The Global Positioning System (GPS) has revolutionized the ability to monitor Earth-system processes, including Earth’s water cycle. Several analysis centers process GPS data to estimate ground-antenna positions at daily temporal resolution. Differences in processing strategies can lead to inconsistencies in coordinate-position estimates and therefore influence the analysis of crustal displacement associated with variations in atmospheric and hydrologic mass loading. Here, we compare five GPS data products produced by three processing centers: the Nevada Geodetic Laboratory, Jet Propulsion Laboratory, and UNAVCO Consortium. We find that 5 to 30% of the scatter in residual GPS time series (commonly considered noise) can be explained by atmospheric loading in the contiguous USA and Alaska, but that the percentages vary widely by data product. Positions derived using high-resolution troposphere models (e.g., ECMWF) exhibit significantly lower scatter after correcting for atmospheric loading than positions estimated using constant or slowly varying troposphere models (e.g., GPT2w). The data products also exhibit differences in seasonal deformation (commonly attributed, in large part, to fluctuations in hydrologic mass loading): median vector differences in estimated seasonal amplitude range from 0.4–1.0 mm in the vertical component and 0.1–0.3 mm in the horizontal components, or about 10–40% of the mean amplitudes of seasonal oscillation. Newer products exhibit lower total scatter and stronger correlations than older products. Network-coherent differences in estimates of seasonal deformation reveal reference-frame inconsistencies between data products. We also cross-check two independent models of atmospheric pressure loading: ESMGFZ and LoadDef.

中文翻译：

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GPS 位置的大气压力载荷：对 GPS 处理方法的依赖以及对美国和阿拉斯加相邻地区季节性变形评估的影响

全球定位系统 (GPS) 彻底改变了监测地球系统过程（包括地球水循环）的能力。几个分析中心处理 GPS 数据，以估计每日时间分辨率的地面天线位置。处理策略的差异会导致坐标位置估计的不一致，从而影响与大气和水文质量载荷变化相关的地壳位移分析。在这里，我们比较了三个处理中心生成的五种 GPS 数据产品：内华达大地测量实验室、喷气推进实验室和 UNAVCO 联盟。我们发现残余 GPS 时间序列中 5% 到 30% 的分散（通常被认为是噪声）可以用邻近的美国和阿拉斯加的大气载荷来解释，但百分比因数据产品而异。与使用恒定或缓慢变化的对流层模型（例如，GPT2w）估计的位置相比，使用高分辨率对流层模型（例如，ECMWF）得出的位置在校正大气载荷后表现出显着更低的散射。数据产品还表现出季节性变形的差异（通常在很大程度上归因于水文质量载荷的波动）：估计的季节性振幅的中值矢量差异范围为垂直分量的 0.4-1.0 毫米和水平分量的 0.1-0.3 毫米分量，或季节性振荡平均振幅的 10-40%。与旧产品相比，新产品的总分散度更低，相关性更强。季节性变形估计的网络相干差异揭示了数据产品之间的参考框架不一致。