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The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) was a year-round campaign conducted by the US Department of Energy at the Scripps Institution of Oceanography in La Jolla, CA, USA, with a focus on characterizing atmospheric processes at a coastal location. The ground-based prototype of a new Ka-, W-, and G-band (35.75, 94.88, and 238.8 GHz) profiling atmospheric radar, named CloudCube, which was developed at the Jet Propulsion Laboratory, took part in the experiment during 6 weeks in March and April 2023. This article describes the unique data sets that were obtained during the field campaign from a variety of marine clouds and light precipitation. These are, to the best of the authors' knowledge, the first observations of atmospheric clouds using simultaneous multifrequency measurements including 238.8 GHz. These data sets therefore provide an exceptional opportunity to study and analyze hydrometeors with diameters in the millimeter- and submillimeter size range that can be used to better understand cloud and precipitation structure, formation, and evolution. The data sets referenced in this article are intended to provide a complete, extensive, and high-quality collection of G-band data in the form of Doppler spectra and Doppler moments. In addition, Ka-band and W-band reflectivity and Ka-, W-, and G-band reflectivity ratio profiles are included for several cases of interest on 6 different days. The data sets can be found at https://doi.org/10.5281/zenodo.10076227 (Socuellamos et al., 2024). [ABSTRACT FROM AUTHOR]

Ship weather routing, which involves suggesting low-emission routes, holds potential for contributing to the decarbonisation of maritime transport. However, including because of a lack of readily deployable open-source and open-language computational models, its quantitative impact has been explored only to a limited extent. As a response, the graph-search VISIR (discoVerIng Safe and effIcient Routes) model has been refactored in Python, incorporating novel features. For motor vessels, the angle of attack of waves has been considered, while for sailboats the combined effects of wind and sea currents are now accounted for. The velocity composition with currents has been refined, now encompassing leeway as well. Provided that the performance curve is available, no restrictions are imposed on the vessel type. A cartographic projection has been introduced. The graph edges are quickly screened for coast intersection via a K -dimensional tree. A least-CO 2 algorithm in the presence of dynamic graph edge weights has been implemented and validated, proving a quasi-linear computational performance. The software suite's modularity has been significantly improved, alongside a thorough validation against various benchmarks. For the visualisation of the dynamic environmental fields along the route, isochrone-bounded sectors have been introduced. The resulting VISIR-2 model has been employed in numerical experiments within the Mediterranean Sea for the entirety of 2022, utilising meteo-oceanographic analysis fields. For a 125 m long ferry, the percentage saving of overall CO 2 expenditure follows a bi-exponential distribution. Routes with a carbon dioxide saving of at least 2 % with respect to the least-distance route were found for prevailing beam or head seas. Two-digit savings, up to 49 %, were possible for about 10 d in a year. In the case of an 11 m sailboat, time savings increased with the extent of path elongation, particularly during upwind sailing. The sailboat's routes were made approximately 2.4 % faster due to optimisation, with the potential for an additional 0.8 % in savings by factoring in currents. VISIR-2 serves as an integrative model, uniting expertise from meteorology, oceanography, ocean engineering, and computer science, to evaluate the influence of ship routing on decarbonisation efforts within the shipping industry. [ABSTRACT FROM AUTHOR]

The Philippine Sea, located at the edge of the northwestern Pacific Ocean, possesses complex seabed topography. Developing a high-precision bathymetric model for this region is of paramount importance, as it provides fundamental geoinformation essential for Earth observation and marine scientific research, including plate motion, ocean circulation, and hydrological characteristics. The gravity–geologic method (GGM), based on marine gravity anomalies, serves as an effective bathymetric prediction technique. To further strengthen the prediction accuracy of conventional GGM, we introduce the improved GGM (IGGM). The IGGM considers the effects of regional seafloor topography by employing weighted averaging to more accurately estimate the short-wavelength gravity component, along with refining the subsequent modeling of long-wavelength gravity component. In this paper, we focus on seafloor topography modeling in the Philippine Sea based on the IGGM, combining shipborne bathymetric data with the Scripps Institution of Oceanography (SIO) V32.1 gravity anomaly. To reduce computational complexity, the optimal parameter values required for IGGM are first calculated before the overall regional calculation, and then, based on the terrain characteristics and distribution of sounding data, we selected four representative local sea areas as the research objects to construct the corresponding bathymetric models using GGM and IGGM. The analysis indicates that the precision of the IGGM models in four regions is improved to varying degrees, and the optimal calculation radius is 2 ′. Based on the above finding, a high-precision 1′×1′ bathymetric model of the Philippine Sea (5–35° N, 120–150° E), known as the BAT_PS model, is constructed using IGGM. Results demonstrate that the BAT_PS model exhibits a higher overall precision compared to the General Bathymetric Chart of the Oceans (GEBCO), topo_25.1, and DTU18 models at single-beam shipborne bathymetric points. [ABSTRACT FROM AUTHOR]

