Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diver...Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.展开更多
In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that o...In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that of salinity profile scheme, we found that there was one different term between the two schemes named the salinity different term. The thermodynamic effect of the salinity difference term on sea ice thickness and sea ice concentration showed that： in the freezing processes from November to next May, the sea ice temperature could rise on the influence of the salinity difference term and restrain sea ice freezing; at the first melting phase from June to August, the upper ice melting rate was faster than the lower ice melting rate. Then sea ice temperature could rise and accelerate the sea ice melting; at the second melting phase from September to October, the upper ice melting rate was slower than the lower ice melting rate, then sea ice temperature could decrease and restrain sea ice melting. However, the effect of the salinity difference term on the sea ice thickness and sea ice concentration was weak. To analyze the impacts of the salinity different term on Arctic sea ice thickness and sea ice concentration, we also designed several experiments by introducing the two salinity parameterizations to the ice-ocean coupled model, Modular Ocean Model （MOM4）, respectively. The simulated results confirmed the previous results of formula derivation.展开更多
Using a crop-water-salinity production function and a soil-water-salinity dynamic model, optimal irrigation scheduling was developed to maximize net return per irrigated area. Plot and field experiments were used to o...Using a crop-water-salinity production function and a soil-water-salinity dynamic model, optimal irrigation scheduling was developed to maximize net return per irrigated area. Plot and field experiments were used to obtain the crop water sensitivity index, the salinity sensitivity index, and other parameters. Using data collected during 35 years to calculate the 10-day mean precipitation and evaporation, the variation in soil salinity concentrations and in the yields of winter wheat and cotton were simulated for 49 irrigation scheduling that were combined from 7 irrigation schemes over 3 irrigation dates and 7 salinity concentrations of saline irrigation water (fresh water and 6 levels of saline water). Comparison of predicted results with irrigation data obtained from a large area of the field showed that the model was valid and reliable. Based on the analysis of the investment cost of the irrigation that employed deep tube wells or shallow tube wells, a saline water irrigation schedule and a corresponding strategy for groundwater development and utilization were proposed. For wheat or cotton, if the salinity concentration was higher than 7.0 g L-1 in groundwater, irrigation was needed with only fresh water; if about 5.0 g L-1, irrigation was required twice with fresh water and once with saline water; and if not higher than 3.0 g L-1, irrigation could be solely with saline water.展开更多
The main source of water in Gaza Strip is the shallow coastal aquifer. It is extremely deteriorated in terms of salinity which influenced by many variables. Studying the relation between these variables and salinity i...The main source of water in Gaza Strip is the shallow coastal aquifer. It is extremely deteriorated in terms of salinity which influenced by many variables. Studying the relation between these variables and salinity is often a complex and nonlinear process, making it suitable to model by Artificial Neural Networks (ANN). Initially, it is assumed that the salinity (represented by chloride concentration, mg/l) may be affected by some variables as: recharge rate, abstraction, abstraction average rate, life time and aquifer thickness. Data were extracted from 56 municipal wells, covering the area of Gaza Strip. After a number of modeling trials, the best neural network was determined to be Multilayer Perceptron network (MLP) with four layers: an input layer of 6 neurons, first hidden layer with 10 neurons, second hidden layer with 7 neurons and the output layer with 1 neuron which gives the final chloride concentration. The ANN model generated very good results depending on the high correlation between the observed and simulated values of chloride concentration. The correlation coefficient (r) was 0.9848. The high value of (r) showed that the simulated chloride concentration values using the ANN model were in very good agreement with the observed chloride concentration which mean that ANN model is useful and applicable for groundwater salinity modeling. ANN model was successfully utilized as analytical tool to study influence of the input variables on chloride concentration. It proved that chloride concentration in groundwater is reduced by decreasing abstraction, abstraction average rate and life time. Furthermore, it is reduced by increasing recharge rate and aquifer thickness.展开更多
From 1997 to 2000, four field surveys were conducted in the East China Sea （ECS） （23°30＇-33°00＇N, 118°30＇-128°00＇E）. A field data yield density model was used to determine the optimal salin...From 1997 to 2000, four field surveys were conducted in the East China Sea （ECS） （23°30＇-33°00＇N, 118°30＇-128°00＇E）. A field data yield density model was used to determine the optimal salinities for 19 dominant copepod species to establish the relationship between surface salinities and abundance of those species. In addition, ecological groups of the copepods were classified based on optimal salinity and geographical distribution. The results indicate that the yield density model is suitable for determining the relationship between salinity and abundance. Cosmocalanus darwini, Euchaeta rimana, Pleuromamma gracilis, Rhincalanus cornutus, Scolecithrix danae and Pareucalanus attenuatus were determined as oceanic species, with optimal salinities of 〉34.0. They were stenohaline and mainly distributed in waters influenced by the Kuroshio or Taiwan warm current. Temora discaudata, T. stylifera and Canthocalanus pauper were nearshore species with optimal salinities of 〈33.0 and most abundant in coastal waters. The remaining 10 species, including Undinula vulgaris and Subeucalanus suberassus, were offshore species, with optimal salinity ranging from 33.0-34.0. They were widely distributed in nearshore, offshore and oceanic waters but mainly in the mixed water of the ECS.展开更多
Salt-affected soils, caused by natural or human activities, are a common environmental hazard in semi-arid and arid landscapes. Excess salts in soils affect plant growth and production, soil and water quality and, the...Salt-affected soils, caused by natural or human activities, are a common environmental hazard in semi-arid and arid landscapes. Excess salts in soils affect plant growth and production, soil and water quality and, therefore, increase soil erosion and land degradation. This research investigates the performance of five different semi-empirical predictive models for soil salinity spatial distribution mapping in arid environment using OLI sensor image data. This is the first attempt to test remote sensing based semi-empirical salinity predictive models in this area: the Kingdom of Bahrain. To achieve our objectives, OLI data were standardized from the atmosphere interferences, the sensor radiometric drift, and the topographic and geometric distortions. Then, the five semi-empirical predictive models based on the Normalized Difference Salinity Index (NDSI), the Salinity Index-ASTER (SI-ASTER), the Salinity Index-1 (SI-1), the Soil Salinity and Sodicity Index-1 and Index-2 (SSSI-1 and SSSI-2), developed for slight and moderate salinity in agricultural land, were implemented and applied to OLI image data. For validation purposes, a fieldwork was organized and different important spots-locations representing different salinity levels were visited, photographed, and localized using an accurate GPS (σ ≤ ±30 cm). Based on this a priori knowledge of the soil salinity, six validation sites were selected to reflect non-saline, low, moderate, high and extreme salinity classes, descriptive statistics extracted from polygons and/or transects over these sites were used. The obtained results showed that the models based on NDSI, SI-1 and SI-ASTER all failed to detect salinity bounds for both extreme salinity (Sabkhah) and non-saline conditions. In Fact, NDSI and SI-ASTER gave respectively only 35% dS/m and 25% dS/m in extreme salinity validation site, while SI-1 and SI-ASTER indicated 38% dS/m and 39% dS/m in non-saline validation site. Therefore, these three models were deemed inadequate for the study site. However, both SSSI-1 and SSSI-2 allowed a detection of the previous salinity bounds and furthermore described similarly and correctly the urban-vegetation areas and the open-land areas. Their predicted EC is around 10% dS/m for non-saline urban soil, about 25% dS/m for low salinity urban-vegetation soil, approximately 30% to 75% dS/m, respectively, for moderate to high salinity soils. SSSI-2 based semi-empirical salinity models was able to differentiate the high salinity versus extreme salinity in areas where both exist and was very accurate to highlight the pure salt where SSSI-1 has reach saturation for both salinity classes. In conclusion, reliable salinity map was produced using the model based on SSSI-2 and OLI sensor data that allows a better characterization of the soil salinity problem in an Arid Environment.展开更多
