Yijun He

A new method to retrieve significant wave height from X-band marine radar image sequences

A new method is proposed to retrieve significant wave height (SWH) from X-band marine radar image sequences. To reduce the inhomogeneity of the nearshore wave field, the principal component (PC) of the radar image sequence is extracted by empirical orthogonal function (EOF) analysis. To measure the information contained in each PC, the Shannon entropy is introduced after the PC is normalized. Based on the information contained in the wave field, a linear relationship is established to retrieve the SWH from the Shannon entropy of the PC. The method is validated by comparison with measurements from in situ buoys: the root mean square error between the SWH measured by a buoy and the retrieved value is 0.22 m, while the corresponding bias and correlation coefficient are 0.01 m and 0.92, respectively. The physical meanings of different EOF modes decomposed from the wave field are also discussed.

Seasonal and Interannual Variability of Satellite-Derived Chlorophyll-a (2000–2012) in the Bohai Sea, China

Knowledge of the chlorophyll-a dynamics and their long-term changes is important for assessing marine ecosystems, especially for coastal waters. In this study, the spatial and temporal variability of sea surface chlorophyll-a concentration (Chl-a) in the Bohai Sea were investigated using 13-year (2000–2012) satellite-derived products from MODIS and SeaWiFS observations. Based on linear regression analysis, the results showed that the entire Bohai Sea experienced an increase in Chl-a on a long-term scale, with the largest increase in the central Bohai Sea and the smallest increase in the Bohai strait. Distinct seasonal patterns of Chl-a existed in different sub-regions of the Bohai Sea. A long-lasting Chl-a peak was observed from May to September in coastal waters (Liaodong bay, Qinhuangdao coast, and Bohai bay) and the central Bohai Sea, whereas Laizhou bay had relatively low Chl-a in early summer. In the Bohai strait, two pronounced Chl-a peaks occurred in March and September, but the lowest Chl-a was in summer. This pattern was quite different from those in other regions of the Bohai Sea. The water column condition (stratified or mixed) was likely an important physical factor that affects the seasonal pattern of Chl-a in the Bohai Sea. Meanwhile, increased human activity (e.g., river discharge) played a significant role in changing the Chl-a distribution in both coastal waters and the central Bohai Sea, especially in summer. The increasing trend of Chl-a in the Bohai Sea might be attributed to the increase in nutrient contents from riverine inputs. The Chl-a dynamics documented in this study provide basic knowledge for the future exploration of marine biogeochemical processes and ecosystem evolution in the Bohai Sea.

Study of Ocean Waves Measured by Collocated HH and VV Polarized X-Band Marine Radars

The significant wave height (SWH) retrieved from collocated HH and VV polarized X-band marine radars under different sea states is studied. The SWH are retrieved from different principal components of X-band marine radar image sequence. As compared with the SWH measured by a buoy, the root-mean-square errors of the SWH are 0.32–0.45u2009m for VV polarization, and they are 0.37–0.60u2009m for HH polarization. At the wind speeds of 0–5u2009m/s, the SWH can be derived from VV polarized radar images, while the backscatter of HH polarized radar is too weak to contain wave signals at very low wind speeds (~0–3u2009m/s). At the wind speeds of 5–18u2009m/s, the SWH retrieved from VV polarization coincide well with the SWH measured by the buoy, while the SWH retrieved from HH polarization correspond with the changes of the wind speed. At the wind speeds of 18–26u2009m/s, the influence of wave breaking on HH polarization is more important than that on VV polarization. This indicates that the imaging mechanisms of HH polarized X-band marine radar are different from those of VV polarized X-band marine radar.

Upper Ocean Response to Typhoon Kalmaegi and Sarika in the South China Sea from Multiple-Satellite Observations and Numerical Simulations

