The Identification and Prediction of Mesoscale Eddy Variation via Memory in Memory With Scheduled Sampling for Sea Level Anomaly

Ocean mesoscale eddies are ubiquitous in world ocean and account for 90% oceanic kinetic energy, which dominate the upper ocean flow field. Accurately predicting the variation of ocean mesoscale eddies is the key to understand the oceanic flow field and circulation system. In this article, we propose to make an initial attempt to explore spatio-temporal predictability of mesoscale eddies, employing deep learning architecture, which primarily establishes Memory In Memory (MIM) for sea level anomaly (SLA) prediction, combined with the existing mesoscale eddy detection. Oriented to the western Pacific ocean (125°−137.5°E and 15°−27.5°N), we quantitatively investigate the historic daily SLA variability at a 0.25° spatial resolution from 2000 to 2018, derived by satellite altimetry. We develop the enhanced MIM prediction strategies, equipped with Gated Recurrent Unit (GRU) and spatial attention module, in a scheduled sampling manner, which overcomes the gradient vanishing and complements to strengthen spatio-temporal features for long-term dependencies. At the early stage, the real value SLA input guides the model training process for initialization, while the scheduled sampling intentionally feeds the newly predicted value, to resolve the distribution inconsistency of inference. It has been demonstrated in our experiment results that our proposed prediction scheme outperformed the state-of-art approaches for SLA time series, with MAPE, RMSE of the 14-day prediction duration, respectively, 5.1%, 0.023 m on average, even up to 4.6%, 0.018 m for the effective sub-regions, compared to 19.8%, 0.086 m in ConvLSTM and 8.3%, 0.040 m in original MIM, which greatly facilitated the mesoscale eddy prediction. This proposed scheme will be beneficial to understand of the underlying dynamical mechanism behind the predictability of mesoscale eddies in the future, and help the deployment of ARGO, glider, AUV and other observational platforms.

Seasonal Ekman upwelling in the Southwest Sumba from INDESO Model

Southwest Sumba water is part of the Indonesian fisheries management region (WPP573). Marine fisheries resources are influenced by oceanographic phenomena such as an upwelling event. This study aims to describe characteristics of seasonal Ekman upwelling by analyzing oceanographic parameters from the validated INDESO model output (2008-2014). It shows that upwelling event in the study area occurs during the Southeast Monsoon period, which creates an Ekman drift of 0.26 Sv towards offshore. This transported water mass is then replaced by an upwelled vertical flow of sub-surface colder and nutrient-rich water at the velocity of the order of 10−4 m/s. Surface features of the upwelling event are seen from a minimum temperature (24.3 °C), sea level anomaly (0.34 m), but the maximum of chlorophyll-a (3.02 mg/m3). During this time, an uplifted isotherm of 25.5 °C is found from sub-surface to 10 m depth, but it is outcropped at the sea surface in the centre of upwelling area. Interestingly, during upwelling event, salinity stratification revealed an isohaline of 34.10 psu is much deeper at 40 m depth, and much fresher water mass from the Ombai Indonesian Throughflow water is dominant. Averaged temperature-based upwelling index between June-September is about 0.3 °C.

Arctic sea surface height maps from multi-altimeter combination

We present a new Arctic sea level anomaly dataset based on the combination of three altimeter missions using an optimal interpolation scheme. Measurements from SARAL/AltiKa, CryoSat-2 and Sentinel-3A are blended together, providing an unprecedented resolution for this type of product. Such high-resolution products are necessary to tackle some contemporaneous science questions in the basin. We use the adaptive retracker to process both open ocean and lead echoes on SARAL/AltiKa, thus removing the need to estimate a bias between open ocean and ice-covered areas. The usual processing approach, involving an empirical retracking algorithm on specular echoes, is applied on CryoSat-2 and Sentinel-3A synthetic aperture radar (SAR) mode echoes. SARAL/AltiKa also provides the baseline for the cross-calibration of CryoSat-2 and Sentinel-3A data. The final gridded fields cover all latitudes north of 50∘ N, on a 25 km EASE2 grid, with one grid every 3 d over 3 years from July 2016 to April 2019. When compared to tide gauge measurements available in the Arctic Ocean, the combined product exhibits a much better performance than mono-mission datasets with a mean correlation of 0.78 and a mean root-mean-square deviation (RMSd) of 5 cm. The effective temporal resolution of the combined product is 3 times better than a single mission analysis. This dataset can be downloaded from https://doi.org/10.24400/527896/a01-2020.001 (Prandi, 2020).