The Ord River Irrigation Area (ORIA) is located within northern Western Australia near the Northern Territory border. Since the beginning of irrigated agriculture in the ORIA the groundwater levels have been continuou...The Ord River Irrigation Area (ORIA) is located within northern Western Australia near the Northern Territory border. Since the beginning of irrigated agriculture in the ORIA the groundwater levels have been continuously rising and are now close to the soil surface in some parts of ORIA in northern Western Australia. The groundwater is now saline throughout most of the ORIA and soil salinity risks are high where the watertables are shallow. This research evaluated irrigation and salinity management strategies for sugarcane and maize crops grown over deep and shallow, non-saline and saline watertables in the ORIA. The LEACHC model, calibrated using field data, was used to predict the impacts of various irrigation management strategies on water use and salt accumulation in the root zone. This study concluded that irrigation application equal to 100% of total fortnightly pan evaporation applied at 14 day intervals was a good irrigation strategy for the maize grown over a deep watertable area. This strategy would require around 11 ML/ha of irrigation water per growing season. Irrigation application equal to 75% of total fortnightly pan evaporation, applied every fortnight during first half of the growing season, and 75% of total weekly pan evaporation, applied on a weekly basis during second half of the growing season, would be the best irrigation strategy if it is feasible to change the irrigation interval from 14 to seven days. This irrigation strategy is predicted to have minimal salinity risks and save around 40% irrigation water. The best irrigation strategy for sugarcane grown on Cununurra clay over a deep watertable area would be irrigation application equal to 50% of the total fortnightly pan evaporation, applied every fortnight during first quarter of the growing season, and irrigation application amounts equal to 100% of total weekly pan evaporation, applied every week during rest of the season. The model predicted no soil salinity risks from this irrigation strategy. The best irrigation strategy for sugarcane over a non-saline, shallow watertable of one or two m depth would be irrigation application amounts equal to 50% of total fortnightly pan evaporation applied every fortnight. In the case of a saline watertable the same irrigation strategy was predicted to the best with respect to water use efficiency but will have high salinity risks without any drainage management.展开更多
Two models have been developed for the evaluation and prediction of salinity changes (chloride concentration;ppm;[Cl]) in Lake Kinneret. They are: 1) RM, which is based on the Salt balance and hydrological budget of t...Two models have been developed for the evaluation and prediction of salinity changes (chloride concentration;ppm;[Cl]) in Lake Kinneret. They are: 1) RM, which is based on the Salt balance and hydrological budget of the lake;2) GM which is based on the geo-hydrological regional properties of Kinneret’s geological structure. The concept of both is partly different: RM is correlating reduction of runoffs to salinity elevation and GM relates salt flux to the aquifer yield and the impact of lake water level is neglected. Long term statistical analyses justify support to GM, excluding conditions of heavy floods. This paper is a combination of a supplemental extended temporal study and a models review. Practical conclusions on Kinneret hydrological management within a frame of constrains aimed at prevention of salinity and eutrophication increase are presented.展开更多
As China’s second longest river,the Yellow River(YR)carries a large volume of fresh water into the Bohai Sea with abundant nutrients and,thus,plays a crucial role in regulating the temperature and salinity near the Y...As China’s second longest river,the Yellow River(YR)carries a large volume of fresh water into the Bohai Sea with abundant nutrients and,thus,plays a crucial role in regulating the temperature and salinity near the YR Delta.In this study,using the runoff data and the Finite Volume Community Ocean Model,we simulated the salinity distribution near the YR Estuary for 2013-2022.We investigated the effect of the YR runoff on salinity dispersion and established the relationship between salinity distribution and the river’s runoff volume.Additionally,we analyzed the relationship between fish eggs and salinity distribution using fish egg da-ta.Findings indicated that the freshwater discharged from the YR converged into Laizhou Bay under the influence of tide.The sever-al years of simulation results(2013-2022)showed that the salinity field near the YR Estuary changed with the variations of river runoff entering the sea.Simultaneously,we found a positive correlation between the area of low-salinity zones(below 27)and the monthly average river runoff,and this relation could be expressed as Y_(s)=0.7457X_(r)+78.904.The characteristics of fish egg distribution revealed that fish eggs were primarily distributed in the areas characterized by salinity in the range of 25-29.展开更多
The prediction of water temperature and salinity in coastal areas is one of the essential tasks in water quality control and management. This paper takes a refined forecasting model of water temperature and salinity i...The prediction of water temperature and salinity in coastal areas is one of the essential tasks in water quality control and management. This paper takes a refined forecasting model of water temperature and salinity in coastal areas as a basic target. Based on the Navier-Stokes equation and k-epsilon turbulence model, taking the characteristics of coastal areas into account, a refined model for water temperature and salinity in coastal areas has been developed to simulate the seasonal variations of water temperature and salinity fields in the Hakata Bay, Japan. The model takes into account the effects of a variety of hydrodynamic and meteorological factors on water temperature and salinity. It predicts daily fluctuations in water temperature and salinity at different depths throughout the year. The model has been calibrated well against the data set of historical water temperature and salinity observations in the Hakata Bay, Japan.展开更多
