Day 3 Wednesday, July 3, 2024 | ||||
3.1 Air Quality I - Plenary | ||||
Chairs: Claus Zehner (ESA/ESRIN), Lucy Ventress (RALSpace) | ||||
3.1.1 | 09:00 09:12 | The CitySatAir Project: Monitoring urban nitrogen dioxide pollution exploiting Sentinel-5P data Bas Mijling (KNMI) | ||
3.1.2 | 09:12 09:24 | Using machine learning to identify air pollution plumes from EO data: developing a reference dataset for scientific applications Paul Palmer (University of Edinburgh) | ||
3.1.3 | 09:24 09:36 | NOx emissions derived from Sentinel 5P observations Ronald Van Der A (KNMI) | ||
3.1.4 | 09:36 09:48 | Wildfires in Greece and their impact on air quality: Is this the new normality? Dimitris Balis (Aristotle University of Thessaloniki) | ||
3.1.5 | 09:48 10:00 | How sensitive is the TROPOMI nitrogen dioxide retrieval to the surface albedo? Henk Eskes (KNMI) | ||
3.1.6 | 10:00 10:12 | Improved determination of natural emissions in Africa from a joint inversion of TROPOMI NO2 and HCHO columns in the MAGRITTE CTM Jenny Stavrakou (BIRA-IASB) | ||
3.1.7 | 10:12 10:24 | Satellites capture socioeconomic disruptions during the 2022 full-scale war in Ukraine Iolanda Ialongo (FMI) | ||
3.1.8 | 10:24 10:36 | Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS Sora Seo (DLR) | ||
3.1.9 | 10:36 10:48 | Identifying and accounting for the Coriolis effect in satellite NO2 observations and emission estimates Daniel Potts (University of Leicester) | ||
10:48 - 11:15 Break | ||||
3.2 Air Quality II - Plenary | ||||
Chairs: Michel van Roozendaal (BIRA-IASB), Elisa Castelli (CNR) | ||||
3.2.1 | 11:15 11:27 | Estimating hourly nitrogen oxide emissions across Asia using GEMS geostationary satellite data Fei Yao (University of Edinburgh) | ||
3.2.2 | 11:27 11:39 | Data assimilation developments at ECMWF in support of global emission inversion capacity Luca Cantarello (ECMWF) | ||
3.2.3 | 11:39 11:51 | LEGO-4-AQ: An AQ policy support service based on the synergistic use of LEO, GEO, and in-situ monitoring Tijl Verhoelst (BIRA-IASB) | ||
3.2.4 | 11:51 12:03 | Visualisation of long-term atmospheric composition datasets from the RAL Space Infrared and Microwave Sounder (IMS) extended retrieval scheme. Lucy Ventress (UKRI STFC, RAL Space) | ||
3.2.5 | 12:03 12:15 | Monitoring wildfires from satellite, integration in Copernicus services and characterizing atmospheric impacts from the regional to the global scales Federico Fierli (EUMETSAT) | ||
3.2.6 | 12:15 12:27 | HONO retrievals over biomass burning regions from satellite UV and IR measurements Nicolas Theys (BIRA-IASB) | ||
3.2.7 | 12:27 12:39 | Bias characterization of HCHO columns from OMI using aircraft and FTIR data Jean-Francois Muller (BIRA-IASB) | ||
3.2.8 | 12:39 12:51 | Towards a minimal hyperspatial sounder of atmospheric ammonia Lara Noppen (ULB) | ||
3.2.9 | 12:51 13:03 | Automated processing of 6 years TROPOMI CO data to identify emissions rates from pollution sources Tobias Borsdorff (SRON) | ||
13:03 - 14:30 Break | ||||
3.3 Air Quality III - Plenary | ||||
Chairs: Federico Fierli (EUMETSAT), Bas Mijling (KNMI) | ||||
3.3.1 | 14:30 14:42 | The Advanced Infra-Red WAter Vapour Estimator-v3 (AIRWAVE-v3) TCWV dataset from clear-sky over water (A)ATSR-1/2 measurements Elisa Castelli (CNR) | ||
3.3.2 | 14:42 14:54 | AIRWAVE-SLSTR: an algorithm to retrieve TCWV from Sentinel 3 SLSTR observations Enzo Papandrea (CNR) | ||
