The FORUM end-to-end simulator project: architecture and results

FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) will fly as the ninth ESA's Earth Explorer mission, and an end-to-end simulator (E2ES) has been developed as a support tool for the mission selection process and the subsequent development phases. The current status of the FORUM E2ES project is presented together with the characterization of the capabilities of a full physics retrieval code applied to FORUM data. We show how the instrument characteristics and the observed scene conditions impact on the spectrum measured by the instrument, accounting for the main sources of error related to the entire acquisition process, and the consequences on the retrieval algorithm. Both homogeneous and heterogeneous case studies are simulated in clear and cloudy conditions, validating the E2ES against appropriate well-established correlative codes. The performed tests show that the performance of the retrieval algorithm is compliant with the project requirements both in clear and cloudy conditions. The far-infrared (FIR) part of the FORUM spectrum is shown to be sensitive to surface emissivity, in dry atmospheric conditions, and to cirrus clouds, resulting in improved performance of the retrieval algorithm in these conditions. The retrieval errors increase with increasing the scene heterogeneity, both in terms of surface characteristics and in terms of fractional cloud cover of the scene

Analysis of far-infrared (FIR) high spectral resolution data for cloud studies

The Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission has recently been selected by the European Satellite Agency (ESA) as 9 th Earth Explorer mission. FORUM mission aims at studying the water vapor and clouds by filling the long-standing gap in Far-Infrared (FIR) spectral observations from space. In the framework of the FORUM mission, this thesis analyses FIR measurements to characterize the spectral signatures of radiance in presence of ice clouds. At this purpose, a cloud identification and classification code (named CIC) is implemented. CIC is an innovative machine learning algorithm, based on principal component analysis, able to perform cloud detection and scene multi-class classification. CIC is easily adaptable to different datasets and type of spectral sensors. It is firstly tested against a synthetic dataset comprising simulated measurements of the FORUM mission. Subsequently, CIC is applied to airborne interferometric data and finally it is used for the analysis of measured downwelling radiances collected in very dry conditions on the Antarctic Plateau. Provided the excellent performances of the algorithm, especially in the identification of thin cirrus clouds, CIC is adopted as the classificator in the official ESA FORUM End-to-End simulator (FE2ES). The FE2ES is a complex chain of codes used to simulate the entire FORUM mission from satellite orbit and geometry to level 2 product analysis. An extensive use of CIC is performed on ground-based radiances collected in Antarctica. The dataset is exploited to test and to optimize the CIC algorithm and for the developing of punctual statistic of cloud occurrence in the Antarctic Plateau. Meteorological conditions from this region are also analysed and correlated with the presence of clouds. The studies presented in this work showed the potentiality and the importance of the exploitation of spectral radiance measurements in the FIR for cloud identification and classification

Comparison of the AIRS, IASI, and CrIS 900 cm-1 Channel for Dome Concordia

We compare AIRS, IASI-A and CrIS under the cold conditions encountered in the daily overpasses of Dome Concordia, which is located on a high plateau in Antarctica, between May 2012 and March 2016. The brightness temperatures at DomeC for the 900 cm-1 atmospheric window channel is 218K on average, but varies seasonally from 185K to 255K. Averaged over all simultaneous overpass data AIRS is 2613 mK warmer than IASI-A, AIRS is 1167 mK colder than CrIS. However, we find that differences for both AIRS/IASI-A and AIRS/CrIS are temperature dependent, with AIRS being 250mK colder than IASI-A at 200K. These effects have been independently verified by other investigators. AIRS and CrIS bt900 results for simultaneous overpasses and daily mean values agree within 100 mK. AIRS and IASI simultaneous overpasses agree within 100 mK, but AIRS is 2K warmer than IASI for daily mean values. We attribute this effect to an overactive IASI QC which is sensitive to scene temperature above about 240K. The DomeC data do not reveal if this QC effect is present at temperatures warmer than 255K. These effects need to be taken into account when comparing results from AIRS, IASI and CrIS, and even more so when analyzing data from vintage instruments with respect to climate change