Generally one dimensional （l-D） empirical salinity intrusion model is limited to natural alluvial estuary. However, this study attempts to investigate its ability to model a sheltered alluvial estuary of the Terengg...Generally one dimensional （l-D） empirical salinity intrusion model is limited to natural alluvial estuary. However, this study attempts to investigate its ability to model a sheltered alluvial estuary of the Terengganu River in Malaysia. The constructed breakwater at the mouth of the river shelters the estuary from direct influence of the open sea. The salinity density along the estuary was collected during the wet and dry seasons for scenarios before and after the constructed breakwater. Moreover, the freshwater discharges, tidal elevations and bathymetry data were also measured as model inputs. A good fit was demonstrated between simulated and observed variables, namely salinity distribution and intrusion length for both scenarios. Thus, the results show that 1-D empirical salinity model can be utilized for sheltered estuarine condition at the Terengganu Estuary, but with an appropriate determination of an initial point. Furthermore, it was observed that the salinity intrusion in the study area is largely dependent on the freshwater discharge rather than tidal elevation fluctuations. The scale of the salinity intrusion length in the study area is proportional to the river discharge of the -1/2 power. It was appeared that the two lines of the 1-D empirical salinity model and discharge power based equation fitted well to each other, with the average predicted minimum freshwater discharge of 150 m^3/s is going to be required to maintain acceptable salinity levels during high water slack （HWS） near the water intake station, which is located at 10.63 km from river mouth.展开更多
Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization.Investigating evaporation rate in loess-like sulfa...Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization.Investigating evaporation rate in loess-like sulfate saline soils under varying salt contents carries crucial implications for understanding regional water loss processes,predicting soil salinization advancement,and formulating effective ecological management strategies.Therefore,this study sampled the loess-like sulfate saline soil that is widely distributed in western China as experimental materials and investigated the impact of different initial salt contents(0.00%,0.50%,1.50%,3.00%,and 5.00%)on the evaporation rate,water content,and temperature of soil.The results showed that the evaporation rate decreased with increasing initial salt content.After a salt accumulation layer formed on the soil surface,the water content of the surface soil fluctuated.An increase in the initial salt content resulted in a corresponding increase in the surface temperature.Considering the evaporation characteristics of loess-like sulfate saline soil and the impact of an anomalous increase in surface soil water content on soil surface resistance,this study proposed a modified evaporation model on the basis of Fujimaki's evaporation model of saline soil by introducing a correction coefficientβto modify the soil surface resistance.A comparison of the calculated evaporation rates before and after the modification with the measured evaporation rates revealed a significant improvement in the calculation accuracy of the modified model,indicating that the modified model is capable of more accurately simulating the evaporation rate of sulfate saline soil with different initial salt contents.This paper proposes an effective method for calculating the evaporation rate of loess-like sulfate saline soils,providing a theoretical basis for evaporation research in saline soil.展开更多
The vertical salinity structure in the Bohai As and the Huanghai Sea have typical self-similar characters. However, horizontal salinity distribution is influenced by advection, horizontal diffusion, river discharge,et...The vertical salinity structure in the Bohai As and the Huanghai Sea have typical self-similar characters. However, horizontal salinity distribution is influenced by advection, horizontal diffusion, river discharge,etc. By using observed sea salinity data, a similarity function of vertical salinity profiles of the Bohai Sea and the Huanghai Sea has been constructed. On the basis of vertical integrated equations of motion and equation of continuity, and governing equations about the distribution of 3 characteristic factors (surface salinity Ss, bottom salinity SH, and thickness of upper homogeneous layer h), and combined with the similarity function, a quasithree-dimensional numerical model of salinity structure bas ben developed. In the model, the comprehensive effects of sea surface wind stress and heat influx, advection, diffusion, entrainment, bottom as well as lateral eddy mixture are taken into consideration. It is shown that the numerical model is more practical and the results of the trial prediction are satisfactory展开更多
The cooling of the Cenozoic, including the Miocene epoch, was punctuated by many geologically abrupt warming and cooling episodes— strong deviations from the cooling trend with time span of ten to hundred thousands o...The cooling of the Cenozoic, including the Miocene epoch, was punctuated by many geologically abrupt warming and cooling episodes— strong deviations from the cooling trend with time span of ten to hundred thousands of years. Our working hypothesis is that some of those warming episodes at least partially might have been caused by dynamics of the Antarctic Ice Sheet, which, in turn, might have caused strong changes of sea surface salinity in the Miocene Southern Ocean. Feasibility of this hypothesis is explored in a series of offline-coupled ocean-atmosphere computer experiments. The results suggest that relatively small and geologically short-lived changes in freshwater balance in the Southern Ocean could have significantly contributed to at least two prominent warming episodes in the Miocene. Importantly, the scenario-based experiments also suggest that the Southern Ocean was more sensitive to the salinity changes in the Miocene than today, which can attributed to the opening of the Central American Isthmus as a major difference between the Miocene and the present-day ocean-sea geometry.展开更多
The simulation of salinity at different locations of a tidal river using physically-based hydrodynamic models is quite cumbersome because it requires many types of data, such as hydrological and hydraulic time series ...The simulation of salinity at different locations of a tidal river using physically-based hydrodynamic models is quite cumbersome because it requires many types of data, such as hydrological and hydraulic time series at boundaries, river geometry, and adjusted coefficients. Therefore, an artificial neural network (ANN) technique using a back-propagation neural network (BPNN) and a radial basis function neural network (RBFNN) is adopted as an effective alternative in salinity simulation studies. The present study focuses on comparing the performance of BPNN, RBFNN, and three-dimensional hydrodynamic models as applied to a tidal estuarine system. The observed salinity data sets collected from 18 to 22 May, 16 to 22 October, and 26 to 30 October 2002 (totaling 4320 data points) were used for BPNN and RBFNN model training and for hydrodynamic model calibration. The data sets collected from 30 May to 2 June and 11 to 15 November 2002 (totaling 2592 data points) were adopted for BPNN and RBFNN model verification and for hydrodynamic model verification. The results revealed that the ANN (BPNN and RBFNN) models were capable of predicting the nonlinear time series behavior of salinity to the multiple forcing signals of water stages at different stations and freshwater input at upstream boundaries. The salinity predicted by the ANN models was better than that predicted by the physically based hydrodynamic model. This study suggests that BPNN and RBFNN models are easy-to-use modeling tools for simulating the salinity variation in a tidal estuarine system.展开更多
Modeling soil salinity in an arid salt-affected ecosystem is a difficult task when using remote sensing data because of the complicated soil context （vegetation cover, moisture, surface roughness, and organic matter...Modeling soil salinity in an arid salt-affected ecosystem is a difficult task when using remote sensing data because of the complicated soil context （vegetation cover, moisture, surface roughness, and organic matter） and the weak spectral features of salinized soil. Therefore, an index such as the salinity index （SI） that only uses soil spectra may not detect soil salinity effectively and quantitatively. The use of vegetation reflectance as an indirect indicator can avoid limitations associated with the direct use of soil reflectance. The normalized difference vegetation index （NDVI）, as the most common vegetation index, was found to be responsive to salinity but may not be available for retrieving sparse vegetation due to its sensitivity to background soil in arid areas. Therefore, the arid fraction integrated index （AFⅡ） was created as supported by the spectral mixture analysis （SMA）, which is more appropriate for analyzing variations in vegetation cover （particularly halophytes） than NDVI in the study area. Using soil and vegetation separately for detecting salinity perhaps is not feasible. Then, we developed a new and operational model, the soil salinity detecting model （SDM） that combines AFⅡ and SI to quantitatively estimate the salt content in the surface soil. SDMs, including SDM1 and SDM2, were constructed through analyzing the spatial characteristics of soils with different salinization degree by integrating AFⅡ and SI using a scatterplot. The SDMs were then compared to the combined spectral response index （COSRI） from field measurements with respect to the soil salt content. The results indicate that the SDM values are highly correlated with soil salinity, in contrast to the performance of COSRI. Strong exponential relationships were observed between soil salinity and SDMs （R2〉0.86, RMSE〈6.86） compared to COSRI （R2=0.71, RMSE=16.21）. These results suggest that the feature space related to biophysical properties combined with AFII and SI can effectively provide information on soil salinity.展开更多
