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# Earth Information System: Sea-Level Change
The NASA Earth Information System (EIS) is a collaborative project that is synthesizing research across many thematic areas to produce a more holistic understanding of the Earth system. The goals of the EIS project are to **pioneer the use of next-generation cyberinfrastructure and data systems** to accelerate scientific discovery and to reduce the barriers to entry for scientists and the broader Earth science community in the EIS process by deploying and championing NASA **Open-Source Science** principles and best practices. More information about EIS can be found here: https://www.earthdata.nasa.gov/dashboard/eis. Resources from across all thematic EIS areas and community discussion can be found here: https://github.com/Earth-Information-System/.
One focus of the Sea-Level Change thematic area within EIS is on deploying Earth process models in the cloud, establishing better ways of linking different models to one another, and connecting the models to data in NASA's Earthdata Cloud. This repository is a living document that describes the resources available via the EIS, as well as lessons learned, which are relevant to sea-level change. The models described below are implemented to run in in the Science Managed Cloud Environment (SMCE), which runs on Amazon Web Services (AWS) cloud-computing resources. **EIS team members with access to the EIS SMCE are able to login and immediately run the models using Jupyter notebooks, without any additional environment configuration or model installation required.** Other resources are publicly available without access to the SMCE and we note those below. All code will ultimately be open source, after it goes through the software release process.
**Points of contact:** [Denis Felikson](mailto:denis.felikson@nasa.gov), [Ian Fenty](mailto:ian.fenty@jpl.nasa.gov)
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The EIS team has deployed several process models in the [Science Managed Cloud Environment (SMCE)](https://www.nccs.nasa.gov/systems/SMCE), which runs on Amazon Web Services (AWS) cloud computing resources:
1. Community Firn Model (CFM)
1. Ice-sheet and Sea-level system model (ISSM)
1. Estimating the Circulation and Climate of the Ocean (ECCO)
### Community Firn Model (CFM)
[EIS CFM code repository](https://git.mysmce.com/eis-sealevel/eis-sea-level-change-general/-/tree/master/CFM)
### Ice-sheet and Sea-level system Model (ISSM) and the Sea-Level Projection System (SLPS)
ISSM is installed on (1) the JupyterHub and (2) the AWS parallel cluster (pCluster) within the EIS Sea-Level Change SMCE. Jupyter notebooks are available to configure and run ISSM, as well as analyze the output.
<mark>Links to code repository coming soon.</mark>
### Estimating the Circulation and Climate of the Ocean (ECCO)
ECCO is installed on the AWS parallel cluster (pCluster) within the EIS Sea-Level Change SMCE.
Several tools can be used to configure and run ECCO:
1. ECCO Perturbation tool web app: http://ecco.smce.nasa.gov/
1. ECCO Perturbation Jupyter notebook: https://git.mysmce.com/jli30/ecco-interface-test
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The Vertical Land Motion (VLM) visualizer is an notebook demonstrating interactive exploration tools for examining VLM from InSAR and GPS measurements. The notebook includes tools for making VLM profiles across cross-sections of land, as well as breaking down contributors to VLM. This notebook is intended to demonstrate these and other interactive capabilities for examining Earth Science datasets in a JupyterHub environment. A web app for such a tool for be developed from this notebook if desired.
[VLM visualization code repository](https://git.mysmce.com/eis-sealevel/eis-sea-level-change-general/-/tree/master/vlm)
For web apps visualizing data across all aspects of the EIS project, we need an extensible and straightforward way of serving that data. As EIS is built on the AWS cloud, an ideal solution would be one that also leverages the AWS cloud and can sit on top of our science processing tools and data stored in the cloud (including within our S3 buckets on AWS). This project showcases one way to host a web API serving various EIS Sea Level geodesy datasets, including MEaSUREs gridded sea surface height anomalies, tide gauges, and GRACE/GRACE-FO mascon solutions.
[Geodesy web API code repository](https://git.mysmce.com/eis-sealevel/geodesy-web-api)
The SWOT mission is an international mission with joint effort between NASA and CNES (the French Space Agency) with contributions from UK and canadian space agencies aimed at providing high-resolution measurements of Earth's surface water and ocean topography. SWOT data has significant potential for advancing our understanding of the world's oceans, freshwater resources, and the global water cycle.
The mission launched its satellite on December 16th, 2022. The data products will be released to public in the fall of 2023. Before the data release, EIS Sea Level team aims to foster a thriving community centered around the use of SWOT data. We specifically focus on the following.
1. **Build a communnity on a collaborative platform**: Utilize the cloud-based platform that brings together researchers, developers who are interested in SWOT data as well as NASA DAACs that host mission data.
1. **Promote open-source software and tools**: Encourage the development and sharing of open-source software, tools, and libraries specifically designed for processing, analyzing, and visualizing SWOT data. By making these resources available, the community can collectively enhance the capabilities of SWOT data analysis, benefiting everyone involved. Early development will enable quick adoption of SWOT data in science and applications.
1. **Organize workshops and conferences**: Outreach through hosting and cohosting workshops, hackathons and training sessions focused on SWOT data applications and research.
1. **Support collaborative research and applications**: Facilitate joint research initiatives and applications development among community members. This includes creating a repository of shared datasets, offering grant opportunities for collaborative projects, and promoting interdisciplinary research that combines SWOT data with other Earth observation data sources.
By these steps, we hope to build a robust community around SWOT data, promoting open-source knowledge and software, and encouraging collaborative research and applications. This will ultimately drive scientific advancements and enable more effective management of the Earth's water resources and predicting the ocean's role in the Earth's climate system.
[SWOT code repository and knowledge base](https://git.mysmce.com/eis-sealevel/swot-pub)
## Discoveries
The EIS team is publishing science Discoveries via NASA's [Visualization, Exploration, and Data Analysis (VEDA)](https://www.earthdata.nasa.gov/esds/veda) Dashboard. This platform offers a way for both peer-reviewed and in-progress research to be presented in an interactive way online. The goals are (1) to connect Discoveries with the analysis code that was used to produce and interpret the data in the Discovery and (2) provide a way for the broader Earth science community to provide feedback and discuss the Discovery.
Here is a VEDA Discover with a contribution from the EIS Sea-Level Change thematic area: https://www.earthdata.nasa.gov/dashboard/eis/discoveries/eis-coastal-risks.