Abstract Lake water height is a key variable in water cycle and climate change studies, which is achievable using satellite altimetry constellation. A method based on data processing of altimetry from several satellites has been developed to interpolate mean lake surface (MLS) over a set of 22 big lakes distributed on the Earth. It has been applied on nadir radar altimeters in Low Resolution Mode (LRM: Jason-3, Saral/AltiKa, CryoSat-2) in Synthetic Aperture Radar (SAR) mode (Sentinel-3A), and in SAR interferometric (SARin) mode (CryoSat-2), and on laser altimetry (ICESat). Validation of the method has been performed using a set of kinematic GPS height profiles from 18 field campaigns over the lake Issykkul, by comparison of altimetry’s height at crossover points for the other lakes and using the laser altimetry on ICESat-2 mission. The precision reached ranges from 3 to 7 cm RMS (Root Mean Square) depending on the lakes. Currently, lake water level inferred from satellite altimetry is provided with respect to an ellipsoid. Ellipsoidal heights are converted into orthometric heights using geoid models interpolated along the satellite tracks. These global geoid models were inferred from geodetic satellite missions coupled with absolute and regional anomaly gravity data sets spread over the Earth. However, the spatial resolution of the current geoid models does not allow capturing short wavelength undulations that may reach decimeters in mountaineering regions or for rift lakes (Baikal, Issykkul, Malawi, Tanganika). We interpolate in this work the geoid height anomalies with three recent geoid models, the EGM2008, XGM2016 and EIGEN-6C4d, and compare them with the Mean Surface of 22 lakes calculated using satellite altimetry. Assuming that MLS mimics the local undulations of the geoid, our study shows that over a large set of lakes (in East Africa, Andean mountain and Central Asia), short wavelength undulations of the geoid in poorly sampled areas can be derived using satellite altimetry. The models used in this study present very similar geographical patterns when compared to MLS. The precision of the models largely depends on the location of the lakes and is about 18 cm, in average over the Earth. MLS can serve as a validation dataset for any future geoid model. It will also be useful for validation of the future mission SWOT (Surface Water and Ocean Topography) which will measure and map water heights over the lakes with a high horizontal resolution of 250 by 250 meters.

中文翻译：

---

从卫星测高和 GPS 运动学测量绘制平均湖面

摘要 湖水高度是水循环和气候变化研究中的关键变量，可通过卫星测高星座实现。已经开发了一种基于对来自多颗卫星的测高数据进行处理的方法，以对分布在地球上的 22 个大湖泊的平均湖面 (MLS) 进行插值。它已应用于低分辨率模式（LRM：Jason-3、Saral/AltiKa、CryoSat-2）、合成孔径雷达（SAR）模式（Sentinel-3A）和合成孔径雷达干涉（SARin）模式的天底雷达高度计（ CryoSat-2) 和激光测高仪 (ICESat)。该方法的验证是使用一组来自 Issykkul 湖上 18 次野外活动的运动学 GPS 高度剖面进行的，通过比较其他湖泊交叉点的高度测量，并在 ICESat-2 任务中使用激光高度测量。根据湖泊的不同，达到的精度范围为 3 到 7 cm RMS（均方根）。目前，从卫星测高推断的湖水位是相对于椭球体提供的。使用沿卫星轨道插值的大地水准面模型将椭球体高度转换为正高。这些全球大地水准面模型是从大地测量卫星任务以及分布在地球上的绝对和区域异常重力数据集推断出来的。然而，当前大地水准面模型的空间分辨率不允许捕捉在登山区或裂谷湖（贝加尔湖、伊塞库尔、马拉维、坦噶尼卡）可能达到分米的短波长波动。我们在这项工作中用三个最近的大地水准面模型 EGM2008、XGM2016 和 EIGEN-6C4d 插入大地水准面高度异常，并将它们与使用卫星高度计计算的 22 个湖泊的平均表面进行比较。假设 MLS 模拟了大地水准面的局部波动，我们的研究表明，在大量湖泊（东非、安第斯山脉和中亚）上，可以使用卫星测高法推导出采样不足地区大地水准面的短波长波动。与 MLS 相比，本研究中使用的模型呈现出非常相似的地理模式。模型的精度在很大程度上取决于湖泊的位置，在地球上平均约为 18 厘米。MLS 可以作为任何未来大地水准面模型的验证数据集。它还将有助于验证未来的 SWOT（地表水和海洋地形）任务，该任务将以 250 x 250 米的高水平分辨率测量和绘制湖泊上方的水高。