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This GO-SHIP manual is a rewrite of the original version by Hydes et al. (2010), and reviews basic sample collection and storage, aspects of CFA using an Auto-Analyzer, and specific nutrient methods in use by many laboratories doing repeat hydrography. The document also covers laboratory best practices including quality control and quality assurance (QC/QA) procedures to obtain the best results, and suggests protocols for the use of reference materials (RM) and certified reference materials (CRMs). Published This is a rewrite of : Hydes, D. J.; Aoyama, M.; Aminot, A.; Bakker, K.; Becker,S.; Coverly, S.; Daniel, A.; Dickson, A. G.; Grosso, O.; Kerouel, R.; van Ooijen, J.; Sato, K.; Tanhua, T.; Woodward, E. M. S. and Zhang, J. Z. (2010) Determination of Dissolved Nutrients (N, P, SI) in Seawater With High Precision and Inter-Comparability Using Gas-Segmented Continuous Flow Analysers. In: The GO-SHIP Repeat Hydrography Manual: A Collection of Expert Reports and Guidelines. Version 1. (eds Hood, E.M., C.L. Sabine, and B.M. Sloyan). IOCCP Report Number 14, ICPO Publication Series Number 134. Available online at: http://www.go-ship.org/HydroMan.html. Refereed Current 14.A Nutrients Mature: Methodologies are well demonstrated for a given objective, documented and peer reviewed; methods are commonly used by more than one organization (TRL 7-9) Best Practice Standard Operating Procedure

The development of phosphate sensors suitable for long-term in situ deployments in natural waters, is essential to improve our understanding of the distribution, fluxes, and biogeochemical role of this key nutrient in a changing ocean. Here, we describe the optimization of the molybdenum blue method for in situ work using a lab-on-chip (LOC) analyzer and evaluate its performance in the laboratory and at two contrasting field sites. The in situ performance of the LOC sensor is evaluated using hourly time-series data from a 56-day trial in Southampton Water (UK), as well as a month-long deployment in the subtropical oligotrophic waters of Kaneohe Bay (Hawaii, USA). In Kaneohe Bay, where phosphate concentrations were characteristic of the dry season (0.13 ± 0.03 μM, n = 704), the in situ sensor accuracy was 16 ± 12% and a potential diurnal cycle in phosphate concentrations was observed. In Southampton Water, the sensor data (1.02 ± 0.40 μM, n = 1,267) were accurate to ±0.10 μM relative to discrete reference samples. Hourly in situ monitoring revealed striking tidal and storm derived fluctuations in phosphate concentrations in Southampton Water that would not have been captured via discrete sampling. We show the impact of storms on phosphate concentrations in Southampton Water is modulated by the spring-neap tidal cycle and that the 10-fold decline in phosphate concentrations observed during the later stages of the deployment was consistent with the timing of a spring phytoplankton bloom in the English Channel. Under controlled laboratory conditions in a 250 L tank, the sensor demonstrated an accuracy and precision better than 10% irrespective of the salinity (0–30), turbidity (0–100 NTU), colored dissolved organic matter (CDOM) concentration (0–10mg/L), and temperature (5–20◦C) of the water (0.3–13 μM phosphate) being analyzed. This work demonstrates that the LOC technology is mature enough to quantify the influence of stochastic events on nutrient budgets and to elucidate the role of phosphate in regulating phytoplankton productivity and community composition in estuarine and coastal regimes. Refereed 14.A Nutrients TRL 8 Actual system completed and "mission qualified" through test and demonstration in an operational environment (ground or space) Manual (incl. handbook, guide, cookbook etc) Standard Operating Procedure

