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The merging of a panchromatic (PAN) image with a multispectral satellite image (MSI) to increase the spatial resolution of the MSI, while simultaneously preserving its spectral information is classically referred as PAN-sharpening. We employed a recent dataset derived from very high resolution of WorldView-2 satellite (PAN and MSI) for two test sites (one over an urban area and the other over Antarctica), to comprehensively evaluate the performance of six existing PAN-sharpening algorithms. The algorithms under consideration were the Gram-Schmidt (GS), Ehlers fusion (EF), modified hue-intensity-saturation (Mod-HIS), high pass filtering (HPF), the Brovey transform (BT), and wavelet-based principal component analysis (W-PC). Quality assessment of the sharpened images was carried out by using 20 quality indices. We also analyzed the performance of nearest neighbour (NN), bilinear interpolation (BI), and cubic convolution (CC) resampling methods to test their practicability in the PAN-sharpening process. Our results indicate that the comprehensive performance of PAN-sharpening methods decreased in the following order: GS > W-PC > EF > HPF > Mod-HIS > BT, while resampling methods followed the order: NN > BI > CC.

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.

This work presents various normalized difference water indices (NDWI) to delineate lakes from Schirmacher Oasis, East Antarctica, by using a very high resolution WorldView-2 (WV-2) satellite imagery. Schirmacher oasis region hosts a number of fresh as well as saline water lakes, such as epishelf lakes, ice-free or landlocked lakes, which are completely frozen or semi-frozen and in a ice-free state. Hence, detecting all these types of lakes distinctly on satellite imagery was the major challenge, as the spectral characteristics of various types of lakes were identical to the other land cover targets. Multiband spectral index pixel-based approach is most experimented and recently growing technique because of its unbeatable advantages such as its simplicity and comparatively lesser amount of processing-time. In present study, semiautomatic extraction of lakes in cryospheric region was carried out by designing specific spectral indices. The study utilized number of existing spectral indices to extract lakes but none could deliver satisfactory results and hence we modified NDWI. The potentials of newly added bands in WV-2 satellite imagery was explored by developing spectral indices comprising of Yellow (585 – 625 nm) band, in combination with Blue (450 – 510 nm), Coastal (400 – 450 nm) and Green (510 – 580 nm) bands. For extraction of frozen lakes, use of Yellow (585 – 625 nm) and near-infrared 2 (NIR2) band pair, and Yellow and Green band pair worked well, whereas for ice-free lakes extraction, a combination of Blue and Coastal band yielded appreciable results, when compared with manually digitized data. The results suggest that the modified NDWI approach rendered bias error varying from ~1 to ~34 m 2 .

High-resolution pansharpened images from WorldView-2 were used for bathymetric mapping around Larsemann Hills and Schirmacher oasis, east Antarctica. We digitized the lake features in which all the lakes from both the study areas were manually extracted. In order to extract the bathymetry values from multispectral imagery we used two different models: (a) Stumpf model and (b) Lyzenga model. Multiband image combinations were used to improve the results of bathymetric information extraction. The derived depths were validated against the in-situ measurements and root mean square error (RMSE) was computed. We also quantified the error between in-situ and satellite-estimated lake depth values. Our results indicated a high correlation (R = 0.60~0.80) between estimated depth and in-situ depth measurements, with RMSE ranging from 0.10 to 1.30 m. This study suggests that the coastal blue band in the WV-2 imagery could retrieve accurate bathymetry information compared to other bands. To test the effect of size and dimension of lake on bathymetry retrieval, we distributed all the lakes on the basis of size and depth (reference data), as some of the lakes were open, some were semi frozen and others were completely frozen. Several tests were performed on open lakes on the basis of size and depth. Based on depth, very shallow lakes provided better correlation (≈ 0.89) compared to shallow (≈ 0.67) and deep lakes (≈ 0.48). Based on size, large lakes yielded better correlation in comparison to medium and small lakes.

