PCO2 And PH Time Series From 40 Surface Buoys And The .
Earth Syst. Sci. Data, 11, 421–439, 2019https://doi.org/10.5194/essd-11-421-2019 Author(s) 2019. This work is distributed underthe Creative Commons Attribution 4.0 License.Autonomous seawater pCO2 and pH time seriesfrom 40 surface buoys and the emergenceof anthropogenic trendsAdrienne J. Sutton1 , Richard A. Feely1 , Stacy Maenner-Jones1 , Sylvia Musielwicz1,2 , John Osborne1,2 ,Colin Dietrich1,2 , Natalie Monacci3 , Jessica Cross1 , Randy Bott1 , Alex Kozyr4 , Andreas J. Andersson5 ,Nicholas R. Bates6,7 , Wei-Jun Cai8 , Meghan F. Cronin1 , Eric H. De Carlo9 , Burke Hales10 ,Stephan D. Howden11 , Charity M. Lee12 , Derek P. Manzello13 , Michael J. McPhaden1 ,Melissa Meléndez14,15 , John B. Mickett16 , Jan A. Newton16 , Scott E. Noakes17 , Jae Hoon Noh18 ,Solveig R. Olafsdottir19 , Joseph E. Salisbury20 , Uwe Send5 , Thomas W. Trull21,22,23 ,Douglas C. Vandemark20 , and Robert A. Weller241 PacificMarine Environmental Laboratory, National Oceanic and AtmosphericAdministration, Seattle, Washington, USA2 Joint Institute for the Study of the Atmosphere and Ocean, University of Washington,Seattle, Washington, USA3 Ocean Acidification Research Center, University of Alaska Fairbanks, Fairbanks, Alaska, USA4 National Centers for Environmental Information, National Oceanic and AtmosphericAdministration, Silver Spring, Maryland, USA5 Scripps Institution of Oceanography, University of California, San Diego, California, USA6 Bermuda Institute of Ocean Sciences, St. Georges, Bermuda7 Department of Ocean and Earth Science, University of Southampton, Southampton, UK8 University of Delaware, School of Marine Science and Policy, Newark, Delaware, USA9 University of Hawai’i at Maānoa, School of Ocean and Earth Science and Technology, Honolulu, Hawaii, USA10 College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, USA11 Department of Marine Science, University of Southern Mississippi, Stennis Space Center, Mississippi, USA12 Ocean Policy Institute, Korea Institute of Ocean Science and Technology, Busan, Korea13 Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and AtmosphericAdministration, Miami, Florida, USA14 Department of Earth Sciences and Ocean Processes Analysis Laboratory, University of New Hampshire,Durham, New Hampshire, USA15 Caribbean Coastal Ocean Observing System, University of Puerto Rico, Mayagüez, Puerto Rico16 Applied Physics Laboratory, University of Washington, Seattle, Washington, USA17 Center for Applied Isotope Studies, University of Georgia, Athens, Georgia, USA18 Marine Ecosystem Research Center, Korea Institute of Ocean Science and Technology, Busan, Korea19 Marine and Freshwater Research Institute, Reykjavik, Iceland20 Ocean Process Analysis Laboratory, University of New Hampshire, Durham, New Hampshire, USA21 Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and IndustrialResearch Organisation, Hobart, Australia22 Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, Australia23 Institute of Marine and Antarctic Studies, University of Tasmania, Hobart, Australia24 Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USACorrespondence: Adrienne J. Sutton (adrienne.sutton@noaa.gov)Received: 20 September 2018 – Discussion started: 4 October 2018Revised: 15 February 2019 – Accepted: 21 February 2019 – Published: 26 March 2019Published by Copernicus Publications.