3.3.3 | 14:54 15:06 | Examining Water Vapour Residency Times from Observational and Model Ensembles Tim Trent (University of Leicester) | ||
3.3.4 | 15:06 15:18 | An improved OClO retrieval from TROPOMI observations Leonardo Alvarado Bonilla (DLR) | ||
3.3.5 | 15:18 15:30 | Improving global SO2 emission inventories using Sentinel-5P TROPOMI satellite data Adrian Jost (MPI for Chemistry) | ||
3.3.6 | 15:30 15:42 | PEGASOS Project Overview: Summary of Activities for the Evaluation of the Operational GEMS L2 Products Ronny Lutz (DLR) | ||
3.3.7 | 15:42 15:54 | Physical models and AI for urban air quality monitoring with PRISMA hyperspectral data: the PRIMARY project Davide De Santis (University of Rome Tor Vergata) | ||
3.3.8 | 15:54 16:30 | Discussion ESA & Co-chairs | ||
16:30 18:00 | Poster Session | |||
16:30 18:00 | Discussion and Recommendations for upcoming Sentinel User Preparation Activity – Atmosphere Science Foundational Experiment | |||
18:00 22:00 | Social Dinner (Pick-up point CNR) |
Day 5 Friday, July 5, 2024 | ||||
5.1 Ozone I - Plenary | ||||
Chairs: Kaley Walker (University of Toronto), Diego Loyola (DLR) | ||||
5.1.1 | 09:00 09:12 | Ozone Recovery from Merged Observational Data and Model Analysis (OREGANO) Mark Weber (University of Bremen) | ||
5.1.2 | 09:12 09:24 | The novel GOME-type Ozone Profile Essential Climate Variable (GOP-ECV) from the European Space Agency’s Climate Change Initiative+ ozone project Melanie Coldewey-Egbers (DLR) | ||
5.1.3 | 09:24 09:36 | Six years of Sentinel-5p TROPOMI operational ozone profiling: Retrieval approach and geophysical validation Arno Keppens (BIRA-IASB) | ||
5.1.4 | 09:37 09:48 | Retrieval of ozone vertical profiles from TROPOMI measurements Alexei Rozanov (University of Bremen) | ||
5.1.5 | 09:48 10:00 | Improved and temporally extended Umkehr Ozone Profile retrievals and their application for Satellite Validation Panagiotis Fountoukidis (Aristotle University of Thessaloniki) | ||
5.1.6 | 10:00 10:12 | Ozone trends derived using merged long-term datasets of ozone profiles developed in the ESA Climate Change Initiative Viktoria Sofieva (FMI) | ||
5.1.7 | 10:12 10:24 | Assessment of the TROPOMI Ozone Profile 0-6km partial column sensitivity to tropospheric ozone enhanced regional and local areas Serena Di Pede (KNMI) | ||
5.1.8 | 10:24 10:36 | Ozone CCI / C3S Climate Data Records: portfolio and recent science results Arno Keppens (BIRA-IASB) | ||
10:36 - 10:55 Break | ||||
5.2 Ozone II - Plenary | ||||
Chairs: Mark Weber (University of Bremen), Viktoria Sofieva (FMI) | ||||
5.2.1 | 10:55 11:07 | Challenges in assessing the quality of Climate Data Records for Precursors of Ozone and Aerosol Essential Climate Variables Steven Compernolle (BIRA-IASB) | ||
5.2.2 | 11:07 11:19 | Total Ozone retrievals from multiple satellite sensors: a consolidated analysis updating their geophysical validation Katerina Garane (Aristotle University of Thessaloniki) | ||
5.2.3 | 11:19 11:31 | Studies of halogenated species using the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) on SCISAT Kaley Walker (University of Toronto) | ||
5.2.4 | 11:31 11:43 | Extension of the S5P/TROPOMI CCD tropospheric ozone retrieval to middle latitudes Swathi Maratt Satheesan (University of Bremen) | ||
5.2.5 | 11:43 11:55 | Sensitivity of Interannual and Long-term Changes in Stratospheric Ozone to Predictors Time Series and Trend Model OINDRILA NATH (BIRA-IASB) | ||