A robust monitoring of the changes in the distribution and density of cryospheric plant species requires accurate and high-resolution baseline maps of vegetation. Mapping such change at the landscape scale is often problematic, particularly in remote areas, such as Antarctica. Vegetation mapping of plant communities at fine spatial scales is increasingly supported by remote sensing technology in cryospheric regions. Less frequent imaging with high spatial resolution satellite sensors enable more detailed analyses of vegetation change frequently. This study is the first to use high-resolution WorldView-2 (WV-2) imagery to classify vegetation communities on Antarctic oases and to provide semi-automated means to map vegetation, as an imperative indicator for environmental change. Multispectral imagery (MSI) and panchromatic imagery (PAN) from very high resolution WV-2 have been used for mapping of vegetation in different forms in Antarctic environment. A range of supervised classification methods have been executed using pan-sharpened WV-2 data. This study comparatively and statistically evaluates vegetation mapping results using supervised and unsupervised classification methods to extract vegetation in Larsemann Hills and Schirmacher oasis, east Antarctica. We also discuss on the use of supervised pixel-based classifiers and textural measures, in addition to standard multispectral information, to improve the classification of Antarctic vegetation communities. Classification results were validated with independent reference datasets. This work indicates that the overall accuracy of mapping vegetation using WV-2 imagery and semi-automated target extraction methods ranged from 90% to 94%.

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.

Supraglacial debris was mapped in the Schirmacher Oasis, east Antarctica, by using WorldView-2 (WV-2) high resolution optical remote sensing data consisting of 8-band calibrated Gram Schmidt (GS)-sharpened and atmospherically corrected WV-2 imagery. This study is a preliminary attempt to develop an object-oriented rule set to extract supraglacial debris for Antarctic region using 8-spectral band imagery. Supraglacial debris was manually digitized from the satellite imagery to generate the ground reference data. Several trials were performed using few existing traditional pixel-based classification techniques and color-texture based object-oriented classification methods to extract supraglacial debris over a small domain of the study area. Multi-level segmentation and attributes such as scale, shape, size, compactness along with spectral information from the data were used for developing the rule set. The quantitative analysis of error was carried out against the manually digitized reference data to test the practicability of our approach over the traditional pixel-based methods. Our results indicate that OBIA-based approach (overall accuracy: 93%) for extracting supraglacial debris performed better than all the traditional pixel-based methods (overall accuracy: 80−85%). The present attempt provides a comprehensive improved method for semiautomatic feature extraction in supraglacial environment and a new direction in the cryospheric research.

Cryospheric surface feature classification is one of the widely used applications in the field of polar remote sensing. Precise surface feature maps derived from remotely sensed imageries are the major requirement for many geoscientific applications in polar regions. The present study explores the capabilities of C-band dual polarimetric (HH & HV) SAR imagery from Indian Radar Imaging Satellite (RISAT-1) for land cryospheric surface feature mapping. The study areas selected for the present task were Larsemann Hills and Schirmacher Oasis, East Antarctica. RISAT-1 Fine Resolution STRIPMAP (FRS-1) mode data with 3-m spatial resolution was used in the present research attempt. In order to provide additional context to the amount of information in dual polarized RISAT-1 SAR data, a band HH+HV was introduced to make use of the original two polarizations. In addition to the data calibration, transformed divergence (TD) procedure was performed for class separability analysis to evaluate the quality of the statistics before image classification. For most of the class pairs the TD values were comparable, which indicated that the classes have good separability. Fuzzy and Artificial Neural Network classifiers were implemented and accuracy was checked. Nonparametric classifier Support Vector Machine (SVM) was also used to classify RISAT-1 data with an optimized polarization combination into three land-cover classes consisting of sea ice/snow/ice, rocks/landmass, and lakes/waterbodies. This study demonstrates that C-band FRS1 image mode data from the RISAT-1 mission can be exploited to identify, map and monitor land cover features in the polar regions, even during dark winter period. For better landcover classification and analysis, hybrid polarimetric data (cFRS-1 mode) from RISAT-1, which incorporates phase information, unlike the dual-pol linear (HH, HV) can be used for obtaining better polarization signatures.

