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Emilio Mayorga

Senior Oceanographer

Email

emiliom@uw.edu

Phone

206-543-6431

Education

B.S. Environmental Engineering Science, Massachusetts Institute of Technology, 1992

Ph.D. Chemical Oceanography, University of Washington, 2004

Projects

Sampling QUantitative Internal-wave Distributions — SQUID

Our goals are to understand the generation, propagation, and dissipation mechanisms for oceanic internal gravity waves to enable seamless, skillful modeling & forecasts of these internal waves between the deep ocean and the shore.

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26 Feb 2024

The SQUID team will provide a globally distributed observing program for shear, energy flux, and mixing by internal waves. We will use profiling floats — measuring temperature, salinity, velocity, and turbulence — that will yield new insights into internal wave regimes and parameterizations, and that will provide direct and derived data products tailored for use by modeling groups for comparison and validation.

GeoHackWeek: Workshop on Geospatial Data Science

APL-UW researchers teamed with University and industry partners to explore open source geospatial software development during a workshop held 14–18 November.

14 Nov 2016

BiGCZ: Cyberinfrastructure for Bio and Geoscience processes in the Critical Zone

The goal of this project is to co-develop with the "Critical Zone" science community a high-performance web-based integration and visualization environment for joint analysis of cross-scale Bio and Geoscience processes in the Critical Zone (BiGCZ), spanning experimental and observational designs.

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1 Dec 2013

The Critical Zone (CZ) is Earth's permeable near-surface layer -- from the atmosphere at the vegetation's canopy to the lower boundary of actively circulating groundwaters. The BiGCZ system will be an open-source software system leveraging the ODM2 information model and specifically designed to address the challenges of managing, sharing, analyzing and integrating diverse data from the multiple disciplines encompassing CZ science.

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Publications

2000-present and while at APL-UW

An inclusive, collaborative approach to developing oceanography data science skills

Mitchell, C., and 9 others including W.-J. Lee and E. Mayorga, "An inclusive, collaborative approach to developing oceanography data science skills," Oceanography, 39, 50-55, doi:10.5670/oceanog.2026.e104, 2026.

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1 Mar 2026

Over the last two decades, there has been an explosion of oceanographic data from a broad array of ocean observing platforms, as well as dramatic improvements in the ability of ocean models to resolve processes across multiple temporal and spatial scales. Ocean researchers' ability to leverage computing tools and resources are key to effectively understanding and monitoring our ocean, the marine ecosystems it supports, and the response of the Earth system to climate change. Therefore, data science skills have become essential in the scientific discovery process, and it is becoming increasingly important to have computational skills in our research toolbox. OceanHackWeek was launched in 2018 to build an inclusive community that promotes data and software proficiency in oceanography. With a mission to meet, collaborate, and learn at the intersection of ocean and data sciences, OceanHackWeek provides a vibrant, diverse, and inclusive community that embodies the vision of an open ocean science future. In this article we present the OceanHackWeek model, provide an overview of the curriculum and formats of the events, and discuss the lessons learned and recommendations for implementing an OceanHackWeek-style event.

Harnessing marine open data science for ocean sustainability in Africa, South Asia, and Latin America

Martin, P.E., E.E. Holmes, E. Mayorga, and 25 others, "Harnessing marine open data science for ocean sustainability in Africa, South Asia, and Latin America," Oceanography, 38, doi:10.5670/oceanog.2025.121, 2025.

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1 Mar 2025

One of the biggest barriers to conducting ocean science around the globe is limited access to computational tools and resources, including software, computing infrastructure, and data. Open tools, such as open-source software, open data, and online computing resources, offer promising solutions toward more equitable access to scientific resources. Here, we discuss the enabling power of these tools in under-resourced and non-English speaking regions, based on experience gained in the organization of three independent programs in West African, Latin American, and Indian Ocean nations. These programs have embraced the "hackweek" learning model that bridges the gap between data science and domain applications. Hackweeks function as knowledge exchange forums and foster meaningful international and regional connections among scientists. Lessons learned across the three case studies include the importance of using open computational and data resources, tailoring programs to regional and cultural differences, and the benefits and challenges of using cloud-based infrastructure. Sharing capacity in marine open data science through the regional hackweek approach can expand the participation of more diverse scientific communities and help incorporate different perspectives and broader solutions to threats to marine ecosystems and communities.

Interoperable and scalable echosounder data processing with Echopype

Lee, W.-J., L. Setiawan, C. Tuguinay, E. Mayorga, and V. Staneva, "Interoperable and scalable echosounder data processing with Echopype," ICES J. Mar. Sci., EOR, doi:10.1093/icesjms/fsae133, 2024.

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12 Oct 2024

Echosounders are high-frequency sonar systems used to sense fish and zooplankton underwater. Their deployment on a variety of ocean observing platforms is generating vast amounts of data at an unprecedented speed from the oceans. Efficient and integrative analysis of these data, whether across different echosounder instruments or in combination with other oceanographic datasets, is crucial for understanding marine ecosystem response to the rapidly changing climate. Here we present Echopype, an open-source Python software library designed to address this need. By standardizing data as labeled, multi-dimensional arrays encoded in the widely embraced netCDF data model following a community convention, Echopype enhances the interoperability of echosounder data, making it easier to explore and use. By leveraging scientific Python libraries optimized for distributed computing, Echopype achieves computational scalability, enabling efficient processing in both local and cloud computing environments. Echopype's modularized package structure further provides a unified framework for expanding support for additional instrument raw data formats and incorporating new analysis functionalities. We plan to continue developing Echopype by supporting and collaborating with the echosounder user community, and envision that the growth of this package will catalyze the integration of echosounder data into broader regional and global ocean observation strategies.

More Publications

Acoustics Air-Sea Interaction & Remote Sensing Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Environmental & Information Systems Ocean Engineering Ocean Physics Polar Science Center
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