Geo-Marine & Geomatics Research Laboratory
School of Earth, Ocean & Climate Sciences
Indian Institute of Technology Bhubaneswar
Ocean Sciences
The recent 2020 Atlantic Hurricane Season was the most active, with 31 storms. September was the most active month of the season, with a simultaneous occurrence of five storms. This study probed into the meteorological and oceanographic conditions prevailing in the Atlantic Main Development Region (MDR) during the high activity months of August, September, and October of 2020. The mean sea surface temperature (SST) for the month of September 2020 was around 0.2 °C higher than the 30 years climatological average. Vertical wind shear (WSH) was well below the threshold for cyclogenesis, with a mean of ~ 5 m/s. Such conditions favoured the consecutive storm formations in the basin. Statistical sensitivity analysis was extended for the above three months of 1991–2020, using SST, WSH, and low-level relative vorticity (VOR) as predictors. The analysis showed mean difference between MDR and tropical region SST (SSTDIFF) to be a better influencer of hurricane count (HC) variability, with r2 values of 0.43 and 0.35 for the months of August and October of 1991–2020 period, respectively. VOR was found to be the dominant influencer of hurricane activity in the month of September...
A standard method for estimating alongshore windstress (AWS) and related cross-shore Ekman transport (ET) is proposed. In the absence of standard methodologies for estimating coastal angles required for AWS estimation, an estimation is typically derived on a case-to-case basis, often approximating entire coastlines with a single line segment. A novel standard parametric method for estimating this coastal angle is developed in this manuscript consisting:
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Computation of Coastal Angle from Global Self-consistent Hierarchical High-resolution Shoreline (GSHHS) coastline data through line simplification
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Estimation of Windstress components at coastal points from Copernicus Marine Environment Monitoring Service (CMEMS) wind data
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Estimation of AWS and associated Ekman Transport
Monsoon winds drive upwelling along the eastern coast of India. This study examined the role of coastally trapped Kelvin waves in modulating the seasonal variability of local alongshore windstress (AWS)-driven coastal upwelling along the western Bay of Bengal. The winds generated AWS resulting in a positive cross-shore Ekman transport (ET) from March to the end of September, which forced coastal upwelling along the eastern coast of India. However, coastally trapped Kelvin waves could also modulate this process by raising or lowering the thermocline. Remotely sensed windstress, sea surface temperature (SST), and sea surface height anomaly (SSHA) were used to compute the AWS (the wind-based proxy upwelling index) and an SST-based proxy upwelling index (UISST). A new parametric method of the estimation of coastal angles was developed to estimate the AWS and ET. Coastal upwelling and the Kelvin waves were identified based on the climatology of SSHA, AWS, and UISST, in addition to a complex principal component (CEOF) analysis of the SSHA...
Indian Space Research Organisation (ISRO) launched SCATSAT-1 scatterometer, on 26 September 2016 as a continuation and enhancement of OSCAT onboard OceanSat-2. The present work carries out a detailed inter-comparison of swath-wise level 2B data from SCATSAT-1 with in situ winds from three moored buoy arrays: Global Tropical Moored Buoy Array (GTMBA), National Data Buoy Center (NDBC) and Ocean Moored Buoy Network for northern Indian Ocean (OMNI). To assess the agreement between the satellite and in situ …
Tropical cyclone (TC) landfalls are among the most damaging natural disasters. The North Indian Ocean (NIO) experiences ~12% of all cyclones every year. TC damage is primarily due to high wind gusts, rainfall, storm surges, waves and coastal flooding which pose serious risks to life, property and coastal ecosystems. Extreme wave activities, vegetation loss due to gale winds and saltwater intrusion during coastal inundation cause coastal erosion and turn agricultural land infertile over extended periods of time. The rate of TC devastation also depends on coastal Land Use and Land Cover (LULC: vegetation density, barren lands, agricultural fields, etc.)...
Eddies are known to play a crucial role in the sudden intensification of tropical cyclones. In this study, Sea Level Anomaly (SLA) data from satellite altimetry is utilized to investigate the role of eddies on tropical cyclones intensification in the North Indian Ocean (NIO) basin. SLA data obtained from Archiving Validation and Interpretation of Satellite Data in Oceanography (AVISO), Tropical Cyclone Heat Potential (TCHP) from National Remote Sensing Centre (NRSC) and cyclone intensity data from Indian Meteorological Department (IMD) have been utilized to analyse and understand the impact of TCHP and eddies on 60 tropical cyclones in the NIO spanning the years 2001–2018. Out of these 60 cyclones, 38 were formed in the Bay of Bengal (BoB) and 22 in the Arabian Sea (AS)...
