A novel temperature and salinity discriminative sensing method based on forward Brillouin scattering(FBS)in 1060-XP single-mode fiber(SMF)is proposed.The measured frequency shifts corresponding to different radial aco...A novel temperature and salinity discriminative sensing method based on forward Brillouin scattering(FBS)in 1060-XP single-mode fiber(SMF)is proposed.The measured frequency shifts corresponding to different radial acoustic modes in 1060-XP SMF show different sensitivities to temperature and salinity.Based on the new phenomenon that different radial acoustic modes have different frequency shift-temperature and frequency shift-salinity coefficients,we propose a novel method for simultaneously measuring temperature and salinity by measuring the frequency shift changes of two FBS scattering peaks.In a proof-of-concept experiment,the temperature and salinity measurement errors are 0.12℃and 0.29%,respectively.The proposed method for simultaneously measuring temperature and salinity has the potential applications such as ocean surveying,food manufacturing and pharmaceutical engineering.展开更多
Roughness-induced emission from ocean surfaces is one of the main issues that affects the retrieval accuracy of sea surface salinity remote sensing.In previous studies,the correction of roughness effect mainly depende...Roughness-induced emission from ocean surfaces is one of the main issues that affects the retrieval accuracy of sea surface salinity remote sensing.In previous studies,the correction of roughness effect mainly depended on wind speeds retrieved from scatterometers or those provided by other means,which necessitates a high requirement for accuracy and synchronicity of wind-speed measurements.The aim of this study is to develop a novel roughness correction model of ocean emissivity for the salinity retrieval application.The combined active/passive observations of normalized radar cross-sections(NRCSs)and emissivities from ocean surfaces given by the L-band Aquarius/SAC-D mission,and the auxiliary wind directions collocated from the National Centers for Environmental Prediction(NCEP)dataset are used for model development.The model is validated against the observations and the Aquarius standard algorithms of roughness-induced emissivity correction.Comparisons between model computations and measurements indicate that the model has better accuracy in computing wind-induced brightness temperature in the upwind/downwind directions or for the surfaces with smaller NRCSs,which can be better than 0.3 K.However,for crosswind directions and larger NRCSs,the model accuracy is relatively low.A model using HH-polarized NRCSs yields better accuracy than that using VV-polarized ones.For a fair comparison to the Aquarius standard algorithms using wind speeds retrieved from multi-source data,the maximum likelihood estimation is employed to produce results combining our model calculations and those using other sources.Numerical simulations show that combined results basically have higher accuracy than the standard algorithms.展开更多
Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and...Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity （SSS） is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation （SSA） model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2-year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately le-4, and the RMSE is slightly larger than le-3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected, and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.展开更多
For the application of soil moisture and ocean salinity（SMOS） remotely sensed sea surface salinity（SSS） products,SMOS SSS global maps and error characteristics have been investigated based on quality control infor...For the application of soil moisture and ocean salinity（SMOS） remotely sensed sea surface salinity（SSS） products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere（negative bias） and along the southern,northern and some other oceanic margins（positive or negative bias）.The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature; errors along the oceanic margins are due to the bias in a brightness temperature（TB） reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean; in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.展开更多
The narrow sense and applicable limit of Practical Salinity Scale 1978 (PSS78) and volumetric titration using silver nitrate to measure the salinity of non conservative oceanwater are discussed.The salinity obtained ...The narrow sense and applicable limit of Practical Salinity Scale 1978 (PSS78) and volumetric titration using silver nitrate to measure the salinity of non conservative oceanwater are discussed.The salinity obtained by electrical conductivity method and chlorinity salinity method obviously deviates from the absolute salinity( S A). The Density Salinity Scale(DSS98)proposed by the writers can be extensively used in conservative and non conservative water samples. The merits of the density salinity scale are as follows. (1)The Density Salinity Scale is only related to seawater mass and its buoyant effect, and is not influenced by the variation in seawater composition, and therefore,has high reliability,and repeatability for salinity determination. (2)The salinity values measured by the DSS98 have a conservative property.For oceanwater samples the salinity values are the same as those determined by the PSS78; for non conservative water samples(e g. samples from industrial sources),the salinity values are close to the absolute salinity values in comparison with those measured by the PSS78 and the Knudsen method. (3)For a solution with given solute mass,the solution concentration can be converted into the corresponding salinity by the Density Salinity Scale using the expansion coefficient of the solution and the calibration coefficient of the partial molar volume of the solute.展开更多
基金supported by the Na-tional Natural Science Foundation of China(Nos.62175105,61875086)Fundamental Research Funds for the Cen-tral Universities of China(No.ILB240041A24)。
文摘A novel temperature and salinity discriminative sensing method based on forward Brillouin scattering(FBS)in 1060-XP single-mode fiber(SMF)is proposed.The measured frequency shifts corresponding to different radial acoustic modes in 1060-XP SMF show different sensitivities to temperature and salinity.Based on the new phenomenon that different radial acoustic modes have different frequency shift-temperature and frequency shift-salinity coefficients,we propose a novel method for simultaneously measuring temperature and salinity by measuring the frequency shift changes of two FBS scattering peaks.In a proof-of-concept experiment,the temperature and salinity measurement errors are 0.12℃and 0.29%,respectively.The proposed method for simultaneously measuring temperature and salinity has the potential applications such as ocean surveying,food manufacturing and pharmaceutical engineering.
