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Remote sensing-based investigation of ice flow dynamics of Polar Record glacier (PRG) during December–April of 2016-2019 has been conducted in this work. Using offset tracking method on the Sentine...

A review is presented on physical oceanographic features based on expendable CTD data collected in the Indian Ocean sector of the Southern Ocean. The thermohaline structure is dominated by Circumpolar Deep Water. The temperature and salinity are affected by cyclonic circulation in the Weddell Sea and Prydz Bay. High chlorophyll-a blooms (2-4 mg m-3) evolve during austral summer due to stratification which is caused by freshwater generated from the sea ice melt and the glacial outflow which traps phytoplankton in a shallow mixed layer, where they are exposed to higher irradiances of photosynthetically active radiation. Attempts have been made to relate the physical characteristics to biomass inferred from data published from previous Indian Scientific expeditions. More in-situ observations related to biophysical and chemical are recommended in the near future projects.

Surface glacier facies are superficial expressions of a glacier that are distinguishable based on differing spectral and structural characteristics according to their age and inter-mixed impurities . Increasing bodies of literature suggest that the varying properties of surface glacier facies differentially influence the melt of the glacier, thus affecting the mass balance. Incorporating these variations into distributed mass balance modelling can improve the perceived accuracy of these models. However, detecting and subsequently mapping these facies with a high degree of accuracy is a necessary precursor to such complex modelling. The variations in the reflectance spectra of various glacier facies permit multiband imagery to exploit band ratios for their effective extraction. However, coarse and medium spatial resolution multispectral imagery can delimit the efficacy of band ratioing by muddling the minor spatial and spectral variations of a glacier. Very high-resolution imagery, on the other hand, creates distortions in the conventionally obtained information extracted through pixel-based classification. Therefore, robust and adaptable methods coupled with higher resolution data products are necessary to effectively map glacier facies. This study endeavours to identify and isolate glacier facies on two unnamed glaciers in the Chandra-Bhaga basin, Himalayas, using an established object-based multi-index protocol. Exploiting the very high resolution offered by WorldView-2 and its eight spectral bands, this study implements customized spectral index ratios via an object-based environment. Pixel-based supervised classification is also performed using three popular classifiers to comparatively gauge the classification accuracies. The object-based multi-index protocol delivered the highest overall accuracy of 86.67%. The Minimum Distance classifier yielded the lowest overall accuracy of 62.50%, whereas, the Mahalanobis Distance and Maximum Likelihood classifiers yielded overall accuracies of 77.50% and 70.84% respectively. The results outline the superiority of the object-based method for extraction of glacier facies. Forthcoming studies must refine the indices and test their applicability in wide ranging scenarios.

Glaciers play a crucial role in the study of the climate change pattern of the Earth. Remote sensing with access to large archives of data has the ability to monitor glaciers frequently throughout the year. Therefore, remote sensing is the most beneficial tool for the study of glacier dynamics. Fed by many tributaries from different sides, the Amery Ice Shelf (AIS) is one of the largest ice shelves that drains ice from the Antarctic ice sheet into the Southern Ocean. This study focuses on the eastern and the western tributaries of the AIS. The primary objective of the study was to derive the velocity of the tributary glaciers and the secondary objective was to compare variations in their velocities between the summer and winter season. This study was carried on using the European Space Agency’s (ESA) Sentinel-1 satellite’s Synthetic Aperture Radar (SAR) data acquired from the Sentinel data portal. Offset tracking method was applied to the Ground Range Detected (GRD) product of the Sentinel-1 interferometric wide (IW) swath acquisition mode. The maximum velocity in summer was observed to be around 610 m/yr in the eastern tributary glacier meeting the ice shelf near the Pickering Nunatak, and around 345 m/yr in the Charybdis Glacier Basin from the western side. The maximum velocity in the winter was observed to be 553 m/yr in the eastern side near the Pickering Nunatak whereas 323 m/yr from the western side in the Charybdis Glacier Basin. The accuracy of the derived glacier velocities was computed using bias and root mean square (RMS) error. For the analysis, the publicly available velocity datasets were used. The accuracy based on RMS error was observed to be 85-90% for both seasons with bias values up to 25 m/yr and root mean square error values up to 30 m/yr.

