The accuracy of the Atmospheric Infrared Sounder (AIRS) water vapor product in China is as yet unknown due to the lack of collocated in situ sounding observations. Based on high‐resolution soundings at 1400 Beijing time from 113 radiosonde sites across China, along with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Global Positioning System (GPS) data sets, a preliminary assessment has been conducted of AIRS water vapor mixing ratio (q) and precipitable water vapor (PWV) products in June 2013 and June 2014. Comparison between AIRS and radiosonde data suggests that the correlation coefficient (R) and mean bias of these two q products in China exhibit a distinct geographical dependence (with the highest R values in northwest China). This suggests that the AIRS q product tends to be underestimated in southeast China where cloud cover prevails, but overestimated in northwest China where cloud cover is sparse. With regard to the height‐resolved distribution, the q products from both AIRS and radiosondes tend to decrease with increasing altitude, irrespective of the particular region. The spatial distribution of AIRS PWV is consistent with that from radiosonde‐derived PWV, except in south China where the AIRS PWV data set is considerably underestimated. The accuracy of the AIRS water vapor product tends to be impaired under highly cloudy conditions, corroborating the notion of clouds affecting the retrieval of AIRS PWV. Our findings highlight the importance of afternoon sounding measurements in validating AIRS data and call for the improved understanding of the role of water vapor in the context of global climate change.

A long-term time series of ice sheet surface elevation change (SEC) is an essential parameter to assess the impact of climate change. In this study, we used an updated plane-fitting least-squares regression strategy to generate a 30-year surface elevation time series for the Greenland Ice Sheet (GrIS) at monthly temporal resolution and 5×5 km grid spatial resolution using ERS-1 (European Remote Sensing), ERS-2, Envisat, and CryoSat-2 satellite radar altimeter observations obtained between August 1991 and December 2020. The ingenious corrections for intermission bias were applied using an updated plane-fitting least-squares regression strategy. Empirical orthogonal function (EOF) reconstruction was used to supplement the sparse monthly gridded data attributable to poor observations in the early years. Validation using both airborne laser altimeter observations and the European Space Agency GrIS Climate Change Initiative (CCI) product indicated that our merged surface elevation time series is reliable. The accuracy and dispersion of errors of SECs of our results were 19.3 % and 8.9 % higher, respectively, than those of CCI SECs and even 30.9 % and 19.0 % higher, respectively, in periods from 2006–2010 to 2010–2014. Further analysis showed that our merged time series could provide detailed insight into GrIS SEC on multiple temporal (up to 30 years) and spatial scales, thereby providing an opportunity to explore potential associations between ice sheet change and climatic forcing. The merged surface elevation time series data are available at https://doi.org/10.11888/Glacio.tpdc.271658 (Zhang et al., 2021).

This study explores an iterative method for simultaneously estimating the present-day glacial isostatic adjustment (GIA), ice mass change and elastic vertical crustal deformation of the Antarctic ice sheet (AIS) for the period October 2003–October 2009. The estimations are derived by combining mass measurements of the GRACE mission and surface height observations of the ICESat mission under the constraint of GPS vertical crustal deformation rates in the spatial domain. The influence of active subglacial lakes on GIA estimates are mitigated for the first time through additional processing of ICESat data. The inferred GIA shows that the strongest uplift is found in the Amundsen Sea Embayment (ASE) sector and subsidence mostly occurs in Adelie Terre and the East Antarctica inland. The total GIA-related mass change estimates for the entire AIS, West Antarctica Ice Sheet (WAIS), East Antarctica Ice Sheet (EAIS), and Antarctic Peninsula Ice Sheet (APIS) are 43 ± 38, 53 ± 24, −23 ± 29 and 13 ± 6 Gt a⁻¹, respectively. The overall ice mass change of the AIS is −46 ± 43 Gt a⁻¹ (WAIS: −104 ± 25, EAIS: 77 ± 35, APIS: −20 ± 6). The most significant ice mass loss and most significant elastic vertical crustal deformations are concentrated in the ASE and northern Antarctic Peninsula.

The elevation changes of ice sheets have been recognized as an essential climate variable. Long-term time series of these changes are an important parameter to understand climate change, and the longest time-series of ice sheet elevation changes can be derived from combining multiple Ku-band satellite altimetry missions. However, unresolved intermission biases obscure the record. Here, we revise the mathematical model commonly used in the literature to simultaneously correct for intermission bias and ascending–descending bias to ensure the self-consistency and cohesion of the elevation time series across missions. This updated approach is applied to combine Envisat and CryoSat-2 radar altimetry in the period of 2002–2019. We tested this approach by validating it against airborne and satellite laser altimetry. Combining the detailed temporal and spatial evolution of elevation changes with firn densification-modeled volume changes due to surface processes, we found that the Amundsen Sea sector accounts for most of the total volume loss of the Antarctic Ice Sheet (AIS), mainly from ice dynamics. However, surface processes dominate the volume changes in the key regions, such as the Totten Glacier sector, Dronning Maud Land, Princess Elizabeth Land, and the Bellingshausen Sea sector. Overall, accelerated volume loss in the West Antarctic continues to outpace the gains observed in the East Antarctic. The total volume change during 2002–2019 for the AIS was −68.7 ± 8.1 km³/y, with an acceleration of −5.5 ± 0.9 km³/y².

Monitoring the hydrological activities of subglacial lakes is critical to understanding the subglacial hydrological system and evaluating the internal mass changes of the Antarctic ice sheet. Drainage or filling events of active lakes lead to elevation changes in the ice surface. These changes can be observed by satellite altimetry, but the monitoring must be conducted continuously since the water movements in active subglacial lakes may occur frequently. We used CryoSat-2 Baseline-D and ICESat-2 data from 2010 to 2020 to obtain the time series of the ice surface elevation changes for 17 active lakes. We also evaluated the uncertainty of the time series derived from the CryoSat-2 data by cross-validation. The mean and RMS of the biases between the CryoSat-2-based and ICESat-2-based time series are generally less than 0.3 m and 1.0 m, respectively. However, the mean and RMS are greater over the lakes with rough ice surfaces, such as Whillans₆, KT1, Mac3, and Slessor₂₃. The drainage and filling events continue exhibiting in the extended period and the hydrological activities of SLW, L12, Whillans₆, L78, and Mac1 occurred periodically. Furthermore, we inferred the hydrological connections between the lakes combining simulated water pathways.