Archive for pCO2

New over-determined CO2 system solver QUODcarb

Posted by mmaheigan 
· Thursday, May 29th, 2025 

Do you work with over-determined datasets of seawater carbon dioxide system chemistry? QUODcarb (Quantifying Uncertainty in an Over-Determined marine carbonate system), a new over-determined CO2-system solver is described in the recently published “QUODcarb: A Bayesian solver for over-determined datasets of seawater carbon dioxide system chemistry.” The Bayesian formulation of the novel solver and demonstrates its use on an over-determined dataset from the Gulf of Mexico (COMECC-3) that included measurements of DIC, AT, pH, pCO2, and [CO3]. The over-determined calculations, with self-consistent uncertainty quantification, can calculate carbonate ion concentration uncertainty within the GOA-ON climate uncertainty target of 1% with implications for ocean acidification monitoring projects.

Find the Matlab code on GitHub: https://github.com/fprimeau/QUODcarb

Figure caption: Diagram depicting the measured quantities (left side) and the use of thermodynamic constant (pK) formulations and mass balance total (_T) formulations in seawater carbonate chemistry calculations. Adapted from Figure 1 in Carter et al., 2024 a, to illustrate how QUODcarb can replace CO2SYS calculations to include three or more carbonate variable measurements in over-determined calculations while also enabling uncertainty quantification.
Physical measurements are shown with pink backgrounds, mass balance total contents are shown with light green backgrounds, thermodynamic constants are in gray, and carbonate chemistry variables are in yellow. Temperature dependent carbonate chemistry measurements (e.g., pH and pCO2) may be included at different input temperatures. The calculator reflects the analogy that QUODcarb acts as a calculator for solving the system of nonlinear equations.

 

Authors
Marina Fennell (University of California, Irvine)
Francois Primeau (University of California, Irvine)

Swirling Currents: How Ocean Mesoscale Affects Air-Sea CO2 Exchange

Posted by mmaheigan 
· Friday, October 25th, 2024 

Due to a sparsity of in‐situ observations and the computational burden of eddy‐resolving global simulations, there has been little analysis on how mesoscale processes (e.g., eddies, meanders—lateral scales of 10s to 100s km) influence air‐sea CO2 fluxes from a global perspective. Recently, it became computationally feasible to implement global eddy‐resolving [O (10) km] ocean biogeochemical models. Many questions related to the influence of mesoscale motions on CO2 fluxes remain open, including whether ocean eddies serve as hotspots for CO2 sink or source in specific dynamic regions.

A recent study in Geophysical Research Letters investigated the contribution of ocean mesoscale variability to air-sea CO2 fluxes by analyzing the CO2 flux anomaly within the mesoscale band using a coarse-graining approach in a global eddy-resolving biogeochemical simulation. We found that in eddy-rich mid-latitude regions, ocean mesoscale variability can contribute to over 30% of the total CO2 flux variability. The cumulative net CO2 flux associated with mesoscale motions is on the order of 105 tC per year. The global pattern of cumulative mesoscale-related CO2 flux exhibits significant spatial heterogeneity, with the highest values in western boundary currents, the Antarctic Circumpolar Current, and the equatorial Pacific. The local distribution of cumulative mesoscale-related CO2 flux displays zonal bands alternate between positive (a net source) and negative (a net sink) due to the meandering nature of ocean mesoscale currents, which is related to local relative vorticity and the background cross-stream pCO2 gradient.

Figure caption. Mesoscale (<nominal 2 degree) contribution to air‐sea CO2 flux (F<2°CO2)in the model. (a)–(d) Monthly time series of F<2°CO2 (black lines) and cumulative F<2°CO2 (green/red solid lines) in four locations marked in (e). Dashed lines are the least squares regression of cumulative flux for the period 1982–2000; slopes are indicated in the bottom left; (e) Blue colors imply a CO₂ sink, and red colors represent a source. The figure shows the global distribution of the regressed slopes of cumulative F<2°CO2. Units are converted from mol m-2 per year to kg of CO2 per year using the atomic mass of CO2. This figure shows significant spatial heterogeneity of mesoscale-modulated CO2 flux, showing contributions to both CO₂ sources and sinks across different regions of the ocean, with a magnitude on the order of 105 tC per year.

