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Unveiling the Past and Future of Ocean Acidification: A Novel Data Product covering 10 Global Surface OA Indicators

Posted by mmaheigan

· Wednesday, August 23rd, 2023

Accurately predicting future ocean acidification (OA) conditions is crucial for advancing research at regional and global scales, and guiding society’s mitigation and adaptation efforts.

As an update to Jiang et al. 2019, this new model-data fusion product:
1. Utilizes an ensemble of 14 distinct Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) along with three recent observational ocean carbon data products –>instead of relying on just one model (i.e., the GFDL-ESM2M) this approach reduces potential projection biases in OA indicators.
2. Eliminates model biases using observational data, and model drift with pre-Industrial controls.
3. Covers 10 OA indicators, an expansion from the usual pH, acidity, and buffer capacity.
4. Incorporates the new Shared Socioeconomic Pathways (SSPs).

The use of the most recent observational datasets and a large Earth System Model ensemble is a major step forward in the projection of future surface ocean OA indicators and provides critical information to guide OA mitigation and adaptation efforts.

Figure X. Temporal changes of global average surface ocean OA indicators as reconstructed and projected from 14 CMIP6 Earth System Models after applying adjustments with observational data: (a) fugacity of carbon dioxide (fCO₂), (b) total hydrogen ion content ([H⁺]_total), (c) carbonate ion content ([CO₃^2-]), (d) total dissolved inorganic carbon content (DIC), (e) pH on total scale (pH_T), (f) aragonite saturation state (Ω_arag), (g) total alkalinity content (TA), (h) Revelle Factor (RF), and (i) calcite saturation state (Ω_calc). The asterisk signs on the left-side y-axes show the values in 1750. The numbers along right-side y-axes, i.e., 1-1.9, 1-2.6, 2-4.5, 3-7.0, and 5-8.5, indicate the shared socioeconomic pathway SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. These are missing from panel g because the trajectories were more dependent on the model than the SSP.

Authors
Li-Qing Jiang (University Maryland)
John Dunne (NOAA/Geophysical Fluid Dynamics Laboratory)
Brendan R. Carter (University of Washington)
Jerry F. Tjiputra (NORCE Norwegian Research Centre Bjerknes)
Jens Terhaar (Woods Hole Oceanographic Institution)
Jonathan D. Sharp (University of Washington)
Are Olsen (University of Bergen and Bjerknes Centre for Climate Research)
Simone Alin (NOAA/Pacific Marine Environmental Laboratory)
Dorothee C. E. Bakker (University of East Anglia)
Richard A. Feely (NOAA/Pacific Marine Environmental Laboratory)
Jean-Pierre Gattuso (Sorbonne Université)
Patrick Hogan (NOAA/National Centers for Environmental Information)
Tatiana Ilyina (Max Planck Institute for Meteorology)
Nico Lange (GEOMAR Helmholtz Centre for Ocean Research)
Siv K. Lauvset (NORCE Norwegian Research Centre)
Ernie R. Lewis (Brookhaven National Laboratory)
Tomas Lovato (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici)
Julien Palmieri (National Oceanography Centre)
Yeray Santana-Falcón (Université de Toulouse)
Jörg Schwinger (NORCE Norwegian Research Centre)
Roland Séférian (Université de Toulouse)
Gary Strand (US National Center for Atmospheric Research)
Neil Swart (Canadian Centre for Climate Modelling and Analysis)
Toste Tanhua (GEOMAR Helmholtz Centre for Ocean Research)
Hiroyuki Tsujino (JMA Meteorological Research Institute)
Rik Wanninkhof (NOAA/Atlantic Oceanographic Meteorological Laboratory)
Michio Watanabe (Japan Agency for Marine-Earth Science and Technology)
Akitomo Yamamoto (Japan Agency for Marine-Earth Science and Technology)
Tilo Ziehn (CSIRO Oceans and Atmosphere)

Twitter:
@JiangLiqing, @JensTerhaar, @jpGattuso, @j_d_sharp, @AreOlsen, @SimoneAlin, @Dorothee_Bakker, @RFeely, @ilitat, @sivlauvset, @yeraysf, @TosteTanhua,