5.2.6 | 11:55 12:07 | Assessment of the contribution of IRS for the characterisation of ozone over Europe Francesca Vittorioso (University of Bologna) | ||
5.2.7 | 12:07 13:00 | Discussion and conference closure ESA & Co-Chairs | ||
End of the event |
POSTER LIST | ||
Monday July 1 18:00-20:00, Wednesday July 3 16:30-18:00 | ||
P1 Other Trace Gases | ||
P1.1 | Improved TROPOMI-based global VOC emissions constrained by formaldehyde andglyoxal data and a two-compound inversion scheme | Yasmine Sfendla BIRA-IASB |
P1.2 | Balloon-borne flask-sampling technique for retrieving tropospheric water vapor isotopic composition: the WIFVOS project | Daniele Zannoni University of Venice Ca' Foscari |
P1.3 | Investigating the Day and Night Variation of NH3 Concentrations over Agricultural Regions in Asia Using Combined Observations from the IASI and CrIS Satellite Instruments | Adriana Iorga University of Leicester |
P1.4 | Detection of anthropogenic emission point sources of ethylene, propylene, acetylene,and methanol with IASI | Bruno Franco ULB |
P1.5 | Global distributions of major OVOCs derived from IASI measurements | Bruno Franco ULB |
P1.6 | Building a merged dataset from IASI and MOPITT CO Level 3 data | Maya George LATMOS, IPSL |
P1.7 | Pre-operational SO2 COBRA product generated in the S5P-PAL environment | Jonas Vlietinck BIRA-IASB |
P1.8 | Current state of sulphur emissions over Asia observed by GEO and LEO space-born instruments | Mari Liza Koukouli Aristotle University of Thessaloniki |
P1.9 | Assessment of a new cloud treatment on S5P/TROPOMI tropospheric nitrogen dioxide observations | Mari Liza Koukouli Laboratory of Atmospheric Physics Aristotle University of Thessaloniki |
P1.10 | Retrieval of vertical concentration profiles of SO2 using the IASI satellite instrument | Nga Ying Lo KIT |
P1.11 | Carbon monoxide seen by IASI and TROPOMI during the November 2023 severe air pollution episode in Northern India and Pakistan | Selviga Sinnathamby LATMOS, CNRS, Sorbonne Université |
P1.12 | Assessing the future IRS-MTG NH3 and temperature observations | Nadir Guendouz LATMOS, CNRS |
P1.13 | Viewing angle dependencies in glyoxal climate data records for the ESA Climate Change Initiative | Thomas Danckaert BIRA-IASB |
P1.14 | Using GEOS-Chem vertical profiles for improved night-time satellite retrievals of NH3 | Martin Van Damme ULB, BIRA-IASB |
P1.15 | First weekly top-down biogenic VOC emissions over Europe constrained by TROPOMI HCHO data | Glenn-Michael Oomen BIRA-IASB |
P1.16 | Development of new Multi-Sensor Formaldehyde Climate Data Records as part of the ESA Climate Change Initiative | Isabelle De Smedt BIRA-IASB |
P1.17 | Improved retrievals of SO₂ plume height and column density from TROPOMI observations | Lorenzo Fabris BIRA-IASB |
P1.18 | Stratospheric and upper tropospheric measurements of photochemically active species of the nitrogen, chlorine, and bromine families with GLORIA-B | Gerald Wetzel KIT |
P1.19 | Stratospheric and upper tropospheric measurements of long-lived tracers with GLORIA-B | Gerald Wetzel KIT |
P1.20 | Trend analysis of climate change markers through ECMWF CERA-20C secular timeseries | Alessandro Piscini INGV |
P1.21 | Investigating HCN and CO emissions of biomass burning in the Earth system | Antonio Giovanni Bruno NCEO, University of Leicester |