 

Authors
Yiming Guo (Yale University; now at Woods Hole Oceanographic Institution)
Mary-Louise Timmermans (Yale University)

Sea ice loss amplifies CO2 increase in the Arctic

Posted by mmaheigan 
· Thursday, January 7th, 2021 

Warming and sea ice loss over the past few decades have caused major changes in sea surface partial pressure of CO2 (pCO2) of the western Arctic Ocean, but detailed temporal variations and trends during this period of rapid climate-driven changes are not well known.

Based on an analysis of an international Arctic pCO2 synthesis data set collected between 1994-2017, the authors of a recent paper published in Nature Climate Change observed that summer sea surface pCO2 in the Canada Basin is increasing at twice the rate of atmospheric CO2 rise. Warming, ice loss and subsequent CO2 uptake in the Basin are amplifying seasonal pCO2 changes, resulting in a rapid long-term increase. Consequently, the summer air-sea CO2 gradient has decreased sharply and may approach zero by the 2030s, which is reducing the basin’s capacity to remove CO2 from the atmosphere. In stark contrast, sea surface pCO2 on the Chukchi Shelf remains low and relatively constant during this time frame, which the authors attribute to increasingly strong biological production in response to higher intrusion of nutrient-rich Pacific Ocean water onto the shelf as a result of increased Bering Strait throughflow. These trends suggest that, unlike the Canada Basin, the Chukchi Shelf will become a larger carbon sink in the future, with implications for the deep ocean carbon cycle and ecosystem.

As Arctic sea ice melting accelerates, more fresh, low-buffer capacity, high-CO2 water will enter the upper layer of the Canada Basin, which may rapidly acidify the surface water, endanger marine calcifying organisms, and disrupt ecosystem function.

Figure. 1: TOP) Sea surface pCO2 trend in the Canada Basin and Chukchi Shelf. The grey dots represent the raw observations of pCO2, black dots are the monthly mean of pCO2 at in situ SST, and red dots are the monthly means of pCO2 normalized to the long-term means of SST. The arrows indicate the statistically significant change in ∆pCO2. BOTTOM) Sea ice-loss amplifying surface water pCO2 in the Canada Basin. Black dots represent the initial condition for pCO2 and DIC at -1.6 ℃. The arrows indicate the processes of warming (red), CO2 uptake from the atmosphere (green), dilution by ice meltwater (blue). The yellow shaded areas indicate the possible seasonal variations of pCO2, which are amplified by the synergistic effect of ice melt, warming and CO2 uptake.

Authors:
Zhangxian Ouyang (University of Delaware, USA),
Di Qi (Third Institute of Oceanography, China),
Liqi Chen (Third Institute of Oceanography, China),
Taro Takahashi† (Columbia University, USA),
Wenli Zhong (Ocean University of China, China),
Michael D. DeGrandpre (University of Montana, USA),
Baoshan Chen (University of Delaware, USA),
Zhongyong Gao (Third Institute of Oceanography, China),
Shigeto Nishino (Japan Agency for Marine-Earth Science and Technology, Japan),
Akihiko Murata (Japan Agency for Marine-Earth Science and Technology, Japan),
Heng Sun (Third Institute of Oceanography, China),
Lisa L. Robbins (University of South Florida, USA),
Meibing Jin (International Arctic Research Center, USA),
Wei-Jun Cai* (University of Delaware, USA)

Investigating variability and change in subpolar Southern Ocean pCO2 via time-series and float data

Posted by mmaheigan 
· Tuesday, November 6th, 2018 

The Southern Ocean dominates the mean global ocean sink for anthropogenic carbon, but its sparse sampling relative to other basins limits our capacity to quantify carbon uptake and accompanying seasonal to interannual variability, which is critical to predicting future ocean carbon uptake and storage. Since 2002, underway pCO2 measurements collected as part of the Drake Passage Time-series (DPT) Program have informed our understanding of seasonally varying air-sea pCO2 gradients and by inference, the carbon fluxes in this region. Understanding whether Drake Passage air-sea fluxes are representative of the broader subpolar Southern Ocean was the focus of a recent study in Biogeosciences.