Current research study emphasizes the importance of advanced digital image processing methods in order to delineate between various LULC features. In the case of the Antarctica, the present LC (snow/ice, landmass, water, vegetation etc.) and the present LU (research stations of various nations) needs to be mapped accurately for the hassle free routine activities. Geo-location has become the most important part of geosciences studies. In this paper we have tried to locate three most important features (snow/ice, landmass, and water) and also have extracted the extent of the same using the multisource classification (image fusion/pansharpening) and pattern recognition (supervised/unsupervised methods, index ratio methods). Innovation in developing spectral index ratios has led us to come up with an unique ratio named Normalized Difference Landmass Index (NDLI) which performed better (Avg. Bias: 51.99m) than other ratios such as Normalized Difference Snow/Ice Index (NDSII) (Avg. Bias: -1572.11m) and Normalized Difference Water Index (NDWI) (Avg. Bias: 1886.60m). The practiced trial and error methodology quantifies the productivity of not only the classification methods over one other but also that of the fusion methods. In present study, classifiers used (Mahalanobis and Winner Takes All) performed better (Avg. Bias: 122.16 m) than spectral index ratios (Avg. Bias: 620.16 m). The study also revealed that newly introduced bands in WorldView-2, band 1 (Coastal Blue), 4 (Yellow), 6 (Red-edge) and 8 (Near Infrared-2) along with traditional bands have the capacity to mine the polar geospatial information with utmost accuracy and efficiency.

High resolution satellite data provide high spatial, spectral and contextual information. Spatial and contextual information of image objects are in demand to extract the information from high resolution satellite data. The supraglacial environment includes several features that are present on the surface of the glacier. The extraction of features from supraglacial environment is quite challenging using pixel-based image analysis. To overcome this, objectoriented approach is implemented. This paper aims at the extraction of geo-information from the supraglacial environment from high resolution satellite image by object-oriented image analysis using the fuzzy logic approach. The object-oriented image analysis involves the multiresolution segmentation for the creation of objects followed by the classification of objects using the fuzzy logic approach. The multiresolution segmentation is executed on the pixel level initially which merges pixels for the creation of objects thus minimizing their heterogeneity. This is followed by the development of rule sets for the classification of various features such as blue ice, debris, snow from the supraglacial environment in WorldView-2 data. The area of extracted feature is compared with the reference data and misclassified area of each feature using various bands is determined. The present object oriented classification achieved an overall accuracy of ≈ 92% for classifying supraglacial features. Finally, it is suggested that Red band is quite effective in the extraction of blue ice and snow, while NIR1 band is effective in debris extraction.

An accurate spatial mapping and characterization of land cover features in cryospheric regions is an essential procedure for many geoscientific studies. A novel semi-automated method was devised by coupling spectral index ratios (SIRs) and geographic object-based image analysis (OBIA) to extract cryospheric geospatial information from very high resolution WorldView 2 (WV-2) satellite imagery. The present study addresses development of multiple rule sets for OBIA-based classification of WV-2 imagery to accurately extract land cover features in the Larsemann Hills, east Antarctica. Multilevel segmentation process was applied to WV-2 image to generate different sizes of geographic image objects corresponding to various land cover features with respect to scale parameter. Several SIRs were applied to geographic objects at different segmentation levels to classify land mass, man-made features, snow/ice, and water bodies. We focus on water body class to identify water areas at the image level, considering their uneven appearance on landmass and ice. The results illustrated that synergetic usage of SIRs and OBIA can provide accurate means to identify land cover classes with an overall classification accuracy of ≈97%. In conclusion, our results suggest that OBIA is a powerful tool for carrying out automatic and semiautomatic analysis for most cryospheric remote-sensing applications, and the synergetic coupling with pixel-based SIRs is found to be a superior method for mining geospatial information.