P1.22 | Quality assessment of the Sentinel-5P TROPOMI cloud products using ACTRIS/Cloudnet data as a reference | Steven Compernolle BIRA-IASB |
P1.23 | Monitoring geo-engineering scenarios with the EE11 CAIRT instrument | Pasquale Sellitto LISA-IPSL |
P1.24 | Biomass Burning – A Comparative Study Between ACE-FTS Observations and the GEOS-Chem High Performance Model | Kevin Bloxam University of Toronto |
P1.25 | Nitrate and ammonium in the upper troposphere and lower stratosphere - unique contributions from air- and space-borne infrared limb-sounders: CRISTA, MIPAS, GLORIA, CAIRT | Michael Höpfner KIT |
P2 Greenhouse gases | ||
P2.1 | Carbon dioxide concentrations over Italy by using OCO-2 time series acquisitions | Vito Romaniello INGV |
P2.2 | Benchmarking atmospheric methane at high latitudes in support of the Arctic Methaneand Permafrost Challenge (AMPAC) | Hannakaisa Lindqvist FMI |
P2.3 | Navigating the Challenges in Methane Detection Using Machine Learning: A Critical Analysis and Research Agenda | Marco A.,RuedaInstitute for Systems and Robotics Instituto Superior Técnico |
P2.4 | Matched Filter method for detection of CH4 emission from satellite: a proposal of Evolution | Fabrizio Masin University of Bologna |
P2.5 | Evaluating the consistency of methane emissions from regional inversions using different TROPOMI XCH4 satellite products | Aurélien Sicsik-Paré LSCE |
P2.6 | Optimizing GOSAT methane observations to enhance high-latitude data coverage witha genetic algorithm approach | Lakshmi Naduparambil Bharathan NCEO |
P2.7 | How can satellite data and surface isotopic signature data contribute to understanding the global methane budget? | Emeline Tapin LSCE |
P2.8 | Global distribution of methane in the mid-troposphere as seen by IASI onboard three successive Metop platforms | Nicolas Meilhac Fx-conseil/lmd |
P2.9 | Estimating and verifying emissions magnitudes and trends with satellite data: a selection of case studies | Joni Kushta The Cyprus Institute |
P2.10 | Automated Detection and Attribution of Methane Super-Emitters Using Sentinel-2 Satellite Data and Deep Learning | Fei Yao University of Edinburgh |
P2.11 | The first year of COCCON EM27/SUN operation in Rome | Giacomo Gostinicchi Serco Italia Spa |
P2.12 | Towards evaluation of new Copernicus Contributing Missions (CCMs) dedicated for measuring methane emissions with very high spatial resolution | Mahesh Kumar Sha BIRA-IASB |
P2.13 | Exploring the Potential of MTG FCI for Methane Point Source Monitoring | Shanyu Zhou UPV |
P2.14 | Methane sink optimisation using TROPOMI and IASI measurements in TM5-4DVAR | Jacob Van Peet Vrije Universiteit Amsterdam |
P2.15 | Current Status of COCCON (COllaborative Carbon Column Observing Network) | Darko Dubravica KIT |
P2.16 | Improvements in glint retrievals over snowy surfaces for CO2M observations: Selected results from the Snowite study | Leif Vogel Kaioa Analytics |
P2.17 | Atmosphere-ocean carbon dioxide fluxes estimate from satellite and insitu data in the Central Mediterranean | Mattia Pecci Enea |
P2.18 | MEDUSA: Methane Emissions Detection Using Satellites Assessment | lse Aben SRON |
P2.19 | Potential of TIR+SWIR combination from space measurements for CH4 retrievals: application to IASI and S5P | Pascal Prunet Spascia |
P2.20 | Direct satellite measurements of the radiative forcing of long-lived halogenated gases | Simon Whitburn ULB |
P3 Air Quality | ||
