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 <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
 
-<meta name="author" content="Cassie Nickles &amp; Catalina Taglialatela">
 
 <title>2024 SWOT Pre-Conference Workshop: AGU Chapman - Data Access Workshop for NASA’s SWOT Satellite</title>
 <style>
@@ -211,7 +210,7 @@ <h2 id="toc-title">On this page</h2>
 <header id="title-block-header" class="quarto-title-block default">
 <div class="quarto-title">
 <h1 class="title">Data Access Workshop for NASA’s SWOT Satellite</h1>
-<p class="subtitle lead">An in person workshop at AGU Chapman: Remote Sensing of the Water Cycle</p>
+<p class="subtitle lead">In person at AGU Chapman: Remote Sensing of the Water Cycle</p>
 </div>
 
 
@@ -245,7 +244,7 @@ <h3 class="anchored" data-anchor-id="workshop-goals">Workshop Goals</h3>
 <li>Provide an inclusive place to learn about and experience working with NASA’s SWOT Hydrology Data;</li>
 <li>Provide strategies and best practices for finding and accessing NASA Earthdata in the Cloud. Specifically, participants will learn how to access data from AWS S3 buckets and have a better understanding of the Python ecosystem used to analyze the data depending on size and data formats;</li>
 <li>Better understand the needs of Earthdata data scientists by providing a post survey and engaging in discussions with workshop participants;</li>
-<li>Identify and practice using popular open source tools and utilities.</li>
+<li>Practice using popular open source tools and utilities.</li>
 </ul>
 </section>
 <section id="workshop-description" class="level3">
@@ -255,7 +254,7 @@ <h3 class="anchored" data-anchor-id="workshop-description">Workshop Description<
 </section>
 <section id="acknowledgements" class="level2">
 <h2 class="anchored" data-anchor-id="acknowledgements">Acknowledgements</h2>
-<p>This Workshop and its content has been developed by a large team at PO.DAAC.</p>
+<p>This Workshop and its content has been developed by the PO.DAAC team at NASA’s Jet Propulsion Laboratory, California Institute of Technology.</p>
 
 
 </section>

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-    "text": "About\n\nWorkshop Goals\n\nProvide an inclusive place to learn about and experience working with NASA’s SWOT Hydrology Data;\nProvide strategies and best practices for finding and accessing NASA Earthdata in the Cloud. Specifically, participants will learn how to access data from AWS S3 buckets and have a better understanding of the Python ecosystem used to analyze the data depending on size and data formats;\nBetter understand the needs of Earthdata data scientists by providing a post survey and engaging in discussions with workshop participants;\nIdentify and practice using popular open source tools and utilities.\n\n\n\nWorkshop Description\nThe Surface Water and Ocean Topography (SWOT) satellite, a joint NASA-CNES venture, provides unprecedented measurements of surface water extents and elevations for hydrologic science and applications. The observations are offered through a range of data products including river and lake vector data in shapefiles, and raster, pixel cloud, and pixel vector data in netCDF. The shapefile products will also contain estimates of river discharge and lake storage change. In this pre-meeting workshop, participants will be introduced to SWOT and the various ways to access and utilize its data products, including via cloud computing, local download, and data transformation tools. Participants will be able to utilize a provided cloud computing environment accessed via personal laptops, or their own laptop’s compute power to explore SWOT data using data recipes by PO.DAAC, NASA’s Physical Oceanography Data Active Archive Center. No prior cloud computing experience is necessary. We welcome all to come and see how SWOT data could augment existing workflows or initiate new, innovative science and applications! The data tutorials at the workshop will use Python, but no prior experience is needed."
+    "text": "About\n\nWorkshop Goals\n\nProvide an inclusive place to learn about and experience working with NASA’s SWOT Hydrology Data;\nProvide strategies and best practices for finding and accessing NASA Earthdata in the Cloud. Specifically, participants will learn how to access data from AWS S3 buckets and have a better understanding of the Python ecosystem used to analyze the data depending on size and data formats;\nBetter understand the needs of Earthdata data scientists by providing a post survey and engaging in discussions with workshop participants;\nPractice using popular open source tools and utilities.\n\n\n\nWorkshop Description\nThe Surface Water and Ocean Topography (SWOT) satellite, a joint NASA-CNES venture, provides unprecedented measurements of surface water extents and elevations for hydrologic science and applications. The observations are offered through a range of data products including river and lake vector data in shapefiles, and raster, pixel cloud, and pixel vector data in netCDF. The shapefile products will also contain estimates of river discharge and lake storage change. In this pre-meeting workshop, participants will be introduced to SWOT and the various ways to access and utilize its data products, including via cloud computing, local download, and data transformation tools. Participants will be able to utilize a provided cloud computing environment accessed via personal laptops, or their own laptop’s compute power to explore SWOT data using data recipes by PO.DAAC, NASA’s Physical Oceanography Data Active Archive Center. No prior cloud computing experience is necessary. We welcome all to come and see how SWOT data could augment existing workflows or initiate new, innovative science and applications! The data tutorials at the workshop will use Python, but no prior experience is needed."
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