Significant changes in the interannual variation of Arctic snow and sea ice are connected to changes in the global climate. Retreat of ice sheets/glaciers is due to increased melting in many regions of the cryosphere. Active microwave sensors are frequently used to detect surface melting because of their sensitivity to the liquid water presence in snow/ice. We mapped the annual melt duration and summer melt onset for the Svalbard archipelago using microwave scatterometers flown on QuikSCAT, OSCAT, ASCAT, and OSCAT-2, providing one of the longest continuous records of radar backscatter to estimate snowmelt onset and melt duration on Svalbard spanning 2000–17. A single threshold-based model was used to detect the timing of snowmelt; the threshold was calculated using meteorological data from manned weather stations. The results capture the timing and extent of melt events caused by warm air temperature and precipitation, as a consequence of the influx of moist, mild air from the Norwegian and Barents seas. The highest melt duration and earlier melt onset occurred in southernmost and western Svalbard, in response to the influence of the warm West Spitsbergen Current. Compared to earlier studies, we found considerable interannual variability and regional differences. Though the record is short, there is an indication of an increasing trend in total days of melt duration and earlier summer melt onset date, possibly linked to the general warming trend. Climate indices such as Interdecadal Pacific Oscillation and Pacific Decadal Oscillation are well correlated with onset melt and duration across Svalbard. With the reported year-after-year decrease in sea ice cover over the Arctic Ocean, the trend toward longer snowmelt duration inferred from this study is expected to enhance the Arctic amplification.

Glacier movement is a crucial factor for assessing cryospheric climate change. Traditional methods of field surveys for studying glacier movement and velocity are often not possible owing to inaccessibility and harsh terrains. Furthermore, as it is not feasible to physically monitor and survey many glaciers around the globe, these traditional methods are limited in their global coverage. Remote sensing is an ideal tool to study such phenomena on a global scale. Optical remote sensing employs techniques such as feature tracking and pixel tracking, whereas, microwave remote sensing uses intensity tracking, speckle tracking, Interferometric SAR and Differential InSAR (DInSAR). This study focuses on estimation of glacier velocity and its seasonal variations using the image-matching technique for optical images for the Fisher glacier, a tributary glacier of the Amery ice shelf in Antarctica. The tool used in this study is the COSI-Corr module embedded in ENVI which provides the velocity in both azimuth and range resolution. The principle of estimating velocity using this tool is pixel tracking wherein similar pixels on two images are tracked where one is the master image and the other is a slave. This technique correlates the master and slave images over a time period and generates three outputs: displacements in the East-West and North-South directions and signal-to-noise ratio (SNR) image. Landsat 8 image pairs were used for cross correlation over a time span of four years spanning 2013–2017. With a resolution of 15 m, the panchromatic band (Band 8) was the ideal choice for pixel tracking as the resolution of other bands is coarser. The initial window size for correlation was 64 while the final window size was 16. The resolution of the displacement images produced is dependent on the value assigned for the step size, which was set to 8. The resultant velocity was derived using the result of the two displacement images. The SNR image was used to remove all the pixels from the velocity output having the value of SNR less than 0.9, in order to reduce the effect of noise. The annual velocity of the Fisher glacier was estimated to be around 600 to 650 myr−1 near the tongue where it merges with the Amery Ice Shelf, which was reduced to 150 myr−1 as it recedes. The resultant velocity images have a resolution of 120 m. The seasonal variation in velocity for the year 2013–2014 is 1.8 myr−1, while in the succeeding year 2014-2015 it subdued to 1.7 myr−1. The seasonal variation for the year 2015–2016 was estimated to be 7.9 myr−1. The seasonal variation for 2016–2017 was 17.4 myr−1.

Using the Expendable CTDs (XCTDs) collected along two transects between Africa and Antarctica during 1–11 January (Cape Town−Prydz Bay, track-2) and 12-21 April 2018 (Prydz Bay−Cape Town, track-1), frontal locations are delineated and compared with the satellite-based maps of absolute dynamic topography (MADT). The MADT maps revealed that the intensity of the Agulhas Current (AC) was 1.3 ms−1 during both periods; the southernmost limit of the Agulhas Retroflection (AR) was traced to 40°S, 20.5°E/42°S, 15°E on track-1/track-2. The vertical sections of temperature and salinity revealed the Agulhas anticyclonic eddy (AAE) whose core was detected at ~38.4°S/~37.6°S on track-1/track-2. The cumulative transport across track-2 was 50% higher than across track-1 which is attributed to deep-sea upwelling and its subsequent transport across the track-2 to the south of 50°S. On both transects, the winter water was detected up to 50°S in the upper 100 m. The highest AC transport in the upper 1000 m was detected at 37.75°S/38.28°S on track-1/track-2, which was related to the flow characteristics of the AC. The eddies that detached from the AC system transported nutrient-rich water southward which mixed with the ambient water resulting in peak chlorophyll-a concentration (Chl-a) exceeding 0.5 mg/m3 to the north of 42°S on both tracks. The shallow topographic features such as the Ob-Lena rise (54°S) and the southwest Indian Ridge (44°−46°S) also enhanced Chl-a by 39% on track-2.

