diff --git a/.nojekyll b/.nojekyll index a4183897..9d4ba33a 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -ee33ff3e \ No newline at end of file +536d52cd \ No newline at end of file diff --git a/quarto_text/SWOT.html b/quarto_text/SWOT.html index 348efac1..3d69f39f 100644 --- a/quarto_text/SWOT.html +++ b/quarto_text/SWOT.html @@ -1157,12 +1157,12 @@

Access SWOT Oceanography data in the cloud | locally

-
-

Hydrocron: Time series API Multi-reach tutorial - See Hydrocron documentation and more description under tools below.

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SWOT Raster Multifile Access & Quality Flag Application in the cloud | locally

+
+

Hydrocron: Time series API Multi-reach tutorial - See Hydrocron documentation and more description under tools below.

+

Quality Flag Tutorial - Quality Flag Tips for all products, specifically demonstrates SSHA 8-bit quality flag application

diff --git a/search.json b/search.json index 627808b5..8ab6fe14 100644 --- a/search.json +++ b/search.json @@ -4305,7 +4305,7 @@ "href": "quarto_text/SWOT.html#swot-data-resources-tutorials", "title": "SWOT", "section": "SWOT Data Resources & Tutorials", - "text": "SWOT Data Resources & Tutorials\n\nSearch & Download\n\nVia Graphical User Interface:\n\nFind/download SWOT data on Earthdata Search\n\n\n\nProgrammatically: ie. within Python code workflows\n\nSearch and Download via earthaccess\nwith unique SWORD river reach ID\nwith unique Hydrologic Unit Code (HUC) basin ID\n\n\n\nVia Command Line - PO.DAAC subscriber/downloader examples:\nHydrology: These examples will download either the river vector files or the raster files for February 2024:\npodaac-data-downloader -c SWOT_L2_HR_RiverSP_2.0 -d ./SWOT_L2_HR_RiverSP_2.0/ --start-date 2024-02-01T00:00:00Z --end-date 2024-02-29T23:59:59Z\nThis only downloads 1 hours worth of data for the globe:\npodaac-data-downloader -c SWOT_L2_HR_Raster_2.0 -d ./SWOT_L2_HR_Raster_2.0/ --start-date 2024-02-01T00:00:00Z --end-date 2024-02-29T00:59:59Z\nOceanography: These examples will download modeled sea surface heights for the whole SSH collection and then the anomalies using the subscriber then downloader:\npodaac-data-subscriber -c SWOT_L2_LR_SSH_2.0 -d ./SWOT_L2_LR_SSH_2.0/ --start-date 2023-03-29T00:00:00Z \npodaac-data-subscriber -c SWOT_L2_NALT_OGDR_SSHA_2.0 -d ./data/SWOT_L2_NALT_OGDR_SSHA_2.0 --start-date 2023-08-01T00:00:00Z --end-date 2023-08-02T00:00:00Z\npodaac-data-downloader -c SWOT_L2_NALT_OGDR_SSHA_2.0 -d ./data/SWOT_L2_NALT_OGDR_SSHA_2.0 --start-date 2023-06-23T00:00:00Z --end-date 2023-06-23T06:00:00Z\n\nSee how to Download/Subscribe for more information on how to use the PO.DAAC subscriber/downloader including with spatial queries.\n\n\n\nSearch SWOT Passes over Time\nCNES developed this dedicated visualization tool for a quick look at where SWOT has been, where it is, and where it will be. Once you have selected the area of interest, click the Search button to search for SWOT passes. The results are displayed in a table and the swaths that intersect the area of interest are displayed on the map. Click on the marker to view the pass number.\nTo launch the Binder application, click on this link.\nTo launch jupyterlab in binder, clink on this link.\n\n\nSWOT Spatial Coverage\nTo identify spatial coverage/search terms for the science 21-day orbit, PO.DAAC has created a KMZ file that has layers of the SWOT passes and tiles, with corresponding scene numbers identified in the pop-up when a location is selected (see screenshot below). Each layer has direct links to Earthdata Search results (the ‘search’ links) for corresponding files. The passes layer has useful information for all SWOT products, but links to the LR products specifically, the tiles layer is useful for HR products (L1B_HR_SLC, L2_HR_PIXC, and L2_HR_PIXCVec products use tile spatial extents while the L2_HR_Raster product uses scenes. L2_HR_RiverSP and L2_HR_LakeSp use continent-level passes).