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See detailDetection of atmospheric pressure loading using the Global Positioning System
van Dam, Tonie UL; Blewitt, Geoffrey; Heflin, M.

in Journal of Geophysical Research (1994), 99(B12), 23939-23950

Earth deformation signals caused by atmospheric pressure loading are detected in vertical position estimates at Global Positioning System (GPS) stations. Surface displacements due to changes in ... [more ▼]

Earth deformation signals caused by atmospheric pressure loading are detected in vertical position estimates at Global Positioning System (GPS) stations. Surface displacements due to changes in atmospheric pressure account for up to 24% of the total variance in the GPS height estimates. The detected loading signals are larger at higher latitudes where pressure variations are greatest; the largest effect is observed at Fairbanks, Alaska (latitude 65°), with a signal RMS of 5 mm. Out of 19 continuously operating GPS sites (with a mean of 281 daily solutions per site), 18 show a positive correlation between the GPS vertical estimates and the modeled loading displacements. Accounting for loading reduces the variance of the vertical station positions on 12 of the 19 sites investigated. Removing the modeled pressure loading from GPS determinations of baseline length for baselines longer than 6000 km reduces the variance on 73 of the 117 baselines investigated. The slight increase in variance for some of the sites and baselines is consistent with expected statistical fluctuations. The results from most stations are consistent with ∼65% of the modeled pressure load being found in the GPS vertical position measurements. Removing an annual signal from both the measured heights and the modeled load time series leaves this value unchanged. The source of the remaining discrepancy between the modeled and observed loading signal may be the result of (1) anisotropic effects in the Earth's loading response, (2) errors in GPS estimates of tropospheric delay, (3) errors in the surface pressure data, or (4) annual signals in the time series of loading and station heights. In addition, we find that using site dependent coefficients, determined by fitting local pressure to the modeled radial displacements, reduces the variance of the measured station heights as well as or better than using the global convolution sum. [less ▲]

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See detailAtmospheric load response of the oceans determined using Geosat data
van Dam, Tonie UL; Wahr, John

in Geophysical Journal International (1993), 113(1), 1-16

Approximately one year's worth of altimeter-derived sea-surface heights are compared with global sea-level pressure fields to verify the open ocean inverted barometer response (-1 cm mb-1). When pressure ... [more ▼]

Approximately one year's worth of altimeter-derived sea-surface heights are compared with global sea-level pressure fields to verify the open ocean inverted barometer response (-1 cm mb-1). When pressure is fit to the sea-surface height along individual altimeter tracks, the response is found to be only 60–70 per cent of the theoretical response or approximately -0.6 to -0.7 cm mb-1. Fits at fixed geographic locations show a clear dependence on latitude. There is a steady decrease in the absolute value o the regression coefficient between 70° and 20°, and then an abrupt increase again closer to the equator. A simple error analysis demonstrates that errors in the pressure data would reduce the along-track regression values, as is observed, and could produce a similar latitude dependence. But, the errors are unlikely to be large enough to explain the entire departure from inverted barometer. We estimate that pressure errors are apt to perturb the along-track track results by no more than about 0.1-0.2 cm mb-1. The possibility that the remaining disagreement is due to a global coherence between wind- and pressure-driven sea-surface height variability is considered. Winds driven by the pressure gradients of synoptic storms induce a sea-surface height response that is opposite in direction to that caused by the pressure cell. the wind-driven response is estimated for a stationary storm over a homogeneous barotropic ocean and for a moving storm over a two-layer baroclinic ocean by modeling the pressure cell as an idealized Gaussian distribution. the model results indicate that the wind-induced sea-surface height depends on both the radius and the translational velocity of the pressure cell. But, the winds associated with storms moving at average speeds of 10 ms-1 are apt to lower the theoretical pressure response in the model by only approximately 0.1 cm mb-1. the surface stress associated with those winds has the same latitudinal trend between 70° and 20° as the regression coefficients. But, the response of the ocean to that stress does not appear to exhibit the same trend. Nevertheless, the abrupt change in the regression coefficients near the equator suggests the apparent non-inverted barometer response may reflect a real change in sea-surface height related to atmospheric forcing (though the results near the equator are not as well defined as those at higher latitudes). [less ▲]

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See detailDisplacements of the Earth's surface due to atmospheric loading: Effects on Gravity and Baseline Measurements
van Dam, Tonie UL; Wahr, John

in Journal of Geophysical Research (1987), 92

Atmospheric mass loads and deforms the Earth's crust. By performing a convolution sum between daily global barometric pressure data and mass loading Green's functions, we estimate the time dependent ... [more ▼]

Atmospheric mass loads and deforms the Earth's crust. By performing a convolution sum between daily global barometric pressure data and mass loading Green's functions, we estimate the time dependent effects of atmospheric loading, including those associated with short-term synoptic storms, on surface point positioning measurements and surface gravity observations. We calculate the response of both an oceanless Earth and an Earth with an inverted barometer ocean. Peak to peak vertical displacements are frequently 15-20 mm with accompanying gravity perturbations of 3-6 microgal. Baseline changes can be as large as 20 mm or more. The perturbations are largest at higher latitudes and during winter months. These amplitudes are consistent with the results f Rabbel and Zschau (1985) who modeled synoptic pressure disturbances as Gaussian functions of radius about a central point. Deformation can be adequately computes using real pressure data from points within about 1000 km of the station. Knowledge of local pressure alone, is not sufficient. Rabbel and Zschau's hypothesized corrections for these displacements, which use local pressure and regionally averaged pressure, prove accurate at points well inland but are, in general, inadequate within a few hundred kilometers of the coast. [less ▲]

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See detailOn time-variable seasonal signals: comparison of SSA and Kalman filtering based approaches
Chen, Q.; Weigelt, Matthias UL; Sneeuw, N. et al

Scientific Conference (n.d.)

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