Salinity variability and its causes in the tropical Pacific are analyzed using observations, reanalysis products and model simulations. The mixed-layer salinity(MLS) budget analyses from observations and reanalysis pr...Salinity variability and its causes in the tropical Pacific are analyzed using observations, reanalysis products and model simulations. The mixed-layer salinity(MLS) budget analyses from observations and reanalysis products indicate that its interannual evolution is closely related to ENSO and is predominantly governed by surface forcing and surface advection in the western-central equatorial Pacific. It is found that the observed MLS tendency leads Nin?o3.4 by about 12 months due to the effect of negative freshwater flux(evaporation minus precipitation). These observation-based analyses are used to evaluate the corresponding simulation using GFDL-ESM2 M. It is evident that the model can simulate the spatiotemporal variations of MLS with some discrepancies compared to observations. In the warm pool of the equatorial Pacific the MLS tendency in the model is sensitive to ocean dynamics, however model biases cause the tendency to be underestimated. In particular, the freshwater flux is overestimated while the ocean surface zonal current and vertical velocity at the base of the mixed layer are underestimated. Due to model biases in representing the related physics, the effects of surface forcing on the simulated MLS budget are overestimated and those of subsurface and surface advection are relatively weak. Due to weaker surface advection and subsurface forcing than observed, the simulated compensations for surface forcing are suppressed, and the simulated MLS tendency that leads Nin?o3.4 by 8–10 months, which is shorter than the observed lead time. These results are useful for the interpretation of observational analyses and other model simulations in the tropical Pacific.展开更多
The E1 Nifio-Southern Oscillation （ENSO） is emphasized the roles of wind stress and heat flux environmental forcing to the ocean; its effect and modulated by many factors; most previous studies have in the tropical ...The E1 Nifio-Southern Oscillation （ENSO） is emphasized the roles of wind stress and heat flux environmental forcing to the ocean; its effect and modulated by many factors; most previous studies have in the tropical Pacific. Freshwater flux （FWF） is another the related ocean salinity variability in the ENSO region have been of increased interest recently. Currently, accurate quantifications of the FWF roles in the climate remain challenging; the related observations and coupled ocean-atmosphere modeling involve large elements of uncertainty. In this study, we utilized satellite-based data to represent FWF-induced feedback in the tropical Pacific climate system; we then incorporated these data into a hybrid coupled ocean-atmosphere model （HCM） to quantify its effects on ENSO. A new mechanism was revealed by which interannual FWF forcing modulates ENSO in a significant way. As a direct forcing, FWF exerts a significant influence on the ocean through sea surface salinity （SSS） and buoyancy flux （QB） in the western-central tropical Pacific. The SSS perturbations directly induced by ENSO-related interannual FWF variability affect the stability and mixing in the upper ocean. At the same time, the ENSO-induced FWF has a compensating effect on heat flux, acting to reduce interannual Qs variability during ENSO cycles. These FWF-induced processes in the ocean tend to modulate the vertical mixing and entrainment in the upper ocean, enhancing cooling during La Nifia and enhancing warming during E1 Nifio, respectively. The interannual FWF forcing-induced positive feedback acts to enhance ENSO amplitude and lengthen its time scales in the tropical Pacific coupled climate system.展开更多
Various calibration methods have been propounded to determine profiles of apparent bulk soil electrical conductivity (ECa) and soil electrical conductivity of a saturated soil paste extract (ECe) or a 1:5 soil water e...Various calibration methods have been propounded to determine profiles of apparent bulk soil electrical conductivity (ECa) and soil electrical conductivity of a saturated soil paste extract (ECe) or a 1:5 soil water extract (EC1:5) using an electromagnetic induction instrument (EM38). The modeled coefficients, one of the successful and classical methods hitherto, were chosen to calibrate the EM38 measurements of the inverted salinity profiles of characteristic coastal saline soils at selected sites of Xincao Farm, Jiangsu Province, China. However, this method required three parameters for each depth layer. An integration approach, based on an exponential decay profile model, was proposed and the model was fitted to all the calibration sites. The obtained model can then be used to predict EC1:5 at a certain depth from electromagnetic measurements made using the EM38 device positioned in horizontal and vertical positions at the soil surface. This exponential decay model predicted the EC1:5 well according to the results of a one-way analysis of variance, and the further comparison indicated that the modeled coefficients appeared to be slightly superior to, but not statistically different from, this exponential decay model. Nevertheless, this exponential decay model was more significant and practical because it depended on less empirical parameters and could be used to perform point predictions of EC1:5 continuously with depth.展开更多
Based on HYbrid Coordinate Ocean Model (HYCOM) assimilation and observations, we analyzed seasonal variability of the salinity budget in the southeastern Arabian Sea (AS) and the southern part of the Bay of Bengal (BO...Based on HYbrid Coordinate Ocean Model (HYCOM) assimilation and observations, we analyzed seasonal variability of the salinity budget in the southeastern Arabian Sea (AS) and the southern part of the Bay of Bengal (BOB), as well as water exchange between the two basins. Results show that fresh water flux cannot explain salinity changes in salinity budget of both regions. Oceanic advection decreases salinity in the southeastern AS during the winter monsoon season and increases salinity in the southern BOB during the summer monsoon season. In winter, the Northeast Monsoon Current (NMC) carries fresher water from the BOB westward into the southern AS; this westward advection is confined to 4°-6°N and the upper 180 m south of the Indian peninsula. Part of the less saline water then turns northward, decreasing salinity in the southeastern AS. In summer, the Southwest Monsoon Current (SMC) advects high-salinity water from the AS eastward into the BOB, increasing salinity along its path. This eastward advection of high-salinity water south of the India Peninsula extends southward to 2°N, and the layer becomes shallower than in winter. In addition to the monsoon current, the salinity difference between the two basins is important for salinity advection.展开更多
基金supported by the Laoshan Laboratory[grant number LSKJ202202403]the National Natural Science Foundation of China[grant number 42030410]+1 种基金additionally supported by the Startup Foundation for Introducing Talent of NUISTJiangsu Innovation Research Group[grant number JSSCTD202346]。
文摘Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.
