Skip to main content
European Commission logo
polski polski
CORDIS - Wyniki badań wspieranych przez UE
CORDIS
CORDIS Web 30th anniversary CORDIS Web 30th anniversary

Artificial Intelligence for Air Quality

Rezultaty

Data Management Plan (DMP)

A document describing the data management strategy with respect to Open data provision

Publikacje

Near-surface temperature forecasting by deep learning

Autorzy: Gong, Bing; Langguth, Michael; Mozaffari, Amirpasha; Ji, Yianing ; Stadtler, Scarlet; Mache, Karim; Schultz, Martin
Opublikowane w: ML for Earth System Modelling and Analytics workshop 2021, online, Germany,, 2021
Wydawca: Forschungszentrum Jülich

Performance analysis and optimization of a TByte-scale atmospheric observation database

Autorzy: Clara Betancourt; Sabine Schröder; Björn Hagemeier; Martin Schultz
Opublikowane w: EGU2020: Sharing Geoscience Online, EGU2020, online, online conference, 2020-05-04 - 2020-05-08, 2020
Wydawca: Copernicus
DOI: 10.5194/egusphere-egu2020-13637

A Statistical Model for Automated Quality Assessment of the TOAR-II

Autorzy: Najmeh Kaffashzadeh; Kai-Lan Chang; Sabine Schröder; Martin G. Schultz
Opublikowane w: "EGU2020: Sharing Geoscience Online, #shareEGU20, Vienna, Austria, 2020-05-04 - 2020-05-08", 2020
Wydawca: Copernicus
DOI: 10.5194/egusphere-egu2020-13357

TOAR-II data portal for global measurements of ozone and its precursors

Autorzy: Schröder, Sabine; Mozaffari, Amirpasha; Romberg, Mathilde; Selke, Niklas; Leufen, Lukas Hubert; Ahring, Jessica; Schultz, Martin
Opublikowane w: CEOS Atmospheric Composition Virtual Constellation AC-VC-18, virtual, Belgium, 2022
Wydawca: Forschungszentrum Jülich

Global fine resolution mapping of ozone metrics through explainable machine learning

Autorzy: Clara Betancourt; Scarlet Stadtler; Timo Stomberg; Ann-Kathrin Edrich; Ankit Patnala; Ribana Roscher; Julia Kowalski; Martin G. Schultz
Opublikowane w: EGU General Assembly 2021, vEGU21, Online, Online, 2021-04-19 - 2021-04-30, 2021
Wydawca: Copernicus
DOI: 10.13140/rg.2.2.17134.13123

FAIRness in the multi-service data infrastructure of the Tropospheric Ozone Assessment Report (TOAR) and Artificial Intelligence for Air Quality (IntelliAQ) project

Autorzy: Amirpasha Mozaffari; Schröder, Sabine; Apweiler, Sander; Rajveer Saini; Hagemeier, Björn; Schultz, Martin G.
Opublikowane w: RDA Deutschland Tagung 2020, Berlin, Germany, 2020-02-25 - 2020-02-27, Numer 1, 2020
Wydawca: Research Data Alliance
DOI: 10.13140/rg.2.2.24046.13123

Enhancing FAIRness of global air quality data: The Tropospheric Ozone Assessment Report database

Autorzy: Schröder, Sabine. Apweiler, Sander. Saini, Rajveer. Hagemeier, Björn. Schultz, Martin. G.
Opublikowane w: Enhancing FAIRness of global air quality data: The Tropospheric Ozone Assessment Report database, 2019
Wydawca: Zenodo
DOI: 10.5281/zenodo.3549626

Automatic quality control and quality control schema in the Observation to Archive

Autorzy: Silva, Brenner; Kaffashzadeh, Najmeh; Nixdorf, Erik; Immoor, Sebastian; Fischer, Philipp; Anselm, Norbert; Gerchow, Peter; Schäfer, Angela; Koppe, Roland
Opublikowane w: "EGU2020: Sharing Geoscience Online, #shareEGU20, Vienna, Austria, 2020-05-04 - 2020-05-08", Numer 1, 2021
Wydawca: Copernicus
DOI: 10.5194/egusphere-egu2020-15961

FAIRness in Air Quality and Weather Forecast

Autorzy: Mozaffari, Amirpasha; Schröder, Sabine; Apweiler, Sander; Saini, Rajveer; Hagemeier, Björn; Schultz, Martin
Opublikowane w: Research Data Alliance 15th Plenary Meeting, RDA 15, Melbourne, Australia, 2020-03-18 - 2020-03-20, 2020
Wydawca: Research Data Alliance

The TOAR database: metadata harmonization and data quality assurance on global air quality data

Autorzy: Selke, N. Schröder, S. Romberg, M. Ahring, J. Leufen, L. H. Apweiler, S. Schultz, M.
Opublikowane w: 2021
Wydawca: FZJ

