Package: pysamosa
PySAMOSAPySAMOSA is a Python-based software for processing open ocean and coastal waveforms from SAR satellite
altimetry to measure sea surface heights, wave heights, and wind speed for the oceans and inland waters.
Satellite altimetry is a space-borne remote sensing technique used for Earth observation. More details on satellite
altimetry can be foundhere.The process of extracting of the three geophysical parameters from the reflected echoes/waveforms is called retracking. The measured (noisy) waveforms are fitted against the open ocean power return echo waveform model SAMOSA2 [1,2].In the coastal zone, the return echoes are affected by spurious signals from strongly reflective targets such as sand and mud banks, tidal flats, shipping platforms, sheltered bays, or calm waters close to the shoreline.The following European Space Agency (ESA) satellite altimetry missions are supported:Sentinel-3 (S3)Sentinel-6 Michael Freilich (S6-MF)The software retracks the waveforms, i.e. the Level-1b (L1b) data, to extract the
retracked variables SWH, range, and Pu.The open ocean retracker implementation specification documents from the official EUMETSAT baseline are used (S3 [1],
S6-MF [2]).For retracking coastal waveforms the following retrackers are implemented:SAMOSA+ [3]CORAL [4,5]In addition, FF-SAR-processed S6-MF data can be retracked using the zero-Doppler beam of the SAMOSA2 model and a
specially adapted $\alpha_p$ LUT table, created by the ESA L2 GPP project [7]. The application of the FF-SAR-processed data
has been validated in [5].Not validated (experimental) features:CryoSat-2 (CS2) supportSAMOSA++ coastal retracker [2]Monte-carlo SAMOSA2 simulatorGetting-startedUsageInstall pysamosa into your environment$ pip install pysamosaThis is the sample to retrack a single L1b file from the S6-MF missionfrompathlibimportPathimportnumpyasnpfrompysamosa.common_typesimportL1bSourceTypefrompysamosa.data_accessimportdata_vars_s3,data_vars_s6frompysamosa.retracker_processorimportRetrackerProcessorfrompysamosa.settings_managerimportget_default_base_settings,SettingsPresetl1b_files=[]# l1b_files.append(Path('S6A_P4_1B_HR______20211120T051224_20211120T060836_20220430T212619_3372_038_018_009_EUM__REP_NT_F06.nc'))l1b_files.append(Path.cwd().parent/'.data'/'s6'/'l1b'/'S6A_P4_1B_HR______20211120T051224_20211120T060836_20220430T212619_3372_038_018_009_EUM__REP_NT_F06.nc')l1b_src_type=L1bSourceType.EUM_S6_F06data_vars=data_vars_s6# configure coastal CORAL retrackerpres=SettingsPreset.CORALv2rp_sets,retrack_sets,fitting_sets,wf_sets,sensor_sets=get_default_base_settings(settings_preset=pres,l1b_src_type=l1b_src_type)rp_sets.nc_dest_dir=l1b_files[0].parent/'processed'rp_sets.n_offset=0rp_sets.n_inds=0#0 means allrp_sets.n_procs=6#use 6 cores in parallelrp_sets.skip_if_exists=Falseadditional_nc_attrs={'L1B source type':l1b_src_type.value.upper(),'Retracker preset':pres.value.upper(),}rp=RetrackerProcessor(l1b_source=l1b_files,l1b_data_vars=data_vars['l1b'],rp_sets=rp_sets,retrack_sets=retrack_sets,fitting_sets=fitting_sets,wf_sets=wf_sets,sensor_sets=sensor_sets,nc_attrs_kw=additional_nc_attrs,bbox=[np.array([-29.05,-29.00,0,360])],)rp.process()#start processingprint(rp.output_l2)#retracked L2 output can be found in hereA running minimal working example for retracking is shown innotebooks/retracking_example.ipynb.DevelopmentIt is highly recommended to use a proper Python IDE, such asPyCharm Communityor Visual Studio Code.
