The use of degree variances in satellite gradiometry

1997 ◽  
Vol 71 (6) ◽  
pp. 337-343 ◽  
Author(s):  
M. van Gelderen ◽  
R. Koop
Keyword(s):  
Satellite Gradiometry ◽  
Degree Variances

Experiments On the Satellite Gradiometry

2012 ◽  
Vol 870 (13) ◽  
pp. 77-79
Author(s):  
Yu.M. Neiman ◽  
◽  
L.S. Sugaipova ◽  
V.V. Popadyev ◽  
◽  
...  
Keyword(s):  
Satellite Gradiometry

scholarly journals Towards constraining parity-violations in gravity with satellite gradiometry

2019 ◽  
Vol 789 ◽  
pp. 378-386
Author(s):  
Peng Xu ◽  
Zhi Wang ◽  
Li-E Qiang
Keyword(s):  
Satellite Gradiometry

scholarly journals Wind and turbulence measurements by the Middle and Upper Atmosphere Radar (MUR): comparison of techniques

2004 ◽  
Vol 22 (11) ◽  
pp. 3843-3862 ◽  
Author(s):  
A. A. Praskovsky ◽  
E. A. Praskovskaya ◽  
G. Hassenpflug ◽  
M. Yamamoto ◽  
S. Fukao
Keyword(s):  
Correlation Function ◽  
Momentum Flux ◽  
Signal To Noise Ratio ◽  
Spectral Width ◽  
Upper Atmosphere ◽  
Turbulent Velocity ◽  
Comparison Of Techniques ◽  
Horizontal Momentum ◽  
Degree Variances ◽  
Beam Broadening

Abstract. The structure-function-based method (referred to as UCAR-STARS), a technique for estimating mean horizontal winds, variances of three turbulent velocity components and horizontal momentum flux was applied to the Middle and Upper atmosphere Radar (MUR) operating in spaced antenna (SA) profiling mode. The method is discussed and compared with the Holloway and Doviak (HAD) correlation-function-based technique. Mean horizontal winds are estimated with the STARS and HAD techniques; the Doppler Beam Swinging (DBS) method is used as a reference for evaluating the SA techniques. Reasonable agreement between SA and DBS techniques is found at heights from 5km to approximately 11km, where signal-to-noise ratio was rather high. The STARS and HAD produced variances of vertical turbulent velocity are found to be in fair agreement. They are affected by beam-broadening in a different way than the DBS-produced spectral width, and to a much lesser degree. Variances of horizontal turbulent velocity components and horizontal momentum flux are estimated with the STARS method, and strong anisotropy of turbulence is found. These characteristics cannot be estimated with correlation-function-based SA methods, which could make UCAR-STARS a useful alternative to traditional SA techniques.

Gravity field determination from satellite gradiometry

1985 ◽  
Vol 59 (3) ◽  
pp. 233-246 ◽  
Author(s):  
R. Rummel ◽  
O. L. Colombo
Keyword(s):  
Gravity Field ◽  
Satellite Gradiometry ◽  
Gravity Field Determination

Some problems related to satellite gradiometry

1989 ◽  
Vol 63 (4) ◽  
pp. 405-415 ◽  
Author(s):  
F. Sacerdote ◽  
F. sansò
Keyword(s):  
Satellite Gradiometry

scholarly journals Globally covering a-priori regional gravity covariance models

2003 ◽  
Vol 1 ◽  
pp. 143-147 ◽  
Author(s):  
D. Arabelos ◽  
C. C. Tscherning
Keyword(s):  
Gravity Anomaly ◽  
Covariance Function ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Scale Factor ◽  
Covariance Functions ◽  
Covariance Models ◽  
Free Air Gravity ◽  
Regional Gravity ◽  
Degree Variances

Abstract. Gravity anomaly data generated using Wenzel’s GPM98A model complete to degree 1800, from which OSU91A has been subtracted, have been used to estimate covariance functions for a set of globally covering equal-area blocks of size 22.5° × 22.5° at Equator, having a 2.5° overlap. For each block an analytic covariance function model was determined. The models are based on 4 parameters: the depth to the Bjerhammar sphere (determines correlation), the free-air gravity anomaly variance, a scale factor of the OSU91A error degree-variances and a maximal summation index, N, of the error degree-variances. The depth of Bjerhammar-sphere varies from -134km to nearly zero, N varies from 360 to 40, the scale factor from 0.03 to 38.0 and the gravity variance from 1081 to 24(10µms-2)2. The parameters are interpreted in terms of the quality of the data used to construct OSU91A and GPM98A and general conditions such as the occurrence of mountain chains. The variation of the parameters show that it is necessary to use regional covariance models in order to obtain a realistic signal to noise ratio in global applications.Key words. GOCE mission, Covariance function, Spacewise approach`

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