422A. J. Sutton et al.: Autonomous seawater p CO2 and pH time seriesAbstract. Ship-based time series, some now approaching over 3 decades long, are critical climate records thathave 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 improvingthe 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 2004and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surfaceocean 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 tointerannual variability and an estimate of decadal variability indicates that the length of sustained observationsnecessary 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 coastalsites, 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 inthe 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 trendsat more sites; however, the product currently provides a valuable tool in an accessible format for evaluatingclimatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and p097.html(Sutton et al., 2018).1IntroductionBiogeochemical cycling leads to remarkable temporal andspatial variability of carbon in the mixed layer of the globalocean and particularly in coastal seas. The ocean carbon cycle, specifically surface ocean CO2 –carbonate chemistry, isprimarily influenced by local physical conditions and biological processes, basin-wide circulation patterns, and fluxesbetween the ocean and land/atmosphere. Since the industrial period, increasing atmospheric CO2 has been an additional forcing on ocean biogeochemistry, with the ocean absorbing roughly 30 % of anthropogenic CO2 (Khatiwala etal., 2013; Le Quéré et al., 2018). The resulting decrease ofthe seawater pH and carbonate ion concentration, referred toas ocean acidification, has the potential to impact marine lifesuch as calcifying organisms (Bednaršek et al., 2017b; Chanand Connolly, 2013; Davis et al., 2017; Fabricius et al., 2011;Gattuso et al., 2015). Shellfish, shallow-water tropical corals,and calcareous plankton are a few examples of economicallyand ecologically important marine calcifiers potentially affected by ocean acidification.Open ocean observations have shown that the inorganiccarbon chemistry of the surface ocean is changing globallyat a mean rate consistent with atmospheric CO2 increasesof approximately 2.0 µatm yr 1 (Bates et al., 2014; Takahashi et al., 2009; Wanninkhof et al., 2013). However, natural and anthropogenic processes can magnify temporal andspatial variability in some regions, especially coastal systemsthrough eutrophication, freshwater input, exchange with tidalwetlands and the sea floor, seasonal biological productivity,Earth Syst. Sci. Data, 11, 421–439, 2019and coastal upwelling (Bauer et al., 2013). This enhancedvariability can complicate and at times obscure detection andattribution of longer-scale ocean carbon changes. There arealso processes that can act in the opposite direction; for example, riverine and estuarine sources of alkalinity increasethe buffering capacity of coastal waters and reduce the variability of other carbon parameters.Efforts to observe and predict the impact of ocean acidification on marine ecosystems must be integrated with anunderstanding of both the natural and anthropogenic processes that control the ocean carbonate system. Marine organisms experience highly heterogeneous seawater carbonate chemistry conditions, and it is unclear what exact conditions in the natural environment will lead to physiological responses (Hofmann et al., 2010). However, responses associated with exposure to corrosive carbonate conditions such aslow values of the aragonite saturation state ( aragonite ) havebeen observed (e.g., Barton et al., 2012, 2015; Bednaršeket al., 2014, 2016, 2017a; Reum et al., 2015). Observationsshow that present-day surface seawater pH and aragoniteconditions throughout most of the open ocean exceed thenatural range of preindustrial variability, and in some coastalecosystems known biological thresholds for shellfish larvaeare exceeded during certain times of the seasonal cycle (Sutton et al., 2016). Are these present-day conditions significantly impacting marine life in the natural environment?How will the intensity, frequency, and duration of corrosive carbonate conditions change as surface seawater pH and aragonite continue to decline and influence other processes ofthe biogeochemical cycle in the coastal zone? Paired chemi-www.earth-syst-sci-data.net/11/421/2019/