Mapping of surface glacier facies has been a part of several glaciological applications. The study of glacier facies in the Himalayas has gained momentum in the last decade owing to the implications imposed by these facies on the melt characteristics of the glaciers. Some of the most commonly reported surface facies in the Himalayas are snow, ice, ice mixed debris, and debris. The precision of the techniques used to extract glacier facies is of high importance, as the result of many cryospheric studies and economic reforms rely on it. An assessment of a customized semi-automated protocol against conventional and advanced mapping algorithms for mapping glacier surface facies is presented in this study. Customized spectral index ratios (SIRs) are developed for effective extraction of surface facies using thresholding in an object-based environment. This method was then tested on conventional and advanced classification algorithms for an evaluation of the mapping accuracy for five glaciers located in the Himalayas, using very high-resolution WorldView-2 imagery. The results indicate that the object-based image analysis (OBIA) based semi-automated SIR approach achieved a higher average overall accuracy of 87.33% (κ = 0.85) than the pixel-based image analysis (PBIA) approach. Among the conventional methods, the Maximum Likelihood performed the best, with an overall accuracy of 78.71% (κ = 0.75). The Constrained Energy Minimization, with an overall accuracy of 68.76% (κ = 0.63), was the best performer of the advanced algorithms. The advanced methods greatly underperformed in this study. The proposed SIRs show a promise in the mapping of minor features such as crevasses and in the discrimination between ice-mixed debris and debris. We have efficiently mapped surface glacier facies independently of short-wave infrared bands (SWIR). There is a scope for the transferability of the proposed SIRs and their performance in varying scenarios.

The study explores modes of variability in the Southern Polar Cell and their relationship with known global climate modes and Antarctic sea ice. It is found that Polar Cell is barotropic in nature and 500 hPa geo-potential height (Z500) field can satisfactorily represent variability in the Polar Cell. First, three leading Empirical Orthogonal Function (EOF) modes of Z500 account for nearly 80% of observed variability in the Polar Cell. Dominant mode (PC1500) comprises of high pressure divergence zone over Antarctica. Second leading mode (PC2500) is low pressure zone covering Amundsen-Bellingshausen Sea (ABS) similar to ABS low feature. A new climate mode called Polar Coastal Index (PCI) is defined, which describes more than 15% and close to 30% variability of circumpolar trough and ABS low, respectively. Out of four modes defined in this study, only PCI and PC2500 show linear trends and clear seasonality. Interestingly, both modes are affected by modulation of ABS low due to tropical ENSO forcing. SAM signature is present in Polar Cell as PC1500 shares large variance with it. The largest impact on sea ice comes from PC2500 followed by PC1500 in the Antarctic Dipole regions. However, this study suggests contemporary sea ice trends cannot be sustained, and can reverse given that trends in PCI and PC2500 favour a reversal. These results indicate that ENSO-driven Polar Cell variability plays a crucial role influencing Antarctic sea ice as it interacts with other climate modes and leads the combined impact at the interannual time scale.

Iceberg calving is the detachment of ice from ice shelves or glaciers. Although calving is a natural phenomenon, an abnormal rate of calving can be a threat to ice shelves. Some of the events were so large, that an iceberg of approximately 150 × 50 km area was calved in a single event. The most recent reported iceberg calving event was Larsen C and it took place in July 2017. In addition to the large and widely reported calving events, there are several small calving events, which are also of great significance and contribute to the overall mass loss from Antarctica. This study focuses on small calving events in Antarctica along various coasts. Three calving events are studied here, all of them have occurred in the past. This study was performed using Google Earth and Landsat satellite imageries. The first event is identified to have occurred at the Knox coast in 2016. Even after the icebergs were calved, they remained intact with the ice shelf due to ice fronts. The second event took place at the Queen Mary Coast in the year 2014. This event was studied from 2009 to 2016 using Landsat satellite images and many rifts were observed. The third event took place at the Princess Astrid Coast in the year 2016. This event was monitored from 2014 and three icebergs were calved between the years 2014 to 2016. This study emphasizes the exploitation of optical satellite data for studying calving events in Antarctica. Various crevasses and rifts are observed on Landsat imageries, which can be the first sign of a calving process.