Monitoring of total suspended matter (TSM) concentration in the coastal waters is vital for water quality monitoring and coastal management. In this study, TSM over the highly dynamic Hooghly estuary region is derived using moderate resolution imaging spectroradiometer (MODIS) surface reflectances at 645 nm and in situ TSM observations. MODIS TSM products show a correlation of 0.95, root-mean-square error of 24.72 g/m 3 , and mean absolute and percentage errors of 18.25 g/m 3 and 23.2%, respectively, ...
Impact of COVID-19 lockdown in the Hooghly estuarine region, India, is assessed using the Total Suspended Matter (TSM) concentration. Estimation of TSM is performed using Landsat 8/OLI and an inter-comparison of TSM load during the pre-lock down and lockdown period is done. It is observed that during the lockdown period, TSM reduced by 30 - 50%. This is a significant observation considering the ecological balance of the region and the fact that it is home to the largest mangroves in the world. This change in suspended matter presumably reflects the influence of reduction in anthropogenic activities owing to COVID-19 lockdowns such as industries, closure of shipping activities (through less dredging) and brick kilns (through less sediment removal), ...
Latent Heat Flux (LHF) and Sensible Heat Flux (SHF) are the two important parameters in air-sea interactions and hence have significant implications for any coupled ocean-atmospheric model. These two fluxes are conventionally computed from met-ocean parameters using bulk aerodynamic formulations; or the Coupled Ocean Atmosphere Response Experiment (COARE) bulk flux algorithms. Here COARE 3.5 algorithm is used to estimate the heat flux from two Ocean Moored Buoy Network for northern Indian Ocean (OMNI) buoy met-ocean observations in Arabian Sea (AS) ...
Seasonal and interannual variations of Chlorophyll-a concentrations in Agulhas return current region
The Agulhas Return Current (ARC) is one of the current systems in the Southern Indian Ocean (SIO) associated with high Chlorophyll-a Concentrations (CC). This work presents the seasonal and inter-annual variability of the CC during 2003–2017 in three different regions along the ARC pathway, which are selected based on the circulation pattern, bathymetry, and local dynamics. The parts are the retroflection region (R1), middle (R2), and end (R3) of the ARC. The analysis of the CC variability revealed the highest variability of CC in the R3 region, followed by R1, and the least variability in R2 for the entire study period. The CC is high during the austral summer ...
Sea-ice extent is very sensitive to climate change and its minor variations can significantly affect the regional biota of the Southern Ocean (SO). Chlorophyll-a concentration (Chl-a) is a primary proxy for the understanding of phytoplankton distribution and primary productivity in the oceans. Therefore, analysing the relation between Chl-a and sea-ice extent could be significant in understanding the role of SO sea-ice extent on regional Chl-a variability. Local Chl-a variability in the SO was analysed in five major sectors, utilizing 39 years of remotely sensed sea ice and 15 years of Chl-a ...
The North Indian Ocean (NIO) experiences frequent tropical cyclones (TCs). TC heat potential (TCHP) is a major ocean parameter responsible for TC genesis and intensification changes. In this study, Indian National Centre for Ocean Information Services-Global Ocean Data Assimilation System (INCOIS-GODAS) model and satellite-derived TCHP data from National Remote Sensing Centre (NRSC) and National Oceanic and Atmospheric Administration (NOAA) are validated against TCHP from in situ profiles in the NIO during the period 2011–2013 for buoys and during 2005–2015 for Argo data. ...
The SARS-CoV-2 (or COVID-19) lockdown in India, which started at an early stage of its infection curve, has been one of the strictest in the world. Air quality has improved in all urban centers in India, a major emitter of greenhouse gases (GHG). This study is based on the hypothesis that an abrupt halt in all urban activities resulted in a massive decline in NO2 emissions and has also altered coastal nitrogen (N) inputs; in-turn, this affected the trophic status of coastal waters across the country. We present the first evidence of an overall decline in pre-monsoon chlorophyll-a, a proxy for phytoplankton biomass, in coastal waters off urban centers during the peak of the lockdown in April. ...