基金supported by the National Natural Science Foundation of China(No.41075030,41106004,41106159 and 41206013)the Ocean Public Welfare Science Research Project,State Oceanic Administration,People's Republic of China(No.201005019)
文摘In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that of salinity profile scheme, we found that there was one different term between the two schemes named the salinity different term. The thermodynamic effect of the salinity difference term on sea ice thickness and sea ice concentration showed that： in the freezing processes from November to next May, the sea ice temperature could rise on the influence of the salinity difference term and restrain sea ice freezing; at the first melting phase from June to August, the upper ice melting rate was faster than the lower ice melting rate. Then sea ice temperature could rise and accelerate the sea ice melting; at the second melting phase from September to October, the upper ice melting rate was slower than the lower ice melting rate, then sea ice temperature could decrease and restrain sea ice melting. However, the effect of the salinity difference term on the sea ice thickness and sea ice concentration was weak. To analyze the impacts of the salinity different term on Arctic sea ice thickness and sea ice concentration, we also designed several experiments by introducing the two salinity parameterizations to the ice-ocean coupled model, Modular Ocean Model （MOM4）, respectively. The simulated results confirmed the previous results of formula derivation.
基金Project supported by the National Natural Science Foundation of China (Nos. 50339030 and 90202001).
文摘Using a crop-water-salinity production function and a soil-water-salinity dynamic model, optimal irrigation scheduling was developed to maximize net return per irrigated area. Plot and field experiments were used to obtain the crop water sensitivity index, the salinity sensitivity index, and other parameters. Using data collected during 35 years to calculate the 10-day mean precipitation and evaporation, the variation in soil salinity concentrations and in the yields of winter wheat and cotton were simulated for 49 irrigation scheduling that were combined from 7 irrigation schemes over 3 irrigation dates and 7 salinity concentrations of saline irrigation water (fresh water and 6 levels of saline water). Comparison of predicted results with irrigation data obtained from a large area of the field showed that the model was valid and reliable. Based on the analysis of the investment cost of the irrigation that employed deep tube wells or shallow tube wells, a saline water irrigation schedule and a corresponding strategy for groundwater development and utilization were proposed. For wheat or cotton, if the salinity concentration was higher than 7.0 g L-1 in groundwater, irrigation was needed with only fresh water; if about 5.0 g L-1, irrigation was required twice with fresh water and once with saline water; and if not higher than 3.0 g L-1, irrigation could be solely with saline water.
文摘The main source of water in Gaza Strip is the shallow coastal aquifer. It is extremely deteriorated in terms of salinity which influenced by many variables. Studying the relation between these variables and salinity is often a complex and nonlinear process, making it suitable to model by Artificial Neural Networks (ANN). Initially, it is assumed that the salinity (represented by chloride concentration, mg/l) may be affected by some variables as: recharge rate, abstraction, abstraction average rate, life time and aquifer thickness. Data were extracted from 56 municipal wells, covering the area of Gaza Strip. After a number of modeling trials, the best neural network was determined to be Multilayer Perceptron network (MLP) with four layers: an input layer of 6 neurons, first hidden layer with 10 neurons, second hidden layer with 7 neurons and the output layer with 1 neuron which gives the final chloride concentration. The ANN model generated very good results depending on the high correlation between the observed and simulated values of chloride concentration. The correlation coefficient (r) was 0.9848. The high value of (r) showed that the simulated chloride concentration values using the ANN model were in very good agreement with the observed chloride concentration which mean that ANN model is useful and applicable for groundwater salinity modeling. ANN model was successfully utilized as analytical tool to study influence of the input variables on chloride concentration. It proved that chloride concentration in groundwater is reduced by decreasing abstraction, abstraction average rate and life time. Furthermore, it is reduced by increasing recharge rate and aquifer thickness.
基金Supported by the National Natural Science Foundation of China (Nos. 40776047, 90511005)the National Basic Research Program of China (973 Project) (No. 2010CB428705)
文摘From 1997 to 2000, four field surveys were conducted in the East China Sea （ECS） （23°30＇-33°00＇N, 118°30＇-128°00＇E）. A field data yield density model was used to determine the optimal salinities for 19 dominant copepod species to establish the relationship between surface salinities and abundance of those species. In addition, ecological groups of the copepods were classified based on optimal salinity and geographical distribution. The results indicate that the yield density model is suitable for determining the relationship between salinity and abundance. Cosmocalanus darwini, Euchaeta rimana, Pleuromamma gracilis, Rhincalanus cornutus, Scolecithrix danae and Pareucalanus attenuatus were determined as oceanic species, with optimal salinities of 〉34.0. They were stenohaline and mainly distributed in waters influenced by the Kuroshio or Taiwan warm current. Temora discaudata, T. stylifera and Canthocalanus pauper were nearshore species with optimal salinities of 〈33.0 and most abundant in coastal waters. The remaining 10 species, including Undinula vulgaris and Subeucalanus suberassus, were offshore species, with optimal salinity ranging from 33.0-34.0. They were widely distributed in nearshore, offshore and oceanic waters but mainly in the mixed water of the ECS.
