Brightness Temperature Model of Sea Foam Layer at L-band

Permittivity of a sea foam layer is very important in investigating ocean brightness temperature model. At microwave frequency, the Rayleigh method is developed to estimate the effective permittivity of the sea foam layer. To simplify the tedious calculation of sea foam effective permittivity at L band(1.4 GHz), Pade’ approximation is adopted to fit the sea foam effective permittivity computed by the Rayleigh method. With this fitting formula, a new brightness temperature model of sea foam layer defined by certain geophysical parameters, such as air volume fraction(AVF), sea surface temperature(SST), sea surface salinity(SSS) and thickness of foam layer d, is given. Furthermore, the sensitivities of the brightness temperature model to SST, SSS, d and AVF of a sea foam layer at L band are discussed. The sensitivities are ranked from most to least in the order:(1) d;(2) AVF;(3) SSS;(4) SST. This result indicates that the measurement errors of d and AVF have significant impacts on the retrievals of SSS and SST. With the experimental brightness temperature data, the SSS and AFV are retrieved by cost function.     

Retrieve sea surface salinity using principal component regression model based on SMOS satellite data

The sea surface salinity(SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity from Soil Moisture and Ocean Salinity(SMOS) satellite data. Based on the principal component regression(PCR) model, SSS can also be retrieved from the brightness temperature data of SMOS L2 measurements and Auxiliary data. 26 pair matchup data is used in model validation for the South China Sea(in the area of 4?–25?N, 105?–125?E). The RMSE value of PCR model retrieved SSS reaches 0.37 psu(practical salinity units) and the RMSE of SMOS SSS1 is 1.65 psu when compared with in-situ SSS. The corresponding Argo daily salinity data during April to June 2013 is also used in our validation with RMSE value 0.46 psu compared to 1.82 psu for daily averaged SMOS L2 products. This indicates that the PCR model is valid and may provide us with a good approach for retrieving SSS from SMOS satellite data.     

Application of nonlinear multi-channel algorithms for estimating sea surface temperature with NOAA-14 AVHRR data

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Surface sediment diatoms from the western Pacific marginal seas and their correlation to environmental variables

Diatom data of 192 surface sediment samples from the marginal seas in the western Pacific together with modern summer and winter sea surface temperature and salinity data were analyzed.The results of canonical correspondence analysis show that summer sea-surface salinity(SSS) is highly positively correlated with winter SSS and so is summer sea-surface temperature(SST) with winter SST.The correlations between SSSs and SSTs are less positively correlated,which may be due to interactions of regional current pa...     

Evaluation of the retrieval of total suspended matter concentration in Taihu Lake,China from CBERS-02B CCD

Remote sensing techniques is used to quantify the total suspended matter concentration (C _TSM). In this study, we used remotely sensed data to retrieve the C _TSM for the Taihu Lake, China, and developed an atmospheric correction algorithm especially for CBERS-02B CCD data. We simulated the remote sensing reflectance (R _rs) of CCD bands using in-situ observations made in a cruise over the Taihu Lake in autumn 2004, from which a retrieval model is established with simulated R _rs(830) and measured C _TSM. In addition, we applied the atmospheric correction algorithm and retrieval model to process the CCD data over the lake in 2008 and to retrieve the C _TSM. The RMS relative error between the C _TSM retrieved from MODIS and from the CCD images is about 42.9%, indicating that algorithms described in this paper can be used for the application of CCD data in monitoring the C _TSM distribution in the Taihu Lake.     