Changes in the dynamics of glaciers must be assessed, as they are important for sea level changes. Glacier velocity is the most important parameter used in glacier dynamics studies. Various image matching techniques, which are implemented in different domains, have been utilized to estimate the surface velocity of glaciers, since the first use of remote sensing technology. In this study, we derived the precise velocity of the Polar Record Glacier (PRG), east Antarctica, in recent years, using optical remote sensing. The secondary objective of the study was to comparatively test the accurate geospatial tools for velocity estimation. The study was first conducted on a single image pair, and four different tools were used for the estimation of the glacier velocity, which are the COSI-Corr (Co-registration of Optically Sensed Images and Correlation) tool in ENVI (Exelis Visual Information Solutions), the IMGRAFT (Image GeoRectification and Feature Tracking) in MATLAB, the IMCORR (Image correlation) feature tracking tool in SAGA-GIS, and the image correlation software CIAS. After evaluation of the four feature tracking tools, COSI-Corr yielded a pixel-level velocity with both magnitude and directions, while IMGRAFT provided the glacier speed without the directions. On the other hand, IMCORR yielded good results with respect to magnitude and directions of the glacier velocity, but the pixel-wise magnitude was not produced. CIAS also provided closely bundled velocity products without pixel-wise velocity. COSI-Corr and IMGRAFT were found to be the best of the four tools, and COSI-Corr is recommended for further studies to estimate the velocity of the PRG.

The ice flow velocity is a critical variable in understanding the glacier dynamics. The Synthetic Aperture Radar Interferometry (InSAR) is a robust technique to monitor Earth’s surface mainly to measure its topography and deformation. The phase information from two or more interferogram further helps to extract information about the height and displacement of the surface. We used this technique to derive glacier velocity for Polar Record Glacier (PRG), East Antarctica, using Sentinel-1 Single Look Complex images that were captured in Interferometric Wide mode. For velocity estimation, Persistent Scatterer interferometry (PS-InSAR) method was applied, which uses the time coherent of permanent pixel of master images and correlates to the same pixel of the slave image to get displacement by tracking the intensity of those pixels. C-band sensor of European Space Agency, Sentinel-1A, and 1B data were used in this study. Estimated average velocity of the PRG is found to be approximately ≈400 ma−1, which varied from ≈100 to ≈700 ma−1. We also found that PRG moves at ≈700 and 200 ma−1 in the lower part and the upper inland area, respectively.

Glaciers exhibit a wide range of surface facies that can be analyzed as proxies for mass balance studies. Along with hydrological implications, these are in turn quintessential indicators of climate change. Moderate-to-high-resolution (MHR) data for mapping glacier facies have been used previously; however, the use of very high-resolution (VHR) data for this purpose has not yet been fully exploited. This study uses WorldView-2 (WV-2) VHR data to classify available glacier surface facies on the Samudra Tapu glacier, located in the Himalayas. Traditional methods of facies classification using conventional multispectral data involve band rationing and/or supervised classification. This study explores glacier surface facies classification by using the unique bands available in the multispectral range of WV-2 to develop customized spectral index ratios (SIRs) within an object-oriented domain. The results of this object-oriented classification (OOC) are then compared with five popular supervised classification algorithms using error matrices to determine the classification accuracies. The overall accuracy achieved by the object-based image analysis (OBIA) approach is 97.14% (κ = 0.96), and the highest overall accuracy among the pixel-based classification methods is 74.28% (κ = 0.70). The present results show that the object-based approach is far more accurate than the pixel-based classification techniques. Further studies should test the robustness of the object-oriented domain for the classification of glacier surface facies using customized sensor-specific as well as transferable indices, and the resultant accuracies.

