About

Alison Gray is an oceanographer who studies the circulation of the ocean and its impact on the physics and chemistry of the climate system. She uses observations from many different sources, including profiling floats, gliders, satellites, and ships, to investigate the dynamics of the ocean circulation on a variety of scales. Her research also aims to improve our understanding of the interactions between ocean circulation and global biogeochemical cycles.

Research topics

• Oceanography
• Climatology
• Geology
• Environmental science
• Seismology
• Ecology
• Chemistry
• Environmental chemistry
• Atmospheric sciences

Selected publications

• Nonlinear Interactions of Timing and Amplitude Biases in Modeled Southern Ocean pCO2: The Roles of Dissolved Inorganic Carbon, Total Alkalinity, and Sea Surface Temperature

  2026-03-14

  articleOpen accessCorresponding

  The Southern Ocean is a major sink for atmospheric carbon dioxide and critical to the current and future carbon cycle. This net annual CO2 flux reflects the balance between strong seasonal variability characterized by opposing periods of winter outgassing and summer uptake. Using a simple framework, we evaluate how model biases in both the amplitude and timing of dissolved inorganic carbon (DIC) and total alkalinity (TA) and in the amplitude of sea surface temperature (SST) impact simulated pCO2. We examine seasonal CO2 fluxes and pCO2 south of the Subantarctic Front in 42 Earth System Model and three state estimate simulations. Only 11 of the 45 simulations have a seasonal pCO2 cycle with a correlation of ≥0.7 to observed pCO2, while 26 have a correlation of

  PublisherDOI

• Nonlinear Interactions of Timing and Amplitude Biases in Modeled Southern Ocean pCO2: The Roles of Dissolved Inorganic Carbon, Total Alkalinity, and Sea Surface Temperature

  Maryland Shared Open Access Repository (USMAI Consortium) · 2026-01-10

  articleOpen access

  The Southern Ocean is a major sink for atmospheric carbon dioxide and critical to the current and future carbon cycle. This net annual CO2 flux reflects the balance between strong seasonal variability characterized by opposing periods of winter outgassing and summer uptake. Using a simple framework, we evaluate how model biases in both the amplitude and timing of dissolved inorganic carbon (DIC) and total alkalinity (TA) and in the amplitude of sea surface temperature (SST) impact simulated pCO2. We examine seasonal CO2 fluxes and pCO2 south of the Subantarctic Front in 42 Earth System Model and three state estimate simulations. Only 11 of the 45 simulations have a seasonal pCO2 cycle with a correlation of ?0.7 to observed pCO2, while 26 have a correlation of <0. Four of the well-correlated models accurately represent the seasonality of SST, DIC, and TA, while TA biases compensate for DIC or SST biases in the other seven. DIC and SST amplitude biases are related to mixed layer (MLD) biases, with shallow MLDs, especially in the summer, correlated with larger amplitude DIC and SST cycles than observed. The amplitude of seasonal Net Primary Production is correlated to DIC and TA timing. We provide input on the main adjustments needed to correct the simulated pCO2 seasonality in each of the evaluated models. These findings highlight the difficulty and importance of capturing the seasonal processes influencing the carbonate system to correctly model and predict the Southern Ocean carbon sink and its response to a changing climate.

  PublisherDOI

• Shear and Temperature Microstructure Measurements from APEX Floats

  Journal of Atmospheric and Oceanic Technology · 2025-05-23

  articleOpen access

  Abstract Temperature and shear microstructure data were collected by the epsilometer, a custom turbulence package, integrated on to a Teledyne Webb APEX float. Profiles were conducted in both a controlled-ascent mode similar to the Argo mission (∼0.08 m s −1 rise rate) and at the float’s maximum rise rate of ∼0.3 m s −1 , which might be used for shorter missions supporting process studies. In both modes, profiles of turbulent dissipation rate of kinetic energy ε and thermal dissipation rate χ were computed. Valid ε profiles were obtained in both profiling modes, though platform vibration was significant at the faster ascent rate, and probe sensitivity was reduced at the slower rise rate. Shear spectra resolve the viscous rolloff well, giving a noise floor for ε of about 3 × 10 −10 W kg −1 in both modes. Individual temperature spectra also resolve the diffusive rolloff for χ about 2 × 10 −11 K 2 s −1 despite the presence of significant fine-scale structure in temperature, which impacted the quality of the temperature gradient spectra at low wavenumber. Following published best practices, each ε and χ estimate was kept or rejected based on a figure of merit measuring the goodness of fit of the measured spectrum to the theoretical form. The ε cannot be computed when the buoyancy pump is active (3% of the time) due to excessive vibrations. At other times, about >65% and 75% of raw estimates of the turbulent dissipation rates ε and χ met our quality control criteria, respectively. Significance Statement Widespread turbulence measurements will improve our understanding of the ocean but are only possible with large arrays of autonomous profiling instruments. Here, the feasibility of making direct shear and temperature turbulence measurements from a profiling float is demonstrated.

