The determination of a new global GPS-derived surface velocity field and its application to the problem of 20th century sea-level rise

该项目解决了20世纪全球海平面上升估计(1.5-2.0毫米/年)中目前的不确定性。这些对全球海平面上升及其水团贡献者的估计主要来自空间大地测量(测高、时变重力等)。和潮汐测量仪的测量。然而，由于对全球验潮仪(Tg)测量的垂直运动缺乏准确校正的信心，这些测量变得复杂，这阻碍了真正的海平面上升的测量。同样，需要精确、精确和地理分布广泛的表面速度测量，以限制地球从以前的冰川融化(冰川均衡调整，GIA)中反弹的模型，例如在南极洲。也许最重要的是，GIA测量中的不确定性是从GRACE(最近的一次‘称重’地球的卫星任务)获得准确的冰质量增减估计的限制因素。在这两种情况下，全球定位系统(GPS)时间序列都提供了重要的限制，确实已经安装在许多关键地点。然而，迄今为止，在1-2毫米/年的垂直站点速度水平上，GPS时间序列仍然存在不确定性和偏差，这主要是由于GPS信号建模不足(例如，对流层)和由此产生的参照系问题。然而，全球定位系统误差模型的最新进展意味着，与目前国际全球导航卫星系统服务处常规计算的垂直站点速率相比，现在可以在精度和准确度上进行阶跃变化。因此，重新处理这些原始数据甚至可以使用最早的数据来产生与最新数据类似的精度和精度的坐标。此外，基于集群技术的计算能力的根本改进现在允许以前不可能的事情：快速地重新处理数万个站点年的GPS数据，因此，以一种实验性的方式。在这里，我们建议通过全球数百个站点的全球再处理活动，对GIA模型和TG观测施加更好的约束，从而使我们能够在理解全球海平面上升估计和气候相关驱动机制方面取得重大进展。

This project addresses the current uncertainty in 20th Century global sea level rise estimates (1.5-2.0 mm/yr). These estimates of global sea level rise and its water mass contributors are primarily derived from space geodetic (altimetry, time-variable gravity, etc.) and tide gauge measurements. Accurate measurements of these are, however, complicated by a lack of confidence in accurately correcting global tide gauge (TG) measurements for their vertical motion which prevent true sea level rise from being measured. Likewise, accurate, precise and geographically widespread surface velocity measurements are needed to constrain models of Earth's rebound from previous ice melting (glacial isostatic adjustment, GIA), for example in Antarctica. Uncertainty in GIA measurements are, perhaps most importantly, a limiting factor in obtaining accurate ice mass gain/loss estimates from GRACE (a recent satellite mission that 'weighs' the Earth). In both cases, Global Positioning System (GPS) time series offer important constraints and, indeed, have been installed in many of the critical locations. However, to date there is still uncertainty and bias in GPS time series at the 1-2mm/yr level in the vertical site velocity, mainly due to insufficient GPS signal modelling (e.g., troposphere) and resulting reference frame issues. However, recent advances in GPS error modelling mean that vertical site rates may now be obtained with a step-change in precision and accuracy compared to those currently routinely generated by the International GNSS Service. Reprocessing these raw data therefore allows even the earliest data to be used to produce coordinates of similar accuracy and precision as the most recent data. In addition, radical improvements in computational capabilities based on clustering technologies now allow what was previously impossible: the reprocessing of tens-of-thousand site-years of GPS data quickly and, therefore, in an experimental manner. Here, we propose to place improved constraints on GIA models and TG observations through a global reprocessing campaign featuring hundreds of sites globally, thereby allowing a significant advance in our understanding of global sea level rise estimates and climate-related driving mechanisms.