Thanks to its optimal location on the northern Brazilian margin, core MD09-3257 records both ocean circulation and atmospheric changes. The latter occur locally in the form of increased rainfall on the adjacent continent during the cold intervals recorded in Greenland ice and northern North Atlantic sediment cores (i.e., Greenland stadials). These rainfall events are recorded in MD09-3257 as peaks in ln(Ti ∕ Ca). New sedimentary Pa ∕ Th data indicate that mid-depth western equatorial water mass transport decreased during all of the Greenland stadials of the last 40 kyr. Using cross-wavelet transforms and spectrogram analysis, we assess the relative phase between the MD09-3257 sedimentary Pa ∕ Th and ln(Ti ∕ Ca) signals. We show that decreased water mass transport between a depth of ∼1300 and 2300 m in the western equatorial Atlantic preceded increased rainfall over the adjacent continent by 120 to 400 yr at Dansgaard–Oeschger (D–O) frequencies, and by 280 to 980 yr at Heinrich-like frequencies. We suggest that the large lead of ocean circulation changes with respect to changes in tropical South American precipitation at Heinrich-like frequencies is related to the effect of a positive feedback involving iceberg discharges in the North Atlantic. In contrast, the absence of widespread ice rafted detrital layers in North Atlantic cores during D–O stadials supports the hypothesis that a feedback such as this was not triggered in the case of D–O stadials, with circulation slowdowns and subsequent changes remaining more limited during D–O stadials than Heinrich stadials.

A critical challenge in paleoclimate data analysis is the fact that the proxy data are heterogeneously distributed in space, which affects statistical methods that rely on spatial embedding of data. In the paleoclimate network approach nodes represent paleoclimate proxy time series, and links in the network are given by statistically significant similarities between them. Their location in space, proxy and archive type is coded in the node attributes. We develop a semi-empirical model for Spatio-Temporally AutocoRrelated Time series, inspired by the interplay of different Asian Summer Monsoon (ASM) systems. We use an ensemble of transition runs of this START model to test whether and how spatio–temporal climate transitions could be detectable from (paleo)climate networks. We sample model time series both on a grid and at locations at which paleoclimate data are available to investigate the effect of the spatially heterogeneous availability of data. Node betweenness centrality, averaged over the transition region, does not respond to the transition displayed by the START model, neither in the grid-based nor in the scattered sampling arrangement. The regionally defined measures of regional node degree and cross link ratio, however, are indicative of the changes in both scenarios, although the magnitude of the changes differs according to the sampling. We find that the START model is particularly suitable for pseudo-proxy experiments to test the technical reconstruction limits of paleoclimate data based on their location, and we conclude that (paleo)climate networks are suitable for investigating spatio–temporal transitions in the dependence structure of underlying climatic fields.

In the field of ocean observing, the term of “observatory” is often used without a unique meaning. A clear and unified definition of observatory is needed in order to facilitate the communication in a multidisciplinary community, to capitalize on future technological innovations and to support the observatory design based on societal needs. In this paper, we present a general framework to define the next generation Marine OBservatory (MOB), its capabilities and functionalities in an operational context. The MOB consists of four interconnected components or “gears” (observation infrastructure, cyberinfrastructure, support capacity, and knowledge generation engine) that are constantly and adaptively interacting with each other. Therefore, a MOB is a complex infrastructure focused on a specific geographic area with the primary scope to generate knowledge via data synthesis and thereby addressing scientific, societal, or economic challenges. Long-term sustainability is a key MOB feature that should be guaranteed through an appropriate governance. MOBs should be open to innovations and good practices to reduce operational costs and to allow their development in quality and quantity. A deeper biological understanding of the marine ecosystem should be reached with the proliferation of MOBs, thus contributing to effective conservation of ecosystems and management of human activities in the oceans. We provide an actionable model for the upgrade and development of sustained marine observatories producing knowledge to support science-based economic and societal decisions. Refereed 14.A Manual (incl. handbook, guide, cookbook etc) 2018-09-07

Water/ice velocity data and instrument status from a Nortek Aquadopp Profiler 2MHz acoustic doppler current profiler (ADCP) attached to a remotely operated vehicle (ROV) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. The Aquadopp System Integrator Manual by Nortek AS can be found here: https://sensor.awi.de/rest/sensors/onlineResources/getOnlineResourcesFile/1764/system-integrator-manual_Mar2016.pdf

Raw data acquired by GPS1 position sensors on board research aircraft Polar 6 during the campaign P6_237_BACSAM_2022 were processed to receive a validated master track which can be used as reference of further expedition data. Novatel FlexPak6 GPS receiver was used as navigation sensors during the campaign. Data were downloaded from DAVIS SHIP data base (https://dship.awi.de) with a resolution of 1 sec. Processed data are provided as a master track with 1 sec resolution and a generalized track with a reduced set of the most significant positions of the master track. A detailed report on processing is also available for each flight.