文摘Salt-affected soils, caused by natural or human activities, are a common environmental hazard in semi-arid and arid landscapes. Excess salts in soils affect plant growth and production, soil and water quality and, therefore, increase soil erosion and land degradation. This research investigates the performance of five different semi-empirical predictive models for soil salinity spatial distribution mapping in arid environment using OLI sensor image data. This is the first attempt to test remote sensing based semi-empirical salinity predictive models in this area: the Kingdom of Bahrain. To achieve our objectives, OLI data were standardized from the atmosphere interferences, the sensor radiometric drift, and the topographic and geometric distortions. Then, the five semi-empirical predictive models based on the Normalized Difference Salinity Index (NDSI), the Salinity Index-ASTER (SI-ASTER), the Salinity Index-1 (SI-1), the Soil Salinity and Sodicity Index-1 and Index-2 (SSSI-1 and SSSI-2), developed for slight and moderate salinity in agricultural land, were implemented and applied to OLI image data. For validation purposes, a fieldwork was organized and different important spots-locations representing different salinity levels were visited, photographed, and localized using an accurate GPS (σ ≤ ±30 cm). Based on this a priori knowledge of the soil salinity, six validation sites were selected to reflect non-saline, low, moderate, high and extreme salinity classes, descriptive statistics extracted from polygons and/or transects over these sites were used. The obtained results showed that the models based on NDSI, SI-1 and SI-ASTER all failed to detect salinity bounds for both extreme salinity (Sabkhah) and non-saline conditions. In Fact, NDSI and SI-ASTER gave respectively only 35% dS/m and 25% dS/m in extreme salinity validation site, while SI-1 and SI-ASTER indicated 38% dS/m and 39% dS/m in non-saline validation site. Therefore, these three models were deemed inadequate for the study site. However, both SSSI-1 and SSSI-2 allowed a detection of the previous salinity bounds and furthermore described similarly and correctly the urban-vegetation areas and the open-land areas. Their predicted EC is around 10% dS/m for non-saline urban soil, about 25% dS/m for low salinity urban-vegetation soil, approximately 30% to 75% dS/m, respectively, for moderate to high salinity soils. SSSI-2 based semi-empirical salinity models was able to differentiate the high salinity versus extreme salinity in areas where both exist and was very accurate to highlight the pure salt where SSSI-1 has reach saturation for both salinity classes. In conclusion, reliable salinity map was produced using the model based on SSSI-2 and OLI sensor data that allows a better characterization of the soil salinity problem in an Arid Environment.
文摘The Ord River Irrigation Area (ORIA) is located within northern Western Australia near the Northern Territory border. Since the beginning of irrigated agriculture in the ORIA the groundwater levels have been continuously rising and are now close to the soil surface in some parts of ORIA in northern Western Australia. The groundwater is now saline throughout most of the ORIA and soil salinity risks are high where the watertables are shallow. This research evaluated irrigation and salinity management strategies for sugarcane and maize crops grown over deep and shallow, non-saline and saline watertables in the ORIA. The LEACHC model, calibrated using field data, was used to predict the impacts of various irrigation management strategies on water use and salt accumulation in the root zone. This study concluded that irrigation application equal to 100% of total fortnightly pan evaporation applied at 14 day intervals was a good irrigation strategy for the maize grown over a deep watertable area. This strategy would require around 11 ML/ha of irrigation water per growing season. Irrigation application equal to 75% of total fortnightly pan evaporation, applied every fortnight during first half of the growing season, and 75% of total weekly pan evaporation, applied on a weekly basis during second half of the growing season, would be the best irrigation strategy if it is feasible to change the irrigation interval from 14 to seven days. This irrigation strategy is predicted to have minimal salinity risks and save around 40% irrigation water. The best irrigation strategy for sugarcane grown on Cununurra clay over a deep watertable area would be irrigation application equal to 50% of the total fortnightly pan evaporation, applied every fortnight during first quarter of the growing season, and irrigation application amounts equal to 100% of total weekly pan evaporation, applied every week during rest of the season. The model predicted no soil salinity risks from this irrigation strategy. The best irrigation strategy for sugarcane over a non-saline, shallow watertable of one or two m depth would be irrigation application amounts equal to 50% of total fortnightly pan evaporation applied every fortnight. In the case of a saline watertable the same irrigation strategy was predicted to the best with respect to water use efficiency but will have high salinity risks without any drainage management.
文摘Two models have been developed for the evaluation and prediction of salinity changes (chloride concentration;ppm;[Cl]) in Lake Kinneret. They are: 1) RM, which is based on the Salt balance and hydrological budget of the lake;2) GM which is based on the geo-hydrological regional properties of Kinneret’s geological structure. The concept of both is partly different: RM is correlating reduction of runoffs to salinity elevation and GM relates salt flux to the aquifer yield and the impact of lake water level is neglected. Long term statistical analyses justify support to GM, excluding conditions of heavy floods. This paper is a combination of a supplemental extended temporal study and a models review. Practical conclusions on Kinneret hydrological management within a frame of constrains aimed at prevention of salinity and eutrophication increase are presented.
基金supported by the Yantai City Science and Technology Innovation Development Plan Project(Nos.2023JCYJ097 and 2023JCYJ094)the Key Project of the National Natural Science Foundation of China(No.42330406).
文摘As China’s second longest river,the Yellow River(YR)carries a large volume of fresh water into the Bohai Sea with abundant nutrients and,thus,plays a crucial role in regulating the temperature and salinity near the YR Delta.In this study,using the runoff data and the Finite Volume Community Ocean Model,we simulated the salinity distribution near the YR Estuary for 2013-2022.We investigated the effect of the YR runoff on salinity dispersion and established the relationship between salinity distribution and the river’s runoff volume.Additionally,we analyzed the relationship between fish eggs and salinity distribution using fish egg da-ta.Findings indicated that the freshwater discharged from the YR converged into Laizhou Bay under the influence of tide.The sever-al years of simulation results(2013-2022)showed that the salinity field near the YR Estuary changed with the variations of river runoff entering the sea.Simultaneously,we found a positive correlation between the area of low-salinity zones(below 27)and the monthly average river runoff,and this relation could be expressed as Y_(s)=0.7457X_(r)+78.904.The characteristics of fish egg distribution revealed that fish eggs were primarily distributed in the areas characterized by salinity in the range of 25-29.
基金The project was financially supported by the National Natural Science Foundation of China(Grant No.59779023,No.59839330)
文摘The prediction of water temperature and salinity in coastal areas is one of the essential tasks in water quality control and management. This paper takes a refined forecasting model of water temperature and salinity in coastal areas as a basic target. Based on the Navier-Stokes equation and k-epsilon turbulence model, taking the characteristics of coastal areas into account, a refined model for water temperature and salinity in coastal areas has been developed to simulate the seasonal variations of water temperature and salinity fields in the Hakata Bay, Japan. The model takes into account the effects of a variety of hydrodynamic and meteorological factors on water temperature and salinity. It predicts daily fluctuations in water temperature and salinity at different depths throughout the year. The model has been calibrated well against the data set of historical water temperature and salinity observations in the Hakata Bay, Japan.
