Precipitable water vapour content from ESR/SKYNET sun–sky radiometers: validation against GNSS/GPS and AERONET over three different sites in Europe
Abstract. The estimation of the precipitable water vapour content ( W ) with high
temporal and spatial resolution is of great interest to both meteorological
and climatological studies. Several methodologies based on remote sensing
techniques have been recently developed in order to obtain accurate and
frequent measurements of this atmospheric parameter. Among them, the relative
low cost and easy deployment of sun–sky radiometers, or sun photometers,
operating in several international networks, allowed the development of
automatic estimations of  W from these instruments with high temporal
resolution. However, the great problem of this methodology is the estimation
of the sun-photometric calibration parameters. The objective of this paper is
to validate a new methodology based on the hypothesis that the calibration
parameters characterizing the atmospheric transmittance at 940 nm are
dependent on vertical profiles of temperature, air pressure and moisture
typical of each measurement site. To obtain the calibration parameters some
simultaneously seasonal measurements of  W , from independent sources, taken
over a large range of solar zenith angle and covering a wide range of  W ,
are needed. In this work yearly GNSS/GPS datasets were used for obtaining a
table of photometric calibration constants and the methodology was applied
and validated in three European ESR-SKYNET network sites, characterized by
different atmospheric and climatic conditions: Rome, Valencia and Aosta.
Results were validated against the GNSS/GPS and AErosol RObotic NETwork (AERONET)
 W  estimations. In both the validations the agreement was very
high, with a percentage RMSD of about 6, 13 and 8 % in the case of
GPS intercomparison at Rome, Aosta and Valencia, respectively, and of 8 %
in the case of AERONET comparison in Valencia. Analysing the results by W  classes, the present methodology was found to
clearly improve W  estimation at low W  content when compared against AERONET in
terms of % bias, bringing the agreement with the GPS (considered the
reference one) from a % bias of 5.76 to 0.52.