The cryosphere is the frozen part of the Earth’s system. Snow and ice are the main constituents of the cryosphere and may be found in different states, such as snow, freshwater ice, sea ice, perma-frost, and continental ice masses in the form of glaciers and ice sheets. The present review mainly deals with state-of-the-art applications of synthetic aperture radar (SAR) with a special emphasize on cryospheric information extraction. SAR is the most important active microwave remote sensing (RS) instrument for ice monitoring, which provides high-resolution images of the Earth’s surface. SAR is an ideal sensor in RS technology, which works in all-weather and day and night conditions to provide useful unprecedented information, especially in the cryospheric regions which are almost inaccessible areas on Earth. This paper addresses the technological evolution of SAR and its applications in studying the various components of the cryosphere. The arrival of SAR radically changed the capabilities of information extraction related to ice type, new ice formation, and ice thickness. SAR applications can be divided into two broad classes-polarimetric applications and interferometric applications. Polarimetric SAR has been effectively used for mapping calving fronts, crevasses, surface structures, sea ice, detection of icebergs, etc. The paper also summarizes both the operational and climate change research by using SAR for sea ice parameter detection. Digital elevation model (DEM) generation and glacier velocity mapping are the two most important applications used in cryosphere using SAR interferometry or interferometric SAR (InSAR). Space-borne InSAR techniques for measuring ice flow velocity and topography have developed rapidly over the last decade. InSAR is capable of measuring ice motion that has radically changed the science of glaciers and ice sheets. Measurement of temperate glacier velocities and surface characteristics by using airborne and space-borne interferometric satellite images have been the significant application in glaciology and cryospheric studies. Space-borne InSAR has contributed to major evolution in many research areas of glaciological study by measuring ice-stream flow velocity, improving understanding of ice-shelf processes, yielding velocity for flux-gate based mass-balance assessment, and mapping flow of mountain glaciers. The present review summarizes the salient development of SAR applications in cryosphere and glaciology.

Evolution of remote sensing sensors technologies is presented, with emphasis on its suitability in observing the polar regions. The extent of influence of polar regions on the global climate and vice versa is the spearhead of climate change research. The extensive cover of sea ice has major impacts on the atmosphere, oceans, and terrestrial and marine ecosystems of the polar regions in particular and teleconnection on other processes elsewhere. Sea ice covers vast areas of the polar oceans, ranging from ~18 × 106 km2 to ~23 × 106 km2, combined for the Northern and Southern Hemispheres. However, both polar regions are witnessing contrasting rather contradicting effects of climate change. The Arctic sea ice extent is declining at a rate of 0.53 × 106 km2·decade–1, whereasAntarcticaexhibits a positive trend at the rate of 0.167 × 106 km2·decade–1. This work reviews literature published in the field of sea ice remote sensing, to evaluate and access success and failures of different sensors to observe physical features of sea ice. The chronological development series of different sensors on different satellite systems, sensor specifications and datasets are examined and how they have evolved to meet the growing needs of users is outlined. Different remote sensing technology and observational methods and their suitability to observe specific sea ice property are also discussed. A pattern has emerged, which shows that microwave sensors are inherently superior to visible and infrared in monitoring seasonal and annual changes in sea ice. Degree of successes achieved through remote sensing techniques by various investigators has been compared. Some technologies appear to work better under certain conditions than others, and it is now well accepted that there is no algorithm that is ideal globally. Contribution of Indian remote sensing satellites is also reviewed in the context of polar research. This review suggests different primary datasets for further research on sea ice features (sea ice extent, ice type, sea ice thickness, etc.). This work also examines past achievements and how far these capabilities have evolved and tap into current state of art/direction of sensor technologies. Effective monitoring and syntheses of past few decades of research pinpoint useful datasets for sea ice monitoring, thereby avoiding wastage of resources to find practical datasets to monitor these physically inaccessible regions.

Anthropogenic warming of near-surface atmosphere in the last 50 years is dominant over the west Antarctic Peninsula. Ozone depletion has led to partly cooling of the stratosphere. The positive polarity of the Southern Hemisphere Annular Mode (SAM) index and its enhancement over the past 50 years have intensified the westerlies over the Southern Ocean, and induced warming of Antarctic Peninsula. Dictated by local ocean-atmosphere processes and remote forcing, the Antarctic sea ice extent is increasing, contrary to climate model predictions for the 21st century, and this increase has strong regional and seasonal signatures. Models incorporating doubling of present day CO2 predict warming of the Antarctic sea ice zone, a reduction in sea ice cover, and warming of the Antarctic Plateau, accompanied by increased snowfall.