Temporal evolution of biophysical properties of Bay of Bengal (BoB) was measured using an Argo float equipped with fluorescence sensor (BGC-float) during the winter monsoon of 2013–2014. This season was subjected to intense vertical mixing due to the passage of several cyclonic storms beginning with ‘Phailin’ in October to ‘Madi’ in December 2013. These events had resulted in anomalous chlorophyll bloom (> 0.9 mg/l) together with an increase of ~ 1 PSU in the surface salinity and a drop-in temperature (~ 1 °C) in the southwestern BoB. The event was well captured by a BGC-float (WMO ID 2902086) ...
Chlorophyll-a can be used as a proxy for phytoplankton and thus is an essential water quality parameter. The presence of phytoplankton in the ocean causes selective absorption of light by chlorophyll-a pigment resulting in change of the ocean color that can be identified by ocean colour remote sensing. The accuracy of chlorophyll-a concentration (Chl-a) estimated from remote sensing sensors depends on the bio-optical algorithm used for the retrieval in specific regional waters. In this work, it is attempted to estimate Chl-a from two currently active satellite sensors with relatively good spatial resolutions considering ocean applications. Suitability of two standard bio-optical Ocean Colour (OC) Chlorophyll algorithms, OC-2 (2-band) and OC-3 (3-band) in estimating Chl-a for turbid waters of the northern coastal Bay of Bengal is assessed. Validation with in-situ data showed that OC-2 algorithm gives an estimate of Chl-a with a better correlation ...
The North Indian Ocean (NIO) is home to severe depressions and frequent Tropical Cyclones (TCs). TCs are largely influenced by TC Heat potential (TCHP), a major ocean parameter responsible for genesis, intensification changes, as well as their propagation tracks. Hence, accurate estimation of TCHP is highly essential for better prediction of TC track and intensity changes. Conventionally, TCHP is estimated from in situ ocean temperature and salinity profiles. However, owing to the spatio-temporal limitations of in situ measurements, estimation of TCHP from satellite observations of ocean parameters namely, Sea Surface Temperature (SST) and Sea Surface Height Anomaly (SSHA) have attained significance in recent times. In order to examine the reliability of satellite based TCHP estimates and a view to fine-tune retrieval algorithms if necessary, satellite based delayed-time (DT) TCHP data from National …
First results from a systematic harmonic analysis of HF radar (HFR) derived ocean surface current observations in the northwestern Bay of Bengal (BoB) during 2010 is presented. The daily-averaged HFR currents compared reasonably well to composite daily surface currents from multiple satellites with correlation coefficient of 0.90 (0.69) for zonal (meridional) component. A set of sequential daily currents demonstrated sustained northward (southward) alongshore flow during February–April (October–December) with peak magnitude of about 1.8 (1.2) m/s. On tidal scales, harmonic analyses of zonal and meridional components at nearshore and offshore locations indicated that among semi-diurnal tidal components, ...
This paper presents the first results on comparisons of Scatterometer Satellite-1 (SCATSat-1) derived wind datasets with the in situ, reanalysis as well as another operational scatterometer derived winds in the Bay of Bengal during the period November 2016-March 2017. The comparisons of daily gridded wind products of SCATSat-1 with buoys show good correlations (>0.83), higher skill scores (>0.92), and lower root mean square errors (RMSEs) of 0-2 m/s for wind speeds (WS) at the buoy locations. Similarly, the results corresponding to wind directions (WD) show higher correlations (>0.95), higher skill scores (>0.96), and relatively lower RMSEs (15-30°). Further, the intercomparisons of SCATSat-1 with Advanced Scatterometer and European Centre for Medium Range Weather Forecasts reanalysis winds show strong correlations for both WS (>0.85) and WD (>0.94). This paper also reports the capability of …
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 ...
SARAL/AltiKa, a joint Ka-band altimetry mission of the Centre National d’Etudes Spatiales (CNES) and Indian Space Research Organisation (ISRO) was successfully launched on February 25, 2013. The main purpose of this mission is to explore the ocean surface topography. As it is a Ka-band altimeter mission unlike other altimeters which were primarily in Ku-band, it is essential to calibrate and validate AltiKa data products before using the data for oceanographic applications. With this objective, two important geophysical parameters, Significant Wave Height (SWH) and Wind Speed (WS) from SARAL/AltiKa are inter-compared with those from 18 moored buoy stations in the North Indian Ocean (NIO) for a two year period from March 2013 to March 2015 ...
