海冰表面积雪深度是利用卫星测高技术反演海冰厚度的关键参数。基于ICESat-2和CryoSat-2测高卫星的协同观测数据（简称IS2CS），对比与评估卫星测高雪深估算的两种时空匹配方法（轨迹搜索法和格网搜索法），并对2018-2024年北极海冰生长期（10月至次年4月）积雪深度的时空分布特征进行分析。结果表明：（1）IS2CS轨迹法雪深与OIB实测数据具有较高的沿轨相关性，能够较好地捕获沿轨积雪深度的变化特征；（2）格网法雪深更适合表征大尺度积雪深度的空间分布和季节性变化特征，本文格网法雪深和GSFC雪深精度相当，在SIMBA数据的评估中本文格网法雪深性能优于GSFC雪深；（3）相比IS2CS雪深，MW99/AMSR2雪深相对偏厚，且在海冰生长期内季节性变化表征能力较弱；（4）海冰积雪深度呈现明显的时空差异，多年冰表面雪深普遍厚于一年冰表面雪深，春季雪深厚于秋冬季雪深。2018-2024年间，北极海冰表面积雪深度总体呈现减薄趋势，且多年冰区域的雪深减薄速率高于一年冰区域。研究成果为改进卫星测高雪深产品和优化海冰厚度反演算法提供了科学依据。

北极海冰是地球气候系统的重要因子,获取精确的海冰厚度及其变化信息对于开展北极和全球变化研究等有着重要的意义.卫星测高是获取连续、大范围海冰厚度的主要方法之一.冰间水道识别是卫星测高方法估算海冰厚度的关键之一.基于CryoSat-2数据,利用遥感影像对两种主要的冰间水道识别方法进行了对比,发现波形特征法能够更好地识别冰间水道.考虑到雷达信号对海冰表面积雪的不完全穿透,对海冰干舷-厚度转化模型进行了优化,通过选取合适的输入参数,获取了2010年11月至2019年12月北极海冰厚度,并利用IceBridge海冰厚度产品和仰视声呐数据对计算结果进行了验证,结果表明本文海冰厚度解算精度优于0.2m.最后,结合PIOMAS海冰模式数据、北极气温和海表面温度数据对北极海冰厚度变化特征进行了分析,发现2014年北极海冰厚度出现剧烈增长的现象.

The negative freeboard of sea ice (i.e., the height of ice surface below sea level) with subsequent flooding is widespread in the Southern Ocean, as opposed to the Arctic, due to the relatively thicker ice and thinner snow. In this study, we used the observations of snow and ice thickness from 103 ice mass balance buoys (IMBs) and NASA Operation IceBridge Aircraft Missions to investigate the spatial distribution of negative freeboard of Arctic sea ice. The Result showed that seven IMBs recorded negative freeboards, which were sporadically located in the seas around Northeast Greenland, the Central Arctic Ocean, and the marginal areas of the Chukchi-Beaufort Sea. The observed maximum values of negative freeboard could reach -0.12 m in the seas around Northeast Greenland. The observations from IceBridge campaigns also revealed negative freeboard comparable to those of IMBs in the seas around North Greenland and the Beaufort Sea. We further investigated the large-scale distribution of negative freeboard using NASA CryoSat-2 radar altimeter data, and the result indicates that except for the negative freeboard areas observed by IMBs and IceBridge, there are negative freeboards in other marginal seas of the Arctic Ocean. However, the comparison of the satellite data with the IMB data and IceBridge data shows that the Cryosat-2 data generally overestimate the extent and magnitude of the negative freeboard in the Arctic.