Using the IDE will allow you to familiarise yourself better with the code, debug and extend it.Clone the repo$ git clone {repo_url}Enter cloned directory$ cd pysamosaInstall dependencies into your conda env/virtualenv$ pip install -r requirements.txtCompile the .pyx files (e.g. model_helpers.pyx) by running cython to build the extensions
For Windows users: An installed C/C++ compiler may be required for installation, e.g. MSCV, which comes with
the freeVisual Studio Community$ python setup.py build_ext --inplaceOptional: Compile on an HPC cluster (not normally required)$ LDSHARED="icc -shared" CC=icc python setup.py build_ext --inplaceTipsThe following list provides a brief description of the recommended use of the software.Getting-started with Jupyter NotebookThenotebooks/retracking_example.ipynbcontains a sample script how to retrack a sample EUMETSAT baseline L1b file.
The retracked SWH and SWH data are compared with the EUMETSAT baseline L2 data. Thenotebooks/demo_script.pyprovides
the code example from above to quickly launch a small retracking example.More entry pointsThe filesmain_s3.py,main_s6.py,main_cs.py, (main_*.py) etc. serve as entry points for batch processing of
multiple nc files.
A list of L1b files (or a single file) is read for retracking, which are fully retracked or based on the given
bounding box (bbox) paramater. A retracked L2 file is written out per processed
L1b file.SettingsTheRetrackerProcessorinputs require theRetrackerProcessorSettings,RetrackerSettings,FittingSettings,WaveformSettings, andSensorSettingsobjects to be inserted during initialisation. The default settings of these settings objects can be retrieved with theget_default_base_settingsfunction based on the three
settingsL1bSourceTypeandSettingsPreset.
For instance, the following code snippet is taken from themain_s3.pyfile and retracks Sentinel-3 data with the default SAMOSA-based open ocean retracker with no SettingsPreset (100 waveforms from measurement index 25800,
and using 6 cores).l1b_src_type=L1bSourceType.EUM_S3pres=SettingsPreset.NONE#use this for the standard SAMOSA-based retracker [2]# pres = SettingsPreset.CORALv2  #use this for CORALv2 [5]# pres = SettingsPreset.NONE  #use this for SAMOSA+ [3]rp_sets,retrack_sets,fitting_sets,wf_sets,sensor_sets=get_default_base_settings(settings_preset=pres,l1b_src_type=l1b_src_type)rp_sets.nc_dest_dir=nc_dest_path/run_namerp_sets.n_offset=25800rp_sets.n_inds=100rp_sets.n_procs=6rp_sets.skip_if_exists=FalseEvaluation environmentThere are several unit tests located in./pysamosa/tests/that aim to analyse the retracked output in more detail.
The most important test scripts aretest_retrack_multi.py, which includes retracking of small along-track
segments of the S3A, S6, CS2 missions (and a generic input nc file).test_retrack_singleallows you to check the retracking result of a single waveform and compare it to reference
retracking result.Please uncomment the linempl.use('TkAgg')in fileconftest.pyto
plot the test output, which is particularly useful for the retracking tests in filestests/test_retrack_multi. pyandtests/test_retrack_multi.py.Difference between CORALv1 and CORALv2v2 has two additional extensions that were required for S6-MFretrack_sets.interference_masking_mask_before_le = True
Interference signals before the leading edge are also masked out by the adaptive inteference mitigation scheme (AIM, CORAL feature)fitting_sets.Fit_Var_2_MinMax_Hs = (0.0, 20)
lower SWH boundary for fitting procedure is set to 0.0, as defined in [2]Quality flagDuring the retracking process, the quality flag variablesswh_qual' andrange_qual' (where the latter is just a copy of the former)
are part of the retracked output and indicate the quality of the retracking of each individual waveform (0=good, 1=bad).
This makes a difference particularly in coastal scenarios where the waveforms are affected by spurious signals which tend
to cause incorrectly retracked waveforms. The CORAL coastal retracker maximises the number of valid records in the coastal zone.