Adaptive emission pathways to stabilize global temperatures

Posted by mmaheigan

· Thursday, May 11th, 2023

Around the world, countries have agreed in the Paris Agreement to limit global warming well below 2°C and to pursue efforts to reduce global warming to 1.5°C. However, large uncertainties remain about which emission pathways will allow us to reach this goal. A recent paper presents a new adaptive approach to create emission pathways and estimate the necessary emission reductions every five years, following the stocktake process of the Paris Agreement. This Adaptive Emissions Reduction Approach (AERA) is solely based on past warming rates, and emissions of CO₂ and non-CO₂ radiative agents, and explicitly does not rely on projections by Earth System Models. Updating the emission pathways every five years, circumvents uncertainties in the climate system and its transient response to cumulative emissions (TCRE). Testing with the Bern3D-LPX Earth System Model of Intermediate Complexity shows that the approach works robustly across a wide range of TCREs, avoids large overshoots, and only small changes to the emission pathways are necessary every five years. This approach will allow policymakers to estimate emission pathways and create a base for international negotiations. Furthermore, it allows simulations with Earth System Models that all converge to the same temperature target to compare the climate at stabilized warming levels.

Figure caption: The three steps of the Adaptive Emission Reduction Approach: 1) Estimating the past anthropogenic warming, 2) estimating the remaining emission budget, and 3) redistributing it over the future years.

Authors
Jens Terhaar (University of Bern, now Woods Hole Oceanographic Institution)
Thomas L Frölicher (University of Bern)
Mathias T Aschwanden (University of Bern)
Pierre Friedlingstein (University of Exeter, Ecole Normale Superieure)
Fortunat Joos (University of Bern)

Twitter @JensTerhaar @froeltho @PFriedling @unibern @snsf_ch @4C_H2020 @ExeterUniMaths @Geosciences_ENS @IPSL_outreach

The ephemeral and elusive COVID blip in ocean carbon

Posted by mmaheigan

· Monday, September 20th, 2021

The global pandemic of the last nearly two years has affected all of us on a daily and long-term basis. Our planet is not exempt from these impacts. Can we see a signal of COVID-related CO₂ emissions reductions in the ocean? In a recent study, Lovenduski et al. apply detection and attribution analysis to output from an ensemble of COVID-like simulations of an Earth system model to answer this question. While it is nearly impossible to detect a COVID-related change in ocean pH, the model produces a unique fingerprint in air-sea DpCO₂ that is attributable to COVID. Challengingly, the large interannual variability in the climate system makes this fingerprint difficult to detect at open ocean buoy sites.

This study highlights the challenges associated with detecting statistically meaningful changes in ocean carbon and acidity following CO₂ emissions reductions, and reminds the reader that it may be difficult to observe intentional emissions reductions — such as those that we may enact to meet the Paris Climate Agreement – in the ocean carbon system.

Figure caption: The fingerprint (pink line) of COVID-related CO2 emissions reductions in global-mean surface ocean pH and air-sea DpCO2, as estimated by an ensemble of COVID-like simulations in an Earth system model. While the pH fingerprint is not particularly exciting, the air-sea DpCO2 fingerprint displays a temporary weakening of the ocean carbon sink in 2021 due to COVID emissions reductions.

Authors:
Nikki Lovenduski (University of Colorado Boulder)
Neil Swart (Canadian Centre for Climate Modeling and Analysis)
Adrienne Sutton (NOAA Pacific Marine Environmental Laboratory)
John Fyfe (Canadian Centre for Climate Modeling and Analysis)
Galen McKinley (Columbia University and Lamont Doherty Earth Observatory)
Chris Sabine (University of Hawai’i at Manoa)
Nancy Williams (University of South Florida)

A new Regional Earth System Model of the Mediterranean Sea biogeochemical dynamics

Posted by mmaheigan

· Thursday, November 19th, 2020

The Mediterranean Sea is a semi-enclosed mid-latitude oligotrophic basin with a lower net primary production than the global ocean. A west-east productivity trophic gradient results from the superposition of biogeochemical and physical processes, including the biological pump and associated carbon and nutrient (nitrogen, phosphorus) fluxes, the spatial asymmetric distribution of nutrient sources (rivers, atmospheric deposition, coastal upwelling, etc.), the estuarine inverse circulation associated with the inflow of Atlantic water through the Gibraltar Strait. The complex and highly variable interface between land and sea throughout this basin add a further layer of complexity in the Mediterranean oceanic and atmospheric circulation and on the associated biogeochemistry dynamics, emphasizing the need for high-resolution truly integrated Regional Earth System Models to track and understand fine-scale processes and ecosystem dynamics.

