The effect of the dynamic wet troposphere on VLBI measurements

Details The effect of the dynamic wet troposphere on VLBI measurements The effect of the dynamic wet troposphere on VLBI measurements

Feb 1986

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1986tdar.nasa....1t&link_type=abstract

In its The Telecommunications and Data Acquisition Report p 1-17 (SEE N86-22784 13-32)

Astronomy and Astrophysics

Astronomy

Refractivity, Statistical Analysis, Troposphere, Very Long Base Interferometry, Water Vapor, Wind Variations, Atmospheric Moisture, Deep Space Network, Delay, Kolmogoroff Theory, Moisture Content, Radio Astronomy, Temporal Distribution

Scientific paper

Calculations using a statistical model of water vapor fluctuations yield the effect of the dynamic wet troposphere on Very Long Baseline Interferometry (VLBI) measurements. The statistical model arises from two primary assumptions: (1) the spatial structure of refractivity fluctuations can be closely approximated by elementary (Kolmogorov) turbulence theory, and (2) temporal fluctuations are caused by spatial patterns which are moved over a site by the wind. The consequences of these assumptions are outlined for the VLBI delay and delay rate observables. For example, wet troposphere induced rms delays for Deep Space Network (DSN) VLBI at 20-deg elevation are about 3 cm of delay per observation, which is smaller, on the average, than other known error sources in the current DSN VLBI data set. At 20-deg elevation for 200-s time intervals, water vapor induces approximately 1.5 x 10 to the minus 13th power s/s in the Allan standard deviation of interferometric delay, which is a measure of the delay rate observable error. In contrast to the delay error, the delay rate measurement error is dominated by water vapor fluctuations. Water vapor induced VLBI parameter errors and correlations are calculated. For the DSN, baseline length parameter errors due to water vapor fluctuations are in the range of 3 to 5 cm. The above physical assumptions also lead to a method for including the water vapor fluctuations in the parameter estimation procedure, which is used to extract baseline and source information from the VLBI observables.

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