\nTo download the KMZ file, for the science 21-day orbit, click here.\nFor the Beta Pre-validated data KMZ that used the cal/val 1-day orbit, click here.\nThese files can be opened in the Google Earth desktop application and viewed like the following:\n\n\n\n\n\nScreenshot of pass and tile layer in spatial coverage KMZ file viewed in the Google Earth Desktop application\n\n\n\nThe KaRIN HR Masks true/false text pop up for tiles comes from the two different masks used for different parts of the year. The ‘Seasonal’ mask is used from Dec 1st to March 1st and removes part of the Canadian archipelago coverage to collect additional data over sea ice instead, indicated by true/false statements.\n\n\nTips for SWOT Spatial Search\nTo support spatial search of SWOT data products, the following naming conventions may be of help. Tip: use these shortname identifiers below when searching for SWOT data in the NASA Earthdata Search portal or programmatically using the CMR API and/or earthaccess python library.\nSWOT HR data products use Tiles, Scenes, or Continent-level Swaths IDs depending on the product, which define the spatial extent of what is in each file, as follows in the chart below. Along-track scene and tile numbers are numbered sequentially following the spacecraft flight direction, so the numbers increase from south to north for ascending passes and from north to south for descending passes. SWOT LR products use global swaths and nadir tracks that use pass numbers. See SWOT Spatial Coverage Section above for information to find the pass, tile or scene numbers.\n\n\n\n\n\n\n\n\n\n\nProduct (organized by…)\nFile Naming Convention\nNotes\n\n\n\n\n\n\nL2_HR_RiverSP L2_HR_LakeSP (continent-level swaths)\nPPP_CC\nPPP = pass number (valid range: 001-584) CC = continent code (options listed below) AF - Africa EU - Europe and Middle East SI - Siberia AS - Central and Southeast Asia AU - Australia and Oceania SA - South America NA - North America and Caribbean AR - North American Arctic GR - Greenland Ex: 013_NA = pass 013, North America\n\n\n\n\nL2_HR_PIXC L2_HR_PIXCVec L1B_HR_SLC (tiles)\nPPP_TTTC\nPPP = pass number (valid range: 001-584) TTT = tile number (valid range: 001-308) C = character L or R corresponding to left or right swaths Ex: 001_120R = pass 001, right swath, tile 120\n\n\n\n\nL2_HR_Raster (scenes)\nPPP_SSS\nPPP = pass number (valid range: 001-584) SSS = scene number (valid range: 001-154) Scenes correspond to 2 x 2 sets of tiles scene number x 2 = tile number Ex: 001_060 = pass 001, scene 60, corresponding to the same location as the PIXC/PIXCVec tile example above.\n\n\n\n\nL2_RAD_(O/I)GDR L2_NALT_(O/I)GDR(nadir) L2_LR_SSH (swath)\nPPP_\nPPP = pass number (valid range: 001-584) Ex: 013_ = pass 013\n\n\n\n\n\nIn Earthdata Search GUI:\n\nUse the top left Search Box and search with keywords, e.g. SWOT L2 HR\nSelect a collection of interest\nA Filter Granule filtering capability will show up on the left hand side of the GUI. Recall naming convention is _cycle_pass_spatialIdentifier_.\n\nUse wildcards to narrow down spatially, using one of the codes from the table above depending on your use case. Tip: use underscores ( _ ) with your wildcard key words for a more specific search.\nExample: *_NA_* will filter the RiverSP or LakeSP collection selected to only return those granules (files) that are part of the North America collection\nExample: *_004_256_* will filter the RiverSP or LakeSP collection selected to only return those granules (files) that correspond to cycle 004, pass 256\nExample: *_004_253_128* will filter the Raster collection selected to only return those granules (files) that correspond to cycle 004, pass 253, scene 128\n\nIn addition, you can also draw a region of interest (ROI) on the map, using the Spatial Search Filter icon or the Advanced Search under the main search box. These will help to filter what is returned for the spatial search. Tip: It is recommended that ROI searches are used together with wildcards described above for a more accurate search.