Ship weather routing, which involves suggesting low-emission routes, holds potential for contributing to the decarbonisation of maritime transport. However, its quantitative impact has been explored only to a limited extent, also for a lack of readily deployable open-source and open-language computational models. As a response, the VISIR model has been refactored in Python, incorporating new features. The velocity composition with currents has been refined, now encompassing leeway as well. For motor vessels, the angle of attack of waves has been considered, while sailboats now account for the combined effects of wind and sea currents. A least-CO2 algorithm in presence of dynamic graph edge weights has been implemented and validated, proving a quasi-linear computational performance which outperforms VISIR-1. The software suite’s modularity has been significantly improved, alongside a thorough validation against arious benchmarks. The resulting VISIR-2 model has been employed in numerical experiments within the Mediterranean Sea for the entire 2022, utilising meteo-oceanographic analysis fields. For a 125-meter-long ferry, the distribution of carbon dioxide savings follows a bi-exponential distribution. Two-digit CO2 savings were possible for more than ten days in a year. Largest savings were achieved in avoiding upwind sailing and using the lowest engine load. In the case of an 11-meter sailboat, time savings increase with the extent of path elongation, particularly during upwind sailing. The sailboat’s routes were approximately 3 % shorter thanks to optimisation, and there was potential for additional savings when favourable currents were in play. The impact of leeway was minor, but disregarding it would result in a systematic underestimation of route durations. VISIR-2 is a collaborative model with the capacity to harness knowledge from oceanography, ocean engineering, and computer science, to contribute to the decarbonisation efforts in the shipping industry. [ABSTRACT FROM AUTHOR]

Over a hundred experiments were conducted between 1998 and 2022 in the Mediterranean Sea using surface Lagrangian drifters at coastal and offshore levels. Raw data were initially unified and pre-processed manually by eliminating spikes and wrong positions or date/time information. The integrity of the received data packages was checked, and incomplete ones were discarded. Deployment information was retrieved for each drifter and integrated into the PostgreSQL database, realized and maintained by the National Institute of Oceanography and Applied Geophysics (OGS) in Trieste (Italy). This database also collects a variety of metadata about the drifter model, project, owner, and operator. Subsequently, data were processed using standard procedures of editing and quality control developed for the OGS drifter dataset to remove spikes generated by malfunctioning of the sensors and to obtain files with common characteristics. Drifter data and plots of each track were also visually checked to remove any point not identified by the automatic procedure and which were clearly erroneous. Drifter trajectories were split into two or more segments that are considered different deployments in the case of specific drifter behaviour. Data were interpolated at defined time intervals providing a dataset of 158 trajectories, available from the public open-access repository of SEA scieNtific Open data Edition (SEANOE) at 10.17882/90537 (Ribotti et al., 2022), in two versions (one compliant with the Copernicus format and the other one usable with Panoply netCDF viewer), and of SeaDataNet at https://cdi.seadatanet.org/search/welcome.php?query=2610&query%5fcode={9F00DF80-1881-42DD-9DF1-B9BD0282F2B0} (last access: 5 October 2023). [ABSTRACT FROM AUTHOR]

In the last decade, an enormous amount of georeferenced oceanographic data, co-located with catch information, have been collected through the use of commercial fishing vessels operating in the Adriatic Sea and belonging to the fleet monitored by the AdriFOOS (Adriatic Fishery and Oceanography Observing System) infrastructure. This document describes the dataset of depth (pressure) and temperature profiles collected by means of AdriFOOS in the period 2012–2020 (available at 10.17882/73008, Penna et al., 2020) and briefly illustrates the structure of this facility, the oceanographic dataset validation procedures, and some of the results achieved, and it also lists some possible operational applications. This information is of the utmost importance to provide data to feed oceanographic models and advance knowledge on climate change, as well as to improve the ecosystem approach to fishery management. [ABSTRACT FROM AUTHOR]