Top left panel: Mean surface ocean seasonal pCO2 cycle estimate for datasets from the Surface Ocean CO2 Atlas (SOCAT) in the subpolar Southern Ocean: black- SOCAT within the Drake Passage (DP) region; green- SOCAT outside the DP region; blue- all SOCAT in Southern Ocean Subpolar Seasonally Stratified (SPSS) biome; red- Self Organizing Map Feed-forward Network (SOM-FFN) product. Shading represents 1 standard error for biome-scale monthly means driven by interannual variability. Bar plot indicates the number of years containing observations in a given month (maximum of 15 years).
Top right panel: Mean surface ocean pCO2 seasonal cycle estimate for black: underway Drake Passage Time-series data for years 2002–2016; purple: DPT for years 2016–2017 to match years covered by the floats; and orange: SOCCOM floats. Seasonal cycles are shown on an 18-month cycle, calculated from a monthly mean time series with the atmospheric correction to year 2017. Shading represents 1 standard error accounting for the spatial and temporal heterogeneity of the sample and the measurement error (2.7 % or ±11 µatm at a pCO2 of 400 µatm for floats; ±2 µatm for DPT data) combined using the square root of the sum of squares.

An analysis of available Southern Ocean pCO2 data from inside vs. outside the Drake Passage showed agreement in the timing and amplitude of seasonal pCO2 variations, suggesting that the seasonality so carefully recorded by DPT is in fact representative of the broader subpolar Southern Ocean. DPT’s high temporal resolution sampling is critical to constraining estimates of the seasonal cycle of surface pCO2 in this region, as wintertime underway pCO2 data remain sparse outside the Drake Passage. Comparisons of the DPT data to an emerging dataset of float-estimated pCO2 from the SOCCOM (Southern Ocean Carbon and Climate Observations and Modeling) project showed that both shipboard and autonomous platforms capture the expected seasonal cycle for the subpolar Southern Ocean, with an austral wintertime peak driven by deep mixing and a summertime low driven by biological uptake. However, the seasonal cycle derived from float-estimated pCO2 has a larger seasonal amplitude compared to the DPT data due to an earlier and much lower observed summertime minimum.

The Drake Passage Time-series illustrates the large variability of surface ocean pCO2 in the Southern Ocean and exemplifies the value of sustained observations for understanding changing ocean carbon uptake in this dynamic region. Coordinated monitoring efforts that combine a robust ship-based observational network with a well-calibrated array of autonomous biogeochemical floats will improve and expand our understanding of the Southern Ocean carbon cycle in the future.

Authors:
Amanda R. Fay (Lamont Doherty Earth Observatory)
Nicole S. Lovenduski (University of Colorado)
Galen A. McKinley (Lamont Doherty Earth Observatory)
David R. Munro (University of Colorado)
Colm Sweeney (University of Colorado, NOAA Earth System Research Laboratory)
Alison R. Gray (University of Washington)
Peter Landschützer (Max Planck Institute for Meteorology, Germany)
Britton B. Stephens (National Center for Atmospheric Research)
Taro Takahashi (Lamont Doherty Earth Observatory)
Nancy Williams (Oregon State University)

Shelf-wide pCO2 increase across the South Atlantic Bight

Posted by mmaheigan 
· Thursday, August 2nd, 2018 

Relative to their surface area, coastal regions represent some of the largest carbon fluxes in the global ocean, driven by numerous physical, chemical and biological processes. Coastal systems also experience human impacts that affect carbon cycling, which has large socioeconomic implications. The highly dynamic nature of these systems necessitates observing approaches and numerical methods that can both capture high-frequency variability and delineate long-term trends.