\n\n\n\n\nAccess & Visualization\n\n\n\n\n\nAccess SWOT Hydrology data in the cloud | locally\n\n\nAccess SWOT Oceanography data in the cloud | locally\n\n\nHydrocron: Time series API Multi-reach tutorial - See Hydrocron documentation and more description under tools below.\n\n\nSWOT Raster Multifile Access & Quality Flag Application in the cloud | locally\n\n\nQuality Flag Tutorial - Quality Flag Tips for all products, specifically demonstrates SSHA 8-bit quality flag application\n\n\n\nData Story\n\nSWOT Hydrology Science Workflow in the Cloud - Retrieving SWOT attributes (WSE, width, slope) and plotting a longitudinal profile along a river or over a basin\n\n\n\nGIS workflows\n\nSWOT: Through a GIS Lens StoryMap\n\n\nShapefile exploration\n\n\nTransform SWOT Datetime field for use in GIS Software\n\n\n\nTransform\n\nHiTIDE subsetter for Sea Surface Height Products - select KaRIn instrument in sensors\n\n\nTransform SWOT Hydrology river reach shapefiles into time series\n\n\nNetCDF to Geotiff Conversion - mac or Linux | Windows\n\n\n\nTools\nHydrocron - an API that repackages the river shapefile dataset (L2_HR_RiverSP) into csv or GeoJSON formats that make time-series analysis easier. SWOT data is archived as individually timestamped shapefiles, which would otherwise require users to perform potentially thousands of file operations per river feature to view the data as a timeseries. Hydrocron makes this possible with a single API call.\nSWODLR - a system for generating on demand raster products from SWOT L2 raster data with custom resolutions, projections, and extents. -in development", + "text": "SWOT Data Resources & Tutorials\n\nSearch & Download\n\nVia Graphical User Interface:\n\nFind/download SWOT data on Earthdata Search\n\n\n\nProgrammatically: ie. within Python code workflows\n\nSearch and Download via earthaccess\nwith unique SWORD river reach ID\nwith unique Hydrologic Unit Code (HUC) basin ID\n\n\n\nVia Command Line - PO.DAAC subscriber/downloader examples:\nHydrology: These examples will download either the river vector files or the raster files for February 2024:\npodaac-data-downloader -c SWOT_L2_HR_RiverSP_2.0 -d ./SWOT_L2_HR_RiverSP_2.0/ --start-date 2024-02-01T00:00:00Z --end-date 2024-02-29T23:59:59Z\nThis only downloads 1 hours worth of data for the globe:\npodaac-data-downloader -c SWOT_L2_HR_Raster_2.0 -d ./SWOT_L2_HR_Raster_2.0/ --start-date 2024-02-01T00:00:00Z --end-date 2024-02-29T00:59:59Z\nOceanography: These examples will download modeled sea surface heights for the whole SSH collection and then the anomalies using the subscriber then downloader:\npodaac-data-subscriber -c SWOT_L2_LR_SSH_2.0 -d ./SWOT_L2_LR_SSH_2.0/ --start-date 2023-03-29T00:00:00Z \npodaac-data-subscriber -c SWOT_L2_NALT_OGDR_SSHA_2.0 -d ./data/SWOT_L2_NALT_OGDR_SSHA_2.0 --start-date 2023-08-01T00:00:00Z --end-date 2023-08-02T00:00:00Z\npodaac-data-downloader -c SWOT_L2_NALT_OGDR_SSHA_2.0 -d ./data/SWOT_L2_NALT_OGDR_SSHA_2.0 --start-date 2023-06-23T00:00:00Z --end-date 2023-06-23T06:00:00Z\n\nSee how to Download/Subscribe for more information on how to use the PO.DAAC subscriber/downloader including with spatial queries.\n\n\n\nSearch SWOT Passes over Time\nCNES developed this dedicated visualization tool for a quick look at where SWOT has been, where it is, and where it will be. Once you have selected the area of interest, click the Search button to search for SWOT passes. The results are displayed in a table and the swaths that intersect the area of interest are displayed on the map. Click on the marker to view the pass number.\nTo launch the Binder application, click on this link.\nTo launch jupyterlab in binder, clink on this link.