Sara Venafra

Diurnal emissivity dynamics in bare versus biocrusted sand dunes

Land surface emissivity (LSE) in the thermal infrared depends mainly on the ground cover and on changes in soil moisture. The LSE is a critical variable that affects the prediction accuracy of geophysical models requiring land surface temperature as an input, highlighting the need for an accurate derivation of LSE. The primary aim of this study was to test the hypothesis that diurnal changes in emissivity, as detected from space, are larger for areas mostly covered by biocrusts (composed mainly of cyanobacteria) than for bare sand areas. The LSE dynamics were monitored from geostationary orbit by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) over a sand dune field in a coastal desert region extending across both sides of the Israel-Egypt political borderline. Different land-use practices by the two countries have resulted in exposed, active sand dunes on the Egyptian side (Sinai), and dunes stabilized by biocrusts on the Israeli side (Negev). Since biocrusts adsorb more moisture from the atmosphere than bare sand does, and LSE is affected by the soil moisture, diurnal fluctuations in LSE were larger for the crusted dunes in the 8.7 μm channel. This phenomenon is attributed to water vapor adsorption by the sand/biocrust particles. The results indicate that LSE is sensitive to minor changes in soil water content caused by water vapor adsorption and can, therefore, serve as a tool for quantifying this effect, which has a large spatial impact. As biocrusts cover vast regions in deserts worldwide, this discovery has repercussions for LSE estimations in deserts around the globe, and these LSE variations can potentially have considerable effects on geophysical models from local to regional scales.

Physical Retrieval of Land Surface Emissivity Spectra from Hyper-Spectral Infrared Observations and Validation with In Situ Measurements

A fully physical retrieval scheme for land surface emissivity spectra is presented, which applies to high spectral resolution infrared observations from satellite sensors. The surface emissivity spectrum is represented with a suitably truncated Principal Component Analysis (PCA) transform and PCA scores are simultaneously retrieved with surface temperature and atmospheric parameters. The retrieval methodology has been developed within the general framework of Optimal Estimation and, in this context, is the first physical scheme based on a PCA representation of the emissivity spectrum. The scheme has been applied to IASI (Infrared Atmospheric Sounder Interferometer) and the retrieved emissivities have been validated with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. It has been found that the retrieved emissivity spectra are independent of background information and in good agreement with in situ observations.

Hyper fast radiative transfer for the physical retrieval of surface parameters from SEVIRI observations

This paper describes the theoretical aspects of a fast scheme for the physical retrieval of surface temperature and emissivity from SEVIRI data, their implementation and some sample results obtained. The scheme is based on a Kalman Filter approach, which effectively exploits the temporal continuity in the observations of the geostationary Meteosat Second Generation (MSG) platform, on which SEVIRI (Spinning Enhanced Visible and InfraRed Imager) operates. Such scheme embodies in its core a physical retrieval algorithm, which employs an hyper fast radiative transfer code highly customized for this retrieval task. Radiative transfer and its customizations are described in detail. Fastness, accuracy and stability of the code are fully documented for a variety of surface features, showing a peculiar application to the massive Greek forest fires in August 2007.

SEVIRI Cloud mask by Cumulative Discriminant Analysis

In the context of cloud detection for satellite observations we want to use the method of Cumulative Discriminant Analysis (CDA) as a tool to distinguish between clear and cloudy sky applied to Spinning Enhanced Visible and Infrared Imager (SEVIRI) data. The methodology is based on the choice of several statistics related to the cloud properties, whose correlation has been analyzed by Principal Component Analysis (PCA). Results have been compared with the SEVIRI reference cloud mask provided by the European Centre for the Exploitation of Meteorological Satellite (EUMETSAT), in order to find suitable thresholds able to discriminate between clear or cloudy conditions. We trained the statistics on a selected region, the Basilicata area, located in the south of Italy, in different periods of the year 2012, in order to take into account the seasonal variability. Moreover we separated land and sea surface and distinguished between day-time or night-time. The validation of thresholds, obtained through SEVIRI observations analysis, shows a good agreement with the reference cloud mask.

