. A violation aborts the run. This check is unrelated to the restart interval — temporal reductions may still span restarts with no restart-interval divisibility requirement.

• Accuracy caveat: the averaged value stays unbiased, but when the interval is not a timestep multiple the per-period sample count may differ by ±1 between periods (a boundary-adjacent sample can snap to either side). This per-period count variation is reproducible across restarts: the sample schedule is anchored to the absolute clock start, so an exact-restart (ERS) run reconstructs the identical boundaries and reproduces the straight-through result bit-for-bit. When the interval is a timestep multiple, the count is constant and this does not arise at all.

Configuration Overview

Analysis groups are configured in the YAML input file under Omega: Analysis:. Each group can be independently enabled or disabled. The initial delivery provides the GlobalStats group.

Common Configuration Parameters

All AnalysisGroups support the following parameters:

• Enable: Required boolean (true or false). Enables or disables the group.

• Filename: Required string. Template for output filenames with optional time-based variables ($Y, $M, $D, $h, $m, $s). The group automatically appends frequency and type information to the filename.

• Stream: Optional map of IOStream parameters to customize output behavior. See Stream Parameters below for details.

Analysis Groups

Each AnalysisGroup encapsulates a set of related analysis operations. Groups inherit from the AnalysisGroup base class, which provides common functionality for operator chain construction and stream management.

When initialized, each group:

1. Parses its configuration to determine which operator chains to build

2. Registers operator chains with the Analysis orchestrator

3. Groups chains by output frequency and type (time reduction vs. instantaneous output)

4. Creates IOStream objects for each unique temporal configuration

All groups automatically handle intermediate operator sharing—if multiple chains require the same intermediate result, it is computed once and reused. Temporal reduction operators automatically checkpoint their mid-period accumulation state to the restart file, so reduction periods may span restarts without any divisibility requirement.

Stream Parameters

All AnalysisGroups support the optional Stream sub-node for customizing IOStream output parameters. If omitted, defaults are used.

Default values set by the Analysis module:

• UsePointerFile: false

• IfExists: append

• Precision: double

• UseStartEnd: false

All other Stream parameters (FileFreq, FileFreqUnits, PointerFilename, StartTime, EndTime) are empty or disabled by default.

Note: The Filename, Freq, and FreqUnits stream parameters are set automatically by AnalysisGroup configuration. Any user-specified values for these parameters will be overwritten.

For complete IOStream documentation, see the IOStreams section of the User’s Guide.

GlobalStats

Computes global spatial statistics (mean, min, max, standard deviation) for user-specified fields. The mean and standard deviation are weighted so that they do not depend on the mesh resolution: by the area of each cell, edge or vertex for a horizontal field, and by mass (area times pseudo-thickness) for a field with a vertical dimension, with an interface field weighted by half the mass of each adjacent layer. Only active layers take part. Each statistic is written with the units and standard_name of the field it reduces and a CF cell_methods attribute describing the reduction, for example area: depth: mean for the mean of a layered field and area: depth: mean time: mean for its time mean.

Example:

Omega:
  Analysis:
    GlobalStats:
      Enable: true
      Fields: [Temperature, GeomZInterface, Salinity, NormalVelocity]
      SpatialStats: [Mean, Max, Min, StdDev]
      ReductionPeriod: [1Day, 1Month]
      SamplingInterval: "dt"
      SnapshotPeriod: [6Hour]
      Filename: global.stats.$Y.nc
      Stream:
        FileFreq: 1
        FileFreqUnits: years
        Precision: single

Group-Specific Parameters:

• Fields: Required list of field names to analyze. The simulation will abort if a requested field does not exist.

• SpatialStats: Required list of spatial operators.

• ReductionPeriod: Optional list of time periods for temporal reduction (e.g., 1Hour, 1Day, 1Month, 1Year). At least one of ReductionPeriod or SnapshotPeriod must be specified.

• SamplingInterval: Cadence at which the temporal reductions accumulate samples; see Sampling interval for temporal reductions. Empty, dt, or timestep samples every timestep.

• SnapshotPeriod: Optional list of intervals for instantaneous output (e.g., 1Hour, 6Hour, 1Day). At least one of ReductionPeriod or SnapshotPeriod must be specified.

Output fields: For each (Field, SpatialStat) combination:

• Instantaneous output: FieldName_SpatialStat (e.g., Temperature_SpatialMean)

• Temporal reduction: FieldName_SpatialStat_TimeMeanPeriod (e.g., Temperature_SpatialMean_TimeMean1Day)

Output streams: Automatically created and named:

• Time reduction: GlobalStats_FreqTimeStats (e.g., GlobalStats_1DayTimeStats)

• Instantaneous output: GlobalStats_FreqInstants (e.g., GlobalStats_6HourInstants)

MOC

Computes the Meridional Overturning Circulation (MOC) streamfunction using two methods: latitude-binned regional MOC and transect-based MOC. The MOC represents zonally integrated meridional mass transport as a function of latitude and depth (regional MOC) or depth alone (transect MOC). Output is in Sverdrups (Sv), where 1 Sv = 10⁶ m³/s, so its units attribute is 1e+06 m3 s-1, the udunits spelling of a Sverdrup (udunits reads Sv as the sievert).

Example:

Omega:
  Analysis:
    MOC:
      Enable: true
      NumBins: 180
      MinLat: -90.0
      MaxLat: 90.0
      Regions: [Global]
      Transects: []
      ReductionPeriod: [1Month]
      SamplingInterval: "dt"
      SnapshotPeriod: [1Day]
      Filename: moc.$Y-$M.nc
      Stream:
        FileFreq: 1
        FileFreqUnits: months

Group-Specific Parameters:

• NumBins: Optional integer specifying the number of latitude bins for regional MOC (default: 180, approximately 1-degree resolution).