TOAR-II Data Workshop

Autorzy: Schultz, Martin. Schröder, Sabine. Selke, Niklas. Epp, Eleonora. Romberg, Mathilde. Sun, Janing. Ahring, Jessica. Mozaffari, Amirphasha. Lensing, Max. Betancourt, Clara. Leufen, Lukas. Hubert. Hagemeier, Björn. Saini, Rajvee.
Opublikowane w: 2021
Wydawca: Forschungszentrum Jülich

Deep learning for short-term temperature forecasts with video prediction methods

Autorzy: Gong, Bing; Stadtler, Scarlet; Langguth, Michael; Mozaffari, Amirpasha; Vogelsang, Jan; Schultz, Martin
Opublikowane w: European Geosciences Union 2020, EGU2020, Virtual, Austria, 2020-05-04 - 2020-05-08, 2020
Wydawca: Copernicus

Geodata enrichment for air quality

Autorzy: Selke, Niklas; Leufen, Lukas Hubert; Mozaffari, Amirpasha; Schröder, Sabine; Schultz, Martin
Opublikowane w: Living Planet Symposium 2022, LPS2022, Bonn, Germany, 2022
Wydawca: Forschungszentrum Jülich

Prediction of Daily Maximum Ozone Threshold Exceedances by Artificial Intelligence Techniques in Germany

Autorzy: Gong, Bing; Kleinert, Felix; Schultz, Martin
Opublikowane w: EGU General Assembly 2019, EGU2019, Vienna, Austria, 2019-04-07 - 2019-04-12, 2019
Wydawca: Copernicus

Near Surface Ozone Predictions Based on Multiple ANN Architectures

Autorzy: Kleinert, Felix; Gong, Bing; Götz, Markus; Schultz, Martin
Opublikowane w: EGU General Assembly 2019, EGU2019, Wien, Austria, 2019-04-07 - 2019-04-12, 2019
Wydawca: Copernicus

A Web Service Architecture for Objective Station Classification Purposes

Autorzy: Martin G. Schultz, Sander Apweiler, Jan Vogelsang, Bjorn Hagemeier, Felix Kleinert, Daniel Mallmann
Opublikowane w: 2018 IEEE 14th International Conference on e-Science (e-Science), 2018, Strona(/y) 283-284, ISBN 978-1-5386-9156-4
Wydawca: IEEE
DOI: 10.1109/escience.2018.00051

On the use of containers for machine learning and visualization workflows on JUWELS

Autorzy: Gong, Bing; Vogelsang, Jan; Amirpasha Mozaffari; Schultz, Martin
Opublikowane w: NIC Symposium 2020, Jülich, Germany, 2020-02-27 - 2020-02-28, 2020
Wydawca: Forschungszentrum Jülich
DOI: 10.13140/rg.2.2.27401.57442

A Novel Concept for Automated Quality Control of Atmospheric Time Series

Autorzy: Kaffashzadeh, Najmeh; Schröder, Sabine; Schultz, Martin
Opublikowane w: European Geoscience Union (EGU), Vienna, Austria, 2019-04-07 - 2019-04-12, 2019
Wydawca: Copernicus

TOAR-II Overview and Database

Autorzy: Cooper, Owen; Schröder, Sabine; Romberg, Mathilde; Selke, Niklas; Leufen, Lukas Hubert; Ahring, Jessics; Mozaffari, Amirpasha; Schultz, Martin
Opublikowane w: 2022
Wydawca: Forschungszentrum Jülich

Tropospheric Ozone Assessment Report (TOAR) Data Infrastructure

Autorzy: Schröder, Sabine; Epp, Eleonora; Leufen, Lukas Hubert; Mozaffari, Amirpasha; Romberg, Mathilde; Schultz, Martin; Sun, Jianing
Opublikowane w: WMO Data Conference, Virtual, Virtual, 2020-11-16 - 2020-11-19, 2020
Wydawca: World Meteorological Organisation

Deep Learning for Weather Forecasting and Climate Prediction

Autorzy: Martin Schultz
Opublikowane w: 2022
Wydawca: aiforgood.itu.int

Advancing FAIRness for global air quality data analyses

Autorzy: Mozaffari, Amirpasha; Schröder, Sabine ; Romberg, Mathilde ; Epp, Eleonora ; Ahring, Jessica Betancourt, Clara ; Leufen, Lukas Hubert; Kleinert, Felix ; Schultz, Martin
Opublikowane w: International Data Week 2022, IDW2022, Seoul, South Korea, 2022
Wydawca: Forschungszentrum Jülich

JUWELS Booster – A Supercomputer for Large-Scale AI Research

Autorzy: Kesselheim, Stefan; Herten, Andreas; Cavallaro, Gabriele; Sedona, Rocco; Schug, Alexander; Strube, Alexandre; Kamath, Roshni; Schultz, Martin G.; Riedel, Morris; Lippert, Thomas; Krajsek, Kai; Ebert, Jan; Jitsev, Jenia; Cherti, Mehdi; Langguth, Michael; Gong, Bing; Stadtler, Scarlet; Mozaffari, Amirpasha
Opublikowane w: Lecture Notes in Computer Science ISBN: 9783030905385, Numer 1, 2022
Wydawca: Arxiv-Preprints
DOI: 10.1007/978-3-030-90539-2_31

