Level 2 Ocean Salinity L20S Tool Box Architecture & Release

1. Level 2 Ocean Salinity L20S Tool Box Architecture & Release 27 June 2014 ARGANS & SMOS L2OS ESL

2. L20S Tool Box Architecture & Release • Goals of the Tool Box: • Provide to the L1 team with a set of tools evaluating L1c product quality from the L2OS perspective. • Build a processing chain from L1c and L2OS products to the metrics, plots and data files. • Reduce at the maximum the required interaction between the software and the user. • Integrate scripts from different origin into a unique programme able to perform all the needed tasks. • Optimize the use of already processed data to provide a faster processing of new products.

3. Set of L1-L2OS tools • Several tools from SM-TN-AURO-L1OP-0003 have been targeted to be implemented: • Long term stability at Ocean (3.2.1) • Short term stability: Descending – Ascending (3.2.3) • Short term stability: Latitudinal drift (3.2.4) • Short term stability: Eclipse regions (3.2.5) • Hovmoller plots (3.2.6) • Spatial Bias at the Ocean (OTT analysis) (3.4.1) • The scripts will make use of the following data files: • L1c vXXX products: To be processed by the L2OS processor. • Derived OSDAP: Retrieval of the snapshots ID, the xi/eta values for each measurement in the snapshot. • Derived AUX_DTBXY: Retrieval of statistics from the OTTs and the averaged values of the Ocean Model and L1c, for each region in the snapshot, to generate the required metrics, plots and data files. • L1c vYYY products: To obtain the metrics from a new product without re-running the L2OS processor.

4. Set of L1-L2OS tools • Long term stability at Ocean (3.2.1) • Evolution of the ascending/descending AFFOV brightness temperature anomalies in Stokes 1 over the set of Pacific Ocean from June 2010 onwards. • Metrics: Mean, standard deviation and slope of the delta TB as L1c – Ocean model.

5. Set of L1-L2OS tools • Short term stability: Descending – Ascending (3.2.3) • Difference between descending and ascending orbits in the AFFOV/EAFFOV anomalies of Stokes-1, from the Ocean Model, evaluated for the set of Pacific Ocean orbits. • Metrics: Mean of the absolute delta TB as L1c – Ocean model.

6. Set of L1-L2OS tools • Short term stability: Latitudinal drift (3.2.4) • Evolution of the ascending/descending EAFFOV brightness temperature anomalies in Stokes 1 over the set of Pacific Ocean only between 50 South and 20 North. • Metrics: Mean of the absolute value of the slopes of the anomalies in Stokes 1 from the Ocean model.

7. Set of L1-L2OS tools • Short term stability: Eclipse regions (3.2.5) • Evolution of the descending AFFOV brightness temperature anomalies in Stokes 1 between 0 North and 48 North from Pacific Ocean orbits in December. • Metrics: Mean of the absolute value of the slopes of the anomalies in Stokes 1 from the Ocean model.

8. Set of L1-L2OS tools • Hovmoller plots (3.2.6) • Evolution of the ascending/descending AFFOV brightness temperature anomalies in Stokes 1 over the entire Ocean between two dates. • Metrics: Mean of the absolute value of the slopes of the anomalies in Stokes 1 from the Ocean model.

9. Set of L1-L2OS tools • Spatial Bias at the Ocean (OTT analysis) (3.4.1) • Spatial distribution of the averaged EAFFOV brightness temperature anomalies in all polarizations for a specific orbit, between 45 South and 8 South. • Metrics: Bias and RMS computed for each region of the snapshot.

10. General processing chain and building of the data set catalogue

11. Configuration File description • It is composed by functional blocks, each of one performing one of the following tasks: • Ingest L2OS products to generate the data set catalogue. • Assimilate a new L1c product, to construct the required parameters using Ocean Model data from an existing L2OS data set from the catalogue. • Execute one of the tools over data contained in one of the data sets. • The user can add as many blocks as desired. However they are executed in the following order: • First, the ingestion and assimilation of L2OS and L1c files. • Second, the running of the tools. • Each block is identified and built using pre-defined tags, which provide control over the input parameters required for each tool.

12. Configuration File description • The function of the tags will be: • Identify the type of block • The data set of those already stored to be used. • The orbit, list of orbits, or set of specific orbits to be analysed or employed in the tool. • The orbit type (ascending, descending, or both) to select. • Polarization to select, when needed. • Geographical areas to filter data, in the form of boxes. The user can provide as many boxes as desired. • Scale parameters to control the plots and avoid results out of scale. • The Tool Box parses and checks the provided configuration file, in order to detect errors in the definition of these parameters.

13. Tool Box processing chain

14. Data assimilation processing chain

15. Tools processing chain

16. L20S Tool Box Architecture & Release • Hardware & Software requirements • Linux OS and Python 2.7, including Scipy, Matplotlib, Basemap… • No less than 6GB of RAM • 2.25 MB of HDD per day (around 820 MB per year) • All the required software does not require special licenses. • Ingestion of files will take a significant amount of time (TBD). However, the ingestion can be done at regular intervals, to include the new files being generated. • Execution of all the tools for one data set will consume no more than 4-6 hours.