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Research vessels are typically equipped with multiple receivers for positioning and attitude measurement; however, there is no data interaction or model fusion to implement the Precise Point Positioning (PPP) for these receivers. Therefore, a Constrained PPP (CPPP) is established by using the baseline length and tropospheric constraints of two receivers to improve the vessel's remote marine positioning performance. Based on two integrated Real-Time Kinematic (RTK) receivers, marine experiments are conducted at a distance of 300-600 km from land. Compared to the ground environment, the Root Mean Square error (RMS) of the multipath and the STandard Deviation (STD) of the carrier-to-noise ratio in the marine environment are increased by 2.87 and 2.6 times, respectively. The length constraints reduce the RMS of positioning in the East, North, and Up (ENU) directions by about 0.053 (67%), 0.020 (34%), and 0.054 m (34%), respectively, and also rapidly recover positioning after interruptions, achieving positioning with errors in the ENU-directions of 10, 15, and 20 cm, respectively, within 3 minutes. When the baseline length and tropospheric constraints are combined, with or without the addition of the Zenith Wet Delay bias (dZWD), the average STD can be reduced by about 0.060 m (43%) and the accuracy of the up-positioning can be significantly improved. The correlation of dZWD to the up-positioning deviation of du=−2.161*dZWD is obtained by simulation. Since the acquisition of dZWD depends on the PPP accuracy, it is recommended that dZWD be set to compensate for unmodeled receiver errors when the STD of the up-positioning is superior to 0.06 m.

Extending oceanographic data beyond the instrumental period is highly needed to better characterize and understand multi-decadal to centennial natural ocean variability. Here, a stable isotope record at unprecedented temporal resolution (1 to 2 years) from a new marine core retrieved off western North Iceland is presented. We aim to better constrain the variability of subsurface, Atlantic-derived Subpolar Mode Water (SPMW), using near surface-dwelling planktic foraminifera and Arctic Intermediate Water (AIW) mass changes using benthic foraminifera over the last ~165 years. The reconstruction overlaps in time with instrumental observations and a direct comparison reveals that the [delta].sup.18 O record of Neogloboquadrina pachyderma is reliably representing temperature fluctuations in the SPMWs. Trends in the N. pachyderma [delta].sup.13 C record match the measured phosphate concentration in the upper 200 m on the North Icelandic Shelf well. Near surface-dwelling foraminifera trace anthropogenic CO.sub.2 in the Iceland Sea by ~ 1950 ± 8, however, a reduced amplitude shift in the Marine Suess effect is identified. We argue that this is caused by a contemporary ongoing increase in marine primary productivity in the upper ocean due to enhanced Greenland's freshwater discharge that has contributed to a nutrient-driven fertilization since the 1940s/50s (Perner et al., 2019). Multi-decadal variability is detected. We find that the 16-year periodicity evident in SPMW and AIWs based on the [delta].sup.18 O of N. pachyderma and M. barleeanum is a signal of SST anomalies propagated into the Nordic Seas via the Atlantic inflow branches around Iceland. Spectral analyses of the planktic foraminiferal [delta].sup.13 C signal indicate intermittent 30-year cycles that are likely reflecting the ocean response to atmospheric variability, presumably the East Atlantic Pattern. A long-term trend in benthic [delta].sup.18 O suggests that Atlantic-derived waters are expanding their core within the water column from the subsurface into deeper intermediate depths towards the present day. This is a result of increased transport by the North Icelandic Irminger Current to the North Iceland Shelf over the historical era.

Abstract—The round-the-world Antarctic expedition of the Russian Navy that took place from December 2019 to June 2020 on board the Russian Navy oceanographic research vessel (ORV) Admiral Vladimirsky was supported by the Russian Geographical Society and was dedicated to the 200th anniversary of the discovery of Antarctica and the 250th birthday anniversary of Admiral Ivan Kruzenshtern. One of the expedition’s main objectives was to instrumentally determine the position of the South Magnetic Pole (SMP) whose latest location had been measured more than twenty years before. Planning of magnetometric research, its monitoring and processing of obtained data were carried out by members of the Chair of Geophysical Methods of the Earth’s Crust Study of the MSU Department of Geology and the Fedorov Institute of Applied Geophysics. Based on a set of instrumental determinations (modular proton-precession differential magnetometers, vector three-component flux-gate magnetometers, the ship compass), the SMP position was measured to a precision of ±5 km. Proceeding from the 1980 and 2000 instrumental SMP determinations, it is proven that over the past 40 years, the SMP has been shifting at a consistent velocity in the same direction.

Over the last two decades, there has been an explosion of oceanographic data from a broad array of ocean observing platforms, as well as dramatic improvements in the ability of ocean models to resolve processes across multiple temporal and spatial scales. Ocean researchers’ ability to leverage computing tools and resources are key to effectively understanding and monitoring our ocean, the marine ecosystems it supports, and the response of the Earth system to climate change. Therefore, data science skills have become essential in the scientific discovery process, and it is becoming increasingly important to have computational skills in our research toolbox. OceanHackWeek was launched in 2018 to build an inclusive community that promotes data and software proficiency in oceanography. With a mission to meet, collaborate, and learn at the intersection of ocean and data sciences, OceanHackWeek provides a vibrant, diverse, and inclusive community that embodies the vision of an open ocean science future. In this article we present the OceanHackWeek model, provide an overview of the curriculum and formats of the events, and discuss the lessons learned and recommendations for implementing an OceanHackWeek-style event.

Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.

