To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model (FIO-ESM) climate forecast system, satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) are assimilated into this system, using the method of localized error subspace transform ensemble Kalman filter (LESTKF). Five-year (2014–2018) Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation. Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent. All the biases of ice concentration, ice cover, ice volume, and ice thickness can be reduced dramatically through ice concentration and thickness assimilation. The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system. The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation. Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-to-seasonal (S2S) Prediction Project, FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast. Since sea ice thickness in the PIOMAS is updated in time, it is a good choice for data assimilation to improve sea ice prediction skills in the near-real-time Arctic sea ice seasonal prediction.

The significant wave height (SWH) is one of the main parameters that describe wave characteristics and is widely used in wave research fields. Wave parameters measured by radar are influenced by the offshore distance and sea state. Validation and calibration are of great significance for radar data applications. The nadir beam of surface wave investigation and monitoring (SWIM) detects the global-ocean-surface SWH. To determine the product quality of SWIM SWH, this paper carried out time-space matching between SWIM and buoy data. The data qualities were evaluated under different offshore distances and sea states. An improved calibration method was proposed based on sea state segmentation, which considered the distribution of the point collocation numbers in various sea states. The results indicate that (1) the SWIM SWH accuracy at offshore distances greater than 50 km is higher than that at distances less than 50 km, with an root mean squared error (RMSE) of 0.244 4 m, scatter index (SI) of 0.115 6 and relative error (RE) of 9.97% at distances greater than 50 km and those of 0.446 0 m, 0.223 0 and 18.66% at distances less than 50 km. (2) SWIM SWH qualities are better in moderate and rough sea states with RMSEs of 0.284 8 m and 0.316 9 m but are worse in slight and very rough sea states. (3) The effect of the improved calibration method is superior to the traditional method in each sea state and overall data, and the RMSE of SWIM SWH is reduced from the raw 0.313 5 m to 0.285 9 m by the traditional method and 0.198 2 m by the improved method. The influence of spatiotemporal window selection on data quality evaluation was analyzed in this paper. This paper provides references for SWIM SWH product applications.

Arctic absolute sea level variations were analyzed based on multi-mission satellite altimetry data and tide gauge observations for the period of 1993–2018. The range of linear absolute sea level trends were found −2.00 mm/a to 6.88 mm/a excluding the central Arctic, positive trend rates were predominantly located in shallow water and coastal areas, and negative rates were located in high-latitude areas and Baffin Bay. Satellite-derived results show that the average secular absolute sea level trend was (2.53±0.42) mm/a in the Arctic region. Large differences were presented between satellite-derived and tide gauge results, which are mainly due to low satellite data coverage, uncertainties in tidal height processing and vertical land movement (VLM). The VLM rates at 11 global navigation satellite system stations around the Arctic Ocean were analyzed, among which 6 stations were tide gauge co-located, the results indicate that the absolute sea level trends after VLM corrected were of the same magnitude as satellite altimetry results. Accurately calculating VLM is the primary uncertainty in interpreting tide gauge measurements such that differences between tide gauge and satellite altimetry data are attributable generally to VLM.

Mesoscale eddies, which are mainly caused by baroclinic effects in the ocean, are common oceanic phenomena in the Northwest Pacific Ocean and play very important roles in ocean circulation, ocean dynamics and material energy transport. The temperature structure of mesoscale eddies will lead to variations in oceanic baroclinity, which can be reflected in the sea level anomaly (SLA). Deep learning can automatically extract different features of data at multiple levels without human intervention, and find the hidden relations of data. Therefore, combining satellite SLA data with deep learning is a good way to invert the temperature structure inside eddies. This paper proposes a deep learning algorithm, eddy convolution neural network (ECN), which can train the relationship between mesoscale eddy temperature anomalies and sea level anomalies (SLAs), relying on the powerful feature extraction and learning abilities of convolutional neural networks. After obtaining the temperature structure model through ECN, according to climatic temperature data, the temperature structure of mesoscale eddies in the Northwest Pacific is retrieved with a spatial resolution of 0.25° at depths of 0–1 000 m. The overall accuracy of the ECN temperature structure is verified using Argo profiles at the locations of cyclonic and anticyclonic eddies during 2015–2016. Taking 10% error as the acceptable threshold of accuracy, 89.64% and 87.25% of the cyclonic and anticyclonic eddy temperature structures obtained by ECN met the threshold, respectively.