We therefore emphasise the importance of consideringswh_qual/range_qualquality flags in the retracked product.ValidationRun testsTo run all the unit tests (using the pytest framework), run$ pytestComparison with EUMETSAT L2 baseline dataComparison of a retracked open ocean segment from S3 and S6-MF missions with the EUMETSAT L2 baseline (S3: 004,
S6-MF: F06)
(generated bynotebooks/retracking_example.ipynbJupyter notebook)S3S6-MFContributionsThis software is intended to be a community-based project. Contributions to this project are very welcome.
In this case:Fork this repositorySubmit a pull request to be merged back into this repository.Before submitting changes, please check that your changes pass flake8, black, isort and the
tests, including testing other Python versions with tox:$ flake8 pysamosa tests scripts
$ black . --check --diff
$ isort . --check-only --diff
$ pytest
$ toxIf your pull request is accepted, you will be included in the next official release and will be listed as a
co-author for the DOI link created by Zenodo.Future workPossible developments of this project are:Retracking-relatedAlign CS-2 retracking with the CS-2 baseline processing chain, validate againstSAMpydeveloped as part of theESA Cryo-TEMPO projectImplement evolutions of the EUMETSAT's baseline processing chain [6], e.g. the numerical retracking planned
for Q3/2023Software-relatedCreate notebook for a coastal retracking demoCreate richer documentation (readthedocs)CitationIf you use this software or the code, please cite this DOI:Florian Schlembach; Marcello Passaro. PySAMOSA: An Open-source Software Framework for Retracking SAMOSA-based, Open
Ocean and Coastal Waveforms of SAR Satellite Altimetry. Zenodo.https://zenodo.org/badge/latestdoi/646028227.AcknowledgementThe authors are grateful toSalvatore Dinardo for his support in implementing the SAMOSA-based and SAMOSA+ [3] retracking algorithms.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.References[1] SAMOSA Detailed Processing Model: Christine Gommenginger, Cristina Martin-Puig, Meric Srokosz, Marco Caparrini, Salvatore Dinardo, Bruno Lucas, Marco Restano, Américo, Ambrózio and Jérôme Benveniste, Detailed Processing Model of the Sentinel-3 SRAL SAR altimeter ocean waveform retracker, Version 2.5.2, 31 October 2017, Under ESA-ESRIN Contract No. 20698/07/I-LG (SAMOSA), Restricted access as defined in the Contract,  Jérôme Benveniste (Jerome.Benvensite@esa.int) pers. comm.[2] EUMETSAT. Sentinel-6/Jason-CS ALT Level 2 Product Generation Specification (L2 ALT PGS), Version V4D; 2022.https://www.eumetsat.int/media/48266.[3] Dinardo, Salvatore. ‘Techniques and Applications for Satellite SAR Altimetry over Water, Land and Ice’.
Dissertation, Technische Universität, 2020.https://tuprints.ulb.tu-darmstadt.de/11343/.[4] Schlembach, F.; Passaro, M.; Dettmering, D.; Bidlot, J.; Seitz, F. Interference-Sensitive Coastal SAR Altimetry
Retracking Strategy for Measuring Significant Wave Height. Remote Sensing of Environment 2022, 274, 112968.https://doi.org/10.1016/j.rse.2022.112968.[5] Schlembach, F.; Ehlers, F.; Kleinherenbrink, M.; Passaro, M.; Dettmering, D.; Seitz, F.; Slobbe, C. Benefits of Fully Focused SAR Altimetry to Coastal Wave Height Estimates: A Case Study in the North Sea. Remote Sensing of Environment 2023, 289, 113517.https://doi.org/10.1016/j.rse.2023.113517.[6] Scharroo, R.; Martin-Puig, C.; Meloni, M.; Nogueira Loddo, C.; Grant, M.; Lucas, B. Sentinel-6 Products Status. Ocean Surface Topography Science Team (OSTST) meeting in Venice 2022.https://doi.org/10.24400/527896/a03-2022.3671.[7] ESA L2 GPP Project: FF-SAR SAMOSA LUT generation was funded under ESA contract 4000118128/16/NL/AI.