In a recent paper published in the Journal of Advances in Modeling Earth System, the authors introduced a new version of the Regional Earth System model RegCM-ES and evaluated its performance in the Mediterranean region. RegCM-ES fully integrates the regional climate model RegCM4, the land surface scheme CLM4.5 (Community Land Model), the river routing model HD (Hydrological Discharge Model), the ocean model MITgcm (MIT General Circulation model) and the Biogeochemical Flux Model BFM.

A comparison with available observations has shown that RegCM-ES was able to capture the mean climate of the region and to reproduce horizontal and vertical patterns of chlorophyll-a and PO₄(the limiting nutrient in the basin) (Figure 1). The same comparison revealed a systematic underestimation of simulated dissolved oxygen (which will be fixed by the use of a new parametrization of oxygen solubility), and an overestimation of NO₃, possibly due to uncertainties in initial and boundary conditions (mostly traced to river and Dardanelles nutrient discharges) and an overly vigorous vertical mixing simulated by the ocean model in some parts of the Basin.

Figure.1 Distributions of chlorophyll-a mg/m³ (top) and PO₄ mmol/m³ (bottom) in the Mediterranean Sea as simulated by RegCM-ES.

Overall, this analysis has demonstrated that RegCM-ES has the capabilities required to become a powerful tool for studying regional dynamics and impacts of climate change on the Mediterranean Sea and other ocean basins around the world.

Authors:
Marco Reale (Abdus Salam International Centre for theoretical physics-ICTP, National Institute of Oceanography and Experimental Geophysics-OGS)
Filippo Giorgi (Abdus Salam International Centre for theoretical physics-ICTP)
Cosimo Solidoro (National Institute of Oceanography and Experimental Geophysics-OGS)
Valeria Di Biagio (National Institute of Oceanography and Experimental Geophysics-OGS)
Fabio Di Sante (Abdus Salam International Centre for theoretical physics-ICTP)
Laura Mariotti (National Institute of Oceanography and Experimental Geophysics-OGS)
Riccardo Farneti (Abdus Salam International Centre for theoretical physics-ICTP)
Gianmaria Sannino (Italian National Agency for New Technologies, Energy and Sustainable Economic Development-ENEA)

Multiyear predictions of ocean acidification in the California Current System

Posted by mmaheigan

· Thursday, August 20th, 2020

The California Current System is a highly productive coastal upwelling region that supports commercial fisheries valued at $6 billion/year. These fisheries are supported by upwelled waters, which are rich in nutrients and serve as a natural fertilizer for phytoplankton. Due to remineralization of organic matter at depth, these upwelled waters also contain large amounts of dissolved inorganic carbon, causing local conditions to be more acidic than the open ocean. This natural acidity, compounded by the dissolution of anthropogenic CO₂ into coastal waters, creates corrosive conditions for shell-forming organisms, including commercial fishery species.

A recent study in Nature Communications showcases the potential for climate models to skillfully predict variations in surface pH—thus ocean acidification—in the California Current System. The authors evaluate retrospective predictions of ocean acidity made by a global Earth System Model set up similarly to a weather forecasting system. The forecasting system can already predict variations in observed surface pH fourteen months in advance, but has the potential to predict surface pH up to five years in advance with better initializations of dissolved inorganic carbon (Figure 1). Skillful predictions are mostly driven by the model’s initialization and subsequent transport of dissolved inorganic carbon throughout the North Pacific basin.

Figure 1. Forecast of annual surface pH anomalies in the California Current Large Marine Ecosystem for 2020. Red colors denote anomalously basic conditions for the given location and blue colors indicate anomalously acidic conditions.

