Search

AbstractAltimetry missions designed for ocean monitoring can also evaluate the Antarctic ice sheet’s mass balance by measuring surface height. However, the returned radar echoes (waveforms) have complex shapes influenced by various snow and ice surface properties at multiple scales. Radar altimeters, operating in different modes and frequencies, interact with these surface properties in diverse ways. In this study, we developed a method to assess Antarctic surface properties using data from SARAL/AltiKa and Sentinel-3A & 3B altimeters for June 2021 and January 2023, respectively. We normalized and averaged the observed waveforms in 5 × 5 km2 grid cells. These were then used to create false-color images, with each grid cell’s average power and time gate represented as different ‘bands’. False-color images were analyzed using Principal Component Analysis (PCA) and ISODATA unsupervised classification to identify regions of Antarctica with similar surface properties. We achieved a percent variance of 73% and 84% for the first three Principal Components (PCs), and 96% and 98% for the first ten PCs with the Sentinel-3 and SARAL/AltiKa datasets, respectively. Finally, we analyzed the Ka and Ku band altimeter waveform shapes for each identified class to better understand snow and ice sensitivity to waveforms. [ABSTRACT FROM AUTHOR]

Intra and inter-annual variations in the sea ice thickness are highly sensitive indicators of climatic variations undergoing in the earth's atmosphere and oceans. This paper describes the method of estimating sea ice thickness using radar waveforms data acquired by SARAL/Altika mission during its drifting orbit phase from July 2016 onwards yielding spatially dense data coverage. Based on statistical analysis of return echoes, classification of the surface has been carried out in three different types, viz. floe, lead and mixed. Time delay correction methods were suitably selected and implemented to make corrections in altimetric range measurements and thereby freeboard. By assuming hydrostatic equilibrium, freeboard data were converted into sea ice thickness. Results show that sea ice thickness varies from 4 to 5 m near ice shelves and 1 to 2.5 m in the marginal sea ice regions. Freeboard and sea ice thickness estimates were also validated using NASA's Operation Ice Bridge (OIB) datasets. Freeboard measurements show very high correlation (0.97) having RMSE of 0.13. Overestimation of approximately 1–2 m observed in the sea ice thickness, which could be attributed to distance between AltiKa footprint and OIB locations. Moreover, sensitivity analysis shows that snow depth and snow density over sea ice play crucial role in the estimation of sea ice thickness. [ABSTRACT FROM AUTHOR]

The present study has been executed for providing sea ice advisory during the 40th Indian Scientific Expedition to Antarctica (ISEA) to carry out a smoother expedition. The near real-time knowledge of sea ice conditions along with safe, optimum and less fuel consumption routes is essential for expedition vessel movement through the Antarctic sea ice regions. The radar can distinguish between more navigable thinner/weaker sea ice and the hazardous, much thicker sea ice along with icebergs to help assure safe navigation in ice-covered regions. In the current study, considering the advantage of spatial and temporal resolutions along with acquisition modes of the Sentinel-1, we have standardized the procedure to find the penetrable passage within the sea ice packs. The pre-processing steps of Sentinel-1 data were performed to generate backscattered products. Further, for intensity images of Interferometric Wide (IW) mode and Extra Wide (EW) mode, the procedure for identification of different types of sea ice and ocean water has been discussed in the paper. Our study also highlights the use of ERA 5 reanalysis data for better interpretation of SAR data due to the presence of the blizzard footprint in the acquired image. And finally, a significantly improved near real-time Sea Ice Advisory (SIA) surrounding two Indian Antarctic Research Stations was produced and utilised to support safer navigation during the 40th ISEA voyage. [ABSTRACT FROM AUTHOR]