基金The National Key R&D Program of China under contract Nos 2018YFA0605403 and 2016YFB0500204the Hainan Provincial Natural Science Foundation of China under contract No.418QN301the National Natural Science Foundation of China under contract No.41801238。
文摘Roughness-induced emission from ocean surfaces is one of the main issues that affects the retrieval accuracy of sea surface salinity remote sensing.In previous studies,the correction of roughness effect mainly depended on wind speeds retrieved from scatterometers or those provided by other means,which necessitates a high requirement for accuracy and synchronicity of wind-speed measurements.The aim of this study is to develop a novel roughness correction model of ocean emissivity for the salinity retrieval application.The combined active/passive observations of normalized radar cross-sections(NRCSs)and emissivities from ocean surfaces given by the L-band Aquarius/SAC-D mission,and the auxiliary wind directions collocated from the National Centers for Environmental Prediction(NCEP)dataset are used for model development.The model is validated against the observations and the Aquarius standard algorithms of roughness-induced emissivity correction.Comparisons between model computations and measurements indicate that the model has better accuracy in computing wind-induced brightness temperature in the upwind/downwind directions or for the surfaces with smaller NRCSs,which can be better than 0.3 K.However,for crosswind directions and larger NRCSs,the model accuracy is relatively low.A model using HH-polarized NRCSs yields better accuracy than that using VV-polarized ones.For a fair comparison to the Aquarius standard algorithms using wind speeds retrieved from multi-source data,the maximum likelihood estimation is employed to produce results combining our model calculations and those using other sources.Numerical simulations show that combined results basically have higher accuracy than the standard algorithms.
基金The National Natural Science Foundation of China under contract No.41371355
文摘Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher, which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity （SSS） is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation （SSA） model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2-year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately le-4, and the RMSE is slightly larger than le-3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected, and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.
基金The National Natural Science Fund of China under contact No.41276088the National Natural Science Fund for Young Scholars of China under contact Nos 41206002 and 41306010
文摘For the application of soil moisture and ocean salinity（SMOS） remotely sensed sea surface salinity（SSS） products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere（negative bias） and along the southern,northern and some other oceanic margins（positive or negative bias）.The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature; errors along the oceanic margins are due to the bias in a brightness temperature（TB） reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean; in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.
文摘The narrow sense and applicable limit of Practical Salinity Scale 1978 (PSS78) and volumetric titration using silver nitrate to measure the salinity of non conservative oceanwater are discussed.The salinity obtained by electrical conductivity method and chlorinity salinity method obviously deviates from the absolute salinity( S A). The Density Salinity Scale(DSS98)proposed by the writers can be extensively used in conservative and non conservative water samples. The merits of the density salinity scale are as follows. (1)The Density Salinity Scale is only related to seawater mass and its buoyant effect, and is not influenced by the variation in seawater composition, and therefore,has high reliability,and repeatability for salinity determination. (2)The salinity values measured by the DSS98 have a conservative property.For oceanwater samples the salinity values are the same as those determined by the PSS78; for non conservative water samples(e g. samples from industrial sources),the salinity values are close to the absolute salinity values in comparison with those measured by the PSS78 and the Knudsen method. (3)For a solution with given solute mass,the solution concentration can be converted into the corresponding salinity by the Density Salinity Scale using the expansion coefficient of the solution and the calibration coefficient of the partial molar volume of the solute.
