Articles | Volume 12, issue 1
https://doi.org/10.5194/amt-12-371-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-371-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Jan 2019
Research article |
| 18 Jan 2019
| 18 Jan 2019
The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) version 2: algorithm evolution, dataset description and performance improvements
Instituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Via
Gobetti 101, 40129 Bologna, Italy
Enzo Papandrea
Serco s.p.a., Via Sciadonna
24–26, 00044 Frascati, Italy
Instituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Via
Gobetti 101, 40129 Bologna, Italy
Alessio Di Roma
Dipartimento di Fisica e Astronomia,
DIFA, Universita' di Bologna, Viale Berti Pichat 6/2, 40127, Bologna, Italy
Bianca Maria Dinelli
Instituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Via
Gobetti 101, 40129 Bologna, Italy
Stefano Casadio
Serco s.p.a., Via Sciadonna
24–26, 00044 Frascati, Italy
Bojan Bojkov
EUMETSAT, Eumetsat Allee 1, 64295 Darmstadt, Germany
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Short summary
The total column water vapour (TCWV) is a key atmospheric variable. The AIRWAVE (Advanced Infra-Red WAter Vapour Estimator) v1 algorithm was developed to retrieve TCWV from satellite measurements. Comparisons with independent TCWV show good agreement with an overall bias of 0.72 kg m−2 due to the polar and coastal regions. Here, we describe the AIRWAVEv2 dataset, which shows significant improvements with a global bias of 0.02 kg m−2. This dataset was used to produce a climatology from 1991 to 2012.
The total column water vapour (TCWV) is a key atmospheric variable. The AIRWAVE (Advanced...
