不同模型的地表质量异常一阶项、二阶项估计

Degree One and Degree Two Contributions to Global Surface Mass Anomaly Derived from Different Models

为了合理补充重力场恢复与气候试验卫星(Gravity Recovery and Climate Experiment,GRACE)时变重力场的一阶斯托克斯系数(C10、C11、S11)和替换二阶斯托克斯系数(C20),介绍了相关GRACE-OBP算法及其改进的算法,比较了相应的Chamber Model和4个Sun Model的一阶系数及其计算的地表质量异常,同时比较了基于卫星激光测距观测的Cheng Model与4个Sun Model的C20及其地表质量异常。结果表明,GRACE-OBP算法的一阶系数、卫星激光测距观测的C20及其地表质量异常与改进的GRACE-OBP算法在趋势项上有很大差异,但周年项差异相对较小。利用不同截断阶数和不同机构的GRACE时变重力场模型,对其趋势项和周年项都有一定影响,且对趋势项影响更大。因此,在计算陆地水储量变化时,建议使用改进的GRACE-OBP算法的估计结果,使用较理想的、截断阶数较高的GRACE时变重力模型。

In order to suitably supplement the degree one Stokes coefficients(C10, C11, S11) in the Gravity Recovery and Climate Experiment(GRACE) time-variable gravity data and substitute the C20 coefficient, we review two commonly applied methods based on different combination models of GRACE data and an Ocean Bottom Pressure(OBP) model, which we call Chambers model and Sun model. We compare the results of the degree one coefficients and derive global surface mass anomalies from the two methods, respectively. We also do the similar comparison for the C20 coefficient and derived global surface mass anomalies from Satellite Laser Ranging(SLR) based estimates and the Sun model. There are obvious differences, particularly in the trend rates of the degree one coefficients, C20 and the derived mass anomalies between the Sun model and both the Chambers model and SLR estimates. However, there are relatively small differences for annual signals. As the GRACE gravity models are released by different institutions applying different data processing and may also have different maximum degrees, the choice of GRACE data additionally affects the annual signals and especially the trend rates. Therefore, for the derivation of terrestrial water storage changes from GRACE, the results of degree one coefficients and C20 from the Sun model are recommended to be used together with the best GRACE time variable gravity data with the highest maximum degree available.