Comparison of Atmospheric Gradients Estimated From Ground-Based GNSS Observations and Microwave Radiometry
Paper in proceedings, 2019

Observations over four years from two nearby groundbased
Global Navigation Satellite System (GNSS) stations
and one microwave radiometer have been used to
estimate linear horizontal gradients in the atmosphere.
We find that gradients estimated by the radiometer have
larger amplitudes than those estimated using data from
the Global Positioning System (GPS). One reason for this
is that they are estimated, every 15 min, independently
of previous estimates, whereas the gradients from GPS
are estimated every 5 min using constraints on their variability.
We also find that the elevation cutoff angle has a
significant impact on the estimated GPS gradients. Decreasing
the cutoff angle results in smaller gradient amplitudes.
The estimated gradients are not homogeneously
distributed in all directions. When studying the largest
gradients they all occur during the warmer period of the
year, beginning in April and ending in October. Specifically,
for the 25 events with the largest gradient amplitudes
from the GPS data, we find that the vast majority of
them are associated with the passage of weather fronts.

microwave radiometry

horizontal gradients

GNSS

water vapour

Author

Gunnar Elgered

Chalmers, Space, Earth and Environment, Onsala Space Observatory, Space Geodesy and Geodynamics

Peter Forkman

Chalmers, Space, Earth and Environment, Onsala Space Observatory, Space Geodesy and Geodynamics

Tong Ning

The Swedish Mapping, Cadastral and Land Registration Authority

The proceedings to the 7th Galileo Science Colloquium

7th International Colloquium on Scientific and Fundamental Aspects of GNSS
Zürich, Switzerland,

Subject Categories

Meteorology and Atmospheric Sciences

Earth and Related Environmental Sciences

Roots

Basic sciences

Infrastructure

Onsala Space Observatory

Related datasets

On the information content in linear horizontal delay gradients estimated from space geodesy observations [dataset]

DOI: https://doi.org/10.5878/nswtyr39 ID: SND 1090

More information

Created

3/14/2020