IOOS
U.S. IOOS is a national and regional partnership working to provide ocean, coastal and Great Lakes observations, data, tools, and forecasts to improve safety, enhance the economy, and protect our environment. Our primary purpose is to provide free and open data about the state of our oceans and Great Lakes to our users. These data are fundamental to understanding the health of our marine ecosystems, to monitor the climate signal as captured in oceanographic conditions, and to provide predictions about the future state of our oceans and coasts.
GSoC Participation History
Technologies
Topics
Past Projects
Filling the gaps within the IOOS quality control schema for ocean glider data.
I propose a development period of 5 stages to gauge community needs, assess the toolbox, and potentially augment it with additional tests or...
Integrating Empirical Dynamic Modeling (EDM) into the Fisheries Integrated Modeling System (FIMS)
This project proposes the integration of Empirical Dynamic Modeling (EDM) into the Fisheries Integrated Modeling System (FIMS), an open-source...
Scalable OCSMesh: Parallelization and Spatial Partitioning
This project aims to transform OCSMesh into a truly HPC-native tool by migrating its parallel architecture to mpi4py for distributed computing....
Enhancing CrocoLakeTools with IOOS Data Sync from ERDDAP
CrocoLakeTools currently downloads ocean datasets from static sources, either a fixed URL or a fixed file list. This works for stable snapshots like...
Enhancing noaa_coops: Bringing Software Engineering Best Practices to Ocean Data Access
The noaa_coops package provides oceanographic data access but has critical gaps: large date ranges fail without pagination, no retry logic for rate...
Add sex structure to FIMS statistical-catch-at-age model
This project extends the Fisheries Integrated Modeling System (FIMS) to support user-defined sex structure in population models. Currently, FIMS...
Enhance NOS skill assessment package’s user and developer experience
The NOS OFS Skill Assessment package is a Python-based framework used to evaluate operational forecast systems (OFS) through observation retrieval,...
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