  PublisherOA PDFDOI

• Random forest regression using autonomous in situ ocean observations: Inferring small-scale nutrient variability during a Southern Ocean field experiment

  Artificial Intelligence for the Earth Systems · 2025-01-07

  preprint

  Abstract Small-scale ocean processes are known to modulate nutrient availability in the upper ocean, yet nutrient variability at scales of O (1) day and O (1) km has remained challenging to characterize from observations. Here, we show that small-scale nutrient information can be inferred from the 2019 Southern Ocean Glider Observations of Submesoscales (SOGOS) field experiment using random forest regression (RFR). In this experiment, a Biogeochemical-Argo float with coarse-resolution nutrient sensing capabilities was co-deployed with two rapid-sampling Seagliders to autonomously observe a turbulent region by the Southwest Indian Ridge over ∼80 days in austral winter. Since the Seagliders did not measure nitrate directly, we used RFR to estimate nitrate from temperature, salinity, pressure, and oxygen data. The RFR was locally trained using nearby ship-based and Biogeochemical-Argo float observations to capture region-specific relationships between these variables. When tested on nitrate data from the SOGOS float, our RFR reproduced these measurements with high fidelity (95% of absolute errors ≤ 0.72 µmolkg −1 ) and outperformed existing, widely-used global nutrient estimation routines trained primarily on ship-based data. Applying the RFR to the Seaglider observations then generated novel nitrate distributions extending to 1000 m with horizontal resolution of ∼1.5 km and 2–3 hours compared to ∼75 km and 5 days for the SOGOS float. Our analysis of high-resolution machine learning estimates of Seaglider nitrate, coupled with Seaglider observations of other properties, suggests that vigorous small-scale stirring enhances upper ocean nutrient availability in this region and highlights the importance of oceanic turbulence in mediating biological productivity.

  PublisherDOI

• Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

  Frontiers in Marine Science · 2025-06-02 · 11 citations

  articleOpen access

  The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

  PublisherOA PDFDOI

• Progressive Oxygenation of the North Atlantic Subpolar Gyre

  Journal of Geophysical Research Oceans · 2025-10-31

  articleOpen access

  Abstract The subpolar North Atlantic (SPNA) is one of the few regions where the deep ocean is in direct contact with the atmosphere, making it a key location for interior ocean ventilation through gas exchange. We use a novel observation‐based data product to analyze large‐scale patterns of the air‐sea flux of oxygen, finding a mean annual flux of 48.1 14.6 Tmol from the atmosphere into the ocean integrated over the SPNA (N–N). An analysis of a fully‐closed oxygen budget from the data‐assimilative ECCO‐Darwin ocean biogeochemistry model suggests that the net uptake is counteracted by oxygen removal through ocean circulation and mixing. Over an annual cycle, a SPNA oxygen uptake of 63.6 13.8 Tmol at densities greater than 26.7 kg drives a wintertime oxygen increase in corresponding mode and deep water layers. 87% of this net annual uptake occurs in the density range of subpolar mode water (SPMW), 26.7 kg 27.63 kg , in the upper branch of the Atlantic Meridional Overturning Circulation (AMOC). Our results demonstrate that oxygen is injected during mode water formation throughout the subpolar gyre's cyclonic pathway from the North Atlantic Current toward the Labrador Sea. Along this path, SPMW becomes progressively denser and more oxygenated, and is ultimately transformed into Labrador Sea Water which exports the accumulated oxygen to the global ocean in the lower branch of the AMOC.

  PublisherDOI

• CbPM estimates of net primary production in the North Atlantic from profiling floats and satellites diverge seasonally due to fluorescence and vertical extrapolation effects

  2025-11-14

  articleOpen access

  Net primary production (NPP), defined as the difference between gross primary production and phytoplankton respiration, is often estimated using algorithms applied to remote sensing data. As satellites only observe the uppermost layers of the ocean, assumptions are needed to extend these measurements to greater depths. Some NPP algorithms, such as the Carbon-based Productivity Model (CbPM), have been adapted for use with vertically-resolved data collected by autonomous profiling floats, eliminating the need for vertical extrapolation but introducing challenges related to float measurements of fluorescence rather than chlorophyll a (Chl-a; a required CbPM input parameter). This study analyzes more than a decade of float observations from the North Atlantic Ocean to estimate NPP with the CbPM algorithm and quantify its sensitivity to different algorithm input parameters. We focus on isolating the effects of (1) fluorescence versus Chl-a, (2) depth-resolved versus vertically-extrapolated information, and (3) remote versus in situ observations of the first optical depth. Applying a novel, per-profile conversion of float fluorescence to Chl-a concentration based on satellite data reveals significant differences between adjusted and unadjusted float estimates of NPP, at seasonal and annual timescales. Depth-integrated production estimates vary between platforms, with notable seasonal compensations that, on an annual scale, mask key differences in the results derived from in situ measurements and remote sensing. The sign and timing of differences in productivity through depth have important implications for accurately quantifying marine NPP on subannual timescales.