Effects of ration, temperature and body weight on metabolism in young black porgy

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Chaos particle swarm optimization combined with circular median filtering for geophysical parameters retrieval from Windsat

This paper established a geophysical retrieval algorithm for sea surface wind vector, sea surface temperature, columnar atmospheric water vapor, and columnar cloud liquid water from WindSat, using the measured brightness temperatures and a matchup database. To retrieve the wind vector, a chaotic particle swarm approach was used to determine a set of possible wind vector solutions which minimize the difference between the forward model and the WindSat observations. An adjusted circular median filtering function was adopted to remove wind direction ambiguity. The validation of the wind speed, wind direction, sea surface temperature, columnar atmospheric water vapor, and columnar liquid cloud water indicates that this algorithm is feasible and reasonable and can be used to retrieve these atmospheric and oceanic parameters. Compared with moored buoy data, the RMS errors for wind speed and sea surface temperature were 0.92 m s~(-1) and 0.88℃, respectively. The RMS errors for columnar atmospheric water vapor and columnar liquid cloud water were 0.62 mm and 0.01 mm, respectively, compared with F17 SSMIS results. In addition, monthly average results indicated that these parameters are in good agreement with AMSR-E results. Wind direction retrieval was studied under various wind speed conditions and validated by comparing to the Quik SCAT measurements, and the RMS error was 13.3?. This paper offers a new approach to the study of ocean wind vector retrieval using a polarimetric microwave radiometer.     

Retrieval of Snow Depth on Sea Ice in the Arctic Using the FengYun-3B Microwave Radiation Imager

Snow on sea ice is a sensitive indicator of climate change because it plays an important role regulating surface and near surface air temperatures. Given its high albedo and low thermal conductivity, snow cover is considered a key reason for amplified warming in polar regions. This study focuses on retrieving snow depth on sea ice from brightness temperatures recorded by the Microwave Radiation Imager(MWRI) on board the FengYun(FY)-3 B satellite. After cross calibration with the Advanced Microwave Scanning Radiometer-EOS(AMSR-E) Level 2 A data from January 1 to May 31, 2011, MWRI brightness temperatures were used to calculate sea ice concentrations based on the Arctic Radiation and Turbulence Interaction Study Sea Ice(ASI) algorithm. Snow depths were derived according to the proportional relationship between snow depth and surface scattering at 18.7 and 36.5 GHz. To eliminate the influence of uncertainties in snow grain sizes and sporadic weather effects, seven-day averaged snow depths were calculated. These results were compared with snow depths from two external data sets, the IceBridge ICDIS4 and AMSR-E Level 3 Sea Ice products. The bias and standard deviation of the differences between the MWRI snow depth and IceBridge data were respectively 1.6 and 3.2 cm for a total of 52 comparisons. Differences between MWRI snow depths and AMSR-E Level 3 products showed biases ranging between-1.01 and-0.58 cm, standard deviations from 3.63 to 4.23 cm, and correlation coefficients from 0.61 to 0.79 for the different months.     

Variations and controlling factors of the coccolith weight in the Western Pacific Warm Pool over the last 200 ka

Using a coccolith weight analytic software (Particle Analyser), we analyze most abundant coccolith species in a sediment core from the central Western Pacific Warm Pool (WPWP) and calculate coccolith size and weight variations over the last 200 ka. These variations are compared with the trends of sea surface temperature (SST), primary productivity (PP), sea surface salinity (SSS), and insolation. Our results demonstrate that the size and weight of the coccoliths varied in response to variations of these factors, and their average total weight is primarily related to the relative abundance of the dominant species GEO (Gephyrocapsa oceanica). The variation in weight of EMI (Emiliania huxleyi) and GEE (Gephyrocapsa ericsonii) are mainly influenced by nutrients, and the variation of GEM (G. muellerae conformis) and GEO (G. oceanica) weight are mainly influenced by SST. For all of the taxa weight, PP and SST present apparent precession or semi-precession cycles, we consider that the mono-coccolith weight of the Equatorial Western Pacific is primarily affected by precession drived thermocline and nutricline variation.     

A joint method to retrieve directional ocean wave spectra from SAR and wave spectrometer data

This paper proposes a joint method to simultaneously retrieve wave spectra at dif ferent scales from spaceborne Synthetic Aperture Radar(SAR) and wave spectrometer data. The method combines the output from the two dif ferent sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coeffi cient is estimated using an ef fective signifi cant wave height(SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coeffi cient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as fi rst guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length(PWL), and peak wave direction(PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR(ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting(ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.     