O3ResNet: A Deep Learning–Based Forecast System to Predict Local Ground-Level Daily Maximum 8-Hour Average Ozone in Rural and Suburban Environments

Autorzy: Lukas Hubert Leufen; Felix Kleinert; Martin G. Schultz
Opublikowane w: Artificial Intelligence for the Earth Systems, Numer Volume 2, Numer 3, 2023
Wydawca: American Meteorological Society
DOI: 10.1175/aies-d-22-0085.1

AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning

Autorzy: Christian Lessig, Ilaria Luise, Bing Gong, Michael Langguth, Scarlet Stadtler, Martin Schultz
Opublikowane w: Arxiv, 2023
Wydawca: Cornell University
DOI: 10.48550/arxiv.2308.13280

Mapping Yearly Fine Resolution Global Surface Ozone through the Bayesian Maximum Entropy Data Fusion of Observations and Model Output for 1990–2017

Autorzy: Marissa N. DeLang, Jacob S. Becker, Kai-Lan Chang, Marc L. Serre, Owen R. Cooper, Martin G. Schultz, Sabine Schröder, Xiao Lu, Lin Zhang, Makoto Deushi, Beatrice Josse, Christoph A. Keller, Jean-François Lamarque, Meiyun Lin, Junhua Liu, Virginie Marécal, Sarah A. Strode, Kengo Sudo, Simone Tilmes, Li Zhang, Stephanie E. Cleland, Elyssa L. Collins, Michael Brauer, and J. Jason West*
Opublikowane w: Environmental Science & Technology, Numer 2021,55,8, 2021, Strona(/y) 4389-4398
Wydawca: ACS Publications
DOI: 10.1021/acs.est.0c07742

Multi-decadal surface ozone trends at globally distributed remote locations

Autorzy: Owen R. Cooper, Martin G. Schultz, Sabine Schröder, Kai-Lan Chang, Audrey Gaudel, Gerardo Carbajal Benítez, Emilio Cuevas, Marina Fröhlich, Ian E. Galbally, Suzie Molloy, Dagmar Kubistin, Xiao Lu, Audra McClure-Begley, Philippe Nédélec, Jason O’Brien, Samuel J. Oltmans, Irina Petropavlovskikh, Ludwig Ries, Irina Senik, Karin Sjöberg, Sverre Solberg, Gerard T. Spain, Wolfgang Spangl, Martin
Opublikowane w: Knowledge Domain: Atmospheric Science, Numer Elementa: Science of the Anthropocene (2020) 8: 23., 2020
Wydawca: ucpress.edu
DOI: 10.1525/elementa.420

Trend detection of atmospheric time series: Incorporating appropriate uncertainty estimates and handling extreme events

Autorzy: Kai-Lan Chang, Martin G. Schultz, Xin Lan, Audra McClure-Begley, Irina Petropavlovskikh, Xiaobin Xu, Jerald R. Ziemke
Opublikowane w: Elementa Science of the Anthropocene, Numer (2021) 9 (1): 00035, 2021
Wydawca: ucpress.edu
DOI: 10.1525/elementa.2021.00035

Advancing caching and automation with FDO

Autorzy: Amirpasha Mozaffari, Niklas Selke, Martin Schultz
Opublikowane w: Research Ideas and Outcomes, Numer 8, e94856, 2022
Wydawca: Pensoft
DOI: 10.3897/rio.8.e94856

AQ-Bench: A Benchmark Dataset for Machine Learning on GlobalAir Quality Metrics

Autorzy: Clara Betancourt; Timo Stomberg; Scarlet Stadtler; Ribana Roscher; Martin G. Schultz
Opublikowane w: Earth System Science Data, 2021, ISSN 1866-3516
Wydawca: Copernicus
DOI: 10.5194/essd-2020-380

MLAir (v1.0) – a tool to enable fast and flexible machine learning on air data time series

Autorzy: Lukas Hubert Leufen, Felix Kleinert, Martin G. Schultz
Opublikowane w: Geoscientific Model Development, Numer 14/3, 2021, Strona(/y) 1553-1574, ISSN 1991-9603
Wydawca: Copernicus
DOI: 10.5194/gmd-14-1553-2021

Can deep learning beat numerical weather prediction?

Autorzy: M. G. Schultz, C. Betancourt, B. Gong, F. Kleinert, M. Langguth, L. H. Leufen, A. Mozaffari, S. Stadtler
Opublikowane w: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Numer 379/2194, 2021, Strona(/y) 20200097, ISSN 1364-503X
Wydawca: Royal Society of London
DOI: 10.1098/rsta.2020.0097

Explainable Machine Learning Reveals Capabilities, Redundancy, and Limitations of a Geospatial Air Quality Benchmark Dataset