P3.1 | Air quality in Bucharest across the seasons: validation of TROPOMI and WRF-Chemtropospheric NO2 density against SWING+ and in situ measurements | Antoine Pasternak BIRA-IASB |
P3.2 | Improved tropospheric NO₂ columns retrieved from TROPOMI on board the Sentinel-5P satellite | Thomas Visarius University of Bremen |
P3.3 | TROPOMI and OMI NO2: slant column uncertainties over time | Jos Van Geffen KNMI |
P3.4 | Synergistic ground-based measurements of aerosols and NO2 using MAX-DOAS and direct-sun DOAS observations over Thessaloniki, Greece | Dimitris Karagkiozidis Aristotle University of Thessaloniki |
P3.5 | S5P/TROPOMI maritime ΝΟΧ emissions in the Mediterranean region | Andreas Pseftogkas Aristotle University of Thessaloniki |
P3.6 | Lightning NOx observation with TROPOMI | Stefani Stanojevic MPI |
P3.7 | Regional air quality degradation during the August 2023 extreme wildfires in Northern Greece | MariLiza Koukouli Aristotle University of Thessaloniki |
P3.8 | InPULS: Impact of TropOMI NO2 observations on daily air quality forecasts for Germany | Frank Baier DLR |
P3.9 | Mountain-top CubeSat Demonstrator for Urban Air Quality Monitoring: A Leap Towards High-Resolution NO₂ Mapping in the Alpine Valley of Innsbruck | Stefanie Morhenn LuftBlick OG |
P3.10 | TROPOMI NO2: a new method to identify unresolved features in DOAS residuals | Jos Van Geffen KNMI |
P3.11 | Quantifying uncertainties of satellite NO2 superobservations fordata assimilation and model evaluation | Pieter Rijsdijk SRON |
P3.12 | Evaluation of decadal regional and local NO2 column densities using space-borneinstruments and CAMS | Stefan-Marius Nicolae INOE |
P3.13 | Two new FTIR instruments for the measurement of trace gases over the Po Valley | Paolo Pettinari CNR, University of Bologna |
P3.14 | Merging OMI and TROPOMI seamlessly to create a 17-year-long tropospheric NO2 afternoon data record. | Isidora Anglou KNMI |
P3.15 | Deep Learning for High-Resolution Reconstruction of NO2 and O3 3D Fields in the Lower Troposphere | Wenfu Sun BIRA-IASB |
P3.16 | Consistent retrieval of global tropospheric HCHO and NO2 VCDs from TROPOMI based on an improved version of the POMINO algorithm | Yuhang Zhang BIRA-IASB |
P3.17 | Monitoring of ground-level pollutant concentrations from space | Johannes Staufer Thales |
P3.18 | Estimating high resolution surface PM2.5 concentrations over Europe using CAMS PM forecast, satellite AOD and a Machine Learning model | Shobitha Shetty NILU |
P3.19 | A level-3 nitrogen dioxide dataset from TROPOMI and OMI with realistic uncertainty | Isolde Glissenaar KNMI |
P3.20 | Advancements in Atmospheric Composition Observations for the next CAMS Reanalysis ‘EAC5’ | Christopher Kelly ECMWF |
P3.21 | Performance evaluation of the flux divergence approach for estimating NOx emissions using simulated TROPOMI-like NO2 data. | Felipe Cifuentes KNMI, WUR |
P3.22 | The impact of extreme wildfires of August 2023 in northern Greece on aerosol optical properties and solar radiation | Konstantinos Michailidis Aristotle University of Thessaloniki |
P3.23 | A light-weight NO2 to NOx conversion model for quantifying NOx emissions of point sources from NO2 satellite observations | Sandro,MeierSwiss Federal Laboratories for Materials Science and Technology |
P3.24 | French ARGONAUT project: Inferring pollutants (NOx, CO, NMVOCs) and CO2 emissions at high resolution over France using Sentinel-5P and the CIF-CHIMERE inversion system | Gaëlle Dufour LISA/CNRS/UPC/UPEC |
