多源卫星测高数据监测拉昂错1992年—2020年水位变化

青藏高原湖泊水位是反映生态环境变化的重要指标,为了使用多源卫星测高数据构建高精度、长时序的湖泊水位时间序列,本文提出了一种基于大气路径延迟校正、波形重定、异常值检测、卫星间偏差调整的高精度湖泊水位序列构建策略.以拉昂错为研究对象,利用本文方法对TOPEX/Poseidon、Jason-1/2/3高度计数据进行处理,构建...

Monitoring lake level change in La-ang Co from 1992 to 2020 using multi-altimeter data

Tibetan Plateau (TP) lakes are located in the high-altitude and rough-terrain region. These lakes are effective indicators and sentinels of climate changes because of the absence of direct anthropogenic influence and their dominant distribution in endorheic basins. Altimetry satellites can be used to monitor the water level changes of inland water bodies. However, satellites cannot easily obtain accurate and continuous observations of Tibetan lakes with steep terrain. This paper presents a robust scheme for constructing accurate and long-term lake level time series using multi-altimeters. We demonstrate the robust scheme over La-ang Co.A robust strategy is presented to obtain lake levels on the TP using multi-altimeter data. The consistency of atmospheric path delay corrections should be carefully checked to integrate various altimeter products issued in different periods. Apparent biases are found in troposphere corrections from different altimeter products and updated by ERA-5 model. ICE retracker is used to correct the altimeter range. A two-step method is proposed for outlier removal, which has accurate performance without any a prior information. Bias adjustment is an essential step in the fusion of multi-altimeters. Tandem mission data of altimeters are used to estimate inter-satellite bias. Finally, a 28-year-long lake level time series are constructed using TOPEX/Poseidon and Jason-1/2/3 altimeter data from 1992 to 2020. The relationship among lake level, area, precipitation, temperature, and evaporation in the basin from 1992 to 2020 is analyzed.The mean lake level for each cycle is estimated after outlier removal. As an example, About 38% of the observations are rejected as outliers in Jason-2 period. The T/P-family satellites share the same ground track and have an overlap between two successive satellites for intersatellite calibration. As a result, Jason-1 has a mean lake level bias of 0.15 m with respect to T/P. The bias of Jason-2 with respect to Jason-1 is 0.02 m. The bias of Jason-3 with respect to Jason-2 is -0.23 m after removing an outlier. Biases between different missions are adjusted, and a 28-year monthly lake level time series is generated. Compared to the in situ data and available lake level databases, our result is the most robust time series for La-ang Co, with high accuracy and considerably continuous samples from 1992 to 2020. The mean STD is about 13.10 cm for T/P-family satellites. From 1992 to 2020, the level of La-ang Co decreased by 6.00 m, with an average change trend of -0.21±0.01 m/a.This result showed that the lake level extraction in this study is more accurate than that of available lake level databases, and the change of lake levels in La-ang Co is similar with the previous studies. Annual and semi-annual variations as well as inter-annual oscillations can be clearly observed in the time series. Evaporation is greater than precipitation, which is the main factor leading to the decrease of lake level. The water level of La-ang Co will continue to decline in the near term due to global warming.