文摘Generally one dimensional （l-D） empirical salinity intrusion model is limited to natural alluvial estuary. However, this study attempts to investigate its ability to model a sheltered alluvial estuary of the Terengganu River in Malaysia. The constructed breakwater at the mouth of the river shelters the estuary from direct influence of the open sea. The salinity density along the estuary was collected during the wet and dry seasons for scenarios before and after the constructed breakwater. Moreover, the freshwater discharges, tidal elevations and bathymetry data were also measured as model inputs. A good fit was demonstrated between simulated and observed variables, namely salinity distribution and intrusion length for both scenarios. Thus, the results show that 1-D empirical salinity model can be utilized for sheltered estuarine condition at the Terengganu Estuary, but with an appropriate determination of an initial point. Furthermore, it was observed that the salinity intrusion in the study area is largely dependent on the freshwater discharge rather than tidal elevation fluctuations. The scale of the salinity intrusion length in the study area is proportional to the river discharge of the -1/2 power. It was appeared that the two lines of the 1-D empirical salinity model and discharge power based equation fitted well to each other, with the average predicted minimum freshwater discharge of 150 m^3/s is going to be required to maintain acceptable salinity levels during high water slack （HWS） near the water intake station, which is located at 10.63 km from river mouth.
基金supported by the National Natural Science Foundation of China(51769013,52168052)。
文摘Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization.Investigating evaporation rate in loess-like sulfate saline soils under varying salt contents carries crucial implications for understanding regional water loss processes,predicting soil salinization advancement,and formulating effective ecological management strategies.Therefore,this study sampled the loess-like sulfate saline soil that is widely distributed in western China as experimental materials and investigated the impact of different initial salt contents(0.00%,0.50%,1.50%,3.00%,and 5.00%)on the evaporation rate,water content,and temperature of soil.The results showed that the evaporation rate decreased with increasing initial salt content.After a salt accumulation layer formed on the soil surface,the water content of the surface soil fluctuated.An increase in the initial salt content resulted in a corresponding increase in the surface temperature.Considering the evaporation characteristics of loess-like sulfate saline soil and the impact of an anomalous increase in surface soil water content on soil surface resistance,this study proposed a modified evaporation model on the basis of Fujimaki's evaporation model of saline soil by introducing a correction coefficientβto modify the soil surface resistance.A comparison of the calculated evaporation rates before and after the modification with the measured evaporation rates revealed a significant improvement in the calculation accuracy of the modified model,indicating that the modified model is capable of more accurately simulating the evaporation rate of sulfate saline soil with different initial salt contents.This paper proposes an effective method for calculating the evaporation rate of loess-like sulfate saline soils,providing a theoretical basis for evaporation research in saline soil.
文摘The vertical salinity structure in the Bohai As and the Huanghai Sea have typical self-similar characters. However, horizontal salinity distribution is influenced by advection, horizontal diffusion, river discharge,etc. By using observed sea salinity data, a similarity function of vertical salinity profiles of the Bohai Sea and the Huanghai Sea has been constructed. On the basis of vertical integrated equations of motion and equation of continuity, and governing equations about the distribution of 3 characteristic factors (surface salinity Ss, bottom salinity SH, and thickness of upper homogeneous layer h), and combined with the similarity function, a quasithree-dimensional numerical model of salinity structure bas ben developed. In the model, the comprehensive effects of sea surface wind stress and heat influx, advection, diffusion, entrainment, bottom as well as lateral eddy mixture are taken into consideration. It is shown that the numerical model is more practical and the results of the trial prediction are satisfactory
文摘The cooling of the Cenozoic, including the Miocene epoch, was punctuated by many geologically abrupt warming and cooling episodes— strong deviations from the cooling trend with time span of ten to hundred thousands of years. Our working hypothesis is that some of those warming episodes at least partially might have been caused by dynamics of the Antarctic Ice Sheet, which, in turn, might have caused strong changes of sea surface salinity in the Miocene Southern Ocean. Feasibility of this hypothesis is explored in a series of offline-coupled ocean-atmosphere computer experiments. The results suggest that relatively small and geologically short-lived changes in freshwater balance in the Southern Ocean could have significantly contributed to at least two prominent warming episodes in the Miocene. Importantly, the scenario-based experiments also suggest that the Southern Ocean was more sensitive to the salinity changes in the Miocene than today, which can attributed to the opening of the Central American Isthmus as a major difference between the Miocene and the present-day ocean-sea geometry.
文摘The simulation of salinity at different locations of a tidal river using physically-based hydrodynamic models is quite cumbersome because it requires many types of data, such as hydrological and hydraulic time series at boundaries, river geometry, and adjusted coefficients. Therefore, an artificial neural network (ANN) technique using a back-propagation neural network (BPNN) and a radial basis function neural network (RBFNN) is adopted as an effective alternative in salinity simulation studies. The present study focuses on comparing the performance of BPNN, RBFNN, and three-dimensional hydrodynamic models as applied to a tidal estuarine system. The observed salinity data sets collected from 18 to 22 May, 16 to 22 October, and 26 to 30 October 2002 (totaling 4320 data points) were used for BPNN and RBFNN model training and for hydrodynamic model calibration. The data sets collected from 30 May to 2 June and 11 to 15 November 2002 (totaling 2592 data points) were adopted for BPNN and RBFNN model verification and for hydrodynamic model verification. The results revealed that the ANN (BPNN and RBFNN) models were capable of predicting the nonlinear time series behavior of salinity to the multiple forcing signals of water stages at different stations and freshwater input at upstream boundaries. The salinity predicted by the ANN models was better than that predicted by the physically based hydrodynamic model. This study suggests that BPNN and RBFNN models are easy-to-use modeling tools for simulating the salinity variation in a tidal estuarine system.
