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A new method for generating synthetic salinity (SS) profiles in the Southwest Atlantic was developed and applied in data assimilation experiments. This method was based on the smallest integrated values of root mean square deviation (RMSD)—with respect to observations—to infer salinity through climatological data and by regressive methods on temperature (T) using a five‐order polynomial function (P5). In the 14 delimited subregions, the averaged RMSD of P5 was 45% smaller than interpolated climatological data. However, climatological salinity presented better results in the first top layers while P5 presented smaller errors in higher depths. Therefore, by joining the best that P5 and climatology may offer, a new hybrid approach was used to generate SS based on T from XBT profiles. The SS would allow more T profiles to be employed in the Oceanographic Modeling and Observation Network (REMO) data assimilation system, called RODAS, into the Hybrid Coordinate Ocean Model (HYCOM). The use of SS estimates has potential to improve model outputs, in which the presence of the T‐S pair is quite necessary. Three integrations were performed: one run without assimilation (FREE), one assimilating sea surface temperature, Argo profilers, and sea level anomaly (RODAS) and one similar to RODAS, but with added XBTs with SS (RODAS_XBT). The inclusion of XBT data in the HYCOM + RODAS system improved the position and magnitude of the Brazil Current (BC). It was shown that SS is feasible for producing ocean reanalysis and initial conditions for ocean forecast systems requiring very low computational cost.

Along-track sea surface height anomaly (SSHA) data from the Jason-1 and Jason-2 satellites were assimilated into the ocean model HYCOM from July 1, 2009 until December 31, 2009. A new and simple approach to overcome the bias between the model and observed SSHA was proposed. It focuses on the meso-scale differences between the data and the model along each satellite track. An optimal interpolation method and the Cooper and Haines (1996) scheme (C&H) were employed to produce a SSHA analysis field and to adjust model layer thicknesses over the Atlantic METAREA V. The corrected model state was used as initial condition for the next assimilation cycle. SSHA data with a 7-day window were assimilated in 3-day intervals centered in the SSHA data window and the C&H scheme was applied taking the SSHA analysis. A control run without assimilation was also performed. The results showed that the model SSHA was completely reorganized by the end of the experiment. The modifications of SSHA were compared to the American Navy HYCOM+NCODA system and AVISO data. Maximum error was reduced from 0.7 m to 0.2 m by assimilation. Comparisons were also made with the Argo temperature and salinity vertical profiles. Improvements in the currents and volume transport were also produced by assimilation. The impact in temperature was in general positive, but there was no substantial modification in salinity.

In this study, the elemental composition of nine medicinal plants and phytomedicines was evaluated by using axial view inductively coupled plasma optical emission spectrometry (ICP OES) after three digestion procedures: dry ashing (DA) and two wet digestions with a mineral acid (HNO 3 /H 2 O 2 ) mixture on a conventional hot plate (CD), besides microwave digestion (MW). Accuracy was assessed from spinach leaves (CRM 1570a) and recovery values were in the range of 82 to 113.8%. Precisions, such as relative standard deviation (RSD), below 10% were reached. The MW procedure was preferred for its accuracy (recovery values of 94 to 102%), reduced contamination, increase in the efficiency of the decomposition process, lower residual acidity and reduced time required for digestion. The concentrations of analytes in the samples (minimummaximum in μg g ). The levels of Al, Ba, Cd, Cr, Mo, Pb, Se and V in all investigated samples were found to be below the limit of detection of ICP OES. The multielement analysis by ICP OES showed that the method is simple, fast and reliable for the multielement determination in medicinal plants and phytomedicines.