In general, a mesoscale cyclonic (anticyclonic) eddy has a colder (warmer) core, and it is considered as a cold (warm) eddy. However, recently research found that there are a number of “abnormal” mesoscale cyclonic (anticyclonic) eddies associated with warm (cold) cores in the South China Sea (SCS). These “abnormal” eddies pose a challenge to previous works on eddy detection, characteristic analysis, eddy-induced heat and salt transports, and even on mesoscale eddy dynamics. Based on a 9-year (2000–2008) numerical modelling data, the cyclonic warm-core eddies (CWEs) and anticyclonic cold-core eddies (ACEs) in the SCS are analyzed. This study found that the highest incidence area of the “abnormal” eddies is the northwest of Luzon Strait. In terms of the eddy snapshot counting method, 8 620 CWEs and 9 879 ACEs are detected, accounting for 14.6% and 15.8% of the total eddy number, respectively. The size of the “abnormal” eddies is usually smaller than that of the “normal” eddies, with the radius only around 50 km. In the generation time aspect, they usually appear within the 0.1–0.3 interval in the normalized eddy lifespan. The survival time of CWEs (ACEs) occupies 16.3% (17.1%) of the total eddy lifespan. Based on two case studies, the intrusion of Kuroshio warm water is considered as a key mechanism for the generation of these “abnormal” eddies near the northeastern SCS.

Latent and sensible heat fluxes based on observations from a Black Pearl wave glider were estimated along the main stream of the Kuroshio Current from the East China Sea to the east coast of Japan, from December 2018 to January 2019. It is found that the data obtained by the wave glider were comparable to the sea surface temperature data from the Operational Sea Surface Temperature and Sea Ice Analysis and the wind field data from WindSat. The Coupled Ocean Atmosphere Response Experiment 3.0 (COARE 3.0) algorithm was used to calculate the change in air-sea turbulent heat flux along the Kuroshio. The averaged latent heat flux (LHF) and sensible heat flux (SHF) were 235 W/m² and 134 W/m², respectively, and the values in the Kuroshio were significant larger than those in the East China Sea. The LHF and SHF obtained from Objectively Analyzed Air-Sea Fluxes for the Global Oceans (OAFlux) were closer to those measured by the wave glider than those obtained from National Centers for Environmental Prediction (NCEP) reanalysis products. The maximum deviation occurred in the East China Sea and the recirculation zone of the Kuroshio (deviation of SHF >200 W/m²; deviation of LHF >400 W/m²). This indicates that the NCEP and OAFlux products have large biases in areas with complex circulation. The wave glider has great potential to observe air-sea heat fluxes with a complex circulation structure.

Arctic sea ice area and thickness have declined dramatically during the recent decades. Sea ice physical and mechanical properties become increasingly important. Traditional methods of studying ice mechanical parameters such as ice-coring cannot realize field test and long-term observation. A new principle of measuring mechanical properties of ice using ultrasonic was studied and an ultrasonic system was proposed to achieve automatic observation of ice mechanical parameters (Young’s modulus, shear modulus and bulk modulus). The ultrasonic system can measure the ultrasonic velocity through ice at different temperature, salinity and density of ice. When ambient temperature decreased from 0°C to −30°C, ultrasonic velocity and mechanical properties of ice increased, and vice versa. The shear modulus of the freshwater ice and sea ice varied from 2.098 GPa to 2.48 GPa and 2.927 GPa to 4.374 GPa, respectively. The bulk modulus of freshwater ice remained between 3.074 GPa and 4.566 GPa and the sea ice bulk modulus varied from 1.211 GPa to 3.089 GPa. The freshwater ice Young’s modulus kept between 5.156 GPa and 6.264 GPa and sea ice Young’s modulus varied from 3.793 GPa to 7.492 GPa. The results of ultrasonic measurement are consistent with previous studies and there is a consistent trend of mechanical modulus of ice between the process of ice temperature rising and falling. Finally, this ultrasonic method and the ultrasonic system will help to achieve the long-term observation of ice mechanical properties of ice and improve accuracy of sea ice models.