• MinLat: Optional minimum latitude in degrees for binning (default: -90.0).

• MaxLat: Optional maximum latitude in degrees for binning (default: 90.0).

• Regions: Optional list of region names for regional MOC computation (default: [Global]). Regional MOC computes the streamfunction as a function of latitude and depth. Currently only Global is supported; region masks are not yet implemented.

• Transects: Optional list of transect names for transect-based MOC computation (default: []). Transect MOC computes the streamfunction as a function of depth only by accumulating transport across specified transect edges. Transect masks are not yet implemented.

• ReductionPeriod: Optional list of time periods for temporal reduction. At least one of ReductionPeriod or SnapshotPeriod must be specified.

• SamplingInterval: Cadence at which the temporal reductions accumulate samples; see Sampling interval for temporal reductions. Empty, dt, or timestep samples every timestep.

• SnapshotPeriod: Optional list of intervals for instantaneous output. At least one of ReductionPeriod or SnapshotPeriod must be specified.

Output fields:

• Regional MOC: MOC_streamfunction_RegionName (2D: latitude bins × depth)

• Transect MOC: MOC_streamfunction_transect_TransectName (1D: depth only)

For temporal reduction, _TimeMeanPeriod is appended (e.g., MOC_streamfunction_Global_TimeMean1Month).

Output streams: Automatically created and named:

• Time reduction: MOC_FreqTimeStats (e.g., MOC_1MonthTimeStats)

• Instantaneous output: MOC_FreqInstants (e.g., MOC_1DayInstants)

Note

Regional and transect masks are not yet implemented. The Regions parameter currently only supports [Global], and Transects is a placeholder for future functionality. The underlying operator infrastructure is complete and ready for use once the mask fields are implemented in Omega.

MonthlyAverages

Computes monthly time averages of a set of requested global fields. Unlike GlobalStats, no spatial reduction is applied: each requested field is passed directly to a temporal-reduction (TimeMean) operator. The averaging period defaults to one month, but may be overridden with the optional ReductionPeriod parameter. The MonghtlyAverages group is specifically for temporal reductions, any defined SnapshotPeriod parameter is ignored. This group mirrors the timeSeriesStatsMonthly analysis member in MPAS-Ocean, which delivers monthly means of prognostic and derived fields.

Example:

Omega:
  Analysis:
    MonthlyAverages:
      Enable: true
      Fields: [Temperature, Salinity, NormalVelocity, PseudoThickness]
      ReductionPeriod: [1Month]   # optional; defaults to [1Month]
      SamplingInterval: "dt"
      Filename: monthly.averages.$Y.nc
      Stream:
        FileFreq: 1
        FileFreqUnits: years

Group-Specific Parameters:

• Fields: Required list of field names to average. The simulation will abort if a requested field does not exist.

• ReductionPeriod: Optional list of time periods for temporal reduction (e.g., 1Day, 1Month, 1Year). Defaults to [1Month] when not specified. Any SnapshotPeriod supplied for this group is ignored.

• SamplingInterval: Cadence at which the temporal reductions accumulate samples; see Sampling interval for temporal reductions. Empty, dt, or timestep samples every timestep.

Output fields: For each requested field, a time-averaged field is produced:

• FieldName_TimeMeanPeriod (e.g., Temperature_TimeMean1Month)

Output streams: Automatically created and named:

• Time reduction: MonthlyAverages_FreqTimeStats (e.g., MonthlyAverages_1MonthTimeStats)

Note

The default field list in Default.yml includes the core prognostic fields (Temperature, Salinity, NormalVelocity, PseudoThickness). Additional registered global fields may be requested by adding them to the Fields list. A reduction period may span a restart; see Temporal Reduction and Restarts below.

Usage Notes

Temporal Reduction and Restarts

Temporal reductions (ReductionPeriod) may span a model restart. There is no requirement that the reduction period divide evenly into the restart interval, so any combination of periods and restart intervals is valid (for example, a 1Month average with a 10-day restart interval). When a restart is written in the middle of a reduction period, the mid-period accumulation state (the partial sum and the sample count) is checkpointed in the restart file and restored on continuation, so the final written average is identical to that of an uninterrupted run. Restart files written before this capability was added remain readable; a reduction that lacks checkpointed state simply begins a fresh accumulation period on restart.

Field Availability

The Analysis module initializes after the model state and validates that all requested fields exist. If a requested field is not found, the simulation aborts during initialization with an error message.

Intermediate Results

Some analysis operators require intermediate computations. For example, computing the standard deviation requires the mean as input. Currently, when configuring the SpatialStats list, users must include both Mean and StdDev if standard deviation is desired. The mean computation will be automatically shared if multiple statistics require it.

Future Extensions

The Analysis framework is designed for extensibility. Future versions will include:

• User-defined composable operator chains: Full control over operator composition specified directly in the configuration file, enabling custom analysis workflows beyond the pre-defined bundles.

• Additional pre-defined analysis groups: Bundled groups for common analysis patterns such as AMOC stream function, eddy statistics, regional diagnostics, and more.

• Additional operators: Vertical operations, horizontal gradients, spatial filtering, and custom transformations.

The bundled AnalysisGroup types like GlobalStats will persist as convenient shorthands for commonly-used analysis outputs, even as the composable operator capability becomes available.

For detailed information about the Analysis architecture, operator composition, dependency resolution, and extending the module with new operators or groups, see the Analysis section of the Developer’s Guide.