SARAL/AltiKa (AltiKa), a Ka-band altimeter is a joint Indo-French satellite mission launched on 25th February, 2013 by Indian Space Research Organization (ISRO). During the calibration/validation phase of the mission, it is essential to calibrate this altimeter and evaluate its performance for further use by the oceanographers' community. With this objective, geophysical parameters namely significant wave height (SWH), wind speed (WS), and sea surface height anomaly (SSHA) from Jason-2 are used to assess the performance of AltiKa quantitatively. Additionally, certain supporting direct and indirect measurements from altimeters and radiometers onboard the two missions like normalized backscatter coefficient (Sigma0), brightness temperature (TB), water vapor (WV), and corresponding ionospheric corrections (IC) have also been analyzed ...
Changes in sea ice extent are strong modulators of climate change as well as indicator of the effect of global warming. The ocean-atmospheric heat budget is also affected by the sea ice dynamics owing to reflection of solar radiation back to the space by sea ice cover. In the present work, we have analysed about 30 years of sea ice data (1981–2013) over the Antarctic and Arctic regions using 25 km spatial resolution re-gridded data products obtained from National Snow and Ice Data Centre (NSIDC), USA. These sea ice data products result from combined observations by the Scanning Multi-channel Microwave Radiometer (SMMR) on Nimbus-7 platform and a series of Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) instruments on board the Defense Meteorological Satellite Program (DMSP) satellites.
Sea surface temperature (SST) is an essential parameter for describing ocean circulation and dynamics in the study of upper ocean physical and biogeochemical processes. In conjunction with other metocean parameters, SST is used in the estimation of latent and sensible heat fluxes which are indicative of air-sea exchanges of heat. Studying the variations of SST over a long period is thus important in understanding the nature of global climate change. Classically SST is measured using conventional techniques, but satellite derived SST have advantages of synoptic view and temporal coverage.
Oceansat-2 scatterometer (OSCAT) is an active microwave sensor, intended to provide ocean surface wind vectors over the global oceans. In the present work, an attempt has been made to generate daily composites of OSCAT Level-3 (L3) wind vectors using Data-Interpolating Variational Analysis (DIVA) method from ascending and descending passes over the Indian Ocean region. This could be useful for operational purposes and in generating value-added products like wind stress and curl of wind stress. The daily composite wind vectors of zonal (U) and meridional (V) components have been validated by comparing with Advanced Scatterometer (ASCAT) and wind from in situ buoys for the year 2012. Wind composites thus generated using DIVA are found to match well with in situ, and ASCAT wind products ...
The derivation of geophysical parameters from satellite-measured brightness temperature (T B ) is an important aspect of satellite remote sensing. This primarily involves the development of complex inversion algorithms and empirical relations comprising T B and in situ data for parameter retrieval and algorithm validation. In the present work, an artificial neural-network model was used to simultaneously obtain sea-surface wind speed (WS) and sea-surface temperature (SST) utilizing T B from eight channels (including vertical and horizontal polarizations) of a multi-frequency scanning microwave radiometer onboard the Indian Remote Sensing Satellite (IRS-P4) and deep-sea ocean buoys in the North Indian Ocean region. The values obtained from the artificial neural network were then compared with actual in situ observations as a test for the performance of the model ...
Expansion of oligotrophic ocean gyre and widespread reduction of phytoplankton biomass will have severe environmental and ecological effect since phytoplankton accounts for half of the global primary production, which forms the trophic base for marine ecosystem. Analysis of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) derived chlorophyll-a (Chl-a) datasets (1998–2010) suggested significant expansion of South Indian Ocean oligotrophic gyre (SOG) at average annual rate of 4.46%/yr (r= 0.66, p= 0.013). The annual trend of SOG expansion was accompanied with the significantly declining trend of Chl-a concentration (− 1.36%/yr, or− 0.0007±0.0001 mg m− 3/yr, r= 0.76, p= 0.002) ...
In most cyclone prediction models, sea surface temperature (SST) is the only oceanographic input, even though storms are known to be impacted by the thermal energy available through oceanic heat content, not just by SST alone. In the tropical Indian Ocean (TIO; 30 ° S -30 ° N, 30-120 ° E), there are no studies that examine the relationship between instantaneous cyclone intensity (CI) and SST as a function of time. Here, we explore that relationship using SST data from the Tropical Rainfall Measuring Mission Microwave Imager and CI data (maximum sustained winds) from the Joint Typhoon Warning Centre. We find that out of 75 TIO cyclones studied during 1998-2011, more than 50% of the cyclones have no significant correlation between CI and SST. The numbers having significant negative (positive) correlations are 31 (3), 13 (10), and 17 (14) with SST leading CI by one, two, and three days, ...
