The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements
2018
Abstract. Total column water vapour (TCWV) is a key atmospheric variable
which is generally evaluated on global scales through the use of satellite
data. Recently a new algorithm, called AIRWAVE (Advanced Infra-Red WAter
Vapour Estimator), has been developed for the retrieval of the TCWV from the
Along-Track Scanning Radiometer (ATSR) instrument series. The AIRWAVE
algorithm retrieves TCWV by exploiting the dual view of the ATSR instruments
using the infrared channels at 10.8 and 12 µ m and nadir and
forward observation geometries. The algorithm was used to produce a TCWV
database over sea from the whole ATSR mission. When compared to independent
TCWV products, the AIRWAVE version 1 (AIRWAVEv1) database shows very good
agreement with an overall bias of 3 % all over the ATSR missions. A large
contribution to this bias comes from the polar and the coastal regions, where
AIRWAVE underestimates the TCWV amount. In this paper we describe an updated
version of the algorithm, specifically developed to reduce the bias in these
regions. The AIRWAVE version 2 (AIRWAVEv2) accounts for the atmospheric
variability at different latitudes and the associated seasonality. In
addition, the dependency of the retrieval parameters on satellite
across-track viewing angles is now explicitly handled. With the new algorithm
we produced a second version of the AIRWAVE dataset. As for AIRWAVEv1, the
quality of the AIRWAVEv2 dataset is assessed through the comparison with the
Special Sensor Microwave/Imager (SSM/I) and with the Analyzed RadioSounding
Archive (ARSA) TCWV data. Results show significant improvements in both
biases (from 0.72 to 0.02 kg m −2 ) and
standard deviations (from 5.75 to 4.69 kg m −2 ), especially in polar
and coastal regions. A qualitative and quantitative estimate of the main error
sources affecting the AIRWAVEv2 TCWV dataset is also given. The new dataset
has also been used to estimate the water vapour climatology from the
1991–2012 time series.
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