**DEFINITION**

Ocean acidification is quantified by decreases in pH, which is a measure of acidity: a decrease in pH value means an increase in acidity, that is, acidification. The observed decrease in ocean pH resulting from increasing concentrations of CO2 is an important indicator of global change. The estimate of global mean pH builds on a reconstruction methodology, 
* Obtain values for alkalinity based on the so called “locally interpolated alkalinity regression (LIAR)” method after Carter et al., 2016; 2018. 
* Build on surface ocean partial pressure of carbon dioxide (CMEMS product: MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008) obtained from an ensemble of Feed-Forward Neural Networks (Chau et al. 2022) which exploit sampling data gathered in the Surface Ocean CO2 Atlas (SOCAT) (https://www.socat.info/)
* Derive a gridded field of ocean surface pH based on the van Heuven et al., (2011) CO2 system calculations using reconstructed pCO2 (MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008) and alkalinity.
The global mean average of pH at yearly time steps is then calculated from the gridded ocean surface pH field. It is expressed in pH unit on total hydrogen ion scale. In the figure, the amplitude of the uncertainty (1σ  ) of yearly mean surface sea water pH varies at a range of (0.0023, 0.0029) pH unit (see Quality Information Document for more details). The trend and uncertainty estimates amount to -0.0017±0.0004e-1 pH units per year.
The indicator is derived from in situ observations of CO2 fugacity (SOCAT data base, www.socat.info, Bakker et al., 2016). These observations are still sparse in space and time.  Monitoring pH at higher space and time resolutions, as well as in coastal regions will require a denser network of observations and preferably direct pH measurements.  
A full discussion regarding this OMI can be found in section 2.10 of the Ocean State Report 4 (Gehlen et al., 2020).

**CONTEXT**

The decrease in surface ocean pH is a direct consequence of the uptake by the ocean of carbon dioxide. It is referred to as ocean acidification. The International Panel on Climate Change (IPCC) Workshop on Impacts of Ocean Acidification on Marine Biology and Ecosystems (2011) defined Ocean Acidification as “a reduction in the pH of the ocean over an extended period, typically decades or longer, which is caused primarily by uptake of carbon dioxide from the atmosphere, but can also be caused by other chemical additions or subtractions from the ocean”. The pH of contemporary surface ocean waters is already 0.1 lower than at pre-industrial times and an additional decrease by 0.33 pH units is projected over the 21st century in response to the high concentration pathway RCP8.5 (Bopp et al., 2013). Ocean acidification will put marine ecosystems at risk (e.g. Orr et al., 2005; Gehlen et al., 2011; Kroeker et al., 2013). The monitoring of surface ocean pH has become a focus of many international scientific initiatives (http://goa-on.org/) and constitutes one target for SDG14 (https://sustainabledevelopment.un.org/sdg14).  

**CMEMS KEY FINDINGS**

Since the year 1985, global ocean surface pH is decreasing at a rate of  -0.0017±0.0004e-1 per year. 

**DOI (product):** 
https://doi.org/10.48670/moi-00224

**References:**

* Bakker, D. et al.: A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT), Earth Syst. Sci. Data, 8, 383-413, https://doi.org/10.5194/essd-8-383-2016, 2016.
* Bopp, L. et al.: Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models, Biogeosciences, 10, 6225–6245, doi: 10.5194/bg-10-6225-2013, 2013.
* Carter, B.R., et al.: Updated methods for global locally interpolated estimation of alkalinity, pH, and nitrate, Limnol. Oceanogr.: Methods 16, 119–131, 2018.
* Carter, B. R., et al.: Locally interpolated alkalinity regression for global alkalinity estimation. Limnol. Oceanogr.: Methods 14: 268–277. doi:10.1002/lom3.10087, 2016.
* Chau, T. T. T., Gehlen, M., and Chevallier, F.: A seamless ensemble-based reconstruction of surface ocean pCO2 and air–sea CO2 fluxes over the global coastal and open oceans, Biogeosciences, 19, 1087–1109, https://doi.org/10.5194/bg-19-1087-2022, 2022. Gehlen, M. et al.: Biogeochemical consequences of ocean acidification and feedback to the Earth system. p. 230, in: Gattuso J.-P. & Hansson L. (Eds.), Ocean acidification. Oxford: Oxford University Press., 2011.
* Gehlen M., Thi Tuyet Trang Chau, Anna Conchon, Anna Denvil-Sommer, Frédéric Chevallier, Mathieu Vrac, Carlos Mejia (2020). Ocean acidification. In: Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 13:sup1, s88–s91; DOI: 10.1080/1755876X.2020.1785097
* IPCC, 2011: Workshop Report of the Intergovernmental Panel on Climate Change Workshop on Impacts of Ocean Acidification on Marine Biology and Ecosystems. [Field, C.B., V. Barros, T.F. Stocker, D. Qin, K.J. Mach, G.-K. Plattner, M.D. Mastrandrea, M. Tignor and K.L. Ebi (eds.)]. IPCC Working Group II Technical Support Unit, Carnegie Institution, Stanford, California, United States of America, pp.164.
* Kroeker, K. J. et al.: Meta- analysis reveals negative yet variable effects of ocean acidifica- tion on marine organisms, Ecol. Lett., 13, 1419–1434, 2010.
* Orr, J. C. et al.: Anthropogenic ocean acidification over the twenty-first century and its impact on cal- cifying organisms, Nature, 437, 681–686, 2005.
* van Heuven, S., et al.: MATLAB program developed for CO2 system calculations, ORNL/CDIAC-105b, Carbon Dioxide Inf. Anal. Cent., Oak Ridge Natl. Lab., US DOE, Oak Ridge, Tenn., 2011.


Hélène Etienne

MULTIOBS Service Desk

Marion Gehlen

MOI-OMI-SERVICE

Quality Information Document

Product User Manual

The original, non-ARCO version of this dataset, as published by the data provider.

Native dataset

An ARCO version of this dataset.
    
Note that the link (`href`) associated to this asset is the base directory
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To download this dataset or part of it, 
use a library such as [xarray](https://docs.xarray.dev/).

Global Ocean acidification - mean sea water pH time series and trend from Multi-Observations Reprocessing

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