重力潮汐观测在全球潮汐模型的建立、重力扰动信号识别等工作中具有重要作用，而潮汐观测精度是完成这些工作的基础。本文利用中国大陆构造环境监测网络10个重力站3年的重力固体潮数据计算了观测潮汐模型。在与历史已有结果进行比较后，分析了观测潮汐模型精度以及环境对精度的影响。结果表明，10个站观测潮汐模型的M₂波潮汐因子中，误差最优为0.00014，主要潮波平均精度优于0.0010，高于20世纪80～90年代弹簧重力仪0.5～1个数量级，部分站点的精度可达早期超导重力仪水平，而与现代OSG型超导重力仪精度相差0.5～1.0个数量级。利用重力站中最优观测潮汐模型进行潮汐改正，潮汐改正精度指标（DRMS）可达±（0.2～0.3）×10^-8m/s²，稍优于DDW/NHi理论潮汐模型结果（±（0.3～0.6）×10^-8m/s²）。10个重力站均表现出了观测优于理论模型的特点。观测环境和场地的干扰会导致观测潮汐模型的精度下降，部分台站受环境变化和观测系统本身老化等不稳定因素干扰，其观测潮汐模型精度下降。DRMS自（0.1～0.2）×10^-8m/s²增至（1.0～1.7）×10^-8m/s²。

Gravity tide observation data plays an important role in the establishment of global tide model,and tide observation correction model,and the recognition of gravity disturbance signal. The accuracy of tide observation is critical to complete the above work. In this paper,the tidal model precision observed by 10 gPhone gravimeters in CMONOC have been compared to the existing ones. The effect of the observation environment and system,as well as the relationship between the accuracy of observed tidal model and of the tidal correction model have been discussed. It is shown that the accuracy of these gPhone gravimeters of which the optimal tide factor accuracy of M₂ is 0.00014 and average one is less than 0.001,which is 0.5～1.0 order higher than in magnitude of the spring gravimeters in 1980～1990s. The accuracy of some gPhone can reach the level of early Superconducting gravimeters(SG). However,compared with of the OSG,the accuracy of gPhone is less than 0.5～1.0 order in magnitude. The tidal correction accuracy of the optimal tidal observation model in CMONOC is about ±(0.2～0.3)×10^-8m/s²,which is higher than ±(0.3～0.6)×10^-8m/s² of DDW/NHi model. And the observed tidal correction model is better than the theoretical one in all of gPhone. The disturbance of the observation environment and system will decrease the accuracy of the observed tidal correction model. In specific,some accuracy have reduced from(0.1～0.2)×10^-8m/s² to(1.0～1.7)×10^-8m/s² by interference of the observation system.

P315

国家自然科学基金（41204058）、中国地震局地震研究所和应急管理部国家自然灾害防治研究院基本科研业务费（IS2018126181）、民用航天技术预先研究项目（D010103）共同资助