Standardizing CPUE of <Emphasis Type="Italic">Ommastrephes bartramii</Emphasis> for Chinese squid-jigging fishery in Northwest Pacific Ocean

Generalized linear models (GLM) and generalized additive models (GAM) were used to standardize catch per unit fishing effort (CPUE) of Ommastrephes bartramii for Chinese squid-jigging fishery in Northwest Pacific Ocean. Three groups of variables were considered in the standardization: spatial variables (longitude and latitude), temporal variables (year and month) and environmental variables, including sea surface temperature (SST), sea surface salinity (SSS) and sea level height (SLH). CPUE was treated as the dependent variable and its error distribution was assumed to be log-normal in each model. The model selections of GLM and GAM were based on the finite sample-corrected Akaike information criterion (AICC) and pseudo-coefficient (Pcf) combined P-value, respectively. Both GAM and GLM analysis showed that the month was the most important variable affecting CPUE and could explain 21.3% of variability in CPUE while other variables only explained 8.66%. The interaction of spatial and temporal variables weakly influenced the CPUE. Moreover, spatio-temporal factors may be more important in influencing the CPUE of this squid than environmental variables. The standardized and nominal CPUEs were similar and had the same trends in spatio-temporal distribution, but the standardized CPUE values tended to be smaller than the nominal CPUE. The CPUE tended to have much higher monthly variation than annual variations and their values increased with month. The CPUE became higher with increasing latitude-high CPUE usually occurred in 145°E–148°E and 149°E–162°E. The CPUE was higher when SST was 14–21°C and the SLH from −22 cm to −18 cm. In this study, GAM tended to be more suitable than GLM in analysis of CPUE.     

Stress Responses to Rapid Temperature Changes of the Juvenile Sea Cucumber （Apostichopusjaponicus Selenka）

Activities of hexokinase （HK）, pyruvate kinase （PK）, superoxide dismutase （SOD） and catalase （CAT） and Hsp70 level were measured to evaluate the response of the commercially important sea cucumber （Apostichopus japonicus Selenka） to rapid temperature changes in laboratory. Animals were subjected to a higher temperature （from 10 to 20℃） （Tinc treatment） or to a lower temperature （from 20 to 10℃） （Tddec treatment） for 72 h. At 1, 3, 12, 24, 72 h of exposure, animals were removed and prepared for further analysis. Results showed that the effect of acute temperature changes on enzyme activities was significant. In Tinc treatment, activities of SOD and CAT increased immediately. The significant enhancement of SOD and CAT activities suggested that oxidative stress increases significantly when ambient temperature increasing from 10 to 20℃. The up-regulation of Flsp70 in Tinc and Tdec treatments indicated that Hsp70 was a bioindicator of thermal stress in the sea cucumber, and the expression pattern depended on the thermal treatment.     

Tidal effects on temperature front in the Yellow Sea

Temperature front (TF) is one of the important features in the Yellow Sea, which forms in spring, thrives in summer, and fades in autumn as thermocline declines. TF intensity ⋎S _T ⋎ is defined to describe the distribution of TF. Based on the MASNUM wave-tide-circulation coupled model, temperature distribution in the Yellow Sea was simulated with and without tidal effects. Along 36°N, distribution of TF from the simulated results are compared with the observations, and a quantitative analysis is introduced to evaluate the tidal effects on the forming and maintaining processes of the TF. Tidal mixing and the circulation structure adapting to it are the main causes of the TF. Supported by the National Basic Research Program of China (No. G1999043809) and the National Science Foundation of China (No. 49736190).     

Effects of Body Weight and Water Temperature on Maximum Food Consumption of Juvenile Sebastodes fuscescens （Houttuyn）

Maximum rate of food consumption ( Cmax ) was determined for juvenile Sebastodes fuscescens (Houttuyn) at water temperature of 10, 15, 20 and 25℃. The relationships of Cmax to the body weight (W) at each temperature were described by a power equation: lnCmax = a b lnW. Covariance analysis revealed significant interaction of the temperature and body weight. The relationship of adjusted Cmax to water temperature (T) was described by a quadratic equation: Cmax = -0.369 0.456T - 0.0117T^2. The optimal feeding temperature calculated from this equation was 19.5 ℃. The coefficients of the multiple regression estimation relating Cmax to body weight (W) and water temperature (T) were given in the Table 2.     

