Abstract
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 µm 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.
Highlights
A key issue in assessing the climate change is the precise knowledge of the distribution and variability of the total column of water vapour (TCWV), i.e. the vertically integrated atmospheric water vapour content
In the same paper, the authors highlighted that, at latitudes higher than 50◦, the agreement was not as good as for the rest of the globe. They speculated that this was due to the fact that AIRWAVEv1 makes use of retrieval parameters calculated though radiative transfer model (RTM) simulations of tropical and midlatitude atmospheric scenarios, which are averaged and used for the whole globe
The second version of the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) TCWV dataset described in this work has been validated against ARSA and SSM/I equivalent products
Summary
A key issue in assessing the climate change is the precise knowledge of the distribution and variability of the total column of water vapour (TCWV), i.e. the vertically integrated atmospheric water vapour content. TCWV is closely linked to clouds, precipitation and to the hydrological cycle (Allan et al, 2014). For this reason it is one of the GCOS (Global Climate Observing System) essential climate variables (ECVs). Sensors operating in the microwave region, such as the Special Sensor Microwave Imager (SSM/I on board Defense Meteorological Satellite Program, DMSP, satellites), are used to infer the accurate amount of TCWV over ocean surfaces (Wentz, 1997), Published by Copernicus Publications on behalf of the European Geosciences Union
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