Observing Three dimensional Water Vapour using a surface network of GPS receivers

Atmospheric water vapour is highly variable both in space and time.
In an operational sense, only radiosonde provide vertical information
on water vapour. Radiosondes are generally launched two to four times
per day at synoptic times and sample primarily synoptic scales. For
nowcasting purposes these observations are very valuable but obviously
lose their importance with elapsing time. Water vapour observations
from a surface network of Global Positioning System (GPS) receivers
can fill this information gap. In this paper, a GPS network is used
to observe integral water vapour quantities along the line of sight,
so-called Slant Water Vapour (SWV). Using a variational technique
(3DVAR) a three-dimensional water vapour field is reconstructed and
its performance is investigated using an Observation Simulation System
Experiment (OSSE) in which the complete atmosphere and observations
were simulated (so-called nature run). The forecasts from a high
resolution limited area model (HIRLAM) embedded in the synthetic
atmosphere of the nature run is compared to the separate GPS-3DVAR
estimates. This experiment showed that assimilation of SWV resulted in
a smaller bias and standard deviation than the HIRLAM forecast with
the nature run. Besides simulated data, real SWV observations are used
to assess impact. Two experiments were conducted; one with a HIRLAM
six hour forecast as a background field (updated every six hours) and
one with persistence as background (updated every hour). The first
experiment showed a reduction of the bias between radiosonde
observations compared to HIRLAM forecast. The second experiment, which
has no information inherited from HIRLAM, showed to have smaller
biases with independent radiosonde observations than the HIRLAM
analysis. The used network, however was too sparse to detect water
vapour inversions correctly.