Glossary

Auxiliary Data

Any data that is input to the geophysical retrieval or gridding that is not radar altimeter sensor data (see Source Data). Auxiliary data sets can be dynamic (e.g. daily) or static fields. The data may be stored in external files or computed form a parametrization. Examples are sea ice concentration or type products, land/ocean or regions masks, data on snow on sea ice or mean sea surface products. The overview of supported auxiliary data sets is available in the Auxiliary Datasets section.

Auxiliary Dataset ID

A unique identifier for an auxiliary dataset in the form of <category>:<dataset_id> required for specifying and referencing auxiliary datasets in pysiral processors. (See Auxiliary Datasets)

C3S

Copernicus Climate Change Service. A program that produces long-term climate and interim data records

CCI

ESA Climate Change Initiative. A program that produces long-term climate data records (term: CDR).

CDR

Climate Data Record. A data record that provides a long-term, consistent, and quality controlled representation of a specific climate variable.

FYI

First year sea ice. This term is used to describe sea ice that has formed during the current freeze-up season and has not yet survived a summer melt season.

Hemisphere

The hemisphere of the Earth, either northern or southern. In pysiral, the hemisphere refers to the Northern and Southern Polar Oceans.

Level-1 Pre-Processor

Dedicated processing step in pysiral that ingests source data and creates orbit segments over the polar oceans with additional pre-computed parameters in a unified file format for all supported radar altimeter missions.

Level-2 Processor

Dedicated processing step that performs the geophysical retrieval based on the output of the Level-1 Pre-Processor. The coverage of the output is identical to the input data.

Level-2 Pre-Processor

Dedicated processing step that ingests output from the Level-2 Processor and filters and aggregates data and writes daily summary files with the same resolution of the Level-2 data.

Level-3 Processor

Aggregates the output of the Level-2 Processor on a spatio-temporal grid. Also allows to compute statistics and additional parameters.

Mission

A satellite mission that may consist of one or more satellite platforms. For example, Sentinel-3A and Sentinel-3B are part of the Sentinel-3 mission.

iCDR

Interim Climate Data Record. A data record that that is a temporal extensions of an CDR and is used to provide data until the next CDR is available.

Platform

A specific (satellite) platform. In pysiral, each platform is referenced by a unique platform identifier, which is by default the lower case name ([a-z0-9]) e.g. cryosat2 or envisat.

Processing Item

A class that can be called during a processing run for a specific processing level (Level-2 processor). Examples are computing variables, statistics or filtering data. The class must be compliant with the conventions of a processing item for the specific processor. These requirements are generally:

1. The class must have a unique name (typically starts with target processing level)

2. The class receives configuration keywords during initialization.

3. The class must be a subclass of a processing item class (sub-classing registers the processing item class)

4. The class must have a required method that receives the data container, which is then modified in-place

It is advisable to implement processing items with a dedicated configuration class and store it in the module pysiral.<target_processing_level>.alg, but any location is technically possible.

Processing items are added in processing configuration files to the workflow. The specification includes the class name, optionally the stage in the workflow and any options if required.

Processing Level

Data processing levels describe the state of data processing from lower (close to the actual sensor data) to higher levels (geophysical retrievals).

Level	Description
L0	Sensor raw data (not supported by pysiral)
L1B	Calibrated sensor data. Typical processing level for Source Data
L1P	Pre-processed sensor data created by the Level-1 Pre-Processor
L2	Geophysical data at the same coverage and resolutions of l1p data. Output of the Level-2 Processor
L2i	Geophysical data at the same coverage and resolutions of l1p data. Same as L2, but also contains variables from the L1P input data. Output of the Level-2 Processor
L2p	Aggregated and filtered l2i data, for example daily summary files only over sea ice Output of the Level-2 Pre-Processor

Product Line

An identifier of products and part of the data id of processing levels 2 or higher. The string is usually a short name of the project or institute funding or implementing the data production (Examples: cci for sea ice thickness climate data records of the ESA Climate Change Initiative).

Record type

The record type defines the type of data record. In pysiral, the record type can be a Timeliness code, but also cdr (climate data record) of icdr (interim climate data record).

Stage of Development

Sea ice classification usually in operational Ice Charts with distinct classes.

Sea Ice Concentration

The fraction of sea ice in a given area. It is usually expressed as a percentage (0-100%) or as a fraction (0-1).

Sea Ice Type

The classification of sea ice into different types based on the stage of development of sea ice. In pysiral, sea ice type is defined as the fraction of multi-year sea ice within in a defined area.

Sensor

The name of the radar altimeter sensor. In pysiral, each sensor is referenced by a unique platform identifier, which is by default the lower case name e.g. siral for cryosat2 or ra-2 for envisat .

Source Data

The term source data refers to calibrated radar altimeter data (waveforms) annotated with a land/ocean mask. geophysical range corrections for path delays in the atmosphere and ionosphere as well as information from tide models.

Timeliness

Defines the delay a data record is produced. Data from a specific platform/sensor is often delivered with more than one timeliness, and each of these products is its own Source Data set. Datasets from satellites that are no longer operational are classified as reprocessed. The table below gives an overview of frequently used timeliness codes and their typical delay. The actual delay of indiviudal source data products may differ from the typical delay.

Code	Meaning	Typical Delay	Alias
nrt	Near Real-Time	< 2 days	stc
stc	Short Time Critical	< 2 day	nrt
rep	Reprocessed	1 month	ntc
ntc	Non Time Critical	1 month	rep