Due to the low spatial resolution of sea surface temperature (T_S) retrieval by real aperture microwave radiometers, in this study, an iterative retrieval method that minimizes the differences between brightness temperature (T_B) measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer, temporarily named 1D-SAMR. Regarding the configuration of the radiometer, an angular resolution of 0.43° was reached by theoretical calculation. Experiments on sea surface temperature retrieval were carried out with ideal parameters; the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters. In the case of no auxiliary parameter errors, the greatest error in retrieved sea surface temperature is obtained at low T_S scene (i.e., 0.710 6 K for the incidence angle of 35° under the radiometer calibration accuracy of 0.5 K). While errors on auxiliary parameters are assumed to follow a Gaussian distribution, the greatest error on retrieved sea surface temperature was 1.330 5 K at an incidence angle of 65° in poorly known sea surface wind speed (W) (the error on W of 1.0 m/s) over high W scene, for the radiometer calibration accuracy of 0.5 K.

This study compares the seasonal and interannual-to-decadal variability in the strength and position of the Kuroshio Extension front (KEF) using high-resolution satellite-derived sea surface temperature (SST) and sea surface height (SSH) data. Results show that the KEF strength has an obvious seasonal variation that is similar at different longitudes, with a stronger (weaker) KEF during the cold (warm) season. However, the seasonal variation in the KEF position is relatively weak and varies with longitude. In contrast, the low-frequency variation of the KEF position is more distinct than that of the KEF strength even though they are well correlated. On both seasonal and interannual-to-decadal time scales, the western part of the KEF (142°–144°E) has the greatest variability in strength, while the eastern part of the KEF (149°–155°E) has the greatest variability in position. In addition, the relationships between wind-forced Rossby waves and the low-frequency variability in the KEF strength and position are also discussed by using the statistical analysis methods and a wind-driven hindcast model. A positive (negative) North Pacific Oscillation (NPO)-like atmospheric forcing generates positive (negative) SSH anomalies over the central North Pacific. These oceanic signals then propagate westward as Rossby waves, reaching the KE region about three years later, favoring a strengthened (weakened) and northward (southward)-moving KEF.

Atmospheric moisture transport plays an important role in latent heat release and hydrologic interactions in the Arctic. In recent years, with the rapid decline in sea ice, this transport has changed. Here, we calculated the vertically integrated atmospheric moisture meridional transport (AMTv) from two global reanalysis datasets, from 1979–2015, and found moisture pathways into the central Arctic. Four stable pathways showed an occurrence frequency greater than 70%, and these pathways exhibited a perennial seasonal pattern in the atmosphere above the Laptev Sea Pathway (LSP), Canadian Arctic Archipelago Pathway (CAAP), both sides of the Greenland plateau. Another seasonal pathway appeared above the east of the Chukchi Sea (CSP) during the melting/freezing months (March to September). Through these pathways, AMTv contributed a total moisture exchange of 60%–80%—averaged over a 75°N circle—and focused on the low troposphere. Transports across the LSP, CSP and CAAP pathways likely create an enclosed moisture route. Meridional moisture fluxes are intensified in the Pacific sector of Arctic (PSA), especially during melting/freezing months. AMTv interannual variabilities are illustrated mainly in the Laptev Sea and the east Greenland pathway. Results indicate that accompanying a tendency for a stronger Beaufort Sea High in this sea level pressure field, AMTv through PSA pathways, switched from output to input, and approximately 960 km³ of equivalent liquid water was transferred into the central Arctic during each decade. The detrended AMTv increment is highly correlated with the rapid decline of old ice areas (correlation coefficient is –0.78) for their synchronous fluctuations in the 1980s and the last decade.

A new paradigm for ship detection in polarimetric synthetic aperture radar (Pol-SAR) image is presented. We firstly utilize the scattering similarity parameters to investigate the differences of scattering mechanism between ships and sea clutter. Based on these differences, we propose a novel ship detection metric, denoted as the scattering similarity based metric (SSM), to conduct ship detection task. The distribution model of SSM metric is investigated and modeled by kernel density estimation (KDE). Based on the statistical distribution, an adaptive constant false alarm rate (CFAR) detection scheme is implemented. We compare the proposed SSM with two classic polarimetric metrics, i.e., the polarimetric cross-entropy (PCE) and the reflection symmetry metric (RSM). The experimental results conducted on C-band RADARSAT-2 Pol-SAR data demonstrate the feasibility and advantage of the proposed SSM metric both in sea clutter modeling and in ship detection.

The present study reveals the fact that the relationship between the spring (April–May) North Atlantic Oscillation (NAO) and the following summer (June–September) tropical cyclone (TC) genesis frequency over the western North Pacific (WNP) during the period of 1950–2018 was not stationary. It is shown that the relationship between the two has experienced a pronounced interdecadal shift, being weak and insignificant before yet strong and statistically significant after the early 1980s. Next we compare the spring NAO associated dynamic and thermodynamic conditions, sea surface temperature (SST) anomalies, and atmospheric circulation processes between the two subperiods of 1954–1976 and 1996–2018, so as to illucidate the possible mechanism for this interdecadal variation in the NAO-TC connection. During the latter epoch, when the spring NAO was positive, enhanced low-level vorticity, reduced vertical zonal wind shear, intensified vertical velocity and increased middle-level relative humidity were present over the WNP in the summer, which is conducive to the genesis of WNP TCs. When the spring NAO is negative, the dynamic and thermodynamic factors are disadvantageous for the summertime TC formation and development over the WNP. The results of further analysis indicate that the persistence of North Atlantic tri-pole SST anomalies from spring to the subsequent summer induced by the spring NAO plays a fundamental role in the linkage between the spring NAO and summer atmospheric circulation. During the period of 1996–2018, a remarkable eastward propagating wave-train occurred across the northern Eurasian continent, forced by the anomalous SST tri-pole in the North Atlantic. The East Asian jet flow became greatly intensified, and the deep convection in the tropics was further enhanced via the changes of the local Hadley circulation, corresponding to a positive spring NAO. During the former epoch, the spring NAO-induced tri-pole SST anomalies in the North Atlantic were non-existent, and the related atmospheric circulation anomalies were extremely weak, thereby leading to the linkage between spring NAO and WNP TC genesis frequency in the following summer being insignificant.

