Calibration of Soil Electromagnetic Conductivity in Inverted Salinity Profiles with an Integration Method

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.

A new method to retrieve salinity profiles from sea surface salinity observed by SMOS satellite

This paper proposes a new method to retrieve salinity profiles from the sea surface salinity （SSS） observed by the Soil Moisture and Ocean Salinity （SMOS） satellite. The main vertical patterns of the salinity profiles are firstly extracted from the salinity profiles measured by Argo using the empirical orthogonal function. To determine the time coefficients for each vertical pattern, two statistical models are developed. In the linear model, a transfer function is proposed to relate the SSS observed by SMOS （SMOS_SSS） with that measured by Argo, and then a linear relationship between the SMOS_SSS and the time coefficient is established. In the nonlinear model, the neural network is utilized to estimate the time coefficients from SMOS_SSS, months and positions of the salinity profiles. The two models are validated by comparing the salinity profiles retrieved from SMOS with those measured by Argo and the climatological salinities. The root-mean-square error （RMSE） of the linear and nonlinear model are 0.08-0.16 and 0.08-0.14 for the upper 400 m, which are 0.01-0.07 and 0.01-0.09 smaller than the RMSE of climatology. The error sources of the method are also discussed.

Assimilating satellite SST/SSH and in-situ T/S profiles with the Localized Weighted Ensemble Kalman Filter

The Localized Weighted Ensemble Kalman Filter(LWEnKF)is a new nonlinear/non-Gaussian data assimilation(DA)method that can effectively alleviate the filter degradation problem faced by particle filtering,and it has great prospects for applications in geophysical models.In terms of operational applications,along-track sea surface height(AT-SSH),swath sea surface temperature(S-SST)and in-situ temperature and salinity(T/S)profiles are assimilated using the LWEnKF in the northern South China Sea(SCS).To adapt to the vertical S-coordinates of the Regional Ocean Modelling System(ROMS),a vertical localization radius function is designed for T/S profiles assimilation using the LWEnKF.The results show that the LWEnKF outperforms the local particle filter(LPF)due to the introduction of the Ensemble Kalman Filter(EnKF)as a proposal density;the RMSEs of SSH and SST from the LWEnKF are comparable to the EnKF,but the RMSEs of T/S profiles reduce significantly by approximately 55%for the T profile and 35%for the S profile(relative to the EnKF).As a result,the LWEnKF makes more reasonable predictions of the internal ocean temperature field.In addition,the three-dimensional structures of nonlinear mesoscale eddies are better characterized when using the LWEnKF.

Observed features of temperature, salinity and current in central Chukchi Sea during the summer of 2012

During the summer of 2012, the fifth CHINARE Arctic Expedition was carried out, and a submersible mooring system was deployed in M5 station located at （69°30.155＇N,169°00.654＇W） and recovered 50d later. A set of temperature, salinity and current profile records was acquired. The characteristics of these observations are analyzed in this paper. Some main results are achieved as below. （1） Temperature generally decreases while salinity generally increases with increasing depth. The average values of all records are 2.98℃ and 32.21 psu. （2） Salinity and temperature are well negatively correlated, and the correlation coefficient between them is -0.84. However, they did not always vary synchronously. Their co-variation featured different characters during different significant periods. （3） The average velocity for the whole water column is 141 mm/s with directional angle of 347.1°. The statistical distribution curve of velocity record number gets narrower with increasing depth. More than 85% of the recorded velocities are northward, and the mean magnitudes of dominated northward velocities are 100-150 mm/s. （4） Rotary spectrum analysis shows that motions with low frequency take a majority of energy in all layers. The most significant energy peaks for all layers are around 0.012 cph （about 3.5 d period）, while the tidal motion in mooring area is nonsignificant. （5） Velocities in all layers feature similar and synchronous temporal variations, except for the slight decrease in magnitude and leftward twist from top to bottom. The directions of velocity correspond well to those of Surface wind. The average northward volume transport per square meter is 0.1-0.2 m3/s under southerly wind, but about -0.2 m3/s during northerly wind burst.

Variation of Indo-Pacific upper ocean heat content during 2001–2012 revealed by Argo

Understanding of the temporal variation of oceanic heat content （OHC） is of fundamental importance to the prediction of climate change and associated global meteorological phenomena. However, OHC characteristics in the Pacific and Indian oceans are not well understood. Based on in situ ocean temperature and salinity profiles mainly from the Argo program, we estimated the upper layer （0-750 m） OHC in the Indo-Pacific Ocean （40°S-40°N, 30°E-80°W）. Spatial and temporal variability of OHC and its likely physical mechanisms are also analyzed. Climatic distributions of upper-layer OHC in the Indian and Pacific oceans have a similar saddle pattern in the subtropics, and the highest OHC value was in the northern Arabian Sea. However, OHC variabilities in the two oceans were different. OHC in the Pacific has an east-west see-saw pattern, which does not appear in the Indian Ocean. In the Indian Ocean, the largest change was around 10°S. The most interesting phenomenon is that, there was a long-term shift of OHC in the Indo-Pacific Ocean during 2001-2012. Such variation coincided with modulation of subsurface temperature/salinity. During 2001-2007, there was subsurface cooling （freshening） nearly the entire upper 400 m layer in the western Pacific and warming （salting） in the eastern Pacific. During 2008-2012, the thermocline deepened in the western Pacific but shoaled in the east. In the Indian Ocean, there was only cooling （upper 150 m only） and freshening （almost the entire upper 400 m） during 2001-2007. The thermocline deepened during 2008-2012 in the Indian Ocean. Such change appeared from the equator to off the equator and even to the subtropics （about 20°N/S） in the two oceans. This long-term change of subsurface temperature/salinity may have been caused by change of the wind field over the two oceans during 2001-2012, in turn modifying OHC.