Generalization of the complete data fusion to multi-target retrieval of atmospheric parameters and application to FORUM and IASI-NG simulated measurements

Abstract In the context of a growing need for innovatory techniques to take advantage of the largest amount of information from the great number of available remote sensing data, the Complete Data Fusion (CDF) algorithm was presented as a new method to combine independent measurements of the same vertical profile of an atmospheric parameter into a single estimate for a concise and complete characterization of the atmospheric state. The majority of the atmospheric composition measurements determine the altitude distribution of a great number of quantities: multi-target retrievals (MTRs) are increasingly applied to remote sensing observations to determine simultaneously atmospheric constituents with the purpose to reduce the systematic error caused by interfering species. In this work, we optimised the CDF for the application to MTR products. We applied the method to simulated retrievals in the thermal infrared and in the far infrared spectral ranges, considering the instrumental specifications and performances of IASI-NG (Infrared Atmospheric Sounding Interferometer New Generation) and FORUM (Far-Infrared Outgoing Radiation Understanding and Monitoring) instruments, respectively. The obtained results show that the CDF algorithm can cope with state vectors from MTRs, that must share at least one retrieved variable. In particular, the results show that the fused profile has the greatest number of degrees of freedom and the smallest error for all considered cases. The comparison between the CDF products and the synergistic retrieval ones shows the equivalence of the two methods when the linear approximation is adopted to simplify the treatment of the retrieval problem

Cabozantinib After a Previous Immune Checkpoint Inhibitor in Metastatic Renal Cell Carcinoma: A Retrospective Multi-Institutional Analysis

Background: Angiogenesis has been recognized as the most important factor for tumor invasion, proliferation, and progression in metastatic renal cell carcinoma (mRCC). However, few clinical data are available regarding the efficacy of cabozantinib following immunotherapy. Objective: To describe the outcome of cabozantinib in patients previously treated with immunotherapy. Patients and methods: Patients with mRCC who received cabozantinib immediately after nivolumab were included. The primary endpoint was to assess the outcome in terms of efficacy and activity. Results: Eighty-four mRCC patients met the criteria to be included in the final analysis. After a median follow-up of 9.4 months, median overall survival was 17.3 months. According to the IMDC criteria, the rates of patients alive at 12 months in the good, intermediate, and poor prognostic groups were 100%, 74%, and 33%, respectively (p < 0.001). The median progression-free survival (PFS) was 11.5 months (95% CI 8.3-14.7); no difference was found based on duration of previous first-line therapy or nivolumab PFS. The overall response rate was 52%, stable disease was found as the best response in 25.3% and progressive disease in 22.7% of patients. Among the 35 patients with progressive disease on nivolumab, 26 (74.3%) patients showed complete/partial response or stable disease with cabozantinib as best response after nivolumab. The major limitations of this study are the retrospective nature and the short follow-up. Conclusions: Cabozantinib was shown to be effective and active in patients previously receiving immune checkpoint inhibitors. Therefore, cabozantinib can be considered a valid therapeutic option for previously treated mRCC patients, irrespective of the type and duration of prior therapies

How Certain are We of the Uncertainties in Recent Ozone Profile Trend Assessments of Merged Limbo Ccultation Records? Challenges and Possible Ways Forward

Most recent assessments of long-term changes in the vertical distribution of ozone (by e.g. WMO and SI2N) rely on data sets that integrate observations by multiple instruments. Several merged satellite ozone profile records have been developed over the past few years; each considers a particular set of instruments and adopts a particular merging strategy. Their intercomparison by Tummon et al. revealed that the current merging schemes are not sufficiently refined to correct for all major differences between the limb/occultation records. This shortcoming introduces uncertainties that need to be known to obtain a sound interpretation of the different satellite-based trend studies. In practice however, producing realistic uncertainty estimates is an intricate task which depends on a sufficiently detailed understanding of the characteristics of each contributing data record and on the subsequent interplay and propagation of these through the merging scheme. Our presentation discusses these challenges in the context of limb/occultation ozone profile records, but they are equally relevant for other instruments and atmospheric measurements. We start by showing how the NDACC and GAW-affiliated ground-based networks of ozonesonde and lidar instruments allowed us to characterize fourteen limb/occultation ozone profile records, together providing a global view over the last three decades. Our prime focus will be on techniques to estimate long-term drift since our results suggest this is the main driver of the major trend differences between the merged data sets. The single-instrument drift estimates are then used for a tentative estimate of the systematic uncertainty in the profile trends from merged data records. We conclude by reflecting on possible further steps needed to improve the merging algorithms and to obtain a better characterization of the uncertainties involved

PREMIER Analysis of Campaign Data ESA-ESTEC Contract 4000101374/NL/10/CT

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