A. J. Sutton et al.: Autonomous seawater p CO2 and pH time seriescal and biological observations at timescales relevant to biological processes, such as food availability, seasonal spawning, larval growth, and recruitment, are one tool for identifying and tracking the response of marine life to ocean acidification.Long-term, sustained time-series observations resolvingdiurnal to seasonal conditions encompass many timescalesrelevant to biological processes and can help to characterizeboth natural variability and anthropogenic change in oceancarbon. Fixed time-series observations fill a unique nichein ocean observing as they can serve as sites of multidisciplinary observations and process studies, high-quality reference stations for validating and assessing satellite measurements and Earth system models, and test beds for developingand evaluating new ocean sensing technology. If of sufficientlength and measurement quality to detect the anthropogenicsignal above the noise (i.e., in this case the natural variability of the ocean carbon system), these observations can alsoserve as critical climate records.Here, we introduce time-series data from 40 moored stations in open ocean, coastal, and coral reef environments.These time series include 3-hourly autonomous measurements of surface seawater temperature (SST), salinity (SSS),mole fraction of atmospheric CO2 (xCO2 ), partial pressureof atmospheric and seawater CO2 (pCO2 ), and seawaterpH. This data product was developed to provide easy accessto uninterrupted time series of high-quality pCO2 and pHdata for those who do not require the detailed deploymentlevel information archived at the National Centers forEnvironmental Information (NCEI; https://www.nodc.noaa.gov/ocads/oceans/time series moorings.html, last access:11 March 2019).We also present an overview of the seasonal variability tolong-term trends revealed in the pCO2 and pH observations,as well as an estimate of the length of time series requiredto detect an anthropogenic signal at each location. We use astatistical method described by Tiao et al. (1990) and furtherapplied to environmental data by Weatherhead et al. (1998)to estimate the number of years of observations needed todetect a statistically significant trend over variability, whichwe refer to here as time of emergence (ToE). An input required in this statistical model is an estimate of the trend.We adopt a trend in seawater pCO2 of 2 µatm yr 1 , whichassumes surface seawater changes track the current rate ofglobally averaged atmospheric CO2 increase. This assumption allows for the comparison of the trend-to-variance pattern across the network of 40 time series locations. The ToEmethodology does not allow for the identification of actuallong-term trends that may be different from 2 µatm yr 1 dueto other long-term changes in, for example, biological production/respiration or coastal carbon sources/sinks. Nor doesit address the point in time at which a system may cross theenvelope of preindustrial variability or biological thresholds(e.g., Pacella et al., 2018; Sutton et al., 2016). It indicatesthe time at which the imposed signal of 2 µatm yr 1 from the variance, and not necessarily when the actual anthropogenic signal may emerge or when organisms may beimpacted.Another caveat of this methodology is that the resultsapply to present-day conditions, and these estimates willchange as the time series lengthen due to continued anthropogenic forcing. For example, even if using seasonally detrended monthly anomalies (i.e., when the mean seasonalityof ocean carbonate chemistry is accounted for), magnification of the seasonal amplitude of pCO2 due to warming, reduction in buffering capacity, and/or other carbon cycle feedbacks could add variance to the monthly anomalies, resulting in increased detection time (Kwiatkowski and Orr, 2018;Landschützer et al., 2018). Changes in circulation, stratification, and meltwater inputs in the Arctic cryosphere dueto anthropogenic warming could also influence these estimates over time. For regions where the drivers of anthropogenic forcing and natural variability are well constrained,the methodology could be modified to provide more accurateestimates of trend detection time. However, ToE estimatespresented here use