Sea surface temperature and salinity reconstruction based on stable isotopes and Mg/Ca of planktonic foraminifera in the western Pacific Warm Pool during the last 155 ka

Changes in sea surface temperature(SST), seawater oxygen isotope(δ 18 O sw), and local salinity proxy(δ 18 O sw-ss) in the past 155 ka were studied using a sediment core(MD06-3052) from the northern edge of the western Pacifi c Warm Pool(WPWP), within the fl ow path of the bifurcation of the North Equatorial Current. Our records reveal a lead-lag relationship between paired Mg/Ca-SST and δ 18 O during Termination II and the last interglacial period. Similarity in SST between our site and the Antarctic temperature proxy and in CO 2 profi le showed a close connection between the WPWP and the Antarctic. Values of δ 18 O sw exhibited very similar variations to those of mean ocean δ 18 O sw, owing to the past sea-level changes on glacial-interglacial timescale. Calculated values of δ 18 O sw-ss refl ect a more saline condition during high local summer insolation(SI) periods. Such correspondence between δ 18 O sw-ss and local SI in the WPWP may refl ect complex interaction between ENSO and monsoon, which was stimulated by changes in solar irradiance and their infl uence on the local hydrologic cycle. This then caused a striking reorganization of atmospheric circulation over the WPWP.     

Satellite retrieval of hurricane wind speeds using the AMSR2 microwave radiometer

The AMSR2 microwave radiometer is the main payload of the GCOM-W1 satellite,launched by the Japan Aerospace Exploration Agency in 2012. Based on the pre-launch information extraction algorithm,the AMSR2 enables remote monitoring of geophysical parameters such as sea surface temperature,wind speed,water vapor,and liquid cloud water content. However,rain alters the properties of atmospheric scattering and absorption,which contaminates the brightness temperatures measured by the microwave radiometer. Therefore,it is difficult to retrieve AMSR2-derived sea surface wind speeds under rainfall conditions. Based on microwave radiative transfer theory,and using AMSR2 L1 brightness temperature data obtained in August 2012 and NCEP reanalysis data,we studied the sensitivity of AMSR2 brightness temperatures to rain and wind speed,from which a channel combination of brightness temperature was established that is insensitive to rainfall,but sensitive to wind speed. Using brightness temperatures obtained with the proposed channel combination as input parameters,in conjunction with HRD wind field data,and adopting multiple linear regression and BP neural network methods,we established an algorithm for hurricane wind speed retrieval under rainfall conditions. The results showed that the standard deviation and relative error of retrievals,obtained using the multiple linear regression algorithm,were 3.1 m/s and 13%,respectively. However,the standard deviation and relative error of retrievals obtained using the BP neural network algorithm were better(2.1 m/s and 8%,respectively). Thus,the results of this paper preliminarily verified the feasibility of using microwave radiometers to extract sea surface wind speeds under rainfall conditions.     

Optimum temperature for the growth performance of juvenile orange-spotted grouper （Epinephelus coioides H.）

Effects of water temperature （17, 21, 25, 30 and 35℃） and body size （14.75-281.41 g initial body weight） on food consumption, growth, feed conversion, and dry matter content in orange-spotted grouper fed to satiation were investigated. The combined effect of temperature （T, ℃） and body weight （W, g） on maximum food consumption （Cmax, g/day） was described as： InCmax=-7.411＋0.828 InW＋0.317T4）.004 7T2, and the optimum feeding temperature was 33.9℃. The combined effect of temperature and body weight on growth （G） was described as： lnG=-4.461-0.2081nW＋0.394T-0.006 3T^2. The optimum growth temperature was 31.4℃, whereas overall growth rates were high at 25, 30 and 35 ℃. Feed conversion efficiencies （FCE, %）, increasing first and then decreasing with increasing temperature, averaged from 1.8 to 2.1 in terms of dry weight of food fish. The optimum temperature for FCE tended to be lower than that for growth or feeding. Dry matter content increased with both increasing water temperature （17, 25, 30 and 35℃） and body weight, and the combined effect of temperature and body weight on dry matter content （DM, %） was described as： lnDM =3.232＋0.01 4 lnW-0.004 4T＋0.001 2TInW.     

