scholarly journals Supplementary material to "The "Ocean Carbon States" Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle"

Author(s):  
Rebecca Latto ◽  
Anastasia Romanou
2017 ◽  
Author(s):  
Rebecca Latto ◽  
Anastasia Romanou

Abstract. In this paper, we present a database of the basic regimes of carbon cycle in the ocean as obtained using data mining and patter recognition techniques in observational as well as model data. Advanced data mining techniques are becoming widely used in Climate and Earth Sciences with the purpose of extracting new meaningful information from large and complex datasets. Such techniques need to be rigorously tested, however, in simple, well-understood cases to better assess their utility. This is particularly important for studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In addition to observational data of the carbon cycle, numerical simulations of the Earth System are becoming increasingly more complex and harder to evaluate. Without reliable numerical models, however, our predictions of future climate change are haphazard. Here we describe the use of a specific data-mining technique, cluster analysis, as a means of identifying and comparing spatial and temporal patterns extracted from observational and model datasets. As the observational data is organized into various regimes, which we will call "ocean carbon states", we gain insight into the physical and/or biogeochemical processes controlling the ocean carbon cycle in nature as well as how well these processes are simulated by the model. Assessment of cluster analysis results demonstrates that this technique effectively produces realistic, dynamic regimes that can be associated with specific processes at different temporal scales for both observations and the model. Furthermore, these regimes can be used to illustrate and characterize the model biases in the model air-sea flux of CO2 which are then attributed to model misrepresentations of salinity, sea surface temperature, wind speed, and nitrate. The goal of this proof-of-concept study is to establish a methodology for implementing and interpreting k-means cluster analysis on observations and model output which will enable us to subsequently apply the analysis to larger, higher frequency datasets of the ocean carbon cycle. To enable further testing and extending the method discussed, all data and analysis scripts are freely available at data.giss.nasa.gov/oceans/carbonstates/ (DOI: https://doi.org/doi:10.5281/zenodo.996891).


Author(s):  
Michael D. DeGrandpre ◽  
Wiley Evans ◽  
Mary-Louise Timmermans ◽  
Richard A. Krishfield ◽  
William J Williams ◽  
...  

2011 ◽  
Vol 33 (3) ◽  
pp. 30-34
Author(s):  
Rod W. Wilson ◽  
Erin E. Reardon ◽  
Christopher T. Perry

Human activities, such as burning fossil fuels, are playing an important role in the rising levels of carbon dioxide (CO2) in the Earth's atmosphere1. The oceans may store a large portion of CO2 that we are releasing into the atmosphere, with up to 40% already taken up by the oceans. Although this absorption helps to offset some of the greenhouse effect of atmospheric CO2, it also contributes to ocean acidification, or a fall in the pH of sea water. The historical global mean pH of oceanic sea water is about 8.2, and this has already declined by 0.1 pH units (a 30% increase in H+ concentration) and is predicted to reach pH ~7.7 by the end of the century if current rates of fossil fuel use continue, leading to an atmospheric CO2 level of 800 p.p.m.1,2. Even this extreme potential fall in pH would still leave seawater above the neutral point (pH 7.0), so technically it is more accurate to say that the ocean is becoming less alkaline, rather than truly acidic (i.e. below pH 7.0). However, the magnitude is perhaps less important than the speed of pH change which is occurring faster than at any time during the previous 20 million years. Over this time, the average ocean pH has probably never fallen below pH 8.02,3. It is only during the last decade that the importance of ocean acidification has come to the forefront of concerns for scientists1,2. Consequences of these changes in global CO2 production are predicted to include elevated global temperatures, rising sea levels, more unpredictable and extreme weather patterns, and shifts in ecosystems1. In order to more fully understand the implications of ocean acidification, teams of researchers, including fisheries scientists, physiologists, geologists, oceanographers, chemists and climate modellers, are working to refine current understanding of the ocean carbon cycle.


2007 ◽  
Vol 253 (1-2) ◽  
pp. 83-95 ◽  
Author(s):  
R.E.M. Rickaby ◽  
E. Bard ◽  
C. Sonzogni ◽  
F. Rostek ◽  
L. Beaufort ◽  
...  

2018 ◽  
Vol 45 (10) ◽  
pp. 5062-5070 ◽  
Author(s):  
Jörg Schwinger ◽  
Jerry Tjiputra

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