Digital elevation model (DEM) is indispensable for analysis such as topographic feature extraction, ice sheet melting, slope stability analysis, landscape analysis and so on. Such analysis requires a highly accurate DEM. Available DEMs of Antarctic region compiled by using radar altimetry and the Antarctic digital database indicate elevation variations of up to hundreds of meters, which necessitates the generation of local improved DEM. An improved DEM of the Schirmacher Oasis, East Antarctica has been generated by synergistically fusing satellite-derived laser altimetry data from Geoscience Laser Altimetry System (GLAS), Radarsat Antarctic Mapping Project (RAMP) elevation data and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global elevation data (GDEM). This is a characteristic attempt to generate a DEM of any part of Antarctica by fusing multiple elevation datasets, which is essential to model the ice elevation change and address the ice mass balance. We analyzed a suite of interpolation techniques for constructing a DEM from GLAS, RAMP and ASTER DEM-based point elevation datasets, in order to determine the level of confidence with which the interpolation techniques can generate a better interpolated continuous surface, and eventually improve the elevation accuracy of DEM from synergistically fused RAMP, GLAS and ASTER point elevation datasets. The DEM presented in this work has a vertical accuracy (≈ 23 m) better than RAMP DEM (≈ 57 m) and ASTER DEM (≈ 64 m) individually. The RAMP DEM and ASTER DEM elevations were corrected using differential GPS elevations as ground reference data, and the accuracy obtained after fusing multitemporal datasets is found to be improved than that of existing DEMs constructed by using RAMP or ASTER alone. This is our second attempt of fusing multitemporal, multisensory and multisource elevation data to generate a DEM of Antarctica, in order to address the ice elevation change and address the ice mass balance. Our approach focuses on the strengths of each elevation data source to produce an accurate elevation model.

Satellite-derived sea-ice extent in the Indian Ocean Sector during the period November 1978 to December 2006 was studied in relation to the atmospheric forcing and oceanic thermohaline structure. The study revealed that sea-ice extent increased when the ocean exhibited higher stability. Low sea-ice extent was observed during 1985 to 1993, when the zonal winds and latent flux was relatively weak and when the ocean exhibited strong vertical mixing facilitated by low stability thereby, deepening the mixed layer to ∼250 m. This was reflected in the ocean surface layer temperature, which was relatively warm (−0.3°C). Winds increased during 1996 to 2000, but due to higher oceanic stability mixed layer depth shallowed (< 200 m) leading to reduced vertical mixing of deep warmer layers with the surface water, leading to an enhancement in the sea-ice extent.

Using QuikScat-based vector wind data for 1999–2003, surface wind stress and turbulent heat (Q) have been mapped for the tropical Indian Ocean (IO) to understand their seasonal variability. During July wind stress is enhanced by ∼ 70% in the Arabian Sea compared to that during January. The Arabian Sea experiences a large Q loss (150–200 W/m2) during the summer and winter monsoons, which is nearly 1.3 times of that in the Bay of Bengal. The southeasterlies are strengthened during the southern hemisphere winter. Empirical Orthogonal Function analysis captures different phases of monsoon-induced variability in wind stress and Q, ranging from seasonal to high-frequency perturbations. Coherency between time coefficients of EOF-1 for wind stress and Q suggests that former leads the latter with a temporal lag of 20–40 days for period > 322 days. At high frequencies (< 21 days) Q leads wind stress with a temporal lag of 2 days. Possible explanation for wind stress leading Q over an annual time scale is offered based on the marine atmospheric boundary layer physics and pre-conditioned ocean surface, while on shorter time scales (21 days) ocean thermodynamics through mixed layer processes cause Q to lead wind stress.