Terrestrial water storage (TWS) is a key variable in global and regional hydrological cycles. In this study, the TWS changes in the Yangtze River Basin (YRB) were derived using the Lagrange multiplier method (LMM) from Gravity Recovery and Climate Experiment (GRACE) data. To assess TWS changes from LMM, different GRACE solutions, different hydrological models, and in situ data were used for validation. Results show that TWS changes from LMM in YRB has the best performance with the correlation coefficients of 0.80 and root mean square error of 1.48 cm in comparison with in situ data. The trend of TWS changes over the YRB increased by 10.39 +/- 1.27 Gt yr(-1) during the 2003-2015 period. Moreover, TWS change is disintegrated into the individual contributions of hydrological components (i.e., glaciers, surface water, soil moisture, and groundwater) from satellite data, hydrologic models, and in situ data. The estimated changes in individual TWS components in the YRB show that (1) the contribution of glaciers, surface water, soil moisture, and groundwater to total TWS changes is 15%, 12%, 25% and 48%, respectively; (2) Geladandong glacier melt from CryoSat-2/ICESat data has a critical effect on TWS changes with a correlation coefficients of -0.51; (3) the Three Gorges Reservoir Impoundment has a minimal effect on surface water changes (mainly lake water storage), but it has a substantial effect on groundwater storage (GWS), (4) the Poyang and Doting Lake water storage changes are mainly caused by climate change, (5) soil moisture storage change is mainly influenced by surface water, (6) human-induced GWS changes accounted for approximately half of the total GWS. The results of this study can provide valuable information for decision-making in water resources management.

本文利用CryoSat-2测高数据与Landsat 8光学数据,针对南极Amery冰架区域开展接地线提取研究.首先通过Landsat 8光学影像三次Hermite多项式插值处理,在坡度分析的基础上利用表面曲率改进方法获取接地线特征点;同时对CryoSat-2测高数据进行坡度分析和表面曲率计算,通过沿轨梯度分析方法提取接地点;最后将Landsat 8与CryoSat-2数据获取的接地点进行最小二乘融合得到融合接地线.实验结果表明,融合结果利用高空间分辨率光学数据不仅能保证接地线提取精度,同时测高数据还能够弥补光学数据受云遮挡导致的数据空缺,保持接地线的完整性.与MOA产品比较可以看出,融合数据点与MOA接地线平均距离为367 m,标准差为601 m,所有数据点中距离小于1 km的点占总数的93.19%,与MOA产品具有较好一致.本文提出的融合算法可以实现空间连续的接地线提取结果,对后续研究南极物质平衡、冰流速计算等具有重要的意义.

Gravity Recovery and Climate Experiment (GRACE) and satellite altimetry are suitable for the precise measurement of terrestrial water storage (TWS) and lake water level variations from space. In this study, two GRACE solutions, namely, spherical harmonics (SH) and mascon (MSC), are utilized with the Global Land Data Assimilation System (GLDAS) model to estimate the spatial and temporal variations of TWS in the Upper Indus Basin (UIB) for the study period of January 2003 to December 2016. The TWS estimated by SH, MSC, and the GLDAS model are consistent and generally show negative trends of & x2212;4.47 & x00B1; 0.38 mm/year, & x2212;4.81 & x00B1; 0.49 mm/year, and & x2212;3.77 & x00B1; 0.46 mm/year, respectively. Moreover, we use the GLDAS model data to understand the roles of variations in land surface state variables (snow water equivalent (SWE), soil moisture, and canopy water storage) in enhancing or dissipating the TWS in the region. Results indicate that SWE, which has a significant contribution to GRACE TWS variability, is an important parameter. Spearman & x2019;s rank correlations are calculated to demonstrate the relationship of the GLDAS land surface state variables and the GRACE signals. A highly positive correlation between SWE with TWS is estimated by SH and MSC as 0.691 and 0.649, respectively, indicating that the TWS signal is mainly reliant on snow water in the study region. The ground water storages estimated by SH and MSC solutions are nearly stable with slight increasing trends of 0.63 & x00B1; 0.48 mm/year and 0.29 & x00B1; 0.51 mm/year, respectively. We also take advantage of the potential of satellite altimetry in measuring lake water level variations, and our result indicates that Cryosat-2 SARin mode altimetry data can be used in estimating small water bodies accurately in the high mountainous region of the UIB. Moreover, the climate indices data of El-Ni & x00F1;o Southern Oscillation and Pacific Decadal Oscillation are analyzed to determine the influence of pacific climatic variability on TWS.