Numerous experiments to date have demonstrated that elevated PCO2 is detrimental to biogenic calcification rates. However, most of these experiments have been realized in batch or continuous cultures and give little information on the dynamics of calcification in natural conditions. The present work describes the development and decay of a nutrient-induced bloom of the coccolithophorid Emiliania huxleyi in a mesocosm experiment. The monitoring of Dissolved Inorganic Carbon (DIC) and Total Alkalinity (TAlk) within the seawater enclosures allowed us to describe comprehensively day to day dynamics of both calcification and organic carbon production. Three atmospheric PCO2 conditions (glacial, present and next century) were simulated by bubbling CO2 mixtures, while total alkalinity was left to evolve from its present value. No conspicuous change of Net Community Production under elevated PCO2 was recorded while the production of inorganic carbon appeared to be affected in two ways. Firstly, the production rate of inorganic carbon appeared to be lowered by 40% in the next century PCO2 conditions, decreasing concomitantly the calcification to photosynthesis ratio from 0.75 (glacial conditions) to 0.45 (next century conditions). Secondly, the onset of calcification was delayed by 24~48h under elevated PCO2 conditions, reducing the overall length of calcification in the course of the bloom. These two effects would act to reduce the amount of precipitated CaCO3 by coccolithophorids in a High CO2 world

The data sets under this data collection include detailed snow pit studies of snow temperature, density, specific surface area (SSA), stratigraphy (snow grain type & size and hand hardness), and salinity as well as high-resolution snow penetrometer measurement profiles. The data were collected during the ALERT2018 campaign (Multidisciplinary Arctic Program (MAP) - Last Ice) off Alert, Nunavut, Canada in the Lincoln Sea in May 2018. For more detailed information, please refer to the individual data sets.

This bibliography unites different data types collected by a remotely operated vehicle (ROV) underneath drifting sea ice during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern (AWI, 2017) between November 2019 and September 2020 (Nicolaus et al., 2022). The observation class M500 ROV was manufactured by Ocean Modules AB (Åtvidaberg, Sweden) and is owned by the Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (Bremerhaven, Germany). It was equipped with an extended multidisciplinary sensor payload. To investigate the under-ice light field and bio-optical properties, the ROV was equipped with hyperspectral radiometers, transmissometers and a triplet fluorometer. Oceanographic properties were recorded with a standard CTD package including sensors for dissolved oxygen, nitrate and pH. Single beam and multibeam sonar allowed for a three-dimensional mapping of the ice underside, while an acoustic current profiler measured relative water currents. In addition to different video and still cameras for visual documentation of the under-ice environment, the ROV was equipped with a hyperspectral imager. For sampling of the under-ice ecosystem, a suction sampling system and an under-ice plankton as well as a gypsum net were attached to the ROV. Data were collected for all seasons and for various sea-ice and surface conditions. All data are provided at their original temporal resolution and have a common GPS synchronized timestamp. All times are given in UTC. Horizontal position of the ROV was determined using a long baseline acoustic positioning system and is provided in a floe-fixed, relative coordinate system (X, Y) with the origin (X=0 m, Y=0 m) at the ROV access hole in the MOSAiC central observatory (CO). Operations were conducted in a 300 m radius around the hole. A one function manipulator in combination with the ROV's six degrees of freedom enabled deployment and recovery of equipment (e.g. sediment traps) underneath the ice cover. Details about the respective deployment conditions can be found in the respective cruise reports of MOSAiC. A technical description of the ROV can be found in Katlein et al. (2017). MATLAB codes used for processing the data are published on ZENODO (Anhaus et al., 2023). The data will be described in a respective ROV data paper. When reusing the data, please refer to this data paper (Anhaus et al., in prep.) and the actual datasets listed below (Datasets listed in this bibliography). Please carefully read the comment section below and contact the author(s) before using the data.