\n\n\nSWOT Spatial Coverage\nTo identify spatial coverage/search terms for the science 21-day orbit, PO.DAAC has created a KMZ file that has layers of the SWOT passes and tiles, with corresponding scene numbers identified in the pop-up when a location is selected (see screenshot below). Each layer has direct links to Earthdata Search results (the ‘search’ links) for corresponding files. The passes layer has useful information for all SWOT products, but links to the LR products specifically, the tiles layer is useful for HR products (L1B_HR_SLC, L2_HR_PIXC, and L2_HR_PIXCVec products use tile spatial extents while the L2_HR_Raster product uses scenes. L2_HR_RiverSP and L2_HR_LakeSp use continent-level passes).\nTo download the KMZ file, for the science 21-day orbit, click here.\nFor the Beta Pre-validated data KMZ that used the cal/val 1-day orbit, click here.\nThese files can be opened in the Google Earth desktop application and viewed like the following:\n\n\n\n\n\nScreenshot of pass and tile layer in spatial coverage KMZ file viewed in the Google Earth Desktop application\n\n\n\nThe KaRIN HR Masks true/false text pop up for tiles comes from the two different masks used for different parts of the year. The ‘Seasonal’ mask is used from Dec 1st to March 1st and removes part of the Canadian archipelago coverage to collect additional data over sea ice instead, indicated by true/false statements.\n\n\nTips for SWOT Spatial Search\nTo support spatial search of SWOT data products, the following naming conventions may be of help. Tip: use these shortname identifiers below when searching for SWOT data in the NASA Earthdata Search portal or programmatically using the CMR API and/or earthaccess python library.\nSWOT HR data products use Tiles, Scenes, or Continent-level Swaths IDs depending on the product, which define the spatial extent of what is in each file, as follows in the chart below. Along-track scene and tile numbers are numbered sequentially following the spacecraft flight direction, so the numbers increase from south to north for ascending passes and from north to south for descending passes. SWOT LR products use global swaths and nadir tracks that use pass numbers. See SWOT Spatial Coverage Section above for information to find the pass, tile or scene numbers.\n\n\n\n\n\n\n\n\n\n\nProduct (organized by…)\nFile Naming Convention\nNotes\n\n\n\n\n\n\nL2_HR_RiverSP L2_HR_LakeSP (continent-level swaths)\nPPP_CC\nPPP = pass number (valid range: 001-584) CC = continent code (options listed below) AF - Africa EU - Europe and Middle East SI - Siberia AS - Central and Southeast Asia AU - Australia and Oceania SA - South America NA - North America and Caribbean AR - North American Arctic GR - Greenland Ex: 013_NA = pass 013, North America\n\n\n\n\nL2_HR_PIXC L2_HR_PIXCVec L1B_HR_SLC (tiles)\nPPP_TTTC\nPPP = pass number (valid range: 001-584) TTT = tile number (valid range: 001-308) C = character L or R corresponding to left or right swaths Ex: 001_120R = pass 001, right swath, tile 120\n\n\n\n\nL2_HR_Raster (scenes)\nPPP_SSS\nPPP = pass number (valid range: 001-584) SSS = scene number (valid range: 001-154) Scenes correspond to 2 x 2 sets of tiles scene number x 2 = tile number Ex: 001_060 = pass 001, scene 60, corresponding to the same location as the PIXC/PIXCVec tile example above.\n\n\n\n\nL2_RAD_(O/I)GDR L2_NALT_(O/I)GDR(nadir) L2_LR_SSH (swath)\nPPP_\nPPP = pass number (valid range: 001-584) Ex: 013_ = pass 013\n\n\n\n\n\nIn Earthdata Search GUI:\n\nUse the top left Search Box and search with keywords, e.g. SWOT L2 HR\nSelect a collection of interest\nA Filter Granule filtering capability will show up on the left hand side of the GUI. Recall naming convention is _cycle_pass_spatialIdentifier_.\n\nUse wildcards to narrow down spatially, using one of the codes from the table above depending on your use case. Tip: use underscores ( _ ) with your wildcard key words for a more specific search.