Sonic Layer Depth estimated from XBT temperatures and climatological salinities

Sonic layer depth (SLD) plays an important role in antisubmarine warfare in terms of identifying the shadow zones for submarine safe parking. SLD is estimated from sound velocity profiles (SVP) which is in turn obtained from temperature and salinity (T/S) profiles. Given the limited availability of salinity data in comparison to temperature, SVPs need to be obtained from alternate methods. In the present work, to make use of voluminous temperature data sets from XBT, CTD and other source for estimating SLD, we propose a method of utilizing XBT measurements and World Ocean Atlas climatological salinities to compute SVP and then extract SLD. This approach is demonstrated by utilizing T/S data from Argo floats in the Arabian Sea (40° – 80° E and 0 – 30° N). SLD is estimated from SVP obtained from Argo T/S profiles first and again by replacing the Argo salinity with climatological salinity. It is found that in more than 90% of cases, SLD matched exactly, with the root mean square deviation ranging from 3 – 12 m with an average of 7 m

Technical Report on Argo Data Processing

In this document, details of Argo program, data acquisition system and data processing are documented to serve as a reference for Argo data. Several plots are included to serve as quick reference. The data will be useful to describe major thermo-haline features in the Indian Ocean. In conjunction with other sources of data from various platforms, the data can be used for studying meso-scale structure and dynamics of upper ocean process. At smaller scales, the float temperature and salinity data will be useful to document the seasonal to intra seasonal variability of temperature, salinity and various other derived parameters. This temperature and salinity data can be useful for updating the climatology and for assimilation into ocean model for better forecasts

SoVeAt: a tool for visualizing sound velocity data for Naval applications

This report discusses various functionalities of Sound Velocity Atlas (SoVeAT) tool developed for use by Naval Operations Data Processing and Analysis Centre (NODPAC) a wing of Indian Navy. The subsurface profile data of temperature and salinity (T/S) used in developing this tool is the Argo data which is obtained from INCOIS Argo mirror archives which is obtained from two Global Data Assembly Centre’s (GDAC) namely Coriolis in France and USGODAE in USA. These data sets are processed, quality controlled and merged to form a unique data set for enhancing the Sound Velocity climatology of Indian Ocean (30E - 120 E and 69 S - 30 N). With this sound velocity data derived from Argo T/S, Graphic User Interface (GUI) based tool is built for visualizing parameters viz., Sound Velocity, Temperature, Salinity and bathymetry. This tool has capability to generate climatology dynamically between any chosen periods apart from visualizing various plots which are useful for Navy while at sea. Also provision for adding newly observed T/S data is provided making this most robust sound velocity tool for use by the Indian Navy

Android App for Argo Floats

INCOIS has deployed more than 400 Argo floats till now and soon reaching a special milestone of 500 Indian Argo floats. In this context there is a necessity to have a unique application by which scientists can effectively and efficiently track all the information of these floats and also monitor the active floats among them regularly. The present work describes about an Android application or app which eases the work of researchers to track the information of these Argo floats as well as monitor them regularly. This app is designed and developed to give all the information related to Argo floats like its various types, its deployed positions, its current positions, its functionality, search option, etc., in the form of maps and charts in turn uses real time data to give latest status of Argo floats. In addition to it, this app is also useful in advising the scientists involved in Argo program about the floats in danger of getting grounded or beached that need immediate attention. This app is a very useful tool for the scientists to check the current status of Argo floats from anywhere or anytime using a smart phone

On the possible use of satellite fixed positions for Argo profiles in case of GPS failures

INCOIS had deployed iridium based PROVOR Bio-Argo floats obtained from NKE, France. These floats are fitted with GPS for obtaining accurate position of the Argo profiles. However there are cases where in the GPS fitted with the Argo floats tend to give wrong positions owing to unknown reasons. In this present work we discuss the possibilities of using the Iridium satellite fixed position in case of GPS failures. For this, analysis was done by comparing the GPS and satellite fixed profiles positions of good floats. These statistics can be used for using the satellite fixed position in case of GPS failures. For each comparison the satellite fixed position with least circular error probability (CEP) radius was chosen. The study suggested that on a average the satellite fixed positions tend to differ from the GPS fixed positions by 0.03 degrees. CEP radii are found to be consistent with the difference between satellite fixed position and GPS position. Based on this we suggest a quality flag of 2 for positions with CEP radius <=4 and flag 4 for any other positions