Relationships of interannual variability between the equatorial pacific and tropical Indian Ocean in 17 CMIP5 models

Seventeen coupled general circulation models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed to assess the relationships of interannual variations of sea surface temperature (SST) between the tropical Pacific (TP) and tropical Indian Ocean (TIO). The eastern/central equatorial Pacific features the strongest SST interannual variability in the models except for the model CSIRO-Mk3-6-0, and the simulated maximum and minimum are produced by models GFDL-ESM2M and GISS-E2-H respectively. However, It remains a challenge for these models to simulate the correct climate mean SST with the warm pool-cold tongue structure in the equatorial Pacific. Almost all models reproduce El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole mode (IOD) and Indian Ocean Basin-wide mode (IOB) together with their seasonal phase lock features being simulated; but the relationship between the ENSO and IOD is different for different models. Consistent with the observation, an Indian Ocean basin-wide warming (cooling) takes place over the tropical Indian Ocean in the spring following an El Niño (La Niña) in almost all the models. In some models (e.g., GFDL-ESM2G and MIROC5), positive ENSO and IOB events are stronger than the negative events as shown in the observation. However, this asymmetry is reversed in some other models (e.g., HadGEM2-CC and HadGEM2-ES).     

Modeling a habitat suitability index for the eastern fall cohort of Ommastrephes bartramii in the central North Pacific Ocean

The eastern fall cohort of the neon flying squid, Ommastrephes bartramii, has been commercially exploited by the Chinese squid jigging fleet in the central North Pacific Ocean since the late 1990s. To understand and identify their optimal habitat, we have developed a habitat suitability index (HSI) model using two potential important environmental variables - sea surface temperature (SST) and sea surface height anomaly (SSHA) - and fishery data from the main fishing ground (165°-180°E) during June and July of 1999-2003. A geometric mean model (GMM), minimum model (MM) and arithmetic weighted model (AWM) with different weights were compared and the best HSI model was selected using Akaike’s information criterion (AIC). The performance of the developed HSI model was evaluated using fishery data for 2004. This study suggests that the highest catch per unit effort (CPUE) and fishing effort are closely related to SST and SSHA. The best SST- and SSHA-based suitability index (SI) regression models were SISST-based = 0.7SIeffort-SST + 0.3 SICPUE-SST, and SISSHA-based = 0.5SIeffort-SSHA + 0.5SICPUE-SSHA, respectively, showing that fishing effort is more important than CPUE in the estimation of SI. The best HSI model was the AWM, defined as HSI=0.3SISST-based+ 0.7SISSHA-based, indicating that SSHA is more important than SST in estimating the HSI of squid. In 2004, monthly HSI values greater than 0.6 coincided with the distribution of productive fishing ground and high CPUE in June and July, suggesting that the models perform well. The proposed model provides an important tool in our efforts to develop forecasting capacity of squid spatial dynamics.     

Statistical analysis of surface hydrography and circulation variations in northern South China Sea

1 INTRODUCTIONThe South China Sea (SCS) is a semi-enclosedmarginal sea in western North Pacific Ocean withvery complex topography and is the important pas-sage connecting the Pacific and Indian Oceans. Ithas great impact to the global climate and a greatinterest of many oceanography researchers. Twodominant surface hydrographic and circulation fea-tures in the northern SCS are a strong fresh waterexpansion and a warm and high-salinity seawaterintrusion such as the SCS Diluted Water…