An enhanced digital elevation model (DEM) of the Larsemann Hills region, east Antarctica, is constructed synergistically by using highly accurate ground-based GPS measurements, satellite-derived laser altimetry (GLAS/ICESat) and Radarsat Antarctic Mapping Project (RAMPv2) DEM-based point elevation dataset. Our DEM has a vertical accuracy of about 1.5 times better than RAMPv2 DEM and seven times better than GLAS/ICESAT-based DEM. The accuracy is improved by validating the RAMPv2 DEM elevation by supplementing with GLAS/ICESat and DGPS survey data, when compared to that of DEM constructed by using GLAS/ICESat or RAMPv2 alone. With the use of accurate GPS data as ground control points reference elevations, the DEM extracted is much more accurate with least mean RMSE of 34.5 m than that constructed by using a combination of GLAS/ICESat and RAMPv2 as true reference. The newly constructed DEM 7 achieves highest accuracy with the least average elevation difference of 0.27 m calculated using 46 ground reference points. Available DEMs of Antarctic region generated by using radar altimetry and the Antarctic Digital Database indicate elevation variations in the range of 50–100 m, which necessitates the generation of local DEM and its validation by using ground truth. This is our first attempt of fusing multi-temporal, multi-sensor and multi-source elevation data to generate a DEM of any part of Antarctica, in order to address the ice elevation change to infer the ice mass balance. Our approach focuses on the strengths of each elevation data source to produce an accurate DEM.

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.

Under the International Polar Year endorsed project (IPY#70), the southwest Indian Ocean sector of the Southern Ocean was surveyed during the austral summer of 2008 by deploying expendable CTD probes along the ship tracks : Cape Town–India Bay, Antarctica (Track-1) and Prydz Bay, Antarctica–Cape Town (Track-2). The meteorological data revealed that the unstable marine atmosphere boundary layer (MABL) facilitated a turbulent heat loss of 45 Wm − 2 on average, in conditions of variable wind intensity north of 43°S along Track-1; south of 63°S and north of 51°S the ocean was conducive to higher turbulent heat loss amounting to 95 Wm − 2 (on average) along Track-2. Surface imprints of hydrological fronts were determined by using surface gradient and subsurface temperature and salinity indicators. The core of Agulhas Current was identified between 36.5° and 37.5°S along Track-2, while the Agulhas Retroflection (AR) Front was located at 39.7°S south of Cape Town. The Subtropical (STF), Subantarctic (SAF) and Polar Fronts (PF) exhibited double frontal structures, whose meridional meandering is governed by bottom topography and modulated by planetary vorticity. A large southward deviation in the position of southern PF by 3.5° latitude on Track-1 was observed. Northern and southern SAF and southern STF meander by 2°–3.5° northward; their merger just north of Crozet Island facilitate an enhanced baroclinic transport of 12 Sv in the upper 1000 m. Three anticyclones that detach from the AR transport 17 Sv into the southeast Atlantic. The baroclinic transport contributed by AC and its retroflection across Track-2 amounted to 17.6 Sv. More than 50% of the ACC transport was confined to the 100–500 m depth layer. Water masses have been identified and their zonal extent quantified along the tracks. Strong convective cooling is responsible for the production of Subtropical Mode Water in the eastern Crozet Basin, which was detected near 43.5° and 41.5°S along Track-1 and -2, respectively. The Circumpolar Deep Water was encountered between 600 and 900 m at 51°S on Track-1 and spanned 54°–60°S on Track-2. We also offer an example of the modification of the MABL through strong air–sea interaction in the vicinity of South Africa by employing satellite-derived surface winds and heat fluxes.