Geodetic applications of altimetry have largely been inversions of gravity anomaly. Literatures wherein Earth's gravity gradient tensor has been studied mostly presented only the vertical gravity gradient. However, there are six unique signals that constitute the gravity gradient tensor. Gravity gradients are signals suitable for detecting short-wavelength topographic and tectonic features. They are derived from double differentiation of the geoid (or disturbing potential); and hence, are susceptible to noise amplification which was exacerbated by low across-track resolution of altimetry data in the past. However, current generation of altimetry observations have improved spatial resolutions, with some better than 5 km. Therefore, this study takes advantage of current high-resolution altimetry datasets to present CUGB2023GRAD, a global (latitudinal limits of ±80°) 1 arc-minute model of Earth's gravity gradient tensor over the oceans using deflection of the vertical as inputs in the wavenumber domain. The results are first assessed via Laplace's equation; whereby the resultant residual gradient is virtually zero everywhere except at high latitudes - icy environments known for contaminating altimetry observations. Due to the absence of similar models from other institutions, the results are further assessed by comparing the vertical tensor component, zzT, with equivalent models from Scripps Institution of Oceanography (SIO) and Technical University of Denmark (DTU). The DTU equivalents were derived by multiplying their gravity anomalies by 2 k ? in the wavenumber domain. Analysis showed that the inverted zzT averagely deviates from the DTU and SIO equivalents by 0.09 and 0.18 E with corresponding standard deviations of 3.55 and 6.96 E, respectively. Bathymetric coherence analysis of zzT 20 over a section of the western Pacific showed comparable results with the reference models. This study proves that current generation of altimetry geodetic missions can effectively resolve Earth's gravity gradient tensor. The CUGB2023GRAD model data can be freely accessed at https://doi.org/10.5281/zenodo.7710254 (Annan et al., 2023). [ABSTRACT FROM AUTHOR]

The French coast of the Eastern English Channel (ECC) is classified as potential eutrophication zone by the Paris and Oslo Convention (OSPAR), and as moderate to poor according to phytoplankton quality element of the Water Framework Directive (WFD). Indeed, the French part of the EEC is regularly affected by Phaeocystis globosa bloom events, which have detrimental effects on the marine ecosystem, economy as well as public health. Since phytoplankton is an important indicator of water quality, the MAREL Carnot oceanographic multi-sensor station was installed in the Eastern English Channel at the Carnot wall in Boulogne sur Mer in 2004. The aim of this station was to monitor water quality and phytoplankton in order to complement results from existing more conventional low resolution monitoring programs, with high frequency data (sampling every 20 minutes). The purpose of this paper is to introduce the MAREL Carnot dataset and show how it can be used for several research objectives. MAREL Carnot collects high frequency, multi-parameter observations from surface water, as well as meteorological measurements, and send data almost immediately to an inshore data center. In this paper, we present several physiochemical and biological parameters measured by this station. In addition, we demonstrated, based on previous research activities, that the MAREL Carnot dataset is useful for evaluating environmental or ecological statuses, marine phytoplankton ecology, physical oceanography, turbulence, as well as public policy. Most importantly, we showed its contribution to Marine Strategy Framework Directive (MSFD) and other regional or universal conventions. [ABSTRACT FROM AUTHOR]

High-resolution models have become widely available for the study of the ocean's small-scale processes. Although these models simulate more turbulent ocean dynamics and reduce uncertainties of parameterizations, they are not practical for long-term simulations, especially for climate studies. Besides scientific research, there are also growing needs from key applications for multi-resolution, flexible modeling capabilities. In this study we introduce the Ocean Modeling with Adaptive REsolution (OMARE), which is based on refactoring Nucleus for European Modelling of the Ocean (NEMO) with the parallel computing framework of JASMIN (J parallel Adaptive Structured Mesh applications INfrastructure). OMARE supports adaptive mesh refinement (AMR) for the simulation of the multi-scale ocean processes with improved computability. We construct an idealized, double-gyre test case, which simulates a western-boundary current system with seasonally changing atmospheric forcings. This paper (Part 1) focuses on the ocean physics simulated by OMARE at two refinement scenarios: (1) 0.5–0.1 ∘ static refinement and the transition from laminar to turbulent, eddy-rich ocean, and (2) the short-term 0.1–0.02 ∘ AMR experiments, which focus on submesoscale processes. Specifically, for the first scenario, we show that the ocean dynamics on the refined, 0.1 ∘ region is sensitive to the choice of refinement region within the low-resolution, 0.5 ∘ basin. Furthermore, for the refinement to 0.02 ∘ , we adopt refinement criteria for AMR based on surface velocity and vorticity. Results show that temporally changing features at the ocean's mesoscale, as well as submesoscale process and its seasonality, are captured well through AMR. Related topics and future plans of OMARE, including the upscaling of small-scale processes with AMR, are further discussed for further oceanography studies and applications. [ABSTRACT FROM AUTHOR]