In shallow coastal regions where water surface fluctuations are non-negligible compared to the mean water depth, the use of sigma coordinates allows the calculation of residual velocity around the mean water surface level. Theoretical analysis and generic numerical experiments were conducted to understand the physical meaning of the residual velocities at sigma layers in breadth-averaged tidal channels. For shallow water waves, the sigma layers coincide with the water wave surfaces within the water column such that the Stokes velocity and its vertical and horizontal components can be expressed in discrete forms using the sigma velocity. The residual velocity at a sigma layer is the sum of the Eulerian velocity and the vertical component of the Stokes velocity at the mean depth of the sigma layer and, therefore, can be referred to as a semi-Lagrangian residual velocity. Because the vertical component of the Stokes velocity is one order of magnitude smaller than the horizontal component, the sigma residual velocity approximates the Eulerian residual velocity. The residual transport velocity at a sigma layer is the sum of the sigma residual velocity and the horizontal component of the Stokes velocity and approximates the Lagrangian residual velocity in magnitude and direction, but the two residual velocities are not conceptually the same.

The study of the characteristics of internal solitary waves happened in the Malacca Strait is an urgent problem for submarine, ship navigation and marine engineering. Based on SAR remote sensing data obtained from the high spatial resolution Sentinel-1 and GF-3, the internal solitary wave characteristics of the Malacca Strait are investigated. By use of 20 Sentinel-1 SAR images from June 2015 to December 2016 and 24 GF-3 images from April 2018 to March 2019, the spatial distribution characteristics of internal solitary wave s are statistically analyzed. It is found that the internal solitary waves are usually in the form of wave packets and single solitary waves, and the maximum crest length of the leading wave can reach 39 km. The amplitude and group velocity of internal solitary wave s can be calculated by the inversion model of high-order nonlinear Schrodinger (NLS) equation, and the calculated amplitude of the internal solitary wave s and the propagation group velocity of the wave packets range from 4.7 m to 23.9 m and 0.12 m/s to 0.40 m/s, respectively. The range of phase velocity of single internal solitary waves obtained by KdV equation is 0.26 m/s to 0.60 m/s. In general, the amplitude and the velocity of internal solitary wave s in Malacca strait are related to the topography.

The correlation of ambient noise with wind speed, and the depth dependence of ambient noise are both investigated, where the ocean noise data were recorded by a vertical line array in the northern South China Sea. It is shown that the correlation coefficients increase with increasing hydrophone depth during typhoon periods when the frequency ≥ 250 Hz, which opposes the generally accepted knowledge that the correlation coefficients of noise level and wind speed decrease with increasing depth during non-typhoon periods. Particularly at frequencies of 250 Hz, 315 Hz and 400 Hz, the correlation coefficients increase by more than 0.05 at depths ranging from 155 m to 875 m. At the three frequencies, the average noise levels also increase with increasing depth during typhoon periods. It is suggested that these differences are attributed to the wind-generated noise in shallow waters and the effect of “downslope enhancement” to sound propagation. During typhoon periods, the surf breaking and surf beat upon the shores and reefs are strengthened, and the source levels are increased. The wind-generated noise in shallow waters interacts with the downslope sea floor, with the noise-depth distribution changed by a “downslope enhancement” effect promoting noise propagation.

Sea-water-level (SWL) prediction significantly impacts human lives and maritime activities in coastal regions, particularly at offshore locations with shallow water levels. Long-term SWL forecasts, which are conventionally obtained via harmonic analysis, become ineffective when nonperiodic meteorological events predominate. Artificial intelligence combined with other data-processing methods can effectively forecast highly nonlinear and nonstationary inflow patterns by recognizing historical relationships between input and output. These techniques are considerably useful in time-series data predictions. This paper reports the development of a hybrid model to realize accurate multihour SWL forecasting by combining an adaptive neuro-fuzzy inference system (ANFIS) with wavelet decomposition while using sea-level anomaly (SLA) and wind-shear-velocity components as inputs. Numerous wavelet-ANFIS (WANFIS) models have been tested using different inputs to assess their applicability as alternatives to the artificial neural network (ANN), wavelet ANN (WANN), and ANFIS models. Different error definitions have been used to evaluate results, which indicate that integrated wavelet-decomposition and ANFIS models improve the accuracy of SWL prediction and that the inputs of SLA and wind-shear velocity exhibit superior prediction capability compared to conventional SWL-only models.

Coastal vegetation is capable of decreasing wave run-up. However, because of regrowth, decay or man-made damage, coastal vegetation is always distributed in patches, and its internal distribution is often non-uniform. This study investigates the effects of patchy vegetation on solitary wave run-up by using a numerical simulation. A numerical model based on fully nonlinear Boussinesq equations is established to simulate the wave propagation on a slope with patchy vegetation. By using the model, the process of solitary wave run-up attenuation due to patchy vegetation is numerically analysed. The numerical results reveal that patchy vegetation can considerably attenuate the wave run-up in an effective manner. In addition, high-density patched vegetation can attenuate the solitary wave run-up more effectively than low-density patched vegetation can. For the same density, patchy vegetation with a uniform distribution has a better attenuation effect on wave run-up compared to that of patchy vegetation with a non-uniform distribution.