These results demonstrate, for the first time, the feasibility of using climate models to make multiyear predictions of surface pH in the California Current. Output from this global prediction system could serve as boundary conditions for high-resolution models of the California Current to improve prediction time scale and ultimately help inform management decisions for vulnerable and valuable shellfisheries.

Authors:
Riley X. Brady (University of Colorado Boulder)
Nicole S. Lovenduski (University of Colorado Boulder)
Stephen G. Yeager (National Center for Atmospheric Research)
Matthew C. Long (National Center for Atmospheric Research)
Keith Lindsay (National Center for Atmospheric Research)

Predicting marine ecosystem futures

Posted by mmaheigan

· Wednesday, September 4th, 2019

Earth System Models (ESMs) are powerful and effective tools for exploring and predicting marine ecosystem response to environmental change, including biogeochemical processes that underlie threats to ocean health such as ocean acidification, deoxygenation, and changes in productivity. Seasonal to interannual marine biogeochemical predictions with ESMs hold great promise for exploring links between climate and marine resources such as fisheries but have thus far been challenged by limitations associated with observational initialization, model structure, and computational availability. In a recent study published in Science, authors integrated the Geophysical Fluid Dynamics Laboratory’s (GFDL) COBALT (Carbon, Ocean Biogeochemistry and Lower Trophics) marine biogeochemical model with seasonal to multi-annual climate predictions from GFDL’s CM2.1 climate model to examine marine ecosystem futures on these shorter time scales. The global biogeochemical forecasts were initialized on the first of each month between 1991 and 2017 with 12 ensemble members in each prediction, creating a database of nearly 4000 forecasts and 8000 simulation years. The model skillfully predicted seasonal to multi-annual chlorophyll fluctuations in many ocean regions (Figure 1).

Figure 1: Prediction skill in reproducing observed variations of monthly chlorophyll anomaly. (Top) Correlation coefficient between predicted and observed chlorophyll at 1-3 month lead time during the period 1997-2017. Stippled areas indicate that the correlation is significantly greater than 0 with 95% confidence. Areas with less than 80% satellite chlorophyll coverage are masked in grey. (Lower panels) Correlation coefficient between predicted and observed chlorophyll as a function of forecast initialization month (x-axis) and lead time (y-axis) in tropical Pacific, Indian, North Atlantic, North Pacific, and South Pacific oceans. In all panels, the darker the red, the higher the correlation up to a perfect correlation of 1.0. White indicates no correlation, while blue indicates negative correlation.

These results suggest that annual fish catches in selected large marine ecosystems can be predicted from chlorophyll and sea surface temperature anomalies up to 2-3 years in advance. Given that fisheries predictions sometimes failed to the point of commercial stock collapse in the past, this prediction capacity could be vital for fisheries managers. Biogeochemical prediction systems can extend beyond sea surface temperature and chlorophyll to include other potential drivers (e.g., oxygen, acidity, net primary production, zooplankton, etc.) as highly valuable tools for marine resource managers of dynamic and changing ecosystems.

Authors:
Jong-Yeon Park (Princeton Univ, NOAA GDFL, Chonbuk National Univ., Korea)
Charles A. Stock, John P. Dunne, Xiaosong Yang, and Anthony Rosati (NOAA GFDL)