monthly anomalies of present-day observations and a fixed anthropogenic pCO2 trend of 2 µatm yr 1to compare the trend-to-variance patterns across the networkof 40 moored time series. These estimates provide a startingpoint for trend calculations using this data product.22.1MethodsSite and sensor descriptionThe 40 fixed time series stations are located in the Pacific(29), Atlantic (9), Indian (1), and Southern (1) ocean basinsin open ocean (17), coastal (13), and coral reef (10) ecosystems (Table 1; Fig. 1). All surface ocean pCO2 and pH timeseries were established between 2004 and 2013. Thirty-threeof these stations are active, whereas three have been moved tonearby locations better representing regional biogeochemicalprocesses and four have been discontinued due to the lack ofsustained funding. The range of support and partnerships formaintaining these moored time series is extensive (see Acknowledgements for details). Many of these 40 moored timeseries stations also make physical oceanographic and marine boundary layer meteorological measurements, and subsequently enable multi-disciplinary studies involving carboncycle dynamics.A Moored Autonomous pCO2 (MAPCO2 ) system measuring marine boundary layer air at a height of 0.5–1 m andseawater at a depth of 0.5 m is deployed at each fixedtime series site (Sutton et al., 2014b). The MAPCO2 systems measure xCO2 in equilibrium with surface seawater using a nondispersive infrared gas analyzer (LI-COR, modelLI-820) calibrated prior to each measurement with a reference gas traceable to World Meteorological Organizationstandards. Seawater xCO2 equilibration occurs by cyclinga closed loop of air through a floating bubble equilibratorEarth Syst. Sci. Data, 11, 421–439, 2019
424A. J. Sutton et al.: Autonomous seawater p CO2 and pH time seriesTable 1. Region, coordinates, surface ocean carbon parameters measured, year carbon time series established, and current status of the 40fixed moored time series stations. All time series also include atmospheric CO2 , SST, and SSS.AbbreviationDescriptive nameRegionLatitudeLongitudeCarbonparametersStart yearStatusCCE1California Current Ecosystem 1Northeast Pacific Ocean33.48 122.51pCO2 , pH2008ActivePapaKEOOcean Station PapaNortheast Pacific Ocean50.13 144.84pCO2 , pH2007ActiveKuroshio Extension ObservatoryNorthwest Pacific Ocean32.28144.58pCO2 , pH2007ActiveJKEOJapanese Kuroshio ExtensionObservatoryNorthwest Pacific Ocean37.93146.52pCO22007Discontinuedin 2007WHOTSWoods Hole OceanographicInstitution Hawaii OceanTime-series StationCentral Pacific Ocean22.67 157.98pCO2 , pHTAO110WNational Data Buoy Center(NDBC) Tropical AtmosphereOcean 0 , 110 WEquatorial Pacific Ocean0.00 110.00TAO125WNDBC Tropical AtmosphereOcean 0 , 125 WEquatorial Pacific Ocean0.00TAO140WNDBC Tropical AtmosphereOcean 0 , 140 WEquatorial Pacific OceanTAO155WNDBC Tropical AtmosphereOcean 0 , 155 WTAO170W2004aActivepCO22009Active 125.00pCO22004Active0.00 140.00pCO22004ActiveEquatorial Pacific Ocean0.00 155.00pCO22010ActiveNDBC Tropical AtmosphereOcean 0 , 170 WEquatorial Pacific Ocean0.00 170.00pCO22005ActiveTAO165ENDBC Tropical AtmosphereOcean 0 , 165 EEquatorial Pacific Ocean0.00165.00pCO22010ActiveTAO8S165ENDBC Tropical AtmosphereOcean 8 S, 165 EEquatorial Pacific Ocean 8.00165.00pCO22009ActiveStratusStratusSoutheast Pacific Ocean 19.70 85.60pCO2 , pH2006ActiveBTMBermuda Testbed MooringNorth Atlantic Ocean31.50 64.20pCO22005Discontinuedin 2007IcelandNorth Atlantic OceanAcidification MooringNorth Atlantic Ocean68.00 12.67pCO2 , pH2013ActiveBOBOABay of Bengal OceanAcidification ObservatoryIndian Ocean15.0090.00pCO2 , pH2013ActiveSOFSSouthern Ocean FluxStationSouthern Ocean 46.80142.00pCO22011ActiveGAKOAGulf of Alaska OceanAcidification MooringAlaskan coast59.910 149.350pCO2 , pHb2011ActiveKodiakKodiak Alaska OceanAcidification MooringAlaskan coast57.700 152.310pCO2 , pHb2013Discontinuedin 2016SEAKSoutheast Alaska OceanAcidification MooringAlaskan coast56.260 134.670pCO2 , pHb2013Discontinuedin 2016M2Southeastern Bering SeaMooring Site 2Bering Seacoastal shelf56.510 164.040pCO2 , pHb2013ActiveCapeElizabethNDBC Buoy 46041 inOlympic Coast NationalMarine Sanctuary (NMS)US west coast47.353 124.731pCO22006ActiveChá băChá bă Buoy in the NorthwestEnhanced Moored Observatoryand Olympic Coast NMSUS west coast47.936 125.958pCO2 , pH2010ActiveCCE2California Current Ecosystem 2US west coast34.324 120.814pCO2 , pH2010Active 122.803xCO2 c2011ActiveDabobOceanic Remote ChemicalAnalyzer (ORCA) buoy atDabob in Hood CanalEarth Syst. Sci. Data, 11, 421–439, 2019US west /
