Water vapour radiometry in geodetic very long baseline interferometry telescopes: assessed through simulations

Abstract

The accuracy of geodetic Very Long Baseline Interferometry (VLBI) is affected by water vapour in the atmosphere in terms of variations in the signal propagation delay at the different stations. This “wet” delay may be estimated directly from the VLBI data, as well as from independent instruments, such as collocated microwave radiometers. Rather than having stand-alone microwave radiometers we have, through simulations, evaluated the possibility to use radiometric data from the VLBI receiver in the VGOS telescopes at the Onsala Space Observatory. The advantage is that the emission from water vapour, as sensed by the radiometer, originates from the same atmospheric volume that delays the VLBI signal from the extra-galactic object. We use simulations of the sky brightness temperature and the wet delay together with an assumption of a root-mean-square (rms) noise of the receiver of 1 K, and observations evenly spread between elevation angles of 10$$^\circ $$ ∘ –90$$^\circ $$ ∘ . This results in an rms error of the estimated equivalent zenith wet delay of the order of 3 mm for a one frequency algorithm, used under cloud free conditions, and 4 mm for a two frequency algorithm, used during conditions with liquid water clouds. The results exclude rainy conditions when the method does not work. These errors are reduced by a factor of 3 if the receiver error is 0.1 K meaning that the receivers’ measurements of the sky brightness temperature is the main error source. We study the impact of ground-noise pickup by using a model of an existing wideband feed. Taking the algorithm uncertainty and the ground noise pickup into account we conclude that the method presented will be useful as an independent estimate of the wet delay to assess the quality of the wet delays and linear horizontal gradients estimated from the VLBI data themselves.

Baseline Vector Repeatability at the Sub‐Millimeter Level Enabled by Radio Interferometer Phase Delays of Intra‐Site Baselines

“…This amount of impact may be inevitable and prevalent in the current VLBI products because the signal propagation delays due to water vapor are always estimated in geodetic solutions of VLBI observations. The study may suggest that in order to achieve global geodetic accuracy of 1 mm with VGOS alternatives for measuring wet delays may need to be further developed and verified, such as collocated microwave radiometers (see, e.g., Forkman et al, 2021). estimating with a time interval of 1 hr for piece-wise linear (blue triangles), estimating with a time interval of 24 hr (purple rhombuses), and not estimating (red dots).…”

Baseline vector repeatability at the sub-millimeter level enabled by radio interferometer phase delays of intra-site baselines

“…This amount of impact may be inevitable and prevalence in the current VLBI products because the signal propagation delays due to water vapour are always estimated in geodetic solutions of VLBI observations. The study may suggest that achieving global geodetic accuracy of 1 mm with VGOS will have to reply on corrections for the water vapour-induced delays from independent instruments, such as collocated microwave radiometers (see, e.g., Forkman et al, 2021).…”

Consistency of the Troposphere Wet Delay From Water Vapor Radiometer and Co‐Located GPS Station

“…Combined with Table 3, the WVR ZWD and PPP ZWD sequences are in good agreement at Shanghai station, but there are more water vapor and drastic meteorological changes at this station. Accordingly, the WVR ZWD sequences are more volatile and have more anomalous values related to meteorological changes (Forkman et al., 2021). Section 4.1 will further analyze the relationship between the inconsistently large values in the WVR ZWD and the meteorological parameters.…”

“…, Niell et al (2001), andSteigenberger et al (2007) compared the zenith wet delay (ZWD) obtained from radiosonde, WVR, GPS, and VLBI at the same site within the farthest distance of 50 KM, the results suggest that the anomalies of water vapor radiometer measurements are due to the modeling of radiosonde data, which cannot provide meteorological parameters at higher temporal resolution for weather changes. Therefore water vapor radiometer data needs to be corrected by nearby radiosonde data under different meteorological conditions (Forkman et al, 2021). Some studies have also included numerical weather model data for analysis (Teke et al, 2011(Teke et al, , 2013, compared geodetic techniques such as VLBI, GNSS, DORIS, and WVR with numerical weather models troposphere delay (interpolated to sites) and found that water vapor radiometer could not provide reliable results when it is raining.…”