The causes of the 90-ppm glacial atmospheric CO2 drawdown still strongly debated

Posted by mmaheigan

· Tuesday, July 9th, 2019

Joint feature with GEOTRACES

Figure: Illustration of the two main mechanisms identified by this study to explain lower atmospheric CO₂ during glacial periods. Left: present-day conditions; right: conditions around 19,000 years ago during the Last Glacial Maximum. The obvious explanation for lower CO₂ during glacial periods – cooler ocean temperatures (darker blue shade) making CO₂ more soluble, much as a glass of sparkling wine will remain fizzier for longer when it is colder – has long been dismissed as not being a significant factor. However, previous calculations assumed that the ocean cooled uniformly and was saturated in dissolved CO₂. The model, consistent with reconstructions of sea surface temperature, predicts more cooling at mid latitudes compared with polar regions and also accounts for undersaturation. This nearly doubles the effect of temperature change and accounts for almost half the 90 ppm glacial-interglacial atmospheric CO₂ difference. Another quarter is explained in this model by increased growth of marine algae (green blobs and inset) in the waters off Antarctica. Algae absorb CO₂ from the atmosphere during photosynthesis and “pump” it into the deep ocean when they die and sink. But their growth in the present-day ocean, especially the waters off Antarctica, is limited by the availability of iron, an essential micronutrient primarily supplied by wind-borne dust. In our model an increased supply of iron to the Southern Ocean, likely originating from Patagonia, Australia and New Zealand, enhances their growth and sucks CO₂ out of the atmosphere. This “fertilization” effect was greatly underestimated by previous studies. The study also finds that, contrary to the current consensus, a large expansion of sea ice off Antarctica and reconfiguration of ocean circulation may have played only a minor role in glacial-interglacial CO₂ changes. Credit: Illustration by Andrew Orkney, University of Oxford.

Using an observationally constrained earth system model, S. Khatiwala and co-workers compare different processes that could lead to the 90-ppm glacial atmospheric CO₂drawdown, with an important improvement on the deep carbon storage quantification (i.e. Biological Carbon Pump efficiency). They demonstrate that circulation and sea ice changes had only a modest net effect on glacial ocean carbon storage and atmospheric CO₂, whereas temperature and iron input effects were more important than previously thought due to their effects on disequilibrium carbon storage.

Authors:
Samar Khatiwala (University of Oxford, UK)
Andreas Schmittner and Juan Muglia (Oregon State University)

Forecasting air-sea CO2 flux variations several years in advance

Posted by mmaheigan

· Tuesday, July 9th, 2019

Year-to-year changes in the flux of CO₂ between the atmosphere and the ocean impact the global carbon cycle and climate system, and challenge our ability to verify fossil fuel CO₂ emissions. A new study published in Earth System Dynamics suggests that these air-sea CO₂ flux variations are predictable several years in advance.

A novel set of initialized forecasts of past air-sea CO₂ flux from an Earth system model (Figure 1a) confidently predicts year-to-year variations in the globally-integrated flux up to two years in advance. At regional scales, the forecast lead time increases. The predictability of CO₂ flux from the initialized forecast system exceeds that obtained solely from foreknowledge of variations in external forcing (e.g., volcanic eruptions) or a simple persistence forecast (e.g., CO₂ flux this year will be the same as next year). The longest-lasting forecast enhancements are in the subantarctic Southern Ocean and the northern North Atlantic (Figure 1b).

Figure 1: (a) Forecasts of the past evolution of air-sea CO2 flux in the South Pacific using an Earth System model indicate the potential to predict the future evolution of this quantity. (b) In each biome, the maximum forecast lead time in which the initialized forecast of air-sea CO2 flux beats out other forecast methods.

These results are particularly meaningful for those forecasting year-to-year changes in the global carbon budget, especially as these forecasting efforts are blind to the externally-forced variability in advance (i.e., the external forcing of the future is unknown). In this way, forecasts of air-sea CO₂ flux variations can help to inform future predictions of land-air CO₂ flux and atmospheric CO₂ concentration.

Authors:
Nicole Lovenduski (University of Colorado Boulder)
Stephen G. Yeager (National Center for Atmospheric Research)
Keith Lindsay (National Center for Atmospheric Research)
Matthew C. Long (National Center for Atmospheric Research)

See also the OCB Ocean-Atmosphere Interactions: Scoping directions for U.S. research Workshop to be held in October 1-3, 2019

Suddenly shallow: A new aragonite saturation horizon will soon emerge in the Southern Ocean

Posted by mmaheigan

· Monday, May 27th, 2019

Earth System Models (ESMs) project that by the end of this century, the aragonite saturation horizon (the boundary between shallower, saturated waters and deeper, undersaturated waters that are corrosive to aragonitic shells) will shoal all the way to the surface in the Southern Ocean, yet the temporal evolution of the horizon has not been studied in much detail. Rather than a gradual shoaling, a new shallow aragonite saturation horizon emerges suddenly across many locations in the Southern Ocean between now and the end of the century (Figure 1, left), as detailed in a new study published in Nature Climate Change.