P3.25 | Investigating NO2 processing in power plant plumes from TROPOMI | Steffen Beirle MPI |
P3.26 | Quantifying NOx emissions with TROPOMI satellite observations of 100+ ship NO2plumes | Folkert
Boersma KNMI and WUR |
P3.27 | GLORIA observations of polluted air masses in the 2023 Asian summer monsoon outflow and in connection with wildfires in North America | Wolfgang Woiwode IMK-ASF |
P3.28 | Exploring the Roman NO2 field spatio-temporal patterns with the AOTF-based NO2 camera, and the BAQUNIN supersite | Emmanuel Dekemper BIRA-IASB |
P3.29 | Air Quality studies and satellite validations using MAX-DOAS measurements in Italy | Andrè Achilli CNR |
P3.30 | NitroNet - A deep-learning NO₂ profile retrieval prototype for the TROPOMI satellite instrument | Leon Kuhn MPI |
P3.31 | Climate change variation and mitigation in South Asia: The impact of satellite remote sensing. | Muhammad Umar Aslam University of The Punjab Lahore |
P4 Aerosols & Surface | ||
P4.1 | Long-Term Variability of Aerosol Concentrations and Optical Properties over the Indo-Gangetic Plain in South Asia | Muhammad Zeeshaan ShahidUniversity of the Punjab |
P4.2 | Investigating the Aerosol Index over Asia from GEO and LEO space-born instruments | Panagiotis Fountoukidis Aristotle University of Thessaloniki |
P4.3 | Validation of Aerosol Layer Height product from space-borne instruments using ACTRIS' active sensors | Alexandru Dandocsi INOE |
P4.4 | Evaluating Global Trends in UV-Absorbing Aerosol Presence using TROPOMI and OMI Aerosol Index datasets | Deborah Stein Zweers KNMI |
P4.5 | Cloud detection using machine learning techniques with application to IASI measurements | Chiara Zugarini CNR |
P4.6 | EarthCARE validation measurements from Italian observatories at two central Mediterranean sites | Luca Baldini CNR |
P4.7 | Analysis of Dust Aerosols in the PMAp Satellite Climate Data Record | Dominika
Leskow-Czyzewska EUMETSAT |
P4.8 | A Climate Data Record of Stratospheric Aerosols | Viktoria Sofieva FMI |
P4.9 | Sixteen years surface temperature measurements from IASI | Valentine Jacquet LATMOS, CNRS |
P4.10 | Laboratory investigations of the spectral optical properties of dust aerosols across the infrared in support of the forthcoming FORUM mission | Claudia Di Biagio LISA, CNRS |
P4.11 | Surface classification and property retrievals from GLORIA observations | Tiziano Maestri University of Bologna |
P4.12 | A near-global multiyear climate data record of the submicrometer-mode and supermicrometer-mode components of atmospheric pure-dust. | Emmanouil Proestakis National Observatory Of Athens (NOA) |
P4.13 | Retrieval Black Carbon Aerosol Surface Concentration Using MODIS Data in Italy | Xingxing Jiang China University of Mining and Technology |
P4.14 | A satellite view on wildfire plume aerosols in northern high latitudes in 2023 | Kerstin Stebel NILU |
P4.15 | Enhancing Aerosol Species Discrimination with a Synergistic Approach of AOS Lidarand Polarimeter spaceborne measurements | Abou Bakr Merdji Interuniversity Laboratory Of Atmospheric Systems - National Center Of Scientific Researchs |
P4.16 | Joint Aerosol & Wind Data Assimilation of AEOLUS and preparing for EarthCARE | Thanasis Georgiou NOA |
P4.17 | Offline Optical Post-Processor (OOPP) based on the IFS model for computation of the
optical properties of the atmosphere | Janot Tokaya
TNO |
P.5 Ozone | ||