This document describes the dataset of depth (pressure)/temperature profiles collected by means of the AdriFOOS infrastructure in the period 2012-2020 and briefly illustrates the structure of this facility, the oceanographic dataset validation procedures, some of the results achieved, and also lists some possible operational applications. In fact, in the last decade, CNR IRBIM's AdriFOOS has collected an enormous amount of georeferenced oceanographic and catch data through the use of commercial fishing vessels operating in the Adriatic Sea. This information is of the utmost importance to provide data to feed oceanographic models and advance knowledge on climate change, as well as to improve the ecosystem approach to fisheries management. [ABSTRACT FROM AUTHOR]

Over a hundred of experiments were realised between 1998 and 2022 in the Mediterranean Sea using surface Lagrangian drifters, at coastal and offshore level. Raw data were initially unified and pre-processed manually by eliminating spikes and wrong positions or date/time information. The integrity of the received data packages was checked, and incomplete ones were discarded. Deployment information was retrieved from an initial excel database and campaign notes for each drifter and integrated into the PostgreSQL database, realised and maintained by the National Institute of Oceanography and Applied Geophysics (OGS) in Trieste (IT). This database also collects a variety of metadata about the drifter model, project, owner and operator. Subsequently data were processed using standard procedures of editing and quality control developed for the OGS Mediterranean drifter dataset to remove spikes generated by malfunctioning of the sensors and obtain files with common characteristics. Drifter data and plots of each track were also visually checked to remove any point not identified by the automatic procedure and clearly erroneous. Drifters' trajectories were split into two or more segments that have been considered as different deployments, in case of specific drifters' behaviours. Data were interpolated at defined time intervals to temporarily unify tracks. From the original 138 experiments, a dataset of 204 tracks was obtained, available from the public open-access repository in SEANOE (SEA scieNtific Open data Edition) at https://doi.org/10.17882/90537 (Ribotti et al., 2022). [ABSTRACT FROM AUTHOR]

Measurements targeting mesoscale and smaller-scale processes in the ice-covered part of the Arctic Ocean are sparse in all seasons. As a result, there are significant knowledge gaps with respect to these processes, particularly related to the role of eddies and fronts in the coupled ocean–atmosphere–sea ice system. Here we present a unique observational dataset of upper ocean temperature and salinity collected by a set of buoys installed on ice floes as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network. The multi-sensor systems, each equipped with five temperature and salinity recorders on a 100 m long inductive modem tether, drifted together with the main MOSAiC ice camp through the Arctic Transpolar Drift between October 2019 and August 2020. They transmitted hydrographic in situ data via the iridium satellite network at 10 min intervals. While three buoys failed early due to ice dynamics, five of them recorded data continuously for 10 months. A total of four units were successfully recovered in early August 2020, additionally yielding internally stored instrument data at 2 min intervals. The raw data were merged, processed, quality controlled, and validated using independent measurements also obtained during MOSAiC. Compilations of the raw and processed datasets are publicly available at 10.1594/PANGAEA.937271 and 10.1594/PANGAEA.940320 , respectively. As an important part of the MOSAiC physical oceanography program, this unique dataset has many synergies with the manifold co-located observational datasets and is expected to yield significant insights into ocean processes and to contribute to the validation of high-resolution numerical simulations. While this dataset has the potential to contribute to submesoscale process studies, this paper mainly highlights selected preliminary findings on mesoscale processes. [ABSTRACT FROM AUTHOR]

The South China Sea Operational Oceanography Forecasting System (SCSOFS), constructed and operated by the National Marine Environmental Forecasting Center of China, has been providing daily updated hydrodynamic forecasting in the South China Sea (SCS) for the next 5 d since 2013. This paper presents recent comprehensive updates to the configurations of the physical model and data assimilation scheme in order to improve the forecasting skill of the SCSOFS. This paper highlights three of the most sensitive updates: the sea surface atmospheric forcing method, the discrete tracer advection scheme, and a modification of the data assimilation scheme. Intercomparison and accuracy assessment among the five sub-versions were performed during the entire upgrading process using the OceanPredict Intercomparison and Validation Task Team Class 4 metrics. The results indicate that remarkable improvements have been made to the SCSOFSv2 with respect to the original version (known as SCSOFSv1). The domain-averaged monthly mean root-mean-square errors of the sea surface temperature and sea level anomaly have decreased from 1.21 to 0.52 ∘ C and from 21.6 to 8.5 cm, respectively. [ABSTRACT FROM AUTHOR]