High density CTD and XBT sections were covered from 35° to 56°S along 45°E and 57°30′E to investigate the morphology of the main fronts in the southwest Indian Ocean, as a part of the Indian pilot expedition to the Southern Ocean on board ORV Sagar Kanya. Northern branch of the Subtropical Front (NSTF) was observed at ∼ 35°30′S along 45°E. Along 57°30′E, the signature of the Agulhas Return Front (ARF) + Subtropical Front (STF) was identified with a rapid decrease in surface temperature between 43°30′ and 45°S and it is located with a southward shift compared to that at 45°E. The Subantarctic Front (SAF) was distinguished as two fronts as northern SAF (SAF1) and southern SAF (SAF2) along both the meridional sections. Polar Front1 (PF1) was identified between 49° and 50°S whereas Polar Front2 (PF2) was identified between 52° and 54°S along 45°E. This study reveals a southward shift of the oceanic fronts (ARF + STF) from west to east, with a maximum southward displacement of > 2° latitude at 57°30′E. A novel finding of this study is that along 45°E, SAF1 merged with ARF and SSTF and SAF2 ∼ 4° latitude southwards from the merged fronts whereas along 57°30′E, SAF1 was not identified as a merged front with ARF and STF as opposed to earlier studies [Belkin, I.M., Gordon, A.L., 1996. Southern Ocean fronts from the Greenwich Meridian to Tasmania. Journal of Geophysical Research 101, 3675–3696]. The thermocline region was absent south of PF. An enhancement in the mixed layer thickness from 42° to 52°S occurred in association with the strengthening of the wind forcing. Major water masses like Subtropical Surface Water, Subantarctic Surface Water, Mode Water, Antarctic Intermediate Water, Circumpolar Deep Water and Antarctic Bottom Water were identified along 45°E. Upper-ocean heat-content computation revealed a remarkable drop of 989 × 107 J m−2 at ∼ 42°S and 1405 × 107 J m−2 at ∼ 44°S along 45° and 57°30′E, respectively. We believe that this sudden drop in heat content affects the meridional heat transfer which is crucial to the regional climatic variability.

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.

Large-scale surface atmospheric convergence and divergence patterns in the Indian Ocean are mapped using high-spatial resolution, merged scatterometer wind vectors during 1991–2000. The convergence zone evolves to north of 15°S as a result of convection promoted by warm (> 28 °C) equatorial sea surface temperature (SST), and it exhibits strong intensity during boreal summer and winter. A divergence zone evolves to the south of 15°S as a result of subdued convection caused by colder SST (

Air-sea interaction, coastal circulation and primary production exhibit an annual cycle in the eastern Arabian Sea (AS). During June to September, strong southwesterly winds (4∼9 m s−1) promote sea surface cooling through surface heat loss and vertical mixing in the central AS and force the West India Coastal Current equatorward. Positive wind stress curl induced by the Findlater jet facilitates Ekman pumping in the northern AS, and equatorward-directed alongshore wind stress induces upwelling which lowers sea surface temperature by about 2.5°C (compared to the offshore value) along the southwestern shelf of India and enhances phytoplankton concentration by more than 70% as compared to that in the central AS. During winter monsoon, from November to March, dry and weak northeasterly winds (2–6 m s−1) from the Indo-China continent enhance convective cooling of the upper ocean and deepen the mixed layer by more than 80 m, thereby increasing the vertical flux of nutrients in the photic layer which promotes wintertime phytoplankton blooms in the northern AS. The primary production rate integrated for photic layer and surface chlorophyll-a estimated from the Coastal Zone Color Scanner, both averaged for the entire western India shelf, increases from winter to summer monsoon from 24 to 70 g C m−2month and from 9 to 24 mg m−2, respectively. Remotely-forced coastal Kelvin waves from the Bay of Bengal propagate into the coastal AS, which modulate circulation pattern along the western India shelf; these Kelvin waves in turn radiate Rossby waves which reverse the circulation in the Lakshadweep Sea semiannually. This review leads us to the conclusion that seasonal monsoon forcing and remotely forced waves modulate the circulation and primary production in the eastern AS.

Sea surface temperature (SST) patterns along the west India shelf, extending from 8° to 24°N, are analyzed during 1993–1996 to characterize seasonal variability using the advanced very high-resolution radiometer (AVHRR) SST, momentum and heat fluxes derived from ERS-1 winds and NCEP/NCAR reanalysis data. During winter monsoon (December–March), a 4-year mean SST spatial pattern shows a strong cooling north of 15°N due to surface heat depletion, while warm SSTs evolve in the south due to the intrusion of warm equatorial water. Cold water occupies the entire shelf during summer monsoon, with high degree of SST cooling dominating the Kerala coast, where Ekman pumping and upwelling promoted by the dominant alongshore wind stress component overwhelms the surface heat loss. The spectral analysis reveals semiannual and annual peaks in SST and forcing functions, which highlight the influence of monsoon forcing on the SST variability along the west India shelf.