Figure 1: The South Atlantic Bight (SAB) was divided into four sections using isobaths: the coastal zone (0 to 15 m), the inner shelf (15 to 30 m), the middle shelf (30 to 60 m), and the outer shelf (60 m and beyond). The X’s indicate the locations of the Gray’s Reef mooring (southern X) and the Edisto mooring (northern X).

In two recent studies using mooring- and ship-based ocean CO2 system data, authors observed that pCO2 is increasing from the coastal zone to the outer shelf of the South Atlantic Bight at rates greater than the global average oceanic and atmospheric increase (~1.8 µatm y-1). In recent publications in Continental Shelf Research and JGR-Oceans, the authors analyzed pCO2 data from 46 cruises (1991-2016) using a novel linear regression technique to remove the seasonal signal, revealing an increase in pCO2 of 3.0-3.7 µatm y-1 on the outer and inner shelf, respectively. Using a Generalized Additive Mixed Model (GAMM) approach for trend analysis, authors observed that the rates of increase were slightly higher than the deseasonalization technique, yielding pCO2 increases of 3.3 to 4.5 µatm y-1 on the outer and inner shelf, respectively. The reported pCO2 increases result in potential pH decreases of -0.003 to -0.004 units y-1.

Figure 2: The time series of fCO2 in the four regions of the SAB (cruise observations) and from the Gray’s Reef mooring on the inner shelf indicate an increase across the shelf. These data are the observed values, however, the trend lines for each time series are calculated using deseasonalized values using the reference year method.

Analysis of the pCO2 time-series from the Gray’s Reef mooring (using a NOAA Moored Autonomous pCO2 system from July 2006 -July 2015) yielded a rate of increase (3.5 ± 0.9 µatm y-1) that was comparable to the cruise data on the inner shelf (3.7 ± 2.2 and 4.5 ± 0.6 µatm y-1, linear and GAMM methods, respectively). Validation data collected at the mooring suggest that underway data from cruises and the moored data are comparable. Neither thermal processes nor atmospheric dissolution (the primary driver of oceanic acidification) can explain the observed pCO2 increase and concurrent pH decrease across the shelf. Unlike the middle and outer shelves, where an increase in SST could account for up to 1.1 µatm y-1 of the observed pCO2 trend, there is no thermal influence in the coastal zone and inner shelf. While 1.8 µatm y-1 could be attributed to the global average atmospheric increase, the remainder is likely due to transport from coastal marshes and in situ biological processes.  As the authors have shown, the increasing coastal and oceanic trend in pCO2 can lead to a decrease in pH, especially if there is no increase in buffering capacity.  More acidic waters can have a long term affect on coastal ecosystem services and biota.

Also see Eos Editor’s Vox on this research by Peter Brewer https://eos.org/editors-vox/coastal-ocean-warming-adds-to-co2-burden

Authors:

Multidecadal fCO2 Increase Along the United States Southeast Coastal Margin (JGR-Oceans)
Janet J. Reimer (University of Delaware)
Hongjie Wang (Texas A &M University – Corpus Christi)
Rodrigo Vargas (University of Delaware)
Wei-Jun Cai (University of Delaware)

And

Time series pCO2 at a coastal mooring: Internal consistency, seasonal cycles, and interannual variability (Continental Shelf Research)
Janet J. Reimer (University of Delaware)
Wei-Jun Cai (University of Delaware; University of Georgia)
Liang Xue (University of Delaware; First Institute of Oceanography, China)
Rodrigo Vargas (University of Delaware)
Scott Noakes (University of Georgia)
Xinping Hu (Texas A &M University – Corpus Christi)
Sergio R. Signorini (Science Applications International Corporation)
Jeremy T. Mathis (NOAA Arctic Research Program)
Richard A. Feely (NOAA Pacific Marine Environmental Laboratory)
Adrienne J. Sutton (NOAA Pacific Marine Environmental Laboratory; University of Washington)
Christopher Sabine (University of Hawaii Manoa)
Sylvia Musielewicz (NOAA Pacific Marine Environmental Laboratory; University of Washington)
Baoshan Chen (University of Delaware; University of Georgia)
Rik Wanninkhof (NOAA Atlantic Oceanographic and Meteorological Laboratory)

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