基金financially supported by the National Basic Research Program of China (2009CB825105)the National Natural Science Foundation of China (41261090)
文摘Modeling soil salinity in an arid salt-affected ecosystem is a difficult task when using remote sensing data because of the complicated soil context （vegetation cover, moisture, surface roughness, and organic matter） and the weak spectral features of salinized soil. Therefore, an index such as the salinity index （SI） that only uses soil spectra may not detect soil salinity effectively and quantitatively. The use of vegetation reflectance as an indirect indicator can avoid limitations associated with the direct use of soil reflectance. The normalized difference vegetation index （NDVI）, as the most common vegetation index, was found to be responsive to salinity but may not be available for retrieving sparse vegetation due to its sensitivity to background soil in arid areas. Therefore, the arid fraction integrated index （AFⅡ） was created as supported by the spectral mixture analysis （SMA）, which is more appropriate for analyzing variations in vegetation cover （particularly halophytes） than NDVI in the study area. Using soil and vegetation separately for detecting salinity perhaps is not feasible. Then, we developed a new and operational model, the soil salinity detecting model （SDM） that combines AFⅡ and SI to quantitatively estimate the salt content in the surface soil. SDMs, including SDM1 and SDM2, were constructed through analyzing the spatial characteristics of soils with different salinization degree by integrating AFⅡ and SI using a scatterplot. The SDMs were then compared to the combined spectral response index （COSRI） from field measurements with respect to the soil salt content. The results indicate that the SDM values are highly correlated with soil salinity, in contrast to the performance of COSRI. Strong exponential relationships were observed between soil salinity and SDMs （R2〉0.86, RMSE〈6.86） compared to COSRI （R2=0.71, RMSE=16.21）. These results suggest that the feature space related to biophysical properties combined with AFII and SI can effectively provide information on soil salinity.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41690122, 41690120 and 41475101)the NSFC–Shandong Joint Fund for Marine Science Research Centers (Grant No. U1406401)+1 种基金the NSFC Innovative Group Grant (Project No. 41421005)Taishan Scholarship
文摘Salinity variability and its causes in the tropical Pacific are analyzed using observations, reanalysis products and model simulations. The mixed-layer salinity(MLS) budget analyses from observations and reanalysis products indicate that its interannual evolution is closely related to ENSO and is predominantly governed by surface forcing and surface advection in the western-central equatorial Pacific. It is found that the observed MLS tendency leads Nin?o3.4 by about 12 months due to the effect of negative freshwater flux(evaporation minus precipitation). These observation-based analyses are used to evaluate the corresponding simulation using GFDL-ESM2 M. It is evident that the model can simulate the spatiotemporal variations of MLS with some discrepancies compared to observations. In the warm pool of the equatorial Pacific the MLS tendency in the model is sensitive to ocean dynamics, however model biases cause the tendency to be underestimated. In particular, the freshwater flux is overestimated while the ocean surface zonal current and vertical velocity at the base of the mixed layer are underestimated. Due to model biases in representing the related physics, the effects of surface forcing on the simulated MLS budget are overestimated and those of subsurface and surface advection are relatively weak. Due to weaker surface advection and subsurface forcing than observed, the simulated compensations for surface forcing are suppressed, and the simulated MLS tendency that leads Nin?o3.4 by 8–10 months, which is shorter than the observed lead time. These results are useful for the interpretation of observational analyses and other model simulations in the tropical Pacific.
基金supported in part by NSF Grant(ATM-0727668and AGS-1061998)NOAA Grant(NA08OAR4310885)+3 种基金NASA Grants(NNX08AI74G,NNX08AI76G,and NNX09AF41G)F.Zheng is supported by the National Basic Research Program of China(GrantNos.2012CB417404and2012CB955202)the Natural Science Foundation of China(Grant No.41075064)Pei is additionally supported by China Scholarship Coun-cil(CSC) with the Ocean University of China,Qingdao,China
文摘The E1 Nifio-Southern Oscillation （ENSO） is emphasized the roles of wind stress and heat flux environmental forcing to the ocean; its effect and modulated by many factors; most previous studies have in the tropical Pacific. Freshwater flux （FWF） is another the related ocean salinity variability in the ENSO region have been of increased interest recently. Currently, accurate quantifications of the FWF roles in the climate remain challenging; the related observations and coupled ocean-atmosphere modeling involve large elements of uncertainty. In this study, we utilized satellite-based data to represent FWF-induced feedback in the tropical Pacific climate system; we then incorporated these data into a hybrid coupled ocean-atmosphere model （HCM） to quantify its effects on ENSO. A new mechanism was revealed by which interannual FWF forcing modulates ENSO in a significant way. As a direct forcing, FWF exerts a significant influence on the ocean through sea surface salinity （SSS） and buoyancy flux （QB） in the western-central tropical Pacific. The SSS perturbations directly induced by ENSO-related interannual FWF variability affect the stability and mixing in the upper ocean. At the same time, the ENSO-induced FWF has a compensating effect on heat flux, acting to reduce interannual Qs variability during ENSO cycles. These FWF-induced processes in the ocean tend to modulate the vertical mixing and entrainment in the upper ocean, enhancing cooling during La Nifia and enhancing warming during E1 Nifio, respectively. The interannual FWF forcing-induced positive feedback acts to enhance ENSO amplitude and lengthen its time scales in the tropical Pacific coupled climate system.
基金Project supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (No. KZCX2-YW-406-3)the National Key Basic Research Support Foundation (NKBRSF) of China (No. 2005CB121108).
文摘Various calibration methods have been propounded to determine profiles of apparent bulk soil electrical conductivity (ECa) and soil electrical conductivity of a saturated soil paste extract (ECe) or a 1:5 soil water extract (EC1:5) using an electromagnetic induction instrument (EM38). The modeled coefficients, one of the successful and classical methods hitherto, were chosen to calibrate the EM38 measurements of the inverted salinity profiles of characteristic coastal saline soils at selected sites of Xincao Farm, Jiangsu Province, China. However, this method required three parameters for each depth layer. An integration approach, based on an exponential decay profile model, was proposed and the model was fitted to all the calibration sites. The obtained model can then be used to predict EC1:5 at a certain depth from electromagnetic measurements made using the EM38 device positioned in horizontal and vertical positions at the soil surface. This exponential decay model predicted the EC1:5 well according to the results of a one-way analysis of variance, and the further comparison indicated that the modeled coefficients appeared to be slightly superior to, but not statistically different from, this exponential decay model. Nevertheless, this exponential decay model was more significant and practical because it depended on less empirical parameters and could be used to perform point predictions of EC1:5 continuously with depth.
基金Supported by the National Basic Research Program of China (973Program) (No. 2010CB950300)the Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX2-YW-Q11-02)+1 种基金the Knowledge Innovation Program of Chinese Academy of Sciences(No. KZCX2-YW-BR-04)the National Basic Research Program of China (973 Program) (No. 2012CB955603)
文摘Based on HYbrid Coordinate Ocean Model (HYCOM) assimilation and observations, we analyzed seasonal variability of the salinity budget in the southeastern Arabian Sea (AS) and the southern part of the Bay of Bengal (BOB), as well as water exchange between the two basins. Results show that fresh water flux cannot explain salinity changes in salinity budget of both regions. Oceanic advection decreases salinity in the southeastern AS during the winter monsoon season and increases salinity in the southern BOB during the summer monsoon season. In winter, the Northeast Monsoon Current (NMC) carries fresher water from the BOB westward into the southern AS; this westward advection is confined to 4°-6°N and the upper 180 m south of the Indian peninsula. Part of the less saline water then turns northward, decreasing salinity in the southeastern AS. In summer, the Southwest Monsoon Current (SMC) advects high-salinity water from the AS eastward into the BOB, increasing salinity along its path. This eastward advection of high-salinity water south of the India Peninsula extends southward to 2°N, and the layer becomes shallower than in winter. In addition to the monsoon current, the salinity difference between the two basins is important for salinity advection.
