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Ali Chase

Senior Oceanographer

Email

achase@apl.uw.edu

Phone

206-543-7836

Research Interests

Underway Optical Measurements
Phytoplankton Community Composition
Ocean Color Remote Sensing
Imaging-in-flow Cytometry
Machine Learning
Hyperspectral Radiometry
Cloud Computing

Biosketch

Ali is a bio-optical oceanographer conducting research on the use of optics and remote sensing to study phytoplankton dynamics, with a focus on developing methods and tools that enable the use of large and complex datasets. Ali leads the Marine Phytoplankton & Optics Group (planktonoptics.com) and works on projects spanning regional-to-global scales.

Education

B.A. Geology and Environmental Studies, Bowdoin College, 2009

M.S. Oceanography, University of Maine, 2014

Ph.D. Oceanography, University of Maine, 2020

Ali Chase's Website

http://planktonoptics.com

Publications

2000-present and while at APL-UW

Exploring CO2 fugacity along the east coast of South America aboard the schooner Tara

Olivier, L., and 9 others including A. Chase, "Exploring CO2 fugacity along the east coast of South America aboard the schooner Tara," Earth Syst. Sci. Data, 17, 3583-3598, doi:10.5194/essd-17-3583-2025, 2025.

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30 Jul 2025

The air–sea CO2 flux in the coastal ocean is a critical component of the global carbon budget, yet it remains poorly understood due to limited data, the many sources and sinks of carbon, and their complex interactions. In August–November 2021, the Tara schooner collected over 14 000 km of CO2 fugacity (fCO2) measurements along the coast of South America, including in the Amazon River–ocean continuum (https://doi.org/10.5281/zenodo.13790064, Olivier et al., 2024a). The Amazon River and its oceanic plume exhibit complex interactions under the combined influence of many processes such as tides and bathymetry. Observations revealed a wide range of fCO2 values, from up to 3000 μatm in the river to a minimum of 42 μatm downstream of the plume, where values were notably lower than atmospheric levels. South of the estuary, the fCO2 of the North Brazil Current waters (0–9°S) exceeds 400 μatm, while along the Brazil Current (10–30°S), fCO2 is around 400 μatm and decreases with temperature and distance from the Equator. Due to its high variability in the coastal environment, in the dataset salinity emerged as the primary driver of fCO2 variability across this dynamic region. Despite strong variability, comparison with discrete samples of other carbonate parameters showed a mean difference of 2 μatm, within the range of uncertainties of the chemical formulas used for comparison. This dataset provides critical insights into the under-sampled region of the Brazilian coast, improving our understanding of coastal fCO2 dynamics and their role in the global carbon budget.

A model for community-driven development of best practices: the Ocean Observatories Initiative Biogeochemical Sensor Data Best Practices and User Guide

Palevsky, H.I., and 38 others including A.P. Chase, "A model for community-driven development of best practices: the Ocean Observatories Initiative Biogeochemical Sensor Data Best Practices and User Guide," Front. Mar. Sci., 11, doi:10.3389/fmars.2024.1358591, 2024.

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3 Apr 2024

The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for creating science-ready biogeochemical data products from OOI data, culminating in the publication of the GOOS-endorsed OOI Biogeochemical Sensor Data Best Practices and User Guide. For Best Practices related to ocean observatories, engaging observatory staff is crucial, but having a "user-defined" process ensures the final product addresses user needs. Our process prioritized bringing together a diverse team and creating an inclusive environment where all participants could effectively contribute. Incorporating the perspectives of a wide range of experts and prospective end users through an iterative review process that included "Beta Testers"’ enabled us to produce a final product that combines technical information with a user-friendly structure that illustrates data analysis pipelines via flowcharts and worked examples accompanied by pseudo-code. Our process and its impact on improving the accessibility and utility of the end product provides a roadmap for other groups undertaking similar community-driven activities to develop and disseminate new Ocean Best Practices.

Toward a synthesis of phytoplankton communities composition methods for global-scale application

Kramer, S.J., and 14 others including A.P. Chase, "Toward a synthesis of phytoplankton communities composition methods for global-scale application," Linmol. Oceanogr. Methods, 22, 217-240, doi:10.1002/lom3.10602, 2024.

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1 Apr 2024

The composition of the marine phytoplankton community has been shown to impact many biogeochemical processes and marine ecosystem services. A variety of methods exist to characterize phytoplankton community composition (PCC), with varying degrees of taxonomic resolution. Accordingly, the resulting PCC determinations are dependent on the method used. Here, we use surface ocean samples collected in the North Atlantic and North Pacific Oceans to compare high-performance liquid chromatography pigment-based PCC to four other methods: quantitative cell imaging, flow cytometry, and 16S and 18S rRNA amplicon sequencing. These methods allow characterization of both prokaryotic and eukaryotic PCC across a wide range of size classes. PCC estimates of many taxa resolved at the class level (e.g., diatoms) show strong positive correlations across methods, while other groups (e.g., dinoflagellates) are not well captured by one or more methods. Since variations in phytoplankton pigment concentrations are related to changes in optical properties, this combined dataset expands the potential scope of ocean color remote sensing by associating PCC at the genus- and species-level with group- or class-level PCC from pigments. Quantifying the strengths and limitations of pigment-based PCC methods compared to PCC assessments from amplicon sequencing, imaging, and cytometry methods is the first step toward the robust validation of remote sensing approaches to quantify PCC from space.

More Publications

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