T. V. S. Udaya Bhaskar

A new atlas of temperature and salinity for the North Indian Ocean

The most used temperature and salinity climatology for the world ocean, including the Indian Ocean, is the World Ocean Atlas (WOA) (Antonov et al 2006, 2010; Locarnini et al 2006, 2010) because of the vast amount of data used in its preparation. The WOA climatology does not, however, include all the available hydrographic data from the Indian Exclusive Economic Zone (EEZ), leading to the potential for improvement if the data from this region are included to prepare a new climatology. We use all the data that went into the preparation of the WOA (Antonov et al 2010; Locarnini et al 2010), but add considerable data from Indian sources, to prepare new annual, seasonal, and monthly climatologies of temperature and salinity for the Indian Ocean. The addition of data improves the climatology considerably in the Indian EEZ, the differences between the new North Indian Ocean Atlas (NIOA) and WOA being most significant in the Bay of Bengal, where the patchiness seen in WOA, an artifact of the sparsity of data, was eliminated in NIOA. The significance of the new climatology is that it presents a more stable climatological value for the temperature and salinity fields in the Indian EEZ.

Observed interannual variability of near-surface salinity in the Bay of Bengal

An in situ gridded data of salinity, comprising Argo and CTD profiles, has been used to study the interannual variability of near-surface salinity (within 30 m from sea surface) in the Bay of Bengal (BoB) during the years 2005-2013. In addition to the broad agreement with earlier studies on the north-to-south gradient of surface salinity and general features of seasonal variability of salinity, the data also revealed few episodes of enhanced freshening in the BoB. The observations showed distinct anomalous low salinity (< 2 psu) waters in the northern BoB during June-February of the years 2006-2007 (Y67), 2011-2012 (Y12), and 2012-2013 (Y23). The anomalous freshening during these years showed similar life cycle, such as, it starts in the northern BoB during July-September of current summer and extends up to February-March of next winter with a southward propagation. Analysis showed that the oceanic and atmospheric conditions associated with positive Indian Ocean Dipole (pIOD) lead to these freshening events, and IOD rather than El NiA±o/Southern Oscillation (ENSO) controls the interannual variability of salinity in the BoB. The mixed layer salt budget analysis indicated the dominant role of local fresh water flux (horizontal advection) on the observed salinity tendency during summer (winter) monsoon season. Enhanced precipitation associated with pIOD lead to enhanced freshening in northern BoB during June-September, which remained to this region with prevailing summer monsoon circulation. The weakening or absence of southward east India coastal current (EICC) during October-December of these freshening years trapped anomalous freshwater in the northern BoB. Key Points Anomalous freshening observed in BoB in 3 years Positive IOD initiate the freshening events in northern BoB Salt budget analysis resolve contributions from different processes © 2015. American Geophysical Union. All Rights Reserved.

Comparison of AMSR-E and TMI sea surface temperature with Argo near-surface temperature over the Indian Ocean

Sea surface temperature (SST) measurements from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared with near‐surface temperature (foundation SST) in situ measurements obtained from Argo floats over the Indian Ocean. Spatial variation was compared for 2002–2006 and 11 floats were used for temporal variation collocated observations. The results show that TMI and AMSR‐E SST measurements are slightly overestimated during the pre‐ and post‐monsoon seasons and underestimated during the monsoon season. Statistical analysis shows that the SST from the AMSR‐E is better correlated with the Argo foundation SST compared to the TMI. The standard deviation (SD) and root mean square error (RMSE) for AMSR‐E SST are 0.58°C and 0.35°C, respectively, over the Equatorial Indian Ocean (EIO). The corresponding values for the TMI are 0.66°C and 0.47°C. Over the Arabian Sea the SD values are slightly higher compared to the EIO values, whereas RMSE values are less for both TMI and AMSR‐E SST. These retrieval accuracies are above the expected retrieval accuracy. The seasonal average spatial distribution of AMSR‐E SST shows a better match with the Argo foundation SST compared to TMI SST distributions. The robustness of the good spatial match during the monsoon season may be attributed to strong winds.

Mixed layer variability in Northern Arabian Sea as detected by an Argo float

Seasonal evolution of surface mixed layer in the Northern Arabian Sea (NAS) between 17° N–20.5° N and 59° E-69° E was observed by using Argo float daily data for about 9 months, from April 2002 through December 2002. Results showed that during April - May mixed layer shoaled due to light winds, clear sky and intense solar insolation. Sea surface temperature (SST) rose by 2.3 °C and ocean gained an average of 99.8 Wm−2. Mixed layer reached maximum depth of about 71 m during June - September owing to strong winds and cloudy skies. Ocean gained abnormally low ∼18 Wm−2 and SST dropped by 3.4 °C. During the inter monsoon period, October, mixed layer shoaled and maintained a depth of 20 to 30 m. November - December was accompanied by moderate winds, dropping of SST by 1.5 °C and ocean lost an average of 52.5 Wm−2. Mixed layer deepened gradually reaching a maximum of 62 m in December. Analysis of surface fluxes and winds suggested that winds and fluxes are the dominating factors causing deepening of mixed layer during summer and winter monsoon periods respectively. Relatively high correlation between MLD, net heat flux and wind speed revealed that short term variability of MLD coincided well with short term variability of surface forcing.

