The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) algorithm [Casadio et al. (2016)] exploits the dual view of the Thermal Infrared channels of the ATSR instruments and a sea surface emissivity dataset to compute the Total Column of Water Vapour (TCWV) over water in clear sky conditions. 20-years of day-night TCWV dataset have been produced applying AIRWAVE to the measurements of the Along Track Scanning Radiometer (ATSR) missions. AIRWAVE has been developed for observations over water surfaces but the algorithm can also be applied to land surfaces. The main difficulty in exploiting land measurements is linked to the knowledge of the surface emissivity in the ATSR infrared channels. While sea emissivity is generally close to one and is almost constant all over the globe, land emissivity has strong variations depending on e.g. surface type and vegetation cover. Furthermore, the angular emissivity variations can also be relevant. For the extension of the AIRWAVE algorithm to land surfaces, one strategy is the use of tabulated emissivity datasets. The limitations of these datasets is that they report data relative to only daytime (ATSR measures both day and night) and the data are averaged over long time spans (tenth of days). Another strategy is the use of retrieved emissivities from instruments covering the same spectral region of the TIR channels of ATSR and measuring almost at the same time. Recently Masiello et al. (2013-2015) have developed a retrieval scheme to obtain the Land Emissivity from SEVIRI observations. SEVIRI measures on board the geostationary satellite Meteosat and two of its channels superimpose to the TIR channels of ATSR. Therefore, SEVIRI and AATSR/ENVISAT represent a perfect match to test the possibility of a joint analysis to get both land emissivities and TCWV. In this work we will show the results of the application of the AIRWAVE algorithm to measurements over land. We will critically compare the results obtained using emissivity databases and the SEVIRI retrieved emissivities, assessing their performance through the comparison of the obtained results with correlative data contained into the ESA DUE GlobVapour project (http://www.globvapour.info/). Casadio S., et al. (2016) Remote sensing of Environment, doi:10.1016/j.rse.2015.10.037 Masiello G., et al. (2013), Atmos. Meas. Tech., doi:10.5194/amt-6-3613-2013 Masiello G., et al. (2015). Atmos. Meas. Tech., doi:10.5194/amt-8-2981-2015.
AIRWAVE-SEVIRI: Total Column of Water Vapor Retrieved From AATSR Measurements Over Land Using SEVIRI Retrieved Emissivities
Dinelli B M;Castelli E;Papandrea E
2019
Abstract
The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) algorithm [Casadio et al. (2016)] exploits the dual view of the Thermal Infrared channels of the ATSR instruments and a sea surface emissivity dataset to compute the Total Column of Water Vapour (TCWV) over water in clear sky conditions. 20-years of day-night TCWV dataset have been produced applying AIRWAVE to the measurements of the Along Track Scanning Radiometer (ATSR) missions. AIRWAVE has been developed for observations over water surfaces but the algorithm can also be applied to land surfaces. The main difficulty in exploiting land measurements is linked to the knowledge of the surface emissivity in the ATSR infrared channels. While sea emissivity is generally close to one and is almost constant all over the globe, land emissivity has strong variations depending on e.g. surface type and vegetation cover. Furthermore, the angular emissivity variations can also be relevant. For the extension of the AIRWAVE algorithm to land surfaces, one strategy is the use of tabulated emissivity datasets. The limitations of these datasets is that they report data relative to only daytime (ATSR measures both day and night) and the data are averaged over long time spans (tenth of days). Another strategy is the use of retrieved emissivities from instruments covering the same spectral region of the TIR channels of ATSR and measuring almost at the same time. Recently Masiello et al. (2013-2015) have developed a retrieval scheme to obtain the Land Emissivity from SEVIRI observations. SEVIRI measures on board the geostationary satellite Meteosat and two of its channels superimpose to the TIR channels of ATSR. Therefore, SEVIRI and AATSR/ENVISAT represent a perfect match to test the possibility of a joint analysis to get both land emissivities and TCWV. In this work we will show the results of the application of the AIRWAVE algorithm to measurements over land. We will critically compare the results obtained using emissivity databases and the SEVIRI retrieved emissivities, assessing their performance through the comparison of the obtained results with correlative data contained into the ESA DUE GlobVapour project (http://www.globvapour.info/). Casadio S., et al. (2016) Remote sensing of Environment, doi:10.1016/j.rse.2015.10.037 Masiello G., et al. (2013), Atmos. Meas. Tech., doi:10.5194/amt-6-3613-2013 Masiello G., et al. (2015). Atmos. Meas. Tech., doi:10.5194/amt-8-2981-2015.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.