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Multiple-data-based monthly geopotential model set LDCmgm90

机译:基于多数据的每月地理潜力模型集LDCmgm90

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摘要

While the GRACE (Gravity Recovery and Climate Experiment) satellite mission is of great significance in understanding various branches of Earth sciences, the quality of GRACE monthly products can be unsatisfactory due to strong longitudinal stripe-pattern errors and other flaws. Based on corrected GRACE Mascon (mass concentration) gridded mass transport time series and updated LDCgam (Least Difference Combination global angular momenta) data, we present a new set of monthly gravity models called LDCmgm90, in the form of Stokes coefficients with order and degree both up to 90. The LDCgam inputs are developed by assimilating degree-2 Stokes coefficients from various versions of GRACE (including Mascon products) and SLR (Satellite Laser Ranging) monthly gravity data into combinations of outputs from various global atmospheric, oceanic, and hydrological circulation models, under the constraints of accurately measured Earth orientation parameters in the Least Difference Combination (LDC) scheme. Taking advantages of the relative strengths of the various input solutions, the LDCmgm90 is free of stripes and some other flaws of classical GRACE products.
机译:虽然GRACE(重力恢复和气候实验)卫星任务对于理解地球科学的各个分支都具有重要意义,但由于强烈的纵向条纹图案错误和其他缺陷,GRACE月度产品的质量可能无法令人满意。基于校正的GRACE Mascon(质量浓度)网格化的质量运输时间序列和更新的LDCgam(最小差分组合全局角动量)数据,我们以斯托克斯系数的形式(阶次和阶次均为最多90个。LDCgam输入是通过将来自不同版本的GRACE(包括Mascon产品)和SLR(卫星激光测距)月度重力数据的2度斯托克斯系数同化为来自各种全球大气,海洋和水文环流的输出组合而开发的在最小差分组合(LDC)方案中,在精确测量的地球方向参数的约束下建立模型。利用各种输入解决方案的相对优势,LDCmgm90消除了传统GRACE产品的条纹和其他缺陷。

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