Four years of IASI CO2, CH4, N2O retrievals: validation with in situ observations from the Mauna Loa station

IASI (Infrared Atmospheric Sounder Interferometer) soundings for the years 2014 to 2017 over sea surface for the Hawaii region have been used to retrieve column amount of CO2, CH4, N2O. The analysis allowed us to derive CO2, CH4 and N2O growth rates, trend and seasonality, which have been compared to in situ observations from the Mauna Loa validation station. Day and night soundings have been used. During the day, for CO2 and N2O we make specifically use of the IASI short wave band (2000 to 2250 cm-1), which is sensitive to sun radiation. Our forward/inverse module deals with sun radiation using a Cox-Munck model for the bidirectional reflectance distribution function. This makes it possible to exploit IASI soundings in sun-glint or close to sun-glint mode, which improves sensitivity of retrievals close to the surface. The analysis has been performed with our total IASI level 2 processor or τ2IP, which uses the whole IASI spectral coverage, therefore making it possible to exploit the whole information content of data. The code τ2IP also uses a random projection approach to reduce the dimensionality of the data space. Our analysis show that growth rate, trend and seasonality are extracted with high accuracy (we observe correlation with in situ data close or higher than 0.90). After validation, we have applied τ2IP to seven years of data over the Arctic sea basin and computed summer maps (July to September) of CO2 and sea skin temperature. The results show that the increase of skin temperature parallels the increase of CO2 column amount over the Arctic basin.

The very first multi-temporal and multi-spectral Level-2 SEVIRI processor for the simultaneous physical retrieval of surface temperature and emissivity

The estimation of surface parameters yields important information in several applications on regional and global scale. Because of their high temporal resolution, infrared instruments on board geostationary platforms are capable to provide time sequences of observations, which fully resolve the diurnal cycle. To exploit multi-temporal information, a Kalman filter (KF) methodology has been implemented in order to retrieve simultaneously surface temperature and emissivity from SEVIRI (Spinning Enhanced Visible and Infrared Imager) infrared data. Because of its sequential nature, the Kalman filter methodology yields a very fast software implementation, which can be applied to the SEVIRI full disk for off-line analysis. The software can run in real-time at the regional scale, which makes it very attractive for different applications such as land surveillance, natural hazards, risk management, and so on. The paper will show the basic methodology and applications at regional and global scale.

All-sky radiative transfer calculations for IASI and IASI-NG: The σ-IASI-as code

In the context of the development by EUMETSAT of a new generation of meteorological satellites, we have built the new σ-IASI-as (where “as” stands for “all sky”) radiative transfer code. Unlike its predecessor σ-IASI, the code is able to calculate both clear and cloudy sky radiances, as well as their Jacobians with respect to any desired geophysical parameter. In addition, σ-IASI-as can perform calculations to simulate the extinction effect of the most common types of atmospheric aerosols and of clouds via ab-initio Mie calculations. We briefly describe the analytical scheme on which the model is based, and have a glance to its potentialities illustrating some sample calculations. Overall, the new model is a complete and fast radiative transfer tool for IASI, and already available for IASI-NG and MTG-IRS.

Using the full IASI spectrum for the physical retrieval of temperature, H2O, HDO, O3, minor and trace gases

IASI (Infrared Atmospheric Sounder Interferometer) is flying on the European MetOp series of weather satellites. Besides acquiring temperature and humidity data, IASI also observes the infrared emission of the main minor and trace atmospheric components with high precision. The retrieval of these gases would be highly beneficial to the efforts of scientists monitoring Earths climate. IASI retrieval capability and algorithms have been mostly driven by Numerical Weather Prediction centers, whose limited resources for data transmission and computing is hampering the full exploitation of IASI information content. The quest for real or nearly real time processing has affected the precision of the estimation of minor and trace gases, which are normally retrieved on a very coarse spatial grid. The paper presents the very first retrieval of the complete suite of IASI target parameters by exploiting all its 8461 channels. The analysis has been exemplified for sea surface and the target parameters will include sea ...