P5.1 | ALTIUS Ozone Retrieval Algorithm in Stellar Occultation Mode Validated using GOMOS Observations | Antonin Berthelot BIRA-IASB |
P5.2 | ALTIUS Ozone Retrieval Algorithm in Solar Occultation Mode Validated using SAGE III Observations | Kristof Rose BIRA-IASB |
P5.3 | El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole(IOD) signatures in tropical ozone in the Upper Troposphere Lower Stratosphere (UTLS) | Oindrila Nath BIRA-IASB |
P5.4 | Tropical Tropospheric Ozone observed by European Satellites from ERS-2/GOME(1995) to S5P/TROPOMI (2024) and resulting trends | Klaus-Peter Heue DLR |
P5.5 | Tropical Tropospheric Ozone: Harmonization of GOME-2 and S5P CCD retrievals | Kai-Uwe Eichmann University of Bremen |
P5.6 | ALTIUS Ozone Retrieval Algorithm in Bright Limb Mode Validated using OMPS LPObservations | Sotiris Sotiriadis BIRA-IASB |
P5.7 | Study of stratospheric intrusion of ozone-rich air in the troposphere exploiting the synergy between limb and nadir measurements | Liliana Guidetti CNR |
P5.8 | Geophysical Validation Plan for ALTIUS Ozone Profile Data | Jean-Christopher Lambert BIRA-IASB |
P5.9 | Inter-comparison of tropospheric ozone columns from limb-nadir matched datasets and their trends | Carlo Arosio University of Bremen |
P6 Clouds & Water Vapour | ||
P6.1 | Retrieval of clouds geometrical extension from GLORIA-B limb measurements | Martina Taddia University of Bologna, CNR |
P6.2 | Evaluation of the Precipitation space-time variability for EarthCARE validation purposein the sites of Rome and Lampedusa | Luca Baldini CNR |
P6.3 | Progress in improving SY_2_AOD product quality | Larisa Sogacheva FMI |
P6.4 | Determination of the temperature dependende of the refractive index of ice in the FIR | Cecilia Taverna Synchrotron Soleil |
P6.5 | Developments on the Cloud retrieval algorithm using the O₂–O₂ absorption at 477 nm | Maarten Sneep KNMI |
P6.6 | Harmonized OMI and TROPOMI cloud datasets using the O2-O2 absorption band at 477nm | Huan Yu BIRA-IASB |
P6.7 | Impact of the new SEVIRI cloud masking method on radiative flux estimates | Dora Hegedus RAL SPACE, STFC |
P6.8 | Fast Computations of Upwelling Far- and Mid-Infrared Radiances in the Presence of Clouds: the MAMA algorithm | Michele Martinazzo University of Bologna |
P6.9 | Observation of type-discriminated aerosol vertical distributions with multiwavelength lidars of the future Atmosphere Observing System (AOS) mission | Fazzal Qayyum University of Paris Est Creteil, Université Paris Cité, CNRS, LISA |
P6.10 | Overview of the EarthCARE Cloud, Aerosol and Radiation science products. | Gerd-jan Van Zadelhoff KNMI |
P6.11 | Aerosol and cloud retrievals: ATLID and ALADIN | David Donovan KNMI |
P6.12 | Benefits of initializing equatorial waves on accuracy of extratropical forecasts | Chen WangUniversität Hamburg |
P7 Dynamics | ||
P7.1 | A method proposal for spatially-resolved Age of Air from satellite data | Florian VoetResearch Center Jülich |
P7.2 | Towards the assimilation of MTG-IRS and all-sky microwave radiances in the convection-permitting ICON model | Marcello Grenzi University of Bologna |
P7.3 | High-resolution intercomparison of multi-platform precipitation products over Vietnam | Federico Porcu' University of Bologna |
P7.4 | Towards ensemble-based Data Assimilation on a discontinuous Galerkin (DG) sea ice model with solid-like rheology | Francesca Vittorioso University of Bologna |