Measurements targeting mesoscale and submesoscale processes in the ice-covered part of the Arctic Ocean are sparse in all seasons. As a result, there are significant knowledge gaps with respect to these processes, in particular related to the role of eddies and fronts in the coupled ocean-atmosphere-sea ice system. Here we present a unique observational dataset of upper ocean temperature and salinity collected by a set of buoys installed on ice floes as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network. The multi-sensor systems, each of them equipped with five temperature and salinity recorders on a 100 m long inductive modem tether, drifted together with the main MOSAiC ice camp through the Arctic Transpolar Drift between October 2019 and August 2020. They transmitted hydrographic in situ data via the iridium satellite network at 10 minute intervals. While three buoys failed early due to ice dynamics, five of them recorded data continuously for 10 months. Four units were successfully recovered in early August 2020, additionally yielding internally stored instrument data at 2 minute intervals. The raw datasets (Hoppmann et al., 2021i) were merged, processed, quality-controlled and validated using independent measurements. Upon acceptance of the manuscript, the finally processed dataset (currently under moratorium) will be made publicly available under Hoppmann et al. (2022i). As an important part of the MOSAiC physical oceanography program, this unique dataset has many synergies with the manifold co-located observational datasets, and is expected to yield significant insights into ocean processes, and to contribute to the validation of high-resolution numerical simulations. [ABSTRACT FROM AUTHOR]

The South China Sea Operational Oceanography Forecasting System (SCSOFS), constructed and operated by the National Marine Environmental Forecasting Center of China, has been providing daily updated hydrodynamic forecasting in the South China Sea (SCS) for the next 5 d since 2013. This paper presents recent comprehensive updates to the configurations of the physical model and data assimilation scheme in order to improve the forecasting skill of the SCSOFS. This paper highlights three of the most sensitive updates: the sea surface atmospheric forcing method, the discrete tracer advection scheme, and a modification of the data assimilation scheme. Intercomparison and accuracy assessment among the five sub-versions were performed during the entire upgrading process using the OceanPredict Intercomparison and Validation Task Team Class 4 metrics. The results indicate that remarkable improvements have been made to the SCSOFSv2 with respect to the original version (known as SCSOFSv1). The domain-averaged monthly mean root-mean-square errors of the sea surface temperature and sea level anomaly have decreased from 1.21 to 0.52 ∘ C and from 21.6 to 8.5 cm, respectively. [ABSTRACT FROM AUTHOR]

South China Sea Operational Oceanography Forecasting System (SCSOFS) had been constructed and operated in National Marine Environmental Forecasting Center of China to provide daily updated hydrodynamic forecasting in SCS for the future 5 days since 2013. This paper presents recent comprehensive updates of the configurations of the physical model and data assimilation scheme in order to improve SCSOFS forecasting skills. It highlights three of the most sensitive updates, including sea surface atmospheric forcing method, tracers advection discrete scheme, and modification of data assimilation scheme. Inter-comparison and accuracy assessment among five versions during the whole upgrading processes are performed by employing OceanPredict Inter-comparison and Validation Task Team Class4 metrics. The results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version known as SCSOFSv1. Domain averaged monthly mean root mean square errors decrease from 1.21 °C to 0.52 °C for sea surface temperature, from 21.6 cm to 8.5 cm for sea level anomaly, respectively. [ABSTRACT FROM AUTHOR]

Virioplankton are a key component of the marine biosphere in maintaining diversity of microorganisms and stabilizing ecosystems. They also contribute greatly to nutrient cycles/cycling by releasing organic matter after lysis of hosts. In this study, we constructed the first global viral oceanography database (gVOD) by collecting 10 931 viral abundance (VA) data and 727 viral production (VP) data, along with host and relevant oceanographic parameters when available. Most VA data were obtained in the North Atlantic (32 %) and North Pacific (29 %) oceans, while the southeast Pacific and Indian oceans were quite undersampled. The VA in the global ocean was 1.17(±3.31)×107 particlesmL-1. The lytic and lysogenic VP in the global ocean was 9.87(±24.16)×105 and 2.53(±8.64)×105 particlesmL-1h-1 , respectively. Average VA in coastal oceans was higher than that in surface open oceans (3.61(±6.30)×107 versus 0.73(±1.24)×107 particlesmL-1), while average VP in coastal and surface open oceans was close. Vertically, VA, lytic VP and lysogenic VP deceased from surface to deep oceans by about 1 order of magnitude. The total number of viruses in the global ocean estimated by bin-averaging and the random forest method was 1.56×1030 and 1.49×1030 particles, leading to an estimate of global ocean viral biomass at 35.9 and 34.4 TgC , respectively. We expect that the gVOD will be a fundamental and very useful database for laboratory, field and modeling studies in marine ecology and biogeochemistry. The full gVOD database (Xie et al., 2020) is stored in PANGAEA (10.1594/PANGAEA.915758). [ABSTRACT FROM AUTHOR]