Abstract. Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and https://www.nodc.noaa.gov/ocads/oceans/Moorings/ndp097.html (Sutton et al., 2018).
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A uniform <i>p</i>CO<sub>2</sub> climatology combining open and coastal oceans
Abstract. In this study, we present the first combined open- and coastal-ocean pCO2 mapped monthly climatology (Landschützer et al., 2020b, https://doi.org/10.25921/qb25-f418, https://www.nodc.noaa.gov/ocads/oceans/MPI-ULB-SOM_FFN_clim.html, last access: 8 April 2020) constructed from observations collected between 1998 and 2015 extracted from the Surface Ocean CO2 Atlas (SOCAT) database. We combine two neural network-based pCO2 products, one from the open ocean and the other from the coastal ocean, and investigate their consistency along their common overlap areas. While the difference between open- and coastal-ocean estimates along the overlap area increases with latitude, it remains close to 0 µatm globally. Stronger discrepancies, however, exist on the regional level resulting in differences that exceed 10 % of the climatological mean pCO2, or an order of magnitude larger than the uncertainty from state-of-the-art measurements. This also illustrates the potential of such an analysis to highlight where we lack a good representation of the aquatic continuum and future research should be dedicated. A regional analysis further shows that the seasonal carbon dynamics at the coast–open interface are well represented in our climatology. While our combined product is only a first step towards a true representation of both the open-ocean and the coastal-ocean air–sea CO2 flux in marine carbon budgets, we show it is a feasible task and the present data product already constitutes a valuable tool to investigate and quantify the dynamics of the air–sea CO2 exchange consistently for oceanic regions regardless of its distance to the coast.
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- Award ID(s):
- 1850983
- NSF-PAR ID:
- 10293882
- Date Published:
- Journal Name:
- Earth System Science Data
- Volume:
- 12
- Issue:
- 4
- ISSN:
- 1866-3516
- Page Range / eLocation ID:
- 2537 to 2553
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/essd-12-2537-2020