A. J. Sutton et al.: Autonomous seawater p CO2 and pH time series425Table 1. Continued.AbbreviationDescriptive arStatusNH-10Newport Hydrographic LineStation 10 OceanAcidification MooringUS west coast44.904 124.778pCO2 , pH2014Moved to newlocation in 2017dTwanohORCA buoy at Twanohin Hood CanalUS west coast47.375 123.008xCO2 c2009ActiveAla WaiAla Wai Water Quality Buoyat South Shore OahuPacific islandcoral reef21.280 157.850pCO22008ActiveChuukChuuk Lagoon OceanAcidification MooringPacific islandcoral reef7.460151.900pCO2 , pH2011ActiveCRIMP1Coral Reef InstrumentedMonitoring Platform 1Pacific islandcoral reef21.428 157.788pCO22005Moved toCRIMP2 in2008CRIMP2Coral Reef InstrumentedMonitoring Platform 2Pacific islandcoral reef21.458 157.798pCO22008ActiveKaneoheKaneohe Bay Ocean AcidificationOffshore ObservatoryPacific islandcoral reef21.480 157.780pCO2 , pH2011ActiveKilo NaluKilo Nalu Water Quality Buoyat South Shore OahuPacific islandcoral reef21.288 157.865pCO22008ActiveGray’s ReefNDBC Buoy 41008 in Gray’s ReefNational Marine SanctuaryUS east coast31.400 80.870pCO2 , pH2006ActiveGulf of MaineCoastal Western Gulfof Maine MooringUS east coast43.023 70.542pCO2 , pH2006ActiveCrescent ReefCrescent Reef Bermuda BuoyAtlantic coral reef32.400 64.790pCO22010ActiveHog ReefHog Reef Bermuda BuoyAtlantic coral reef32.460 64.830pCO22010ActiveCoastal MSCentral Gulf of Mexico OceanObserving System Station 01Gulf of Mexico coast30.000 88.600pCO2 , pH2009Moved to newlocation in 2017eCheeca RocksCheeca Rocks Ocean AcidificationMooring in Florida Keys NationalMarine SanctuaryCaribbean coral reef24.910 80.624pCO2 , pH2011ActiveLa PargueraLa Parguera Ocean AcidificationMooringCaribbean coral reef17.954 67.051pCO2 , pH2009ActiveNotes: a data from December 2004 to July 2007 in the WH
Autonomous seawater pCO2 and pH time series from 40 surface buoys and the emergence of anthropogenic trends Adrienne J. Sutton1, Richard A. Feely1, Stacy Maenner-Jones1, Sylvia Musielwicz1,2, John Osborne1,2, Colin Dietrich1,2, Natalie Monacci3, Jessica
a) Vrednosti pH i HCO3 su smanjene, PCO2 je normalan b) Vrednosti PCO2 i HCO3 su smanjene, pH je normalna c) Vrednosti pH i PCO2 se smanjuju, pH pada d) Vrednosti
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and pH to normal levels. Page 13. Summary: Effects of PO2, pH, and PCO2 This chart summarizes how the three major chemical factors - PO2, pH, and PCO2 - modify breathing rate and depth. When the PO2 drops below 60 millimeters of mercury, the peripheral chemo
pCO2 was calculated with the CO2SYS Excel add-in (Lewis and Wallace, 1998) using measured water temperature, pH, and total alkalinity. Constants used for pCO2 calculations include freshwater carbonate dissociation constants (K1 and K2) from Millero (1979) and KHSO4 constants from Dick-son (1990). 2.3 Hemolymph acid-base status
pressure carbon dioxide (pCO2) are well described in literature [4-7]. These three parameters are widespread CPP’s. From this follows the need of the monitoring and the control of pH, dO2 and pCO2 in a defined design space. Additional to temperature and power input, the dissolved ox
values were: pH --- 7.320, Pco2 41 mm. Hg, and [HCO ] 20.7 mEq. per liter. After serial addition of five 0.1 mEq. aliquots of NaHCO8 the pH had only risen to 7.415, and the Pco2 rose from 41 to 70 ram. Hg. In contrast, the addition of equivalent amounts of NaHCO3 to blood in the open system was associated with a rise i
Jul 19, 2016 · 13 . Pre-Analytical . Analytical . Post-Analytical TREATMENT Testing . . pH 7.54, pCO2 17.5, pO2 168.5 POC VBG#2: pH 7.56, pCO2 12.7, pO2 165.9 End tidal CO2 28 . 44 . Air Contamination of Blood Specimens . Background: Anesthesia reports
Agile Development in a Medical Device Company Pieter Adriaan Rottier, Victor Rodrigues Cochlear Limited rrottier@cochlear.com.au Abstract This article discuss the experience of the software development group working in Cochlear with introducing Scrum as an Agile methodology. We introduce the unique challenges we faced due to the nature of our product and the medical device industry. These .