With climate change and rising sea levels, the coastal zone’s flood risk is deteriorating. Previous researches have shown a gradually degrading capacity of traditional hard engineering structures (e.g., seawall, dikes) on flood mitigation due to problems such as land subsidence and insufficient maintenance. To remedy the defects, the “building with nature concept” for coastal protection with saltmarshes was examined by combining field measurements and numerical simulations. The advantages of saltmarsh over traditional seawall on flood protection was demonstrated from the perspective of both flood area mitigation and economic gain, based on scenario simulations. Results show that tidal wetlands are essential in mitigating significant wave heights (H_s) and current velocities even during storm conditions. The storm wave and current velocity reduction ratio ($R{R}_{{\rm{w}}}$ and $R{R}_{{\rm{c}}}$) by saltmarshes on Chongming Dongtan Shoal (CMDS) during Typhoon 9711 is approximately 11% and 51%, respectively. The wave and current mitigation by Scirpus mariqueter are more efficient than Spartina alterniflora and Phragmites australis during measurements in 2010, which were approximately 0.3 m and 0.2 m/s, 0.125 m and 0.155 m/s, 0.086 m and 0.128 m/s per kilometer width, respectively. The summer saltmarsh area 54.2 km² on CMDS protects approximately 32 km² land area behind the seawall from being flooded, equivalent to the seawall heightening of approximately 0.42 m on equivalent flood mitigation. The performance of cost-and-benefit analysis shows a relatively higher (by 3%–7%) net present value (NPV) and a higher (by 1.5 times) benefit-cost ratio (BC) of nature-based solution (i.e., saltmarsh restoration) compared with traditional hard engineering solution (i.e., seawall construction). Thus, building seawall with nature, such as a hybrid flood protection measure, should be implemented in the future coastal redesign and maintenance.

Over the past decades, sea ice in the polar regions has been significantly affecting local and even hemispheric climate through a positive ice albedo feedback mechanism. The role of fast ice, as opposed to drift ice, has not been well-studied due to its relatively small coverage over the earth. In this paper, the optical properties and surface energy balance of land fast ice in spring are studied using in situ observations in Barrow, Alaska. The results show that the albedo of the fast ice varied between 0.57 and 0.85 while the transmittance increased from 1.3×10⁻³ to 4.1×10⁻³ during the observation period. Snowfall and air temperature affected the albedo and absorbance of sea ice, but the transmittance had no obvious relationship with precipitation or snow cover. Net solar shortwave radiation contributes to the surface energy balance with a positive 99.2% of the incident flux, with sensible heat flux for the remaining 0.8%. Meanwhile, the ice surface loses energy through the net longwave radiation by 18.7% of the total emission, while the latent heat flux accounts for only 0.1%. Heat conduction is also an important factor in the overall energy budget of sea ice, contributing 81.2% of the energy loss. Results of the radiative transfer model reveal that the spectral transmittance of the fast ice is determined by the thickness of snow and sea ice as well as the amount of inclusions. As major inclusions, the ice biota and particulates have a significant influence on the magnitude and distribution of the spectral transmittance. Based on the radiative transfer model, concentrations of chlorophyll and particulate in the fast ice are estimated at 5.51 mg/m² and 95.79 g/m², which are typical values in the spring in Barrow.

In conventional marine seismic exploration data processing, the sea surface is usually treated as a horizontal free boundary. However, the sea surface is affected by wind and waves and there often exists dynamic small-range fluctuations. These dynamic fluctuations will change the energy propagation path and affect the final imaging results. In theoretical research, different sea surface conditions need to be described, so it is necessary to study the modeling method of dynamic undulating sea surface. Starting from the commonly used sea surface mathematical simulation methods, this paper mainly studies the realization process of simple harmonic wave and Gerstner wave sea surface simulation methods based on ocean wave spectrum, and compares their advantages and disadvantages. Aiming at the shortcomings of the simple harmonic method and Gerstner method in calculational speed and sea surface simulation effect, a method based on wave equation and using dynamic boundary conditions for sea surface simulation is proposed. The calculational speed of this method is much faster than the commonly used simple harmonic method and Gerstner wave method. In addition, this paper also compares the new method with the more commonly used higher-order spectral methods to show the characteristics of the improved wave equation method.