Permafrost in the Arctic regions is degrading in response to decades of amplified warming. Advanced degradation of ice‐rich permafrost could significantly alter the water balance by increasing runoff and flooding. How do the hydrological changes in river systems, in turn, affect the permafrost thermal state, specifically in floodplains? First, we develop a first‐order heat budget approach to simulate evolving river‐water temperature. The river‐water thermal model includes heat exchanges at both the air‐water and water‐subsurface interfaces and can accurately estimate water temperature. Then, river‐water temperature is employed as an upper boundary condition for the control volume permafrost model, which models the thermal state of shallow permafrost. The combined model is validated and applied in the Kuparuk River floodplain, Alaska. Results indicate that permafrost warms rapidly during inundation and that channelbelt active layer thickness can deepen by more than 1 m. We find that earlier arrival of the spring freshet and associated earlier inundation onset, as well as increase in river discharge, can significantly increase subsurface permafrost temperature and lead to a deepening of the active layer. In recent years Kuparuk River streamflow has arrived earlier, and mean annual river discharge has increased by 35% since the 1970s. New permanent water and seasonal water appeared throughout the river network of the Kuparuk River since the 1980s according to satellite observations. These hydrological changes likely have contributed to the expansion of riverbed thaw bulbs and the degradation of floodplain permafrost.

The past decades have witnessed a rapid loss of the Arctic sea ice and a significant lengthening of the melt season. The years with the lowest summertime sea ice minimum were found to be accompanied by the latest freeze-up onset on record. Here, a synthetic approach is taken to examine the connections between sea ice melt timing and summer sea ice evolution from the remote sensing perspective. A 40-year (1979–2018) satellite-based time-series analysis shows that the date of autumn sea ice freeze-up is significantly correlated with the sea ice extent in early summer (r = −0.90, p < 0.01), while the spring melt onset is not a promising predictor of summer sea ice evolution. The delay in Arctic sea ice freeze-up (0.61 days year⁻¹) in the Arctic was accompanied by a decline in surface albedo (absolute change of −0.13% year⁻¹), an increase in net short-wave radiation (0.21 W m⁻² year⁻¹), and an increase in skin temperature (0.08 °C year⁻¹) in summer. Sea ice loss would be the key reason for the delay in autumn freeze-up, especially in the Laptev, East-Siberian, Chukchi and Beaufort Seas, where sea ice has significantly declined throughout the summer, and strong correlations were found between the freeze-up onset and the solar radiation budget since early summer. This study highlights a connection between the summer sea ice melting and the autumn refreezing process through the ice-albedo feedback based on multisource satellite-based observations.

In this study, we classified the variability in snow cover persistence across China by using a novel method; continuous snow cover days and variability of snow cover were used as the evaluation indicators based on a long-term Advanced Very High Resolution Radiometer (AVHRR) snow cover extent (SCE) product. The product has been generated by the snow research team in the Northwest Institute of Eco-Environment and Resources (NIEER), Chinese Academy of Sciences. There were obvious differences in snow cover classification in three snow cover areas (northern Xinjiang, northeast China, and the Tibetan Plateau): northern Xinjiang was dominated by persistent snow cover, most regions of northeast China were covered by persistent and periodic variable snow cover. There was the most abundant snow cover classification in the Tibetan Plateau. The extents of persistent and periodic variable snow cover were gradually shrinking due to rising temperatures and decreasing snowfall during 1981–2019. In contrast, non-periodic variable snow cover areas increased significantly. This method takes into account the stability, continuity, and variability of snow cover, and better captures the characteristics and changes of snow cover across China. Based on our research, we found that snow disasters in ephemeral-type (belong to non-periodic variable snow cover) regions cannot be well prevented because of the unfixed snow cover timing. Therefore, we recommend that monitoring and forecasting of snow cover in these snow cover regions should be strengthened.

Mass loss from the Antarctic Ice Sheet (AIS) is an important contributor to global sea level rise. To examine the recent ice loss, we estimated the mass budget of the AIS from 2000 to 2020 using multiple ice velocity datasets, state-of-the-art ice thickness datasets, and extended surface mass balance (SMB) records. The AIS lost mass at an average rate of −89 ± 99 Gt/yr over the study period. The East Antarctic Ice Sheet (EAIS) showed a slightly positive mass balance, while the West Antarctic Ice Sheet (WAIS) experienced a significant acceleration in mass loss. The ice discharge from the AIS increased from 1792 ± 47 Gt/yr in 2000 to 1940 ± 37 Gt/yr in 2017–2020, with the increase in the discharge from the WAIS being three to four times higher than that from the EAIS. Moreover, the average mass balance for 2017–2020 was −99 ± 93 Gt/yr, slightly more negative than the average for the early 21st Century. During this recent period, the ice discharge decreased in the East Indian Ocean sector, in contrast to its rapid increase from 2000 to 2013–2017. However, the discharge in the Amundsen Sea sector still greatly increased from 2013–2017 to 2017–2020. Overall, our results are in agreement with recent mass balance estimates for the AIS based on gravimetry and altimetry. Our assessments of the recent AIS mass balance with the mass budget method (input-output method) will contribute to the understanding of ice dynamic processes and provide insights into the stability of the AIS.