The effect of EGM2008-based normal, normal-orthometric and Helmert orthometric height systems on the Australian levelling network

This paper investigates the normal-orthometric correction used in the definition of the Australian Height Datum, and also computes and evaluates normal and Helmert orthometric corrections for the Australian National Levelling Network (ANLN). Testing these corrections in Australia is important to establish which height system is most appropriate for any new Australian vertical datum. An approximate approach to assigning gravity values to ANLN benchmarks (BMs) is used, where the EGM2008-modelled gravity field is used to "re-construct" observed gravity at the BMs. Network loop closures (for first- and second-order levelling) indicate reduced misclosures for all height corrections considered, particularly in the mountainous regions of south eastern Australia. Differences between Helmert orthometric and normal-orthometric heights reach 44 cm in the Australian Alps, and differences between Helmert orthometric and normal heights are about 26 cm in the same region. Normal orthometric heights differ from normal heights by up to 18 cm in mountainous regions >2,000 m. This indicates that the quasigeoid is not compatible with normal-orthometric heights in Australia

Precision measurement of the speed of propagation of neutrinos using the MINOS detectors

We report a two-detector measurement of the propagation speed of neutrinos over a baseline of 734 km. The measurement was made with the NuMI beam at Fermilab between the near and far MINOS detectors. The fractional difference between the neutrino speed and the speed of light is determined to be (v/c-1) = (1.0±1.1) × 10^−6, consistent with relativistic neutrinos

Robustness Analysis of Geodetic Networks

ABSTRACT: Geodetic control networks established for engineering construction (e.g., highways, railways, bridges, dams) typically have coordinates estimated by the method of least-squares and the 'goodness' of the network is measured by a precision analysis based upon the covariance matrix of the estimated parameters. When such a network is designed, traditionally this again is based upon measures derived from the covariance matrix of the estimated parameters. This traditional approach is based upon propagation of random errors. In addition to this precision analysis, reliability (the detection of outliers/gross errors/blunders among the observations) has been measured using a technique pioneered by the geodesist Baarda. In Baarda's method a statistical test (data-snooping) is used to detect outliers. What happens if one or more observations are burdened with an outlier? It is clear that these outliers will affect the observations and produce incorrect estimates of the parameters. If the outliers are detected by the statistical test then those observations are removed, the network re-adjusted, and we obtain the final results. In the approach described here, traditional reliability analysis (Baarda's approach) has been augmented with geometrical strength analysis using strain in a technique called robustness analysis. Robustness analysis is a natural merger of reliability and strain and is defined as the ability to resist deformations induced by the smallest detectable outliers as determined from internal reliability analysis. This paper addresses the consequences of when outliers are not detected by Baarda's test. This may happen for two reasons (i) the observation is not sufficiently checked by other independent observations and (ii) the test does not recognize the gross error. By how much can these undetected errors influence the network? If the influence of the undetected errors is small the network is called robust, if it is not it is called a weak network

Characterizing secular variations of GRACE total water storage estimates for the Canadian Prairies, In : Climate Change Geoscience program : 2006-2011 program final report, A.N. Rencz (ed.), Geological Survey of Canada Open File, 6879

ReportThe primary research question being addressed is: What is the variability in water storage (seasonal, inter-annual) and what are the long-term trends in water storage for the Nelson River drainage basin of mid-continental North America? The answer to this question certainly varies over the Nelson River drainage basin, which includes the North and South Saskatchewan Rivers (which flow through an agriculturally productive but drought-vulnerable region) as well as the lower reaches of the Nelson River itself (which provide significant hydro-electricity)

Development and Testing of In-Context Confidence Regions for Geodetic Survey Networks, Final Report. Geodetic Survey Division-Geomatics

The objectives of the contract were to develop and numerically test in-context absolute and relative confidence regions for geodetic networks. In-context confidence regions are those that relate to many points simultaneously, rather than the conventional notion of speaking about the confidence region about only one point without regard to any others. An out-of-context test is conducted on some piece of data without regard for the remaining data in the set. An in-context test is conducted on a quantity in the context of being a member of a larger set. Adjustment software, such as GHOST and GeoLab, that use the so-called Tau test of residuals are based on in-context testing. However, we are aware of no software that is capable of performing in-context testing on confidence regions for the estimated coordinate parameters. Another issue needing clarification is the matter of local versus global testing. Global testing is understood to be a single test involving the entire group of variates under examination. A global test statistic is typically a quadratic form which transforms the variates into a scalar quantity, containing all the information about the group. On the other hand, local testing is the process of testing individual variates in the group, either in-context or out-of-context. Since these tests can be conducted in either parameter or observation space, they should use a consistent approach in both spaces whenever possible. The development of confidence regions corresponding to one solution is different from the statistical testing of the compatibility (or congruency) of one solution against another. In this report we focus on the development of confidence regions for the analysis of a single network solution, rather than the development of statistical tests for applications such as deformation analyses that require the comparison of two solutions. The key issue of in-context testing is the formation of a mathematical link between the various statistical tests that may be conducted not only on the estimated parameters but also on the estimated residuals. The consequence of a mathematical link is compatibility of statistical tests throughout observation and parameter space. Three approaches to the computation of in-context confidence regions were examined during this contract: the Bonferroni, Baarda and projection approaches. The iv Bonferroni approach equates the simultaneous probability of the individual in-context confidence regions to a selected global probability level. However, it neglects any correlations between the tested quantities, which can have serious consequences for parameter confidence regions. The Baarda (or Delft) approach uses the relation between Type I and II errors for both global and local testing, but arbitrarily assumes the probability and non-centrality parameters for both local and global Type II errors are the same. • Local absolute (point) confidence regions. For absolute in-context confidence regions at individual points in the network, use the in-context significance level α o = α/n, where n is the number of points being simultaneously assessed. • Local relative confidence regions. For relative in-context confidence regions between pairs of points in the network, use the in-context significance level α o = α/m, where m is the number of linearly independent pairs of points to be simultaneously assessed. v

Observation of glacial isostatic adjustment in ‘‘stable’ ’ North America with GPS

[1] Motions of three hundred and sixty Global Positioning System (GPS) sites in Canada and the United States yield a detailed image of the vertical and horizontal velocity fields within the nominally stable interior of the North American plate. By far the strongest signal is the effect of glacial isostatic adjustment (GIA) due to ice mass unloading during deglaciation. Vertical velocities show present-day uplift ( 10 mm/yr) near Hudson Bay, the site of thickest ice at the last glacial maximum. The uplift rates generally decrease with distance from Hudson Bay and change to subsidence (1–2 mm/yr) south of the Great Lakes. The ‘‘hinge line’’ separating uplift from subsidence is consistent with data from water level gauges along the Great Lakes, showing uplift along the northern shores and subsidence along the southern ones. Horizontal motions show outward motion from Hudson Bay with complex local variations especially in the far field. Although the vertical motions are generally consistent with the predictions of GIA models, the horizontal data illustrate the need and opportunity to improve the models via more accurate descriptions of the ice load and laterally variable mantle viscosity. Citation: Sella, G. F., S. Stein, T. H