The northern Arabian Sea is a semienclosed sea with high primary productivity and a complicated flow pattern consisting of several eddies. This paper reports on phytoplankton blooms, which were associated with a cold eddy in the northern Arabian Sea during November 1996, inferred from Ocean Color and Temperature Scanner (OCTS) and Sea-view Wide Field-of-view Sensor (SeaWiFS)-derived chlorophyll a (Chl-a hereafter), AVHRR sea surface temperature (SST), and other available oceanography data. The blooms emerged at 100 km from both coasts in the Gulf of Oman (60.5°E, 24.5°N) where the depth is about 3000 m. The Chl-a concentrations patch first appeared on November 2 and decayed after about 4 weeks (December 3, 1996). The high Chl-a concentrations patch was about 100 km in diameter and it was located at 60.3–61.3°E, 23.5–24.5°N. The bloom, having a mean Chl-a concentration of 6.8 mg m−3 on November 6, was located in a cold SST eddy, which was accompanied by another feature, an anticyclone eddy (of 100 km in diameter) with high SST and low Chl-a concentrations to the southwest (61.5°E, 22.5°N). An SST drop occurred around November 14, which coincides with a peak of the vertical pumping velocity derived from NSCAT-derived wind stress. Two SeaWiFS-derived Chl-a images obtained in November 1998 and 1999 show good agreement in terms of the locations and features with those described above through the OCTS observations. The possible mechanism for this newly identified Chl-a patch is discussed.

This work addresses the analysis of winter monsoon forcing and sea surface temperature (SST) cooling events in the Gulf of Mannar, which is situated between the southeast of the Indian tip and northwest of Sri Lanka, using a 7-year data set derived from satellite sensors. The surface forcing consists of wind stress and turbulent heat flux, which were estimated through the TOGA/COARE algorithm using Special Sensor Microwave Imager (SSM/I) wind, Advanced Very High Resolution Radiometer (AVHRR) SST, and surface atmospheric conditions derived from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalyses data. Net heat flux was derived by combining the turbulent heat flux with net short- and long-wave radiation from the NCEP/NCAR reanalysis data set. SST cooling was monitored by using 9-km spatial resolution pathfinder SST that was derived from the AVHRR. The 7-year weekly mean maps of wind stress, net heat flux, and SST indicate that SST cooling is locally influenced by surface forcing in- and offshore of the Gulf of Mannar. A time series of these parameters near the Indian tip reveal that the strong wind stress and high surface heat loss, which are punctuated in time varying from 15 days to more than a month, occur every winter and lower SST by ∼1.5°C. The occurrence of such a phenomenon is referred to as an event in this work. The bell-shaped events, which have a periodicity of 15 days with a maximum wind stress around Day 8, occur every winter and are characterized by the SST cooling of less than a degree. The features of these events are studied by using the statistical correlation and composite technique. It is inferred that the SST cooling is strongly correlated with the surface forcing.

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.

This report addresses a case of topographic air–sea interaction in the Gulf of Mannar, near the Indian tip, for the winter monsoon of 1996–1997. Using high spatial resolution NASA-Scatterometer (NSCAT) wind data, a 1°×1° region of strong wind is identified in the Gulf during the peak of the winter monsoon. The characteristic topography of South India and Sri Lanka and their orientation to the monsoon wind tend to channel this strong wind. Air–sea heat flux analyses, using the NSCAT wind and the European Center for Medium-Range Weather Forecast objective analyses surface data, reveal that the strong winter monsoon bursts cause large latent heat loss (180 W/m2) from a wind-fetch region centered on 7.5°N, 77.5°E during January. Weak air–sea temperature gradients result in weak sensible heat loss (

[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

[1] Seasonal variability of surface wind stress derived from SeaWINDS onboard the NASA's QuikSCAT satellite is mapped over the latitude range 30°–60°S in the Southern Ocean for the period from August 1999 to July 2003. Seasonal variability is pronounced on basin-wide scale which dominates the Atlantic-Indian Ocean sector during austral winter. Harmonic analysis reveals that seasonal harmonic captures larger than 60% of the variance on regional scales. The cyclonic wind stress curl induces divergence around Antarctica and facilitates ACC meandering equatorward in the Atlantic-Indian Ocean sector of the Southern Ocean.

