Search

The Infrared Atmospheric Sounding Interferometer (IASI) forms the main infrared sounding component of the European Organisation for the Exploitation of Meteorological Satellites's (EUMETSAT's) Meteorological Operation (MetOp)-A satellite (Klaes et al. 2007), which was launched in October 2006. This article presents the results of the first 4 yr of the operational IASI mission. The performance of the instrument is shown to be exceptional in terms of calibration and stability. The quality of the data has allowed the rapid use of the observations in operational numerical weather prediction (NWP) and the development of new products for atmospheric chemistry and climate studies, some of which were unexpected before launch. The assimilation of IASI observations in NWP models provides a significant forecast impact; in most cases the impact has been shown to be at least as large as for any previous instrument. In atmospheric chemistry, global distributions of gases, such as ozone and carbon monoxide, can be produced in near–real time, and short-lived species, such as ammonia or methanol, can be mapped, allowing the identification of new sources. The data have also shown the ability to track the location and chemistry of gaseous plumes and particles associated with volcanic eruptions and fires, providing valuable data for air quality monitoring and aircraft safety. IASI also contributes to the establishment of robust long-term data records of several essential climate variables. The suite of products being developed from IASI continues to expand as the data are investigated, and further impacts are expected from increased use of the data in NWP and climate studies in the coming years. The instrument has set a high standard for future operational hyperspectral infrared sounders and has demonstrated that such instruments have a vital role in the global observing system.

Evapotranspiration (ET) represents one of the essential processes controlling the exchange of energy by terrestrial vegetation, providing a strong connection between energy and water fluxes. Different methodologies have been developed in order to measure it at different spatial scales, ranging from individual plants to an entire watershed. In the last few years, several methods and approaches based on remotely sensed data have been developed over different ecosystems for the estimation of ET. In the present work, we outline the correlation between ET measured at four eddy covariance (EC) sites in Italy (situated either in forest or in grassland ecosystems) and (1) the emissivity contrast index (ECI) based on emissivity data from thermal infrared spectral channels of the MODIS and ASTER satellite sensors (CAMEL data-set); (2) the water deficit index (WDI), defined as the difference between the surface and dew point temperature modeled by the ECMWF (European Centre for Medium-Range Weather Forecasts) data. The analysis covers a time-series of 1 to 7 years depending on the site. The results showed that both the ECI and WDI correlate to the ET calculated through EC. In the relationship WDI-ET, the coefficient of determination ranges, depending on the study area, between 0.5 and 0.9, whereas it ranges between 0.5 and 0.7 when ET was correlated to the ECI. The slope and the sign of the latter relationship is influenced by the vegetation habitat, the snow cover (particularly in winter months) and the environmental heterogeneity of the area (calculated in this study through the concept of the spectral variation hypothesis using Rao’s Q heterogeneity index).

Top of the atmosphere synthetic spectral radiances are computed for widespread atmospheric conditions by alternatively using the discrete ordinate algorithm solution or approximate methodologies where the scattering effects are simulated by appropriate scaling of the absorption properties of the diffusive layers. The residuals between the full scattering solution and the scaling methods are evaluated at far- and mid- infrared wavelengths and compared with the goal noise of the FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) satellite sensor, that will be the next European Space Agency (ESA) 9 t h Earth Explorer, capable of spectrally resolved measurements in the 100–1600 cm − 1 band. The results define the limit of validity of the fast methodologies considered: the Chou approximation, that is provided as an improved version, and a simple scaling based on the similarity principle. In particular, it is shown that in case of water clouds the scaling methodologies are sufficiently accurate in the mid infrared, except when very small effective radii are accounted for, independently of the cloud optical depths. The same holds in the far infrared for low level water clouds and for humid regions, while not negligible inaccuracies are observed in an increasingly dry atmosphere above the cloud and for small effective radii. Ice clouds are accurately simulated by scaling methods at mid infrared wavelengths in all conditions and for very optically thin clouds at far infrared. Nevertheless, the computational errors become larger than the FORUM noise for optical depths of the order of unity at far infrared. Examples of desert dust and volcanic aerosol are also analysed, showing that the approximate solutions could drive to significant errors also at mid infrared wavelengths.