Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. ...Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. However, high-altitude and high-latitude lakes undergo seasonal freezing and melting, affecting satellite altimetry accuracy. This paper evaluates the accuracy of lake level height observations by the CryoSat-2, which uses synthetic aperture radar(SAR) across seasons. First, we used lake boundary based on optical remote sensing data to extract the footprints of CryoSat-2 that fall on Namco and Zhari Namco.After elevation conversion and anomaly identification, we obtained the time series of lake levels. These data were compared and verified against lake levels from in-situ measurements to assess the accuracy of CryoSat-2. The results show that CryoSat-2 can monitor lake level height with an accuracy of about 10-13 cm. The correlation coefficient between CryoSat-2 observations and in-situ measurements over Namco is 0.80(p < 0.01), with a Root Mean Square Error(RMSE) of 13 cm. For Zhari Namco, the correlation coefficient is 0.91, with an RMSE of 10 cm, indicating a better match. At the seasonal scale, the seasonal correlation coefficients between CryoSat-2 and in-situ measurement in Namco are 0.47(spring),0.79(summer), and 0.91(fall) with no observations available for winter. The lower correlation in spring may be due to incomplete ice melting. For Zhari Namco, the seasonal correlation coefficients are 0.89(spring), 0.93(summer), 0.89(fall), and 0.87(winter). The results show that CryoSat-2 accuracy is higher in summer and fall, while slightly lower in spring and winter, indicating that ice formation affects accuracy. Even during winter, the altimetry results do not significantly exceed the in-situ lake water level observations.展开更多
基于Cryosat-2三年半的卫星测高GDR(geophysical data records)数据,使用海面高梯度,依据最小二乘配置方法得到了南海部分海域垂线偏差格网,结合移去-恢复技术采用逆Vening-Meinesz的球面一维傅里叶变换算法快速计算我国近海海域测高重...基于Cryosat-2三年半的卫星测高GDR(geophysical data records)数据,使用海面高梯度,依据最小二乘配置方法得到了南海部分海域垂线偏差格网,结合移去-恢复技术采用逆Vening-Meinesz的球面一维傅里叶变换算法快速计算我国近海海域测高重力异常CASM_GRA.与船载重力测量数据融合后,重力场精度在2.75~5.38mgal之间,平均偏差在-0.21~0.45mgal之间.与DTU13重力场模型相比,平均值最大改进为12.98mgal,标准差最大降幅近3.40mgal.与Sandwell V23.1模型相比,平均值最大改进为13.58 mgal,标准差最大降幅为1.09mgal.展开更多
基金financial supported by National Natural Science Foundation of China (42104010, 42174097, 41974093, and 41774088)the Fundamental Research Funds for the Central Universities
文摘Changes in lake levels, as an indicator of climate change, are crucial for understanding water resources.Satellite altimetry has proven to be an effective technique for monitoring water level changes in inland lakes. However, high-altitude and high-latitude lakes undergo seasonal freezing and melting, affecting satellite altimetry accuracy. This paper evaluates the accuracy of lake level height observations by the CryoSat-2, which uses synthetic aperture radar(SAR) across seasons. First, we used lake boundary based on optical remote sensing data to extract the footprints of CryoSat-2 that fall on Namco and Zhari Namco.After elevation conversion and anomaly identification, we obtained the time series of lake levels. These data were compared and verified against lake levels from in-situ measurements to assess the accuracy of CryoSat-2. The results show that CryoSat-2 can monitor lake level height with an accuracy of about 10-13 cm. The correlation coefficient between CryoSat-2 observations and in-situ measurements over Namco is 0.80(p < 0.01), with a Root Mean Square Error(RMSE) of 13 cm. For Zhari Namco, the correlation coefficient is 0.91, with an RMSE of 10 cm, indicating a better match. At the seasonal scale, the seasonal correlation coefficients between CryoSat-2 and in-situ measurement in Namco are 0.47(spring),0.79(summer), and 0.91(fall) with no observations available for winter. The lower correlation in spring may be due to incomplete ice melting. For Zhari Namco, the seasonal correlation coefficients are 0.89(spring), 0.93(summer), 0.89(fall), and 0.87(winter). The results show that CryoSat-2 accuracy is higher in summer and fall, while slightly lower in spring and winter, indicating that ice formation affects accuracy. Even during winter, the altimetry results do not significantly exceed the in-situ lake water level observations.
文摘基于Cryosat-2三年半的卫星测高GDR(geophysical data records)数据,使用海面高梯度,依据最小二乘配置方法得到了南海部分海域垂线偏差格网,结合移去-恢复技术采用逆Vening-Meinesz的球面一维傅里叶变换算法快速计算我国近海海域测高重力异常CASM_GRA.与船载重力测量数据融合后,重力场精度在2.75~5.38mgal之间,平均偏差在-0.21~0.45mgal之间.与DTU13重力场模型相比,平均值最大改进为12.98mgal,标准差最大降幅近3.40mgal.与Sandwell V23.1模型相比,平均值最大改进为13.58 mgal,标准差最大降幅为1.09mgal.
