Pankajakshan Thadathil

XBT Fall Rate in Waters of Extreme Temperature: A Case Study in the Antarctic Ocean

Abstract XBT fall-rate variation in waters of extreme temperature and the resulting depth error has been addressed using controlled XBT–CTD datasets collected from two cruises in the Southern Ocean. Mean depth errors deduced from both the datasets are significantly different from those reported earlier for tropical and subtropical regions. The comprehensive study of Hanawa et al. (making use of controlled XBT–CTD data, mostly from tropical and subtropical waters) showed that the manufacturers equation underestimates the probes fall rate. This is manifested by the mean negative depth error reported from this region. However, results from the present study show that the manufacturers equation slightly overestimates the fall rate in this region, as indicated by the small positive error (5–10 m). In order to provide theoretical support to the observed depth error, an analytical approach is adopted based on the viscosity effect on the probes fall rate. Observed as well as analytical results suggest that th...

An evaluation of XBT depth equations for the Indian Ocean

For the purpose of finding XBT depth equations applicable to the entire Indian Ocean we carried out experiments through the collection of controlled XBT-CTD data on four cruises. These experiments were conducted in various locations of the Indian Ocean with highly variable physicochemical conditions. We estimated the mean depth error to vary from ! 2t o !27 m in a depth range of 0—750 m, which is comparable to that reported by Hanawa, Rual, Bailey, Sy and Szabados (1995, Deep-Sea Research I 43 (8), 1423—1451; hereafter referred to as HN-95), but is much higher than the manufacturer’s specified accuracy. The coeƒcients of the mean depth-time equation derived from the present data set do not di⁄er significantly from HN-95. Depth error does not seem to be influenced by regional water characteristics. Our analysis confirms the applicability of the HN-95 equation for Indian Ocean as well. ( 1998 Elsevier Science Ltd. All rights reserved.

Surface layer temperature inversion in the Bay of Bengal: Main characteristics and related mechanisms

Surface layer temperature inversion (SLTI), a warm layer sandwiched between surface and subsurface colder waters, has been reported to frequently occur in conjunction with barrier layers in the Bay of Bengal (BoB), with potentially commensurable impacts on climate and postmonsoon tropical cyclones. Lack of systematic measurements from the BoB in the past prevented a thorough investigation of the SLTI spatiotemporal variability, their formation mechanisms, and their contribution to the surface temperature variations. The present study benefits from the recent Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) buoys located in BoB along 90°E at 4°N, 8°N, 12°N, and 15°N over the 2006–2014 period. Analysis of data from these RAMA buoys indicates that SLTI forms after the summer monsoon and becomes fully developed during winter (December–February). SLTI exhibits a strong geographical dependency, with more frequent (80% times during winter) and intense inversions (amplitude, ΔT ∼ 0.7°C) occurring only in the northern BoB compared to central and southern Bay. SLTI also exhibits large interannual and intraseasonal variations, with intraseasonal amplitude significantly larger (ΔT ∼ 0.44°C) than the interannual amplitude (∼0.26°C). Heat budget analysis of the mixed layer reveals that the net surface heat loss is the most dominant process controlling the formation and maintenance of SLTI. However, there are instances of episodic advection of cold, low-saline waters over warm-saline waters leading to the formation of SLTI as in 2012–2013. Vertical processes contribute significantly to the mixed layer heat budget during winter, by warming the surface layer through entrainment and vertical diffusion.

Do cold, low salinity waters pass through the Indo-Sri Lanka Channel during winter?

During winter, along the east coast of India, the near-surface flow is characterized by the southward-flowing East India Coastal Current (EICC) which bends around Sri Lanka and enters into the south-eastern Arabian Sea (AS). This current carries cooler, low-salinity waters from the head Bay of Bengal (BoB) into the south-eastern AS. But due to a lack of any direct in situ measurements, it is not clear whether any part of this current that flows through the Indo-Sri Lanka Channel (ISLC) is significant. An attempt is made in this study to look for any observational evidence for the southward flow of cooler, low salinity waters through the ISLC during winter. In the absence of direct in situ measurements on the observed currents in the non-navigable shallow ISLC, the observed high resolution, advanced very high resolution radiometer (AVHRR) sea surface temperature (SST), and sea-viewing wide field-of-view sensor (SeaWiFS) chlorophyll-a and historic sea surface salinity (SSS) data are utilized as tracers to track any southward water flow through the Pamban Pass and Adams Bridge in the ISLC. The analysis suggests that both the non-navigable shallow Pamban Pass and the Adams Bridge in the ISLC act as barriers and limit the southward flow of cooler, low salinity waters into the Gulf of Mannar in the south during winter.

VALIDATION OF ARGO DATA IN THE INDIAN OCEAN

ARGO -salinity data from the Indian Ocean are validated using salinity from floatversus-float match-ups and also using CTD observations from three cruises. Validation data sets are selected in such a way that the float and the match-up data are collocated with tolerable space-time difference. For validation a time difference of less than 10 days and space difference less than 100 Km have been considered. The evaluation is done using salinity data on theta (potential temperature) surfaces from deeper observations. One of the significant observation of float-versus-float validation is the large random error observed in the initial profiles of the float-salinity compared to later profiles. While the float salinity data is found to be largely in good agreement with the ship based CTD observations, there are cases where the salinity error exceeds the desired 0.01 PSU.

An interactive graphical system for XBT data quality control and visualization

Abstract A PC-based system has been developed for quality control and visualization of expendable bathy thermograph (XBT) data archived at the Indian Oceanographic Data Centre. The system, coded in Visual C++, is user interactive and runs on Windows-95 platform. Quality control module of the system incorporates various quality norms/checks and has two levels; inventory and data levels. Inventory level checks are applied for land–sea position, speed of the vessel, invalid date/time, duplicates and station sounding. Station sounding check is performed based on the ETOPO bathymetry file having 5′×5′ spatial resolution. Although the QCS is developed for quality control and visualization of the XBT data, it could be used for inventory level quality checks of any general oceanographic data. Data quality module involves tests for XBT-specific errors such as surface transient, temperature inversions, fall rate and depth reversal. This level also involves visual inspection of the profiles for identifying and correcting/flagging of features caused by wire stretch, wire break, bowing and nub in the mixed layer. Provision is given to compare individual XBT profiles with neighboring stations and also with 1°×1° monthly climatologies. Quality flags are assigned for each inventory and depth fields. Since data exchange (national and international), under the IODE system, stipulates standard quality flags, the Integrated Global Ocean Observing System recommended flags are applied in the system. Station having data with erroneous or doubtful flags are sent to error bin, which can be accessed by privileged users for possible correction and subsequent modifications in the data base. The data visualization module has options for data queries, selection and graphical presentations, like vertical and horizontal distribution of temperature.