Figure 1: Maximum step-change in the depth of the aragonite saturation horizon (left), timing of the step-change (center), and cause of the change (right). Xs on the time axis (center) indicate when the shallow horizon emerges in each ensemble member. (click image to enlarge)

The emergence of the shallow aragonite saturation horizon is apparent in each member of an ensemble of climate projections from an ESM, but the step change occurs during different years (Figure 1, center). The shoaling is driven by the gradual accumulation of anthropogenic CO₂ in the Southern Ocean thermocline, where the carbonate ion concentration exhibits a local minimum and approaches undersaturation (Figure 1, right).

The abrupt shoaling of the Southern Ocean aragonite saturation horizon occurs under both business-as-usual and emission-stabilizing scenarios, indicating an inevitable and sudden decrease in the volume of suitable habitat for aragonitic organisms such as shelled pteropods, foraminifers, cold-water corals, sea urchins, molluscs, and coralline algae. Widespread reductions in these habitats may have far-reaching consequences for fisheries, economies, and livelihoods.

Authors:
Gabriela Negrete-García (Scripps Institution of Oceanography)
Nicole Lovenduski (University of Colorado Boulder)

See also OCB2019 plenary session: Carbon cycle feedbacks from the seafloor (Wednesday, June 26, 2019)

Improved method to identify and reduce uncertainties in marine carbon cycle predictions

Posted by mmaheigan

· Wednesday, September 26th, 2018

Improved method to identify and reduce uncertainties in marine carbon cycle predictions

How well do contemporary Earth System Models (ESMs) represent the dynamics of the modern day ocean? Often we question the fidelity of biological and chemical processes represented in these ESMs. The fact is representations of biogeochemical processes in models are plagued with some degree of uncertainties; therefore, identifying and reducing such deficiencies could advance ESM development and improve model predictions.

An overview of several models with respect to each of the variables, using absolute (left) and relative (right) scores to determine the degree of uncertainty in relation to referenced datasets.

A recent publication in Atmosphere described the ongoing efforts to develop the International Ocean Model Benchmarking (IOMB) package to evaluate ESM skill sets in simulating marine biogeochemical variables and processes. Model performances were scored based on how well they captured the distribution and variability contained in high-quality observational datasets. The authors highlighted systematic model–data benchmarking as a technique to identify ocean model deficiencies, which could provide a pathway to improving representations of sub-grid-scale parameterizations. They have scaled the absolute score from zero to unity, where the red color tends toward zero to quantify weaknesses in the skill set of a particular model in capturing values from the observational datasets. On the other side of the spectrum, the green color signifies considerable temporal and spatial overlap between the predicted and the observational values. The authors also present the standard score to show the relative scores within two standard deviations from the model mean. The benchmarking package was employed in the published study to assess marine biogeochemical process representations, with a focus on surface ocean concentrations and sea–air fluxes of dimethylsulfide (DMS). The production and emission of natural aerosols remain one of the major limitations in estimating global radiative forcing. Appropriate representation of aerosols in the marine boundary layer (MBL) is essential to reduce uncertainty and provide reliable information on offsets to global warming. Results show that model–data biases increased as DMS enters the MBL, with models over-predicting sea surface concentrations in the productive region of the eastern tropical Pacific by almost a factor of two and the sea–air fluxes by a factor of three. The associated uncertainties with oceanic carbon cycle processes may be additive or antagonistic; in any case, a constructive effort to disentangle the subtleties begins with an objective benchmarking effort, which is focused specifically on marine biogeochemical processes. The tool in development will ensure we satisfy some of the Model Intercomparison Project (MIP) benchmarking needs for the sixth phase of Coupled Model Intercomparison Project (CMIP6).

Authors:
Oluwaseun Ogunro (ORNL)
Scott Elliott (LANL)
Oliver Wingenter (New Mexico Tech)
Clara Deal (University of Alaska)
Weiwei Fu (UC Irvine)
Nathan Collier (ORNL)
Forrest M. Hoffman (ORNL)

Funding for the Ocean Carbon & Biogeochemistry Project Office is provided by the National Science Foundation (NSF) and the National Aeronautics and Space Administration (NASA). The OCB Project Office is housed at the Woods Hole Oceanographic Institution.

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