Across-shore Propagation of Subthermocline Eddies in the California Current System

Though subthermocline eddies (STEs) have often been observed in the world oceans, characteristics of STEs such as their patterns of generation and propagation are less understood. Here, the across-shore propagation of STEs in the California Current System (CCS) is observed and described using 13 years of sustained coastal glider measurements on three glider transect lines off central and southern California as part of the California Underwater Glider Network (CUGN). The across-shore propagation speed of anticyclonic STEs is estimated as 1.35-1.49 ± 0.33 cm s−1 over the three transects, Line 66.7, Line 80.0, and Line 90.0, close to the westward long first baroclinic Rossby wave speed in the region. Anticyclonic STEs are found with high salinity, high temperature, and low dissolved oxygen anomalies in their cores, consistent with transporting California Undercurrent water from the coast to offshore. Comparisons to satellite sea-level anomaly indicate that STEs are only weakly correlated to a sea surface height expression. The observations suggest that STEs are important for the salt balance and mixing of water masses across-shore in the CCS.

Seasonal M2 Internal Tides in the Arabian Sea

Internal tides play a crucial role in ocean mixing. To explore the seasonal features of mode-1 M2 internal tides in the Arabian Sea, we analyzed their propagation and energy distribution using along-track sea-level anomaly data collected by satellite altimeters. We identified four primary source regions of internal tides: Abd al Kuri Island, the Carlsberg Ridge, the northeastern Arabian Sea, and the Maldive Islands. The baroclinic signals that originate from Abd al Kuri Island propagate meridionally, whereas those originating from the west coast of India propagate southwestward. The strength and energy flux of the internal tides in the Arabian Sea exhibit significant seasonal and spatial variability. The internal tides generated during winter are more energetic and can propagate further than those generated in summer. Doppler shifting and horizontal variations in stratification can explain the differences in the internal tides’ seasonal distributions.

Sea-level variability and change along the Norwegian coast between 2003 and 2018 from satellite altimetry, tide gauges and hydrography

Sea-level variations in coastal areas can differ significantly from those in the nearby open ocean. Monitoring coastal sea-level variations is therefore crucial to understand how climate variability can affect the densely populated coastal regions of the globe. In this paper, we study the sea-level variability along the coast of Norway by means of in situ records, satellite altimetry data, and a network of eight hydrographic stations over a period spanning 16 years (from 2003 to 2018). At first, we evaluate the performance of the ALES-reprocessed coastal altimetry dataset by comparing it with the sea-level anomaly from tide gauges over a range of timescales, which include the long-term trend, the annual cycle and the detrended and deseasoned sea level anomaly. We find that coastal altimetry outperforms conventional altimetry products at most locations along the Norwegian coast. We later take advantage of the coastal altimetry dataset to perform a sea level budget along the Norwegian coast. We find that the thermosteric and the halosteric signals give a comparable contribution to the sea-level trend along the Norwegian coast, except for three, non-adjacent hydrographic stations, where salinity variations affect the sea-level trend more than temperature variations. We also find that the sea-level annual cycle is more affected by variations in temperature than in salinity, and that both temperature and salinity give a comparable contribution to the detrended and deseasoned sea-level along the entire Norwegian coast.

Arctic sea surface height maps from multi-altimeter combination

We present a new Arctic sea level anomaly dataset, based on the combination of three altimeter missions using an optimal interpolation scheme. Measurements from SARAL/AltiKa, CryoSat-2 and Sentinel-3A are blended together providing an unprecedented resolution for this type of products. The final gridded fields cover all latitudes north of 50° N, on a 25 km EASE2 grid, with one grid every three days over three years from July 2016 to April 2019. We use the Adaptive retracker to process both open ocean and lead echoes on SARAL/AltiKa thus removing the need to estimate a bias between open ocean an ice covered areas. SARAL/AltiKa also provides the baseline for the cross-calibation of CryoSat-2 and Sentinel-3A data. When compared to independent data, the combined product exhibits a much better performance than previously available datasets based on the analysis of a single mission.

The Regional Ice Ocean Prediction System v2: a pan-Canadian ocean analysis system using an online tidal harmonic analysis

