Himalayan glaciers are the major source of fresh water supply to the Himalayan Rivers, which support the livelihoods of more than a billion people living in the downstream region. However, in the face of recent climate change, these glaciers might be vulnerable, and thereby become a serious threat to the future fresh water reserve. Therefore, special attention is required in terms of understanding moisture sources for precipitation over the Himalayan glaciers and the hydrograph components of streams and rivers flowing from the glacierized region. We have carried out a systematic study in one of the benchmark glaciers, “Sutri Dhaka” of the Chandra Basin, in the western Himalayas, to understand its hydrograph components, based on stable water isotopes (δ¹⁸O and δ²H) and field-based ablation measurements. Further, to decipher moisture sources for precipitation and its variability in the study region, we have studied stable water isotopes in precipitation samples (rain and snow), and performed a back-trajectory analysis of the air parcel that brings moisture to this region. Our results show that the moisture source for precipitation over the study region is mainly derived from the Mediterranean regions (>70%) by Western Disturbances (WDs) during winter (October–May) and a minor contribution (<20%) from the Indian Summer Monsoon (ISM) during summer season (June–September). A three-component hydrograph separation based on δ¹⁸O and d-excess provides estimates of ice (65 ± 14%), snowpack (15 ± 9%) and fresh snow (20 ± 5%) contributions, respectively. Our field-based specific ablation measurements show that ice and snow melt contributions are 80 ± 16% and 20 ± 4%, respectively. The differences in hydrograph component estimates are apparently due to an unaccounted snow contribution ‘missing component’ from the valley slopes in field-based ablation measurements, whereas the isotope-based hydrograph separation method accounts for all the components, and provides a basin integrated estimate. Therefore, we suggest that for similar types of basins where contributions of rainfall and groundwater are minimal, and glaciers are often inaccessible for frequent field measurements/observations, the stable isotope-based method could significantly add to our ability to decipher moisture sources and estimate hydrograph components.

Antarctic sea ice is a critical component of the ocean‐climate system. Sea ice concentration (SIC) records of various oceanic sectors of Antarctica available since 1979 reveal dramatic changes in recent years; however, there is no consensus yet on drivers of sea ice variability, changes and their future projections. The lack of long‐term SIC records has impeded the quantification of sea ice variability, trends and various forcing factors and mechanisms. Here, we present a long‐term SIC record (1809−1993 CE) for the Western Indian Ocean Sector (WIOS) of Antarctica derived from a new ice core oxygen isotope (δ¹⁸O) record together with three available records from Dronning Maud Land (DML), East Antarctica. This long‐term SIC record at annual resolution reveals a significant decline during 1830–1884 CE with a rate of 0.58% ± 0.12% decade⁻¹ followed by moderate increase during 1927–1993 CE with a rate of 0.24% ± 0.11% decade⁻¹. Current satellite‐derived SIC records reveal an increase of 2.59 ± 0.86% decade⁻¹ during 1994–2014 CE, which is unprecedented over the last two centuries as determined by the ice core‐derived SIC record. The satellite and ice core combined SIC record (1809−2019 CE) also reveals a significant increase in interannual variability at El Niño Southern Oscillation band and decadal variability at 16–32 years band in the last few decades. Our investigation suggests that wind‐driven sea‐ice dynamics associated with switching phases of Southern Annular Mode and remote teleconnections of Pacific oscillations largely control the interannual to decadal sea ice variability in this region.

The coastal Droning Maud Land in East Antarctica is characterized by small ice shelves with numbers of promontories and locally grounded isles, both called ice rises. These ice rises are typically dome-shaped and surface elevations are hundreds of meters above the surrounding ice shelves, which cause strong orographic effects on surface mass balance (SMB). We conducted shallow ice-penetrating radar sounding to visualize firn stratigraphy in the top 35 m over ~400 km of profiles across the Nivlisen Ice Shelf, and in a grid pattern over two adjacent ice rises (Djupranen and Leningradkollen). We tracked six reflectors (isochrones) and dated them using two ice cores taken at the ice rise summits, from which SMB over six periods in the past three decades was retrieved. The overall SMB pattern across the ice shelf remained similar for all periods; however, the eastwest contrast in SMB varies by a factor of 1.5–2 between the Leningradkollen and Djupranen grounding lines. The SMB patterns over the ice rises are more varied owing to complex interactions between topography, snowfall and wind. We use our results to evaluate the regional climate model RACMO2.3p2 in terms of the spatial SMB distribution and temporal changes over the ice shelf and ice rises at regional scale.

Atmospheric dust influences global climate and ocean biogeochemistry. Here we present a high‐resolution ice core dust record (1905–2005 CE) from coastal Dronning Maud Land (71°20′S, 11°35′E), East Antarctica, to understand dust flux variability, its causes, and potential contribution to radiative forcing during the 20th century in the South Atlantic sector of East Antarctica (SASA). The dust flux profile (sum of 1–25 μm size fractions) reveals three stepwise increase during 1905–1929, 1930–1979, and 1980–2005 CE time with an average of 0.83, 4.7, and 12.88 mg·m⁻²·year⁻¹, respectively. Our investigation for such dramatic dust flux increase reveals that the increased aridity and favorable wind conditions over Southern South America (SSA), a potential dust source to Antarctica, caused increase in dust production and transport during the late 20th century. The dust flux variability in Southern Hemisphere is concomitant with in‐phase relationship between El‐Niño Southern Oscillation and Pacific Decadal Oscillations, which influenced the spatial distribution of global wet‐dry phase (precipitation pattern). Further, shifting of Southern Annular Mode to positive phase made wind conditions more conducive for long‐range dust transport from SSA to coastal Dronning Maud Land region. To the best of our knowledge, this is the first report of past radiative forcing estimates for Antarctica using ice core dust record into a radiative transfer model. Our estimates of radiative forcing corresponding to the enhanced dust flux yield nearly 30% increase in aerosol forcing during the late 20th century. This has resulted 40% decrease in atmospheric cooling rate, which contributed to net atmospheric warming over SASA.

Establishing an accurate chronology is crucial for interpretation of ice core-based climatic records. While high snow accumulation rates characterise coastal Antarctica, thus enabling recovery of highly resolved climatic records, summertime melting at such low-elevation sites offers challenges in establishing a reliable chronological framework through traditional approaches using the seasonality of stable water isotope and ionic proxy records. Here, we assess visual stratigraphy (VS) obtained from line-scan images as a proxy for annual layer counting in firn section (top 50 m) of the IND-36/B9 ice core (dated 1919–2016 CE) from the Djupranen Ice Rise in central Dronning Maud Land, East Antarctica. We also used these images to obtain melt history for the site and found that traditional thickness-based quantification of melt proportion results in significant overestimations. Since density has dominant control on VS profile over the firn section, we first used circulant single-spectrum analysis to remove the secular trend and then we extracted the seasonal VS signals attributed to dust and sea-salt inclusions. We find that melt layers do not significantly alter the VS records if masked during pre-processing. The age–depth model based on the reconstructed VS profile revealed an excellent match with identified time-markers within an uncertainty of ±2 years.