Present study focuses on the utilization of Earth observation satellite-04 (EOS-04) synthetic aperture radar (SAR) data for maintaining the continuity of the first Indian radar imaging satellite (RISAT)-1 SAR derived products along with exploring the potential of capability of the improved sensor over mountain and polar cryospheric region. Backscattering coefficient (σ0) of various snow and ice features over mountain and polar cryosphere have been analysed to understand the interaction mechanism using C-band SAR data. EOS-04 is able to pick up the spatio-temporal variability of SAR backscatters over accumulation and ablation zone of the glacier due to melt-freeze cycles, and observations were in accordance with variation in elevations over the glacier surface. When analysed for Drang-Drung glacier, wet snow zone was found to be prominently centered around 5500 m elevation zone, having sigmanaught backscatter lower than –10 dB in the ablation months, whereas percolation zone was observed at more than 6000 m elevation with higher sigma-naught backscatter of around –4 dB and above as winter started setting in. EOS-04 also showed the potential to classify various polar ice features based on backscattering signature using HH (H, horizontal) (σ0), HV (V, vertical) (σ0) and normalized difference polarization ratio index (NDPRI) respectively. EOS-04 data have been used to implement approaches to retrieve wet snow cover and set up of Weather Research and Forecasting Model Hydrological Modelling System (WRF hydro) model for snow melt runoff studies, interaction mechanism of snow and ice, snow/ice facies extraction, ice shelf monitoring, sea ice properties and sea ice advisory for Indian scientific expedition to Antarctica. Enrichment of EOS-04 data, suitable for cryosphere studies, will be employed to retrieve parameters such as snowpack properties, elevation, ice surface velocities over mountain and polar region, and to further improve comprehensive understanding on regional and global frozen ice dynamics. [ABSTRACT FROM AUTHOR]

We present the observed area changes in 5234 glaciers (out of which 3435 are debris-free) of Himalaya–Karakoram (H–K) region, mapped at a scale of 1 : 25,000 using primarily IRS LISS III data between the years 2001 and 2016/2017/2018. Area change is a direct observable parameter in the monitoring of glaciers. The mapping results have been analysed in different sectors of H–K region. In the Karakoram region, 2143 glacier bodies with an area coverage of 18343.39 km2 show a gain of 0.026%, whereas in Himalayan region, 3091 glaciers covering an area of 11451.53 km2 show a loss of 1.44% over a span of 17 years. Loss in glacier area in Himalayan region varies from 0.76% in sub-basins located in the left side of NW flowing Indus River (N–W Himalaya/J&K and Ladakh), 2.2% in Chenab and Sutlej basins (Western Himalaya/Himachal Pradesh), 0.84% in Ganga basin (West-Central Himalaya/ Uttarakhand), 2.16% in Ganga basin (Central Himalaya/Nepal and a few glaciers of Tibetan region) and 2.15% in Tista sub-basin (Eastern Himalaya/ Sikkim). The mapping uncertainty is less than 0.01%. The results also show that debris free glaciers are more vulnerable to global warming thereby affirming the earlier theories of differential impact of warming on debris free and debris covered glaciers. Overall, the statistics clearly indicate the effect of latitudinal variations on the gain/loss in the area of glaciers from higher to lower latitudes in addition to microclimatic and geomorphological factors. [ABSTRACT FROM AUTHOR]

In this study, a bottom-up approach of ion irradiation from hot cathode DC discharge plasma was used to investigate the role of energetic ion flux on the self-assembly of GaSb nanodots (NDs) at normal incidence. It was observed that, when increasing the flux in the range of 10 14 -10 15 ions cm -2 s -1 , the lateral dimension and root mean square (RMS) roughness of NDs is reduced even at constant temperature conditions in the ion energy range from 400-800 eV. The evolution of the surface morphology for different flux regimes is observed in a numerical integration simulation using the nonlinear isotropic damped Kuramoto-Sivashinsky (DKS) equation. By introducing a redeposition term, the DKS equation is found to be in good qualitative agreement with the experimental results. We have demonstrated the linear dependency of the redeposition coefficient on the ion flux and also reported the nonlinear dependency on the thermal diffusion coefficient, transition time, and characteristic length with the flux. In accordance with the nonlinearity, we have also discussed the effect of the variation of the ion flux on the RMS roughness and lateral dimension of NDs.