\nExample: *_NA_* will filter the RiverSP or LakeSP collection selected to only return those granules (files) that are part of the North America collection\nExample: *_004_256_* will filter the RiverSP or LakeSP collection selected to only return those granules (files) that correspond to cycle 004, pass 256\nExample: *_004_253_128* will filter the Raster collection selected to only return those granules (files) that correspond to cycle 004, pass 253, scene 128\n\nIn addition, you can also draw a region of interest (ROI) on the map, using the Spatial Search Filter icon or the Advanced Search under the main search box. These will help to filter what is returned for the spatial search. Tip: It is recommended that ROI searches are used together with wildcards described above for a more accurate search.\n\n\n\n\nAccess & Visualization\n\n\n\n\n\nAccess SWOT Hydrology data in the cloud | locally\n\n\nAccess SWOT Oceanography data in the cloud | locally\n\n\nSWOT Raster Multifile Access & Quality Flag Application in the cloud | locally\n\n\nHydrocron: Time series API Multi-reach tutorial - See Hydrocron documentation and more description under tools below.\n\n\nQuality Flag Tutorial - Quality Flag Tips for all products, specifically demonstrates SSHA 8-bit quality flag application\n\n\n\nData Story\n\nSWOT Hydrology Science Workflow in the Cloud - Retrieving SWOT attributes (WSE, width, slope) and plotting a longitudinal profile along a river or over a basin\n\n\n\nGIS workflows\n\nSWOT: Through a GIS Lens StoryMap\n\n\nShapefile exploration\n\n\nTransform SWOT Datetime field for use in GIS Software\n\n\n\nTransform\n\nHiTIDE subsetter for Sea Surface Height Products - select KaRIn instrument in sensors\n\n\nTransform SWOT Hydrology river reach shapefiles into time series\n\n\nNetCDF to Geotiff Conversion - mac or Linux | Windows\n\n\n\nTools\nHydrocron - an API that repackages the river shapefile dataset (L2_HR_RiverSP) into csv or GeoJSON formats that make time-series analysis easier. SWOT data is archived as individually timestamped shapefiles, which would otherwise require users to perform potentially thousands of file operations per river feature to view the data as a timeseries. Hydrocron makes this possible with a single API call.\nSWODLR - a system for generating on demand raster products from SWOT L2 raster data with custom resolutions, projections, and extents. -in development", "crumbs": [ "Tutorials", "Dataset Specific", diff --git a/sitemap.xml b/sitemap.xml index e224eea3..f9c138aa 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -2,426 +2,426 @@ https://podaac.github.io/tutorials/external/ECCO_download_data.html - 2024-05-15T20:44:04.203Z + 2024-05-15T21:03:57.029Z https://podaac.github.io/tutorials/external/access-cloud-python.html - 2024-05-15T20:44:04.427Z + 2024-05-15T21:03:57.137Z https://podaac.github.io/tutorials/external/access-local-opendap.html - 2024-05-15T20:44:04.819Z + 2024-05-15T21:03:57.289Z https://podaac.github.io/tutorials/external/insitu_dataviz_demo.html - 2024-05-15T20:44:03.555Z + 2024-05-15T21:03:56.653Z https://podaac.github.io/tutorials/external/access-local-python.html - 2024-05-15T20:44:04.643Z + 2024-05-15T21:03:57.225Z https://podaac.github.io/tutorials/external/SWOT_SSH_dashboard.html - 2024-05-15T20:44:09.999Z + 2024-05-15T21:04:01.237Z https://podaac.github.io/tutorials/external/Downloader.html - 2024-05-15T20:44:05.651Z + 2024-05-15T21:03:57.669Z https://podaac.github.io/tutorials/external/read_data.html - 2024-05-15T20:44:05.467Z + 2024-05-15T21:03:57.593Z https://podaac.github.io/tutorials/external/cof-zarr-reformat.html - 2024-05-15T20:43:59.595Z + 2024-05-15T21:03:54.293Z https://podaac.github.io/tutorials/external/Subscriber.html - 2024-05-15T20:44:05.847Z + 2024-05-15T21:03:57.757Z https://podaac.github.io/tutorials/external/zarr_access.html - 2024-05-15T20:44:00.091Z + 2024-05-15T21:03:54.489Z https://podaac.github.io/tutorials/quarto_text/Tutorials.html - 2024-05-15T20:43:20.831Z + 2024-05-15T21:03:16.841Z https://podaac.github.io/tutorials/quarto_text/Advanced.html - 2024-05-15T20:43:20.831Z + 2024-05-15T21:03:16.841Z https://podaac.github.io/tutorials/quarto_text/Questions.html - 2024-05-15T20:43:20.831Z + 2024-05-15T21:03:16.841Z https://podaac.github.io/tutorials/quarto_text/SMODE.html - 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