Teles (Germany)

The Copernicus carbon dioxide monitoring (CO2M) mission is the space component of the European integrated monitoring and verification support capacity dedicated to monitoring anthropogenic CO2 emissions. Due to the high accuracy requirements of this measurement, it is critical to measure and characterise cloud and aerosol in support of the CO2 retrieval. The Cloud Imager (CLIM) and the Multi-Angle Polarimeter (MAP) are therefore included as a payloads on the CO2M mission and the measured cloud and aerosol properties are used to correct for scattering and transmission in the downstream greenhouse gas (GHG) retrieval. The synergistic use of the cloud and aerosol products within the CO2M ground segment will be described. 

Exergames can be an appealing strategy that is integrated into post-abdominal surgery rehabilitation. The aim of this study was to assess the effectiveness of exergame rehabilitation in improving independence in activities of daily living (ADLs) and patient balance after abdominal cancer surgery. A randomized control-group study was carried out in an oncological hospital in Portugal. Seventy postoperative patients were included, and data collection took place between January 2023 and May 2023. The patients were randomly assigned to either an exergame rehabilitation program (n = 35) or a traditional rehabilitation program (n = 35). The assessed outcomes were the Barthel and Berg scales, and data collection occurred at 3 different time points: admission, 48 hours postoperatively, and on the seventh day after surgery. At the third assessment, a statistically significant difference was observed between the 2 groups for both indicators, ADLs and balance. There was an improvement in ADLs and balance in the exergames group. By the seventh day after surgery, the intervention group showed improvement in balance and ADLs compared with the control group. The use of exergames can be a solution to the challenges of traditional rehabilitation methods after abdominal surgery for cancer for postoperative patients. This is the first study carried out in this specific population.

Space missions increasingly rely on Artificial Intelligence (AI) for a variety of tasks, ranging from planning and monitoring of mission operations, to processing and analysis of mission data, to assistant systems like, e.g., a bot that interactively supports astronauts on the International Space Station.In general, the use of AI brings about a multitude of security threats.In the space domain, initial attacks have already been demonstrated, including, e.g., the Firefly attack that manipulates automatic forest-fire detection using sensor spoofing.In this article, we provide an initial analysis of specific security risks that are critical for the use of AI in space and we discuss corresponding security controls and mitigations.We argue that rigorous risk analyses with a focus on AI-specific threats will be needed to ensure the reliability of future AI applications in the space domain.

Abstract. In early 2020, an international team set out to investigate trade-wind cumulus clouds and their coupling to the large-scale circulation through the field campaign EUREC4A: ElUcidating the RolE of Clouds-Circulation Coupling in ClimAte. Focused on the western tropical Atlantic near Barbados, EUREC4A deployed a number of innovative observational strategies, including a large network of water isotopic measurements collectively known as EUREC4A-iso, to study the tropical shallow convective environment. The goal of the isotopic measurements was to elucidate processes that regulate the hydroclimate state – for example, by identifying moisture sources, quantifying mixing between atmospheric layers, characterizing the microphysics that influence the formation and persistence of clouds and precipitation, and providing an extra constraint in the evaluation of numerical simulations. During the field experiment, researchers deployed seven water vapor isotopic analyzers on two aircraft, on three ships, and at the Barbados Cloud Observatory (BCO). Precipitation was collected for isotopic analysis at the BCO and from aboard four ships. In addition, three ships collected seawater for isotopic analysis. All told, the in situ data span the period 5 January–22 February 2020 and cover the approximate area 6 to 16∘ N and 50 to 60∘ W, with water vapor isotope ratios measured from a few meters above sea level to the mid-free troposphere and seawater samples spanning the ocean surface to several kilometers depth. This paper describes the full EUREC4A isotopic in situ data collection – providing extensive information about sampling strategies and data uncertainties – and also guides readers to complementary remotely sensed water vapor isotope ratios. All field data have been made publicly available even if they are affected by known biases, as is the case for high-altitude aircraft measurements, one of the two BCO ground-based water vapor time series, and select rain and seawater samples from the ships. Publication of these data reflects a desire to promote dialogue around improving water isotope measurement strategies for the future. The remaining, high-quality data create unprecedented opportunities to close water isotopic budgets and evaluate water fluxes and their influence on cloudiness in the trade-wind environment. The full list of dataset DOIs and notes on data quality flags are provided in Table 3 of Sect. 5 (“Data availability”).