Collecting data in the ocean requires scientists to choose, use, and interpret the output of sensor-based instruments. With the increasing accessibility of do-it-yourself (DIY) technology, researchers are able to develop innovative and cost-​effective instruments with relative ease compared to just 10 years ago. As part of a project-based course to teach undergraduates and graduate students engineering skills that are useful in marine science, we developed an Arduino-based instrument to measure temperature and depth. By building, calibrating, and testing this instrument, students learn about sensors and circuits, are introduced to hardware and software design, and collect, analyze, and interpret their own data. More broadly, students learn principles of instrument design and develop problem-​solving skills.

Polar temperatures over the last several million years have, at times, been slightly warmer than today, yet global mean sea level has been 6–9 metres higher as recently as the Last Interglacial (130,000 to 115,000 years ago) and possibly higher during the Pliocene epoch (about three million years ago). In both cases the Antarctic ice sheet has been implicated as the primary contributor, hinting at its future vulnerability. Here we use a model coupling ice sheet and climate dynamics—including previously underappreciated processes linking atmospheric warming with hydrofracturing of buttressing ice shelves and structural collapse of marine-terminating ice cliffs—that is calibrated against Pliocene and Last Interglacial sea-level estimates and applied to future greenhouse gas emission scenarios. Antarctica has the potential to contribute more than a metre of sea-level rise by 2100 and more than 15 metres by 2500, if emissions continue unabated. In this case atmospheric warming will soon become the dominant driver of ice loss, but prolonged ocean warming will delay its recovery for thousands of years. Climate and ice-sheet modelling that includes ice fracture dynamics reveals that Antarctica could contribute more than a metre of sea-level rise by 2100 and more than 13 metres by 2500, if greenhouse gas emissions continue unabated. A 500-year model of Antarctica's contribution to future sea-level rise Robert DeConto and David Pollard use a newly improved numerical ice-sheet model calibrated to Pliocene and Last Interglacial sea-level estimates to develop projections of Antarctica's evolution over the next five centuries, driven by a range of greenhouse gas scenarios. The modelling shows that the Antarctic ice sheet has the potential to contribute between almost nothing, to contributing more than a metre of sea-level rise by 2100 and more than 15 metres by 2500. The startling high-end estimate arises from unabated emissions and previously underappreciated mechanisms: ice-fracturing by surface meltwater and collapse of large ice cliffs. The low end shows that a scenario of strong climate mitigation can radically reduce societal exposure to higher sea levels.

The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This paper gives a full description of the OCEAN5 system, with the focus on upgrades of system components with respect to its predecessors, ORAS4 and ORAP5. An important novelty in OCEAN5 is the ensemble generation strategy that includes perturbation of initial conditions and a generic perturbation scheme for observations and forcing fields. Other upgrades include revisions to the a priori bias correction scheme, observation quality control and assimilation method for sea-level anomalies. The OCEAN5 historical reconstruction of the ocean and sea-ice state is the ORAS5 reanalysis, which includes five ensemble members and covers the period from 1979 onwards. Updated versions of observation data sets are used in ORAS5 production, with special attention devoted to the consistency of sea surface temperature (SST) and sea-ice observations. Assessment of ORAS5 through sensitivity experiments suggests that all system components contribute to an improved fit to observation in reanalyses, with the most prominent contribution from direct assimilation of ocean in situ observations. Results of observing system experiments further suggest that the Argo float is the most influential observation type in our data assimilation system. Assessment of ORAS5 has also been carried out for several key ocean state variables and verified against reference climate data sets from the ESA CCI (European Space Agency Climate Change Initiative) project. With respect to ORAS4, ORAS5 has improved ocean climate state and variability in terms of SST and sea level, mostly due to increased model resolution and updates in assimilated observation data sets. In spite of the improvements, ORAS5 still underestimates the temporal variance of sea level and continues exhibiting large SST biases in the Gulf Stream and its extension regions which are possibly associated with misrepresentation of front positions. Overall, the SST and sea-ice uncertainties estimated using five ORAS5 ensemble members have spatial patterns consistent with those of analysis error. The ensemble spread of sea ice is commensurable with the sea-ice analysis error. On the contrary, the ensemble spread is under-dispersive for SST.

The first 2000 m of the global thermohaline structure of the ocean are statistically decomposed into vertical thermohaline modes, using a multivariate functional principal component analysis (FPCA). This method is applied on the Monthly Isopycnal and Mixed-Layer Ocean Climatology (MIMOC). The first three modes account for 92% of the joint temperature and salinity ( T – S ) variance, which yields a surprisingly good reduction of dimensionality. The first mode (69% of the variance) is related to the thermocline depth and delineates the subtropical gyres. The second mode (18%) is mostly driven by salinity and mainly displays the asymmetry between the North Pacific and Atlantic basins and the salty circumpolar deep waters in the Southern Ocean. The third mode (5%) identifies the low- and high-salinity intermediate waters, covarying with the freshwater inputs of the upper ocean. The representation of the ocean in the space defined by the first three modes offers a simple visualization of the global thermohaline structure that strikingly emphasizes the role of the Southern Ocean in linking and distributing water masses to the other basins. The vertical thermohaline modes offer a convenient framework for model and observation data comparison. This is illustrated by projecting the repeated Pacific section P16 together with profiles from the Array for Real-Time Geostrophic Oceanography (ARGO) global array of profiling floats on the modes defined with the climatology MIMOC. These thermohaline modes have a potential for water mass identification and robust analysis of heat and salt content.