Variability of Sea level and its steric contribution in the Tropical Indian Ocean (TIO) was studied based on 15 years (1993–2007) satellite altimeter observations of sea surface height (SSH) anomaly and steric height (STH) anomaly computed using temperature and salinity fields obtained from Simple Ocean Data Assimilation (SODA) product. Complex Empirical Orthogonal Function (CEOF) analysis was carried out to decompose variability of SSH and STH into various modes to examine the coherency between them. It is revealed that both the parameters exhibit variability in all the time scales. First three major modes of CEOF corresponds to 90% and 84% of the total variability of SSH and STH respectively. There exists strong coherence between the respective CEOF modes of SSH and STH ...
The biophysical effects of a storm in the most oligotrophic waters of the South Indian Ocean (SIO) subtropical gyre have been investigated by conjunctive analyses using space-borne sensors and in situ observations. The most oligotrophic waters of the SIO are identified using more than 8-years of chlorophyll-a images derived from Aqua-Moderate Resolution Imaging Spectroradiometer (Aqua-MODIS). Earlier studies revealed that the source of oceanic primary production enhancement in these oligotrophic waters has remained inconclusive. However, the present study succeeded in attributing the cyclone, named Edzani, which passed over these waters and to be responsible for enriching the chlorophyll-a pigment, lowering of sea surface temperature (SST) and deepening of mixed layer ...
This work attempts to predict bathymetry from satellite altimeter based gravity in the Arabian Sea. A collocated match-up database (n = 17,016) was created on Multibeam Echosounder (MBES) bathymetry and satellite gravity values (∼1 min spatial resolution) derived from remote sensing satellites. A Radial Basis Function (RBF) based Artificial Neural Network (ANN) model was developed to predict bathymetry from satellite gravity values. The ANN model was trained with variable undersea features such as seamount, knoll, abyssal plain, hill, etc. to familiarize the network with all possible geomorphic features as inputs through learning and the corresponding target outputs ...
Owing to the importance of middle atmosphere, recently, a Middle Atmospheric Dynamics (MIDAS) program was carried out during the period 2002–2007 at Thumba (8.5°N, 77°E). The measurements under this program, involving regular radiosonde/rocket flights as well as atmospheric radars, provided long period observations of winds and temperature in the middle atmospheric region from which waves and oscillations as well as their forcing mechanisms particularly in the low-latitude middle atmosphere could be analyzed. However, a detailed analysis of the forcing mechanisms remains incomplete due to the lack of important measurements like ozone which is a significant contributor to atmospheric dynamics. Presently, profiles of ozone are available from TIMED/SABER (Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics/Sounding of the Atmosphere using Broad Emission Radiometry …
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 …
Measurements of atmospheric temperature profiles in the troposphere and lower stratosphere were made over Thumba Equatorial Rocket Launching Station (TERLS) (8.5° N, 76.9° E) during a partial solar eclipse (22 July 2009) and an annular solar eclipse (15 January 2010). It was observed that during the partial solar eclipse, the temperature decreased by 2–3 °C in the vicinity of the tropopause and in the lower stratosphere the temperature increased by ~2.6 °C during the maximum phase of the partial solar eclipse. During the annular solar eclipse, a temperature reduction of ~2 °C was observed around the tropopause. This study also revealed a feature of delayed effect in the form of a very intense warming of ~8 °C at 18 km after about 4 h of the annular solar eclipse. The Cold-Point Tropopause (CPT) temperature increased slowly before the beginning of the eclipse (up to 10:00 IST) and during the maximum phase of the eclipse, the difference in CPT temperature and height was −3.5 °C and ~110 m, respectively, as that of the control day ...