P7.5 | Gravity wave observations with the EE11-candidate limb imager CAIRT | Sebastian Rhode Forschungszentrum Juelich |
P8 Platforms & Methods | ||
P8.1 | Sentinel-5P products in Terrascope | Jeroen van Gent BIRA-IASB |
P8.2 | ECOMAP - Exploitation of ongoing and future Copernicus Missions for Atmospheric Applications | Ann Mari Fjæraa NILU |
P8.3 | Optimal variables for retrieval products of vertical profile measurements | Simone Ceccherini CNR |
P8.4 | Extension of the Complete Data Fusion algorithm to two-dimensional products | Cecilia Tirelli CNR |
P8.5 | Engeenering the sigma-IASI radiative transfer code | Luca Sgheri IAC - CNR |
P8.6 | The EUMETSAT EPS-SG MWI and MWS day-1 Machine Learning algorithms for snowfall and rainfall surface precipitation rate retrieval | Paolo Sanò CNR |
P8.7 | Copernicus Observations In-Situ (COINS) project and its activities for Copernicus Entrusted Entities | Shridhar Jawak NILU |
P8.8 | Influence of using absolute slant columns for trace gas profile retrievals | Ragi Ambika Rajagopalan Luftblick OG |
P8.9 | Copernicus Polar Roadmap for Service Evolution Report: specific recommendations for atmospheric observations and the Copernicus Atmosphere Monitoring Service (CAMS) | Shridhar Jawak NILU |
P8.10 | Latest developments and upcoming innovations in Py4CAtS - Python for Computational Atmospheric Spectroscopy | Philipp Hochstaffl DLR |
P8.11 | Bayesian de-noising of noisy trace gas satellite images using co-registered trace gas imag-es for improved hot-spot emission estimation | Erik Koene EMPA |
P8.12 | Improvements in accounting for the I0 effect in DOAS retrievals | Janis Pukite MPI for Chemistry |
P8.13 | MC-FORUM: exploiting FORUM observations in meteorological and climate models | Alberto Ortolani CNR |
P8.14 | Development of the Lunar Earth Temperature Observatory (LETO) infrastructure for the Earth-Moon-Mars (EMM) project | Simone Menci CNR |
P8.15 | DIVA: Demonstration of an Integrated approach for the Validation and exploitation of Atmospheric missions | Marcos Herreras-Giralda GRASP-SAS |
P8.16 | FDR4ATMOS: New release of SCIAMACHY Level 1 and Level 2 products | Günter Lichtenberg DLR-IMF |
P8.17 | Latest developments and upcoming innovations in Py4CAtS - Python for Computational Atmospheric Spectroscopy | Philipp Hochstaff DLR |
P8.18 | Impact of Spectroscopy on IASI and FORUM Clear-Sky Simulations | Viviana Volonnino Météo-France, CNRS |
P9 Calibration & Validation | ||
P9.1 | Long-term trends in the TROPOMI L1 radiance signal | Emiel van der Plas KNMI |
P9.2 | Sharp Detector Features Correction for the TROPOMI Instrument | Edward Van Amelrooy KNMI |
P9.3 | Overview of ESA SVANTE campaign activities planned in 2024-2027 for S5p validation | Frederik Tack BIRA-IASB |
P9.4 | On the use of the FRM4DOAS MAXDOAS processing facility for Sentinel-5P NO2 andHCHO validation | GaiaPinardi BIRA-IASB |
P9.5 | The Sentinel-5 Precursor Validation Framework | Matteo Alparone Serco c/o ESA |
P9.6 | Enhancing Satellite Calibration and Validation with ACTRIS Data Centre | Shridhar Jawak NILU |
P9.7 | Comparison of land surface albedo between MODIS and ground-based measures at the Thule High Arctic Atmospheric Observatory (THAAO) in Pituffik, Greenland | Monica Tosco University of Venice Ca' Foscari |
P9.8 | ALTIUS: Call for Announcement of Opportunity for participation in the
calibration/validation | Daniel Navarro Reyes ESA |