Spatio-temporal evolution of chlorophyll-a in the Bay of Bengal: a remote sensing and bio-argo perspective

Argo floats equipped with sensors to measure Dissolved Oxygen, Chlorophyll-a and backscattering are deployed in the Arabian Sea, Bay of Bengal and Southern Indian Ocean as part of Indian Argo program. In this study, abnormal chlorophyll-a bloom observed by a float with WMO ID 2902086 deployed in the south central Bay of Bengal is analyzed. High concentration of chlorophyll > 0.8 mg/l is observed during December 2013. This period is also associated with drop in temperature and increase in salinity. Analysis of data from the bio-Argo float has shown the impact of many cyclones and depressions that occurred during the period. Of particular importance is cyclone ‘Madi’, which passed very near to the position of mentioned float, during December 2013. This is also evident from the satellite based wind observations from OSCAT through curl of wind stress and Ekman pumping. The sub-surface chlorophyll bloom is substantiated by the surface chlorophyll-a values of MODIS during the period. Intense mixing caused due to the passage of cyclone might have resulted in mixing of subsurface waters thereby breaking the stratification of otherwise stable surface waters of Bay of Bengal, enhancing the nutrient supply, which resulted in strong chlorophyll bloom. The subsurface chlorophyll structure of Bay of Bengal and its variability during the passage of cyclone is for the first time revealed by the floats equipped with biological sensors. This work reveals the synergistic application of in-situ (Bio- Argo) and satellite data to monitor the changes in subsurface structure during the passage of cyclones.

Characterization of oceanic Noctiluca blooms not associated with hypoxia in the Northeastern Arabian Sea

Intense blooms of the heterotrophic dinoflagellate, green Noctiluca scintillans, have been reported annually in the Northern Arabian Sea since the early 2000s. Although not known to produce organic toxins, these blooms are still categorized as a harmful due to their association with massive fish mortalities. Recent work has attributed these blooms to the vertical expansion of the oxygen minimum zone, driven by cultural eutrophication from major coastal cities in western India. As diatoms are preferred prey of green Noctiluca scintillans, more frequent blooms of this mixotroph will likely impact the productivity of important fisheries in the region. The present study uses a satellite algorithm to determine the distribution of both diatom and green Noctiluca blooms in the Northeastern Arabian Sea from 2009 to 2016. The results from shipboard microscopy of phytoplankton community composition were used to validate the satellite estimates. The satellite algorithm showed 76% accuracy for detection of green Noctiluca and 92% for diatoms. Shipboard measurements and data from biogeochemical-Argo floats were used to assess the relationship between oxygen concentrations and green Noctiluca blooms in the Northeastern Arabian Sea. Regardless of the presence of a Noctiluca bloom, the dissolved oxygen in the photic zone was always >70% saturated, with an average oxygen saturation >90%. The variability in the relative abundance of diatoms and green Noctiluca is not correlated with changes in oxygen concentration. These findings provide no evidence that cultural eutrophication has contributed to the decadal scale shifts in plankton composition in the Northeastern Arabian Sea oceanic waters. Conversely, the climatic warming of surface waters would have intensified stratification, thereby reducing net nutrient flux to the photic zone and decreasing silicate to nitrate ratios (Si:N); both factors that could increase the competitive advantage of the mixotroph, green Noctiluca, over diatoms. If so, the decadal-scale trajectory of phytoplankton community composition in the Northeastern Arabian Sea may be a harbinger of future climate-driven change in other productive oceanic systems.

Detecting and Correcting the Degradations of Sensors on Argo Floats Using Artificial Neural Networks

Argo floats are autonomous floats designed to measure temperature and salinity of the world oceans. Once deployed these floats goes to as deep as 2000 m and while coming up measure temperature and salinity of the underlying ocean automatically. These floats act as a substitute to the ship-based data sets and currently as many as ~3800 are active in the global oceans. These instruments being autonomous in nature, measure and transmit data seamlessly irrespective of the weather, season, and region. However, the salinity sensors on these floats are sensitive to bio-fouling and can cause degradation to the data. As these are one time deployed and data is continuously obtained they are not available for calibration unlike the instruments on the ship. In this work ANN is used to check the degradation of the sensors and correct the same so that the data can be use in scientific analysis.

Quality control of oceanographic in situ data from Argo floats using climatological convex hulls

Graphical abstract

Relation between tropical cyclone heat potential and cyclone intensity in the North Indian Ocean

Ocean Heat Content (OHC) plays a significant role in modulating the intensity of Tropical Cyclones (TC) in terms of the oceanic energy available to TCs. TC Heat Potential (TCHP), an estimate of OHC, is thus known to be a useful indicator of TC genesis and intensification. In the present study, we analyze the role of TCHP in intensification of TCs in the North Indian Ocean (NIO) through statistical comparisons between TCHP and Cyclone Intensities (CI). A total of 27 TCs (20 in the Bay of Bengal, and 7 in the Arabian Sea) during the period 2005–2012 have been analyzed using TCHP data from Global Ocean Data Assimilation System (GODAS) model of Indian National Center for Ocean Information Services and cyclone best track data from India Meteorological Department. Out of the 27 cyclones analyzed, 58% (86%) in the Bay (Arabian Sea) have negative correlation and 42% (14%) cyclones have positive correlation between CI and TCHP. On the whole, more than 60% cyclones in the NIO show negative correlations between CI and TCHP. The negative percentage further increases for TCHP leading CI by 24 and 48 hours. Similar trend is also seen with satellite derived TCHP data obtained from National Remote Sensing Center and TC best track data from Joint Typhoon Warming Centre. Hence, it is postulated that TCHP alone need not be the only significant oceanographic parameter, apart from sea surface temperature, responsible for intensification and propagation of TCs in the NIO.