简要介绍CSR、GFZ和JPL机构的GRACE RL06时变重力场模型数据，并对比分析RL06和RL05数据的解算模型。从全球陆地水储量变化反演结果、时变重力场模型阶方差和C20项时间序列3个方面，对2004-01~2014-11期间RL06和RL05时变重力场模型数据进行对比分析。结果表明，GRACE RL06时变重力场模型数据质量的和精度较RL05有明显提高，其全球陆地水储量变化反演结果去条带噪声效果更好、信噪比更高；在高阶项部分，RL06模型数据的阶方差小于RL05；RL06模型数据的C20项时间序列幅值变化小于RL05，与SLR所得C20项数据也更接近。相同条件下，采用CSR RL06模型阶方差最小，利用RL06模型所得全球陆地水储量变化反演结果信噪比值最大。"/>
Preliminary Comparative Analysis of GRACE RL06 and RL05 Time-Variable Gravity Models" />
This article briefly introduces GRACE RL06 time-varying gravity field model data from CSR, GFZ and JPL institutions, and compares and analyzes the calculation models of RL06 and RL05 data. Using the RL06 and RL05 time-varying gravity field model data from 2004-01 to 2014-11, we analyze the RL06 and RL05 data from three aspects: the global land storage change inversion results, the time-variable gravity field model degree variance, and the C20 term time series. We perform a comparative analysis. The experimental results show that the quality and accuracy of RL06 data is improved significantly. The de-stripe effect of results using RL06 data is better and the signal-to-noise ratios of results are larger. The degree variance of RL06 data is smaller than degree variance of RL05 data in high degree. The C20 time series of RL06 data is closer to SLR data. The quality of CSR RL06 is best in CSR, GFZ and JPL RL06 data. The signal-to-noise ratios of global terrestrial water storage inversion results with using CSR RL06 data is largest and degree variance of CSR RL06 data is largest under the same conditions."/>
GRACE RL06与RL05时变重力场模型数据初步比较分析
Abstract：This article briefly introduces GRACE RL06 time-varying gravity field model data from CSR, GFZ and JPL institutions, and compares and analyzes the calculation models of RL06 and RL05 data. Using the RL06 and RL05 time-varying gravity field model data from 2004-01 to 2014-11, we analyze the RL06 and RL05 data from three aspects: the global land storage change inversion results, the time-variable gravity field model degree variance, and the C20 term time series. We perform a comparative analysis. The experimental results show that the quality and accuracy of RL06 data is improved significantly. The de-stripe effect of results using RL06 data is better and the signal-to-noise ratios of results are larger. The degree variance of RL06 data is smaller than degree variance of RL05 data in high degree. The C20 time series of RL06 data is closer to SLR data. The quality of CSR RL06 is best in CSR, GFZ and JPL RL06 data. The signal-to-noise ratios of global terrestrial water storage inversion results with using CSR RL06 data is largest and degree variance of CSR RL06 data is largest under the same conditions.