We investigated ocean surface and subsurface physical responses to Typhoons Kalmaegi and Sarika in the South China Sea, utilizing synergistic multiple-satellite observations, in situ measurements, and numerical simulations. We found significant typhoon-induced sea surface cooling using satellite sea surface temperature (SST) observations and numerical model simulations. This cooling was mainly caused by vertical mixing and upwelling. The maximum amplitudes were 6 °C and 4.2 °C for Typhoons Kalmaegi and Sarika, respectively. For Typhoon Sarika, Argo temperature profile measurements showed that temperature response beneath the surface showed a three-layer vertical structure (decreasing-increasing-decreasing). Satellite salinity observations showed that the maximum increase of sea surface salinity (SSS) was 2.2 psu on the right side of Typhoon Sarika’s track, and the maximum decrease of SSS was 1.4 psu on the left. This SSS seesaw response phenomenon is related to the asymmetrical rainfall on both sides of the typhoon track. Acoustic Doppler Current Profilers measurements and numerical simulations both showed that subsurface current velocities rapidly increased as the typhoon passed, with peak increases of up to 1.19 m/s and 1.49 m/s. Typhoon-generated SST cooling and current velocity increases both exhibited a rightward bias associated with a coupling between typhoon wind-stress and mixed layer velocity.

Ku-Band Sea Surface Radar Backscatter at Low Incidence Angles under Extreme Wind Conditions

This paper reports Ku-band normalized radar cross section (NRCS) at low incidence angles ranging from 0° to 18° and in the wind speed range from 6 to 70 m/s. The precipitation radar onboard the tropical rainfall measuring mission and Jason-1 and 2 have provided 152 hurricanes observations between 2008 and 2013 that were collocated with stepped-frequency microwave radiometer measurements. It is found that the NRCS decreases with increasing incidence angle. The decrease is more dramatic in the 40–70 m/s range of wind speeds than in the 6–20 m/s range, indicating that the NRCS is very sensitive to low incidence angles under extreme wind conditions and insensitive to the extreme wind speed. Consequently, the sea surface appears relatively “smooth” to Ku-band electromagnetic microwaves. This phenomenon validates the observed drag coefficient reduction under extreme wind conditions, from a remote sensing viewpoint. Using the NRCS dependence on incidence angle under extreme wind conditions, we also present an empirical linear relationship between NRCS and incidence angles, which may assist future-satellites missions operating at small incidence angles to measure sea surface wind and wave field.

Using Landsat 8 data to estimate suspended particulate matter in the Yellow River estuary

The distribution of suspended particulate matter (SPM) and its variations in estuary regions are key to promoting carbon, oxygen, and nutrient cycling in coastal regions and nearby seas. This study presents SPM estimations for the Yellow River estuary from Landsat 8 Operational Land Imager (L8/OLI) data from 2013 to 2016. L8/OLI-measured remote sensing reflectance (Rrs) was cross-validated with Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, and SPM concentrations calculated from the tuned retrieval model were validated with in situ observations. The validation shows that L8/OLI can provide reasonably Rrs, which can be used to quantify SPM distributions and variations in the Yellow River estuary. Three year averaged SPM maps show that highly turbid waters are mostly found in an ovate area surrounding the mouth of the Yellow River. The corresponding area proportion is less than 30%, with SPM concentrations greater than 100 g m−3. High variations of SPM distributions are consistent with high SPM concentrations, and vice versa. Significant difference is observed between dry and wet seasons. Higher SPM in the dry season is observed both in range and intensity compared to those of the wet season. Furthermore, multiyear averaged SPM distributions with high concentrations are mainly attributable to currents. Significant seasonal variations are mainly controlled by sediment resuspension processes driven by wind-wave forces. Due to human interventions, seasonal variability in river runoff and sediment discharge from the Yellow River has decreased in recent years. Accordingly, seasonal variability in SPM distributions in the Yellow River estuary due to sediment discharge has decreased.

Remote‐Sensing Estimation of Phytoplankton Size Classes From GOCI Satellite Measurements in Bohai Sea and Yellow Sea