Argo data quality control based on climatological convex hulls

This report discusses a new method of identifying erroneous data in temperature and salinity (T/S) profiles measured by Argo profiling floats. The proposed method uses World Ocean Atlas 2009 (WOA09) climatology to classify good against bad data. An 'n' sided polygon (convex hull) with least area encompassing all the points is constructed based on the Jarvis March algorithm. The mean and standard deviation fields of temperature and salinity obtained from WOA09 corresponding to each standard depth are used for building these polygons. Subsequently Points In Polygon (PIP) principle which is implemented using ray casting algorithm is used to classify the T/S data as within or without acceptable bounds. It is observed that various types of anomalies in the Argo profile data viz., spikes, bias, sensor drifts etc can be identified using this method

MaMeAT - A tool for visualizing marine meteorological data for Naval applications

This report discusses various functionalities of tool developed for use by Naval Operations Data Processing and Analysis Centre (NODPAC) a wing of Indian Navy. The data for this tool is obtained from the Indian Meteorological Department (IMD), Naval Operations Data Processing and Analysis Centre (NODPAC) and individual records of International Comprehensive Ocean-Atmosphere Dataset (ICOADS). These data sets are processed, quality controlled and merged to form a unique data set for enhancing the marine met climatology of Indian Ocean. The IMD and NODPAC data are compared with the unique records from COADS and duplicates are eliminated. With addition of around 12% unique records to ICOADS data, enhanced climatology is regenerated. With this base data, Graphic User Interface (GUI) based tool is build for visualizing parameters viz., SST, SLP, Wind, Relative Humidity, SSS and bathymetry. This tool has capability to generate climatology dynamically between any chosen periods apart from visualizing various plots which are useful for Navy while at sea. Also provision for adding newly observed marine met data is provided making this most robust tool for use by the Indian Navy

INCOIS-Real time Automatic Weather Station(IRAWS) dataset - Quality control and significance of height correction

The INCOIS-Real time Automatic Weather Station(IRAWS) program was started in the year 2009 and was first installed onboard ORV Sagar Nidhi. Currently, there are 36 ships carrying IRAWS setup. Apart from storing one minute observations in the log onboard the ship, hourly averaged observations are reported through INSAT satellite communication. This report briefs about the hourly dataset of IRAWS and its quality control. In this report, QC results of SST and all meteorological parameters except radiation parameters is discussed. Specific quality check was applied to wind speed (WS) and sea surface temperature (SST) observations. The WS observations measured onboard few ships had a dimensional correction and SST was observed only on few ships. As SST observations are required to compute meteorological variables like DBT, RH, WS to standard height of 10 m, level-3 dataset of AVHRR SST was utilized in place of IRAWS SST wherever the data is found to be faulty. On similar terms bias correction could not be applied to IRAWS SST with the help of AVHRR SST as the error in SST observations are due to the failure of sensor. However all those IRAWS SST observations that passed the QC check were observed to be of high quality and have a correlation coefficient of 0.5 with AVHRR SST and is significant at 95% significant level. Apart from SST and radiation observations, all other parameters observations are found out to be of good quality with 70 to 90 QC pass percentage . Apart from the details of QC check, significance of representing climate variable at a homogeneous standard height is also shown in this repor

A Roadmap for Unified Ocean Modeling and Forecasting system for INCOIS

INCOIS, being the nodal organization to provide operational oceanographic services, is actively involved in the numerical modeling of ocean circulation, waves, tsunami and storm-surge as well as regional coupled ocean-atmosphere models for the prediction of track and intensity of tropical cyclones. In order to optimise the models used in INCOIS for these activities and to make a seamless prediction system from global to regional domains, it was decided to have a revisit on the ocean modeling efforts of INCOIS. Outcome of this review as well as a proposal to develop a seamless prediction system is documented in this report. It is envisaged that this document will be used as a guideline for the future ocean modeling efforts in INCOI

More than 50 years of successful continuous temperature section measurements by the global expendable bathythermograph network, its integrability, societal benefits, and future

The first eXpendable BathyThermographs (XBTs) were deployed in the 1960s in the North Atlantic Ocean. In 1967 XBTs were deployed in operational mode to provide a continuous record of temperature profile data along repeated transects, now known as the Global XBT Network. The current network is designed to monitor ocean circulation and boundary current variability, basin-wide and trans-basin ocean heat transport, and global and regional heat content. The ability of the XBT Network to systematically map the upper ocean thermal field in multiple basins with repeated trans-basin sections at eddy-resolving scales remains unmatched today and cannot be reproduced at present by any other observing platform. Some repeated XBT transects have now been continuously occupied for more than 30 years, providing an unprecedented long-term climate record of temperature, and geostrophic velocity profiles that are used to understand variability in ocean heat content (OHC), sea level change, and meridional ocean heat transport. Here, we present key scientific advances in understanding the changing ocean and climate system supported by XBT observations. Improvement in XBT data quality and its impact on computations, particularly of OHC, are presented. Technology development for probes, launchers, and transmission techniques are also discussed. Finally, we offer new perspectives for the future of the Global XBT Network