Ran J, Ditmar P, Klees R, Farahani H H
Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands.
J Geod. 2018;92(3):299-319. doi: 10.1007/s00190-017-1063-5. Epub 2017 Sep 13.
We present an improved mascon approach to transform monthly spherical harmonic solutions based on GRACE satellite data into mass anomaly estimates in Greenland. The GRACE-based spherical harmonic coefficients are used to synthesize gravity anomalies at satellite altitude, which are then inverted into mass anomalies per mascon. The limited spectral content of the gravity anomalies is properly accounted for by applying a low-pass filter as part of the inversion procedure to make the functional model spectrally consistent with the data. The full error covariance matrices of the monthly GRACE solutions are properly propagated using the law of covariance propagation. Using numerical experiments, we demonstrate the importance of a proper data weighting and of the spectral consistency between functional model and data. The developed methodology is applied to process real GRACE level-2 data (CSR RL05). The obtained mass anomaly estimates are integrated over five drainage systems, as well as over entire Greenland. We find that the statistically optimal data weighting reduces random noise by 35-69%, depending on the drainage system. The obtained mass anomaly time-series are de-trended to eliminate the contribution of ice discharge and are compared with de-trended surface mass balance (SMB) time-series computed with the Regional Atmospheric Climate Model (RACMO 2.3). We show that when using a statistically optimal data weighting in GRACE data processing, the discrepancies between GRACE-based estimates of SMB and modelled SMB are reduced by 24-47%.
我们提出了一种改进的质量块方法，用于将基于GRACE卫星数据的月度球谐函数解转换为格陵兰岛的质量异常估计值。基于GRACE的球谐系数用于合成卫星高度处的重力异常，然后将其反演为每个质量块的质量异常。通过在反演过程中应用低通滤波器来适当考虑重力异常有限的频谱内容，以使函数模型在频谱上与数据一致。利用协方差传播定律正确传播月度GRACE解的完整误差协方差矩阵。通过数值实验，我们证明了适当的数据加权以及函数模型与数据之间频谱一致性的重要性。所开发的方法应用于处理真实的GRACE二级数据（CSR RL05）。将获得的质量异常估计值整合到五个排水系统以及整个格陵兰岛上。我们发现，统计上最优的数据加权可将随机噪声降低35%至69%，具体取决于排水系统。对获得的质量异常时间序列进行去趋势处理，以消除冰流量的贡献，并与使用区域大气气候模型（RACMO 2.3）计算的去趋势表面质量平衡（SMB）时间序列进行比较。我们表明，在GRACE数据处理中使用统计上最优的数据加权时，基于GRACE的SMB估计值与模拟的SMB之间的差异减少了24%至47%。