Upper layer (0}400 m) geostrophic volume transport associated with the major current systems of the tropical Indian Ocean along the near-meridional TOGA-India XBT tracklines from Mumbai to Mauritius during 1992}1996 is discussed. The transport of the eastward #owing Indian Monsoon Current (IMC) varies between 9 and 14 Sv (1 Sv"106 m3 s~1) during southwest monsoon. The westward #owing North Equatorial Current (NEC) transports about 8 Sv during boreal winter. The westward #owing south equatorial current (SEC) has its lowest transport (10}12 Sv) during austral fall and spring and highest transport (18}21 Sv) during austral winter and summer. The northern boundary of the SEC extends equatorward as far north as for 4}53S during southwest monsoon from its usual location of 8}103S. The eastward #owing South Equatorial Counter Current (SECC) exhibits highest transport (37 Sv) during peak austral summer (January) and between 5 and 20 Sv during the rest of the year. In March and May, eastward undercurrents are noticed near the equator. In June and July, the undercurrents are present south of Sri Lanka away from the equator. The equatorial #ow in the zonal belts 1}23N and 1}23S exhibits westward transport of 6}20 Sv during January}February. This broad westward #ow and the SECC constitute an anticlockwise equatorial gyre during boreal winter. In addition to the above current systems, signatures of a warm-core anticyclonic eddy centered at 83N, 72.53E and a cold-core cyclonic eddy centered at 10.53N, 72.53E are also noticed in February and October, respectively, o! the southwest coast of India. The volume transport associated with the warm-core eddy is about 10 Sv directed equatorward and that with the cold-core eddy is 2.5 Sv directed poleward. ( 2000 Elsevier Science Ltd. All rights reserved.

[1] Topographic meandering of Antarctic Circumpolar Current (ACC) is found to be an impediment in the propagation of Antarctic Circumpolar Wave (ACW) in the Indian Ocean sector of Antarctica. Reasons for this are attributed to the southward advection of the ACW anomalies associated with the topographic meandering of the ACC. The southward meandering of ACC facilitates warming up of the region east of 20°E by about 1°C during winter, thereby reducing the sea ice; these processes interfere with the eastward propagating positive sea‐ice anomalies, and reduce its strength. Warming of ocean induced by topographic meandering leads to upward vertical velocities between 40°–60°E, where the ocean surface velocities are weak and southward, and the vertical/meridional advection of temperature dominates the zonal advection in the atmosphere. This results in the decoupling of the ACW in the region east of 40°E. In regions out side the Indian Ocean sector, vertical advection is minimum and zonal velocity of ACC becomes positive, which facilitates the ACW propagation in the Central Pacific, Ross and Weddell Seas. Citation: Nuncio, M., A. J. Luis, and X. Yuan (2011), Topographic meandering of Antarctic Circumpolar Current and Antarctic Circumpolar Wave in the ice‐ ocean‐atmosphere system, Geophys. Res. Lett., 38, L13708

Glacier facies are zones of snow on a glacier that have certain specific spectral characteristics that enable their characterization. The accuracy of their extraction will determine the end accuracy of the distributed mass balance model calibrated by this information. Therefore, coarse to medium resolution satellites are not preferable for this particular function as the data derived from such sensors will potentially blur out the minute spatial variations on the surface of a glacier. Very high resolution (VHR) sensors (such as, WorldView (WV)-1, 2, 3) are thus much more suited for this particular task. Hence, this study aims to extract the available glacier facies on the Sutri Dhaka glacier, Himalayas, using very high-resolution WorldView-2 (WV-2) imagery. Extensive pre-processing of the imagery was performed to prepare the data for this purpose. The steps incorporated for this purpose consist of 1) Data Calibration, 2) Mosaicking, 3) Pan Sharpening, 4) Generation of 3D surface, and 5) Digitization. Using image classification as the primary method of information extraction, this study tests the ever-popular pixel-based classification technique against the uprising object-based classification technique. In doing so, this study aims to determine the most accurate technique of information extraction for the WV-2 imagery in the given scenario. The presence of unique bands (Coastal (0.40–0.45 μm), Red Edge (0.705–0.745 μm), NIR-1 (0.770–0.895 μm) and NIR-2 (0.86–1.04 μm) in the multispectral range of WV-2, allows this study to perform facies classification through the development of customized spectral index ratios (SIRs) in the object-based domain. Establishment of thresholds was hence necessitated for information extraction through the developed SIRs. Three supervised classifiers, namely, a) Mahalanobis distance, b) Maximum likelihood, and c) Minimum distance to mean, were then used to perform classification, thereby allowing a comparative analysis between the classification schemes. Accuracy assessment for each classification scheme was performed using error matrices. The object-based approach achieved an overall accuracy of 90% (κ = 0.88) and the highest overall accuracy among the pixel-based classification methods is 78.57% (κ = 0.75). The results clearly portray that the object-based method delivered much higher accuracy than the pixel-based methods. The carry home message is that future studies must examine the transferability and accuracy of the customized SIRs in varying scenarios, as different scenarios will require varying threshold adjustments. Forthcoming studies can also develop sensor specific and unique indices for other sensors that are suitable for such applications.