Phytoplankton size class (PSC), a measure of different phytoplankton functional and structural groups, is a key parameter to the understanding of many marine ecological and biogeochemical processes. In turbid waters where optical properties may be influenced by terrigenous discharge and nonphytoplankton water constituents, remote estimation of PSC is still a challenging task. Here based on measurements of phytoplankton diagnostic pigments, total chlorophyll a, and spectral reflectance in turbid waters of Bohai Sea and Yellow Sea during summer 2015, a customized model is developed and validated to estimate PSC in the two semienclosed seas. Five diagnostic pigments determined through high-performance liquid chromatography (HPLC) measurements are first used to produce weighting factors to model phytoplankton biomass (using total chlorophyll a as a surrogate) with relatively high accuracies. Then, a common method used to calculate contributions of microphytoplankton, nanophytoplankton, and picophytoplankton to the phytoplankton assemblage (i.e., Fm, Fn, and Fp) is customized using local HPLC and other data. Exponential functions are tuned to model the size-specific chlorophyll a concentrations (Cm, Cn, and Cp for microphytoplankton, nanophytoplankton, and picophytoplankton, respectively) with remote-sensing reflectance (Rrs) and total chlorophyll a as the model inputs. Such a PSC model shows two improvements over previous models: (1) a practical strategy (i.e., model Cp and Cn first, and then derive Cm as C-Cp-Cn) with an optimized spectral band (680 nm) for Rrs as the model input; (2) local parameterization, including a local chlorophyll a algorithm. The performance of the PSC model is validated using in situ data that were not used in the model development. Application of the PSC model to GOCI (Geostationary Ocean Color Imager) data leads to spatial and temporal distribution patterns of phytoplankton size classes (PSCs) that are consistent with results reported from field measurements by other researchers. While the applicability of the PSC model together with its parameterization to other optically complex regions and to other seasons is unknown, the findings of this study suggest that the approach to develop such a model may be extendable to other cases as long as local data are used to select the optimal band and to determine the model coefficients.

Vertical Structure Anomalies of Oceanic Eddies and Eddy-Induced Transports in the South China Sea

Using satellite altimetry sea surface height anomalies (SSHA) and Argo profiles, we investigated eddy’s statistical characteristics, 3-D structures, eddy-induced physical parameter changes, and heat/freshwater transports in the South China Sea (SCS). In total, 31,744 cyclonic eddies (CEs, snapshot) and 29,324 anticyclonic eddies (AEs) were detected in the SCS between 1 January 2005 and 31 December 2016. The composite analysis has uncovered that changes in physical parameters modulated by eddies are mainly confined to the upper 400 m. The maximum change of temperature (T), salinity (S) and potential density (σθ) within the composite CE reaches −1.5 °C at about 70 m, 0.1 psu at about 50 m, and 0.5 kg m−3 at about 60 m, respectively. In contrast, the maximum change of T, S and σθ in the composite AE reaches 1.6 °C (about 110 m), −0.1 psu (about 70 m), and −0.5 kg m−3 (about 90 m), respectively. The maximum swirl velocity within the composite CE and AE reaches 0.3 m s−1. The zonal freshwater transport induced by CEs and AEs is (373.6 ± 9.7)×103 m3 s−1 and (384.2 ± 10.8)×103 m3 s−1, respectively, contributing up to (8.5 ± 0.2)% and (8.7 ± 0.2)% of the annual mean transport through the Luzon Strait.

Ocean Wind and Current Retrievals Based on Satellite SAR Measurements in Conjunction with Buoy and HF Radar Data

A total of 168 fully polarimetric synthetic-aperture radar (SAR) images are selected together with the buoy measurements of ocean surface wind fields and high-frequency radar measurements of ocean surface currents. Our objective is to investigate the effect of the ocean currents on the retrieved SAR ocean surface wind fields. The results show that, compared to SAR wind fields that are retrieved without taking into account the ocean currents, the accuracy of the winds obtained when ocean currents are taken into account is increased by 0.2–0.3 m/s; the accuracy of the wind direction is improved by 3 – 4 ° . Based on these results, a semi-empirical formula for the errors in the winds and the ocean currents is derived. Verification is achieved by analysis of 52 SAR images, buoy measurements of the corresponding ocean surface winds, and high-frequency radar measurements of ocean currents. Results of the comparisons between data obtained by the semi-empirical formula and data measured by the high-frequency radar show that the root-mean-square error in the ocean current speed is 12.32 cm/s and the error in the current direction is 6.32°.

Characterizing overwater roughness Reynolds number during hurricanes

The Reynolds number, which is the dimensionless ratio of the inertial force to the viscous force, is of great importance in the theory of hydrodynamic stability and the origin of turbulence. To investigate aerodynamically rough flow over a wind sea, pertinent measurements of wind and wave parameters from three data buoys during Hurricanes Kate, Lili, Ivan, Katrina, Rita, and Wilma are analyzed. It is demonstrated that wind seas prevail when the wind speed at 10xa0m and the wave steepness exceed 9xa0mxa0s−1 and 0.020, respectively. It is found that using a power law the roughness Reynolds number is statistically significantly related to the significant wave height instead of the wind speed as used in the literature. The reason for this characterization is to avoid any self-correlation between Reynolds number and the wind speed. It is found that although most values of