Indian Remote Sensing Satellite Multifrequency Scanning Microwave Radiometer (MSMR)-measured brightness temperatures ( T B ) in 6.6-, 10.65-, 18-, and 21-GHz channels with dual polarizations were utilized to retrieve sea-surface wind speed (SSWS). A concurrent and collocated database was constructed on MSMR T B - and deep-sea (DS)-buoy-recorded wind speeds for the period of June 1999-July 2001 over the north Indian Ocean. A radial-basis-function-based artificial-neural-network (ANN) algorithm was developed to estimate SSWS from MSMR T B values. Multiple ANNs were generated by the systematic variation of the architecture of input- and hidden-layer nodes. The performance of the most successful algorithm was evaluated based on statistical summary and network performance. The accuracy of the ANN-based wind-speed algorithm was compared with DS-buoy observations, and the result …
Spatial and temporal distribution of sonic layer depth (SLD) in the Arabian Sea (AS) was studied using temperature and salinity (T/S) profiles from Argo floats during the years 2003–2004 and World Ocean Atlas 2001 (WOA01) climatology. SLD was obtained from sound velocity profiles computed from T/S data. SLD variability as obtained from Argo matched well with those obtained from the WOA01 in certain locations and showed remarkable difference in some other. SLD variability in the AS is mainly related to seasonal variations in T/S owing to influence of seasonal phenomena as well as the geography of the region. Deeper SLDs were observed during summer monsoon (> 90 m) and winter monsoon (> 80 m) respectively. Up-welling and down-welling (Ekman dynamics) associated with the Findlater Jet controlled SLD during the summer monsoon. While in winter monsoon, cooling and convective mixing regulated SLD in the study region ...
Turbulent surface heat fluxes (latent and sensible heat) are the two most important parameters through which air–sea interaction takes place at the ocean–atmosphere interface. These fluxes over the global ocean are required to drive ocean models and to validate coupled ocean–atmosphere global models. But because of inadequate in situ observations these are the least understood parameters over the tropical Indian Ocean. Surface heat fluxes also contribute to the oceanic heat budget and control the sea surface temperature in conjunction with upper ocean stratification and ocean currents. The most widely used flux products in diagnostic studies and forcing of ocean general circulation models are the ones provided by the National Centres for Environment Prediction (NCEP) reanalysis. In this study we have compared NCEP reanalysed marine meteorological parameters, which are used for turbulent …
The seasonal variability of sonic layer depth (SLD) in the central Arabian Sea (CAS) (0 to 25°N and 62-66°E) was studied using the temperature and salinity (T/S) profiles from Argo floats for the years 2002–2006. The atmospheric forcing responsible for the observed changes was explored using the meteorological data from NCEP/NCAR and Quickscat winds. SLD was obtained from sound velocity profiles computed from T/S data. Net heat flux and wind forcing regulated SLD in the CAS. Up-welling and down-welling (Ekman dynamics) associated with the Findlater Jet controlled SLD during the summer monsoon. While in winter monsoon, cooling and convective mixing regulated SLD in the study region. Weak winds, high insolation and positive net heat flux lead to the formation of thin, warm and stratified sonic layer during pre and post summer monsoon periods, respectively.
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 …
Mixed layer depth (MLD) is an important oceanographic parameter. However, the lack of direct observations of MLD hampers both specification and investigation of its spatial and temporal variability. An important alternative to direct observation would be the ability to estimate MLD from surface parameters easily available from satellites. In this study, we demonstrate estimation of MLD using Artificial Neural Network methods and surface meteorology from a surface mooring in the Arabian Sea. The estimated MLD had a root mean square error of 7.36 m and a coefficient of determination (R2) of 0.94. About 67% (91%) of the estimates lie within ± 5 m (± 10 m) of the MLD determined from temperature sensors on the mooring.
The seasonal and spatial variability of mixed layer depth (MLD) was examined in the Western Indian Ocean (WIO) (30E – 80E and 10S – 30N) for three consecutive years starting from June 2002 – May 2005 using Argo temperature and salinity (T/S) profiles. These were compared with MLD estimates from World Ocean Atlas 2001 (WOA01) T/S data. Temporal and spatial variability of MLD estimated from Argo T/S profiles were found to correspond well with the MLD obtained from WOA01 T/S data. However, slight deviations in the form of months of occurrence of minima and maxima MLDs were observed. MLD from WOA01 climatology is underestimated compared to MLD from Argo for almost the entire three years of study. It is also observed that MLD variability features as brought out by both the data sets followed the dynamics that govern the mixed layer variability in this region.
Satellite remote sensing provides diverse and useful ocean surface observations. It is of interest to determine if such surface observations can be used to infer information about the vertical structure of the ocean's interior, like that of temperature profiles. Earlier studies used either sea surface temperature or dynamic height/sea surface height to infer the subsurface temperature profiles. In this study we have used neural network approach to estimate the temperature structure from sea surface temperature, sea surface height, wind stress, net radiation, and net heat flux, available from an Arabian Sea mooring from October 1994 to October 1995, deployed by the Woods Hole Oceanographic Institution. On the average, 50% of the estimations are within an error of ±0.5°C and 90% within ±1.0°C. The average RMS error between the estimated temperature profiles and in situ observations is 0.584°C with a depth‐wise …