Atmospheric convergence regions over the tropical Indian Ocean have been mapped for the first time using 31 years of vector wind data. The convergence fields reveal that the energetic summer monsoon winds enhance convergence in the central Arabian Sea and in the eastern Bay of Bengal when compared with weak winter monsoon winds. The summer monsoon is also effective in spatial migration of convergence regions in both basins. Area-integrated convergence time series reveals an annual cycle with high amplitude during summer monsoon, which occurs in phase with Indian rainfall. The study explores the prospects of using the convergence as one of the predictors of Indian rainfall.

[1] We report on sea surface temperature (SST) cooling in the Gulf of Oman during winter monsoon 1993 using evidence from the advanced very high resolution radiometer (AVHRR). A combination of the AVHRR SST and scatterometer-based momentum and heat fluxes is used to discuss the SST-cooling mechanism. Cold SST evolves in the gulf during an intense outbreak of wintertime winds. The turbulence generated by these winds in the surface atmospheric boundary layer depletes large heat from the sea surface and cause 1–2°C SST cooling during January–March. Additionally, the alongshore component of the wind stress promotes Ekman dynamics and further enhances SST cooling along the periphery of the gulf.

[1] Wintertime sea surface temperature (SST) cooling south of the Indian tip (hereafter tip) is investigated during a 14 day gap wind event (21 January to 3 February 1997) using satellite data and the three-dimensional, primitive equation, sigma coordinate Princeton Ocean Model (POM). The advanced very high resolution radiometer SST reveals surface cooling of 1.5°C over the 14 day period near west of Sri Lanka. A spatial-mean time series of surface forcing west of Sri Lanka indicate a bell-shaped pattern, which is characterized by maximum wind stress and outgoing heat flux (sum of turbulent heat flux and net surface long-wave radiation) of 0.12 N/m2 and 450 W/m2, respectively, on 27 January. POM simulation is performed with realistic bottom topography, with seasonal stratification, and with daily mean surface forcing derived from NASA scatterometer (NSCAT) winds and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) meteorological variables. During 21–28 January, Ekman dynamics together with positive wind stress curl promote SST cooling along the west coast of Sri Lanka. Thereafter irregular and shallow topography near the tip promotes diapycnal mixing, and the characteristic surface circulation significantly influences the evolution of the SST pattern along the periphery of the tip. An anticyclonic circulation evolves in the Gulf of Mannar under the influence of local negative wind stress curl after 27 January. Examination of a zonal section of density and vertical heat diffusion reveals that the initial stratification in the vicinity of the tip weakens because of diapycnal mixing and vertical diffusion of the surface heat. The mixed layer heat budget near the west of Sri Lanka and south of the tip reveals that the surface heat depletion dictates SST changes throughout the event. From our earlier works [Luis and Kawamura, 2000, 2001] and from the results of the present investigation it is inferred that the wintertime SST cooling in the vicinity of the tip is a case of topography-monsoon-ocean interaction.

We compared four different image classification methods to improve the accuracy of cryospheric land cover mapping from very high-resolution WorldView-2 (WV-2) satellite images. We used four pixel-by-pixel classification methods and then integrated the classified images using a winner-takes-all (WTA) approach. The images on which we performed the classification techniques were made up of eight-band multispectral images and panchromatic WV-2 images fused using the hyperspherical color sharpening method. We used four distinctly different methods to classify the WV-2 PAN-sharpened data: a support vector machine (SVM), a maximum likelihood classifier (MXL), a neural network classifier (NNC), and a spectral angle mapper (SAM). Three classes of land cover—land mass/rocks, water/lakes, and snow/ice—were classified using identical training samples. The final thematic land cover map of Larsemann Hills, east Antarctica, was integrated using ensemble classification based on a majority voting–coupled WTA method. Results indicate that the WTA integration method and the SVM classification method were more accurate than the MXL, NNC, and SAM classification methods. The overall accuracy of the WTA method was 97.23% (96.47% with the SVM classifier) with a 0.96 kappa coefficient (0.95 with the SVM classifier). The accuracy of the other classifiers were 93.73 to 95.55% with kappa coefficients of 0.91 to 0.93. This work demonstrates the strengths of different classifiers to extract land cover information from multispectral data collected in cryospheric regions.