  PublisherDOI

• Three centuries of biogeochemical change in a temperate embayment as revealed by sediment core stable isotopes, radiometric dating, and historical ecology

  Marine Ecology Progress Series · 2025-01-21 · 1 citations

  articleOpen access

  Efforts to improve water quality in urbanized embayments may be complicated by changes that predate contemporary ecological monitoring efforts. Such is the case in Wickford Harbor, Rhode Island, one of the oldest continuous settlements in the northeastern USA, that is exhibiting degraded water quality after centuries of land use change, physical modifications, and nutrient loading. Here, we used historical ecology and sediment geochemical records to discern the biogeochemical impacts of these anthropogenic forcings over time. Segmented linear regressions fitted to the radiometrically dated sediment cores found break points in the geochemical record that align with physical modifications in the 1800s and nutrient enrichment in the 1930s. Reductions in grain size and sorting over time suggest that railway construction in the late 1800s constrained the hydrodynamic flushing of the study system and is an important driver of current water quality. Ratios of bulk carbon, nitrogen, and phosphorus content are indicative of a system that has been persistently eutrophic. Indeed, bulk N isotope composition reflects a 5‰ increase in δ 15 N since the colonial era, representing a shift to anthropogenic N sources that accompanied regional land use change. Subsequent increases in bulk C stable isotope composition and biogenic silica concentration suggest that primary production increased during the 18 th and late 20 th centuries. This work illustrates how ecological changes contributing to poor water quality can occur prior to contemporary nutrient loading, and efforts to restore systems in the absence of a historical ecological baseline are unlikely to produce a predictable ecosystem recovery.

  PublisherDOI

• Future Priorities for Observing the Dynamics of the Southern Ocean

  Bulletin of the American Meteorological Society · 2024-11-01 · 1 citations

  articleOpen access
  PublisherOA PDFDOI

• Global Estimates of Mesoscale Vertical Velocity Near 1,000 m From Argo Observations

  Journal of Geophysical Research Oceans · 2024-01-01 · 4 citations

  articleOpen access

  Abstract Global estimates of mesoscale vertical velocity remain poorly constrained due to a historical lack of adequate observations on the spatial and temporal scales needed to measure these small magnitude velocities. However, with the wide‐spread and frequent observations collected by the Argo array of autonomous profiling floats, we can now better quantify mesoscale vertical velocities throughout the global ocean. We use the underutilized trajectory data files from the Argo array to estimate the time evolution of isotherm displacement around a float as it drifts at 1,000 m, allowing us to quantify vertical velocity averaged over approximately 4.5 days for that depth level. The resulting estimates have a non‐normal, high‐peak, and heavy‐tail distribution. The vertical velocity distribution has a mean value of (1.9 ± 0.02) × 10 −6 m s −1 and a median value of (1.3 ± 0.2) × 10 −7 m s −1 , but the high‐magnitude events can be up to the order of 10 −4 m s −1 . We find that vertical velocity is highly spatially variable and is largely associated with a combination of topographic features and horizontal flow. These are some of the first observational estimates of mesoscale vertical velocity to be taken across such large swaths of the ocean without assumptions of uniformity or reliance on horizontal divergence.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: Observations of Three-dimensional Transport Pathways and Biogeochemical Fluxes in the Southern Ocean using Autonomous Gliders

  NSF · $431k · 2018–2024

Frequent coauthors

• Dhruv Balwada

  Lamont-Doherty Earth Observatory

  37 shared

• K. Shafer Smith

  27 shared

• Ryan Abernathey

  Lamont-Doherty Earth Observatory

  27 shared

• Qiyu Xiao

  Hunan Cancer Hospital

  27 shared

• Lynne D. Talley

  Scripps Institution of Oceanography

  24 shared

• Stephen C. Riser

  University of Washington

  21 shared

• Jorge L. Sarmiento

  15 shared

• Nancy L. Williams

  13 shared

Labs

• Our Advancement TeamPI

Education

• Ph.D., School of Oceanography

  University of Washington

  2014