Canada has the longest coastline in the world and includes diverse ocean environments, from the frozen waters of the Canadian Arctic Archipelago to the confluence region of Labrador and Gulf Stream waters on the east coast. There is a strong need for a pan-Canadian operational regional ocean prediction capacity covering all Canadian coastal areas in support of marine activities including emergency response, search and rescue, and safe navigation in ice-infested waters. Here we present the first pan-Canadian operational regional ocean analysis system developed as part of the Regional Ice Ocean Prediction System version 2 (RIOPSv2) running in operations at the Canadian Centre for Meteorological and Environmental Prediction (CCMEP). The RIOPSv2 domain extends from 26∘ N in the Atlantic Ocean through the Arctic Ocean to 44∘ N in the Pacific Ocean, with a model grid resolution that varies between 3 and 8 km. RIOPSv2 includes a multivariate data assimilation system based on a reduced-order extended Kalman filter together with a 3D-Var bias correction system for water mass properties. The analysis system assimilates satellite observations of sea level anomaly and sea surface temperature, as well as in situ temperature and salinity measurements. Background model error is specified in terms of seasonally varying model anomalies from a 10-year forced model integration, allowing inhomogeneous anisotropic multivariate error covariances. A novel online tidal harmonic analysis method is introduced that uses a sliding-window approach to reduce numerical costs and allow for the time-varying harmonic constants necessary in seasonally ice-infested waters. Compared to the Global Ice Ocean Prediction System (GIOPS) running at CCMEP, RIOPSv2 also includes a spatial filtering of model fields as part of the observation operator for sea surface temperature (SST). In addition to the tidal harmonic analysis, the observation operator for sea level anomaly (SLA) is also modified to remove the inverse barometer effect due to the application of atmospheric pressure forcing fields. RIOPSv2 is compared to GIOPS and shown to provide similar innovation statistics over a 3-year evaluation period. Specific improvements are found near the Gulf Stream for all model fields due to the higher model grid resolution, with smaller root mean squared (rms) innovations for RIOPSv2 of about 5 cm for SLA and 0.5 ∘C for SST. Verification against along-track satellite observations demonstrates the improved representation of mesoscale features in RIOPSv2 compared to GIOPS, with increased correlations of SLA (0.83 compared to 0.73) and reduced rms differences (12 cm compared to 14 cm). While the RIOPSv2 grid resolution is 3 times higher than GIOPS, the power spectral density of surface kinetic energy provides an indication that the effective resolution of RIOPSv2 is roughly double that of the global system (35 km compared to 66 km). Observations made as part of the Year of Polar Prediction (2017–2019) provide a rare glimpse at errors in Arctic water mass properties and show average salinity biases over the upper 500 m of 0.3–0.4 psu in the eastern Beaufort Sea in RIOPSv2.

The new Black Sea Reanalysis System within CMEMS

<p>Ocean reanalyses are becoming increasingly important to reconstruct and provide an overview of the ocean state from the past to the present-day. These products require advanced scientific methods and techniques to produce a more accurate ocean representation. In the scope of the Copernicus Marine Environment Monitoring Service (CMEMS), a new Black Sea (BS) reanalysis, BS-REA (BSE3R1 system), has been produced by using an advanced variational data assimilation method to combine the best available observations with a state-of-the-art ocean general circulation model. The hydrodynamical model is based on Nucleus for European Modeling of the Ocean (NEMO, v3.6), implemented for the BS domain with horizontal resolution of 1/27° x 1/36°, and 31 unevenly distributed vertical levels. NEMO is forced by atmospheric surface fluxes computed via bulk formulation and forced by ECMWF ERA5 atmospheric reanalysis product. At the surface, the model temperature is relaxed to daily objective analysis fields of sea surface temperature from CMEMS SST TAC. The exchange with Mediterranean Sea is simulated through relaxation of the temperature and salinity near Bosporus toward a monthly climatology computed from a high-resolution multi-year simulation, and the barotropic Bosporus Strait transport is corrected to balance the variations of the freshwater flux and the sea surface height measured by multi-satellite altimetry observations. A 3D-Var ocean data assimilation scheme (OceanVar) is used to assimilate sea level anomaly along-track observations from CMEMS SL TAC and available in situ vertical profiles of temperature and salinity from both SeaDataNet and CMEMS INS TAC products. Comparisons against the previous Black Sea reanalysis (BSE2R2 system) show important improvements for temperature and salinity, such that errors have significantly decreased (about 50%). Temperature fields present a continuous warming in the layer between 25-150 m, within which there is the presence of the Black Sea Cold Intermediate Layer (CIL). SST exhibits a positive bias and relatively higher root mean square error (RMSE) values are present in the summer season. Spatial maps of sea level anomaly reveal the largest RMSE close to the shelf areas, which are related to the mesoscale activity along the Rim current. The BS-REA catalogue includes daily and monthly means for 3D temperature, salinity, and currents and 2D sea surface height, bottom temperature, mixed layer fields, from Jan 1993 to Dec 2019.  The BSE3R1 system has produced very accurate estimates which makes it very suitable for assessing more realistic climate trends and indicators for important ocean properties.</p>

New insights into the ice-covered Southern Ocean circulation from multi-altimeter combination.

<p>Subtle changes in the Southern Ocean subpolar ocean circulation patterns can lead to major changes in the global overturning circulation, as well as for floating ice-shelves with critical implications for global sea-level. It is therefore crucial to carefully understand Antarctic polar ocean circulation, but the lack of ocean observation has considerably blocked our advance in this field in the past.</p><p>In this study we benefit from a new high-resolution Sea Level Anomaly (SLA) product that has been specifically constructed to document sea-level in the ice-covered Southern Ocean. This product combines up to 3 satellite altimetry missions to map SLA data daily on an equal-area grid, including the ice-covered areas of the ocean from 2013 to 2019.</p><p>Results suggest that we can map ocean features with unprecedented resolution for the region. We characterize the main features of the subpolar Southern Ocean SLA and circulation seasonal cycle, being composed of three main modes of variability, significantly impacting the dynamics of the region. We explore how they are linked with atmospheric and sea-ice forcings. Dynamics at smaller scales are investigated, by identifying the properties of mesoscale variability where possible.</p>