Here, we discuss the improvements in urban classification that were made using the spatial-spectral-angular information from a WorldView-2 (WV-2) multiangle image sequence. In this study, we evaluate the use of multiangle high resolution WV-2 panchromatic (PAN) and multispectral image (MSI) data for extracting urban geospatial information. Current multiangular WV-2 data were classified into misclassification-prone surfaces, such as vegetation, water bodies, and man-made features, using a cluster of normalized difference spectral index ratios (SIR). A novel multifold methodology protocol was designed to estimate the consequences of multiangularity and germane PAN-sharpening algorithms on the spectral characteristics (distortions) of satellite data and on the resulting land use/land cover (LU/LC) mapping using an array of SIRs. Eight existing PAN-sharpening algorithms were used for data fusion, followed by estimation of multiple SIRs to mitigate spectral distortions arising from the multiangularity of the data. This research highlights the benefits of using traditional PAN-sharpening techniques with a specific set of SIRs on land cover mapping based on five available tiles of satellite data. The research provides a method to overcome the atmospherically triggered spectral distortions of multiangular acquisitions, which will facilitate better mapping and understanding of the earth’s surface.

This study evaluates the potential of 8-band high resolution WorldView-2 (WV-2) panchromatic (PAN) and multispectral image (MSI) data for the extraction of polar geospatial information. We introduce a novel method based on a customized set of normalized difference Spectral Index Ratios (SIRs), incorporating multiple bands, to improve the accuracy of land-cover mapping in the Antarctic. Most recently available WV-2 data are classified into land-cover surfaces such as snow/ice, water bodies, and landmass using the customized normalized difference SIRs. A novel multi-fold methodology is used to evaluate the effect of pan-sharpening algorithms on spectral characteristics of satellite data, and on subsequent land-cover mapping using an array of SIRs. A set of existing pan-sharpening algorithms was implemented in order to fuse PAN with MSI data, followed by estimation of multiple SIRs to extract target land-cover classes. These algorithms were compared on the basis of their effectiveness in extracting target classes using a defined set of SIRs. Our results indicate that the use of 8-band WV-2, customized SIRs, and appropriate pan-sharpening can greatly improve the extraction of land-cover information.

This paper addresses analysis of surface meteorological and hydrographic data collected along the transects Durban–India Bay, Antarctica (Track-1) and Prydz Bay–Mauritius (Track-2) during February–March 2007 as part of the International Polar Year project (IPY#70). Strong winds (>12 m s−1) resulted in enhanced turbulent heat loss north of 45°S. Whereas a highly stable marine atmospheric boundary layer (MABL) and strong winds facilitated the release of latent heat of condensation along Track-1, a highly unstable MABL and strong winds resulted in large turbulent heat loss from the sea surface along Track-2, in the 40–45°S belt. The northern and southern branches of Subantarctic Front on both tracks coalesce, while the Agulhas Retroflection Front (AF) and South Subtropical Front (SSTF) merge between 43° and 44°S on Track-2. The southern branch of the Polar Front (PF2) meanders 550 km southward towards the east. The Subtropical Surface Water, Central Water, and Mode Water are located north of 43.5°S, while the Subantarctic Surface Water, Antarctic Surface Water, Antarctic Intermediate Water, and Circumpolar Deep Water are encountered in the region of the Antarctic Circumpolar Current (ACC). Baroclinic transport relative to 1000 db reveals that the ACC is enhanced by 10 × 106 m3 s−1 eastward, and a four-fold increase in transport occurs south of the ACC. Nearly 50% of the ACC transport occurs in the 100–500 m slab. We discuss the effects of the feedback of AC and hydrological fronts on the MABL.

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.