<p>Satellite observations of cloud properties are of critical importance for a number of established, operational, and emerging applications serving a wide user community. Examples include the support to nowcasting activities in National Weather Services for the anticipation of evolving severe storms, icing risk evaluation for air traffic, estimation of surface radiation for photovoltaic systems. Numerical Weather Prediction Models (NWP), whilst generally not directly assimilating cloud products, use them for model evaluation and, in the context of climate change, Thematic Climate Data Records from level-2 products can support Climate Analysis. Cloud products are also direct inputs to several level-2 retrievals such as Atmospheric Motion Vectors (AMV), for which quality cloudy pixel identification and height assessment are crucial for their use in NWP.</p><p>Similarly, satellite observations of aerosol properties provide support to regulatory and legislative activities in Member States to support air quality monitoring and climate products, particularly in case of dust storms or volcanic ash events. The Copernicus Atmosphere Monitoring Service (CAMS) facilitates the use of the data for this purpose and has a need for high quality near-real time operational aerosol products for use in data assimilation. High quality aerosol products are becoming increasingly important for NWP and climate modelling due to the influence of aerosols on the radiation budget and their role in cloud processes and precipitation.</p><p>The potential for EUMETSAT to provide state of the art cloud products will significantly increase with the Meteosat Third Generation (MTG) and the EUMETSAT Polar System programme Second Generation (EPS-SG) and with the possibility of deriving cloud properties from the Copernicus Sentinel-3 instruments. Improvements include higher spatial resolution and richer spectral coverage, which together will allow more accurate cloud detection, estimation of the cloud phase, layering, altitude and spatial inhomogeneity, at the same time maintaining continuity with the legacy products based on current instruments. </p><p>Moreover, EUMETSAT, as the only European agency providing aerosol products for near real time services, will significantly benefit from the new suite of instruments, such as dedicated aerosol polarimeter (3MI), the Multi Angle Polarimeter (MAP) from the Copernicus CO2M mission and from synergy between sensors. These new sensors will allow the exploration of the new information from multi-angle, multi-spectral polarimetric observations together with other instrument classes, to improve estimates of the aerosol optical depth, aerosol type, optical characteristics and layer height. </p><p>The talk will provide an overview of the activities within EUMETSAT to prepare for the challenges and opportunities offered by the new imagers and spectrometers on board of the upcoming geostationary and polar orbiting missions, will outline the potential for development of multi-instrument synergistic products, and discuss the plans for calibration and validation of level-2 products against surface and satellite-borne reference datasets.</p>

We have proposed a simple algorithm to retrieve the total ozone column and snow properties (spectral albedo and effective light absorption path) using the high spatial resolution single – view MSI/S-2 measurements over Antarctica.

<strong class="journal-contentHeaderColor">Abstract.</strong> We present a global and multi-annual space-borne dataset of tropospheric {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) on board the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in <span class="cit" id="xref_text.1"><a href="#bib1.bibx38">Schneider et al.</a> (<a href="#bib1.bibx38">2021</a><a href="#bib1.bibx38">b</a>)</span>. From the independently retrieved <span class="inline-formula">H₂O</span> and <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span> proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset, we generate an optimal estimation product for pairs of <span class="inline-formula">H₂O</span> and <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>. Here, this standard MUSICA method for deriving {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pair dataset for the whole period from October 2014 to December 2020 with global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1500 million individually processed observations. The retrievals are most sensitive to variations in {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but higher latitudes also show a considerable amount of reliable data. Exemplary time series over the tropical Atlantic and West Africa are chosen to illustrate the potential of the MUSICA IASI {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pair data for atmospheric moisture pathway studies. Furthermore, in order to facilitate the application of this rather comprehensive MUSICA IASI {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pair dataset (referred to as Level-2), we additionally provide the data in a re-gridded and simplified format (Level-3) with focus on the quality-filtered {<span class="inline-formula">H₂O</span>, <span class="inline-formula"><i>δ</i></span><span class="inline-formula">D</span>} pairs in the free troposphere. A technical documentation for guiding the use of both datasets is attached as the Supplement. Finally, the Level-2 dataset is referenced with the DOI <a href="https://doi.org/10.35097/415">https://doi.org/10.35097/415</a> <span class="cit" id="xref_paren.2">(<a href="#bib1.bibx10">Diekmann et al.</a>, <a href="#bib1.bibx10">2021</a><a href="#bib1.bibx10">a</a>)</span> and the Level-3 dataset with DOI <a href="https://doi.org/10.35097/495">https://doi.org/10.35097/495</a> <span class="cit" id="xref_paren.3">(<a href="#bib1.bibx11">Diekmann et al.</a>, <a href="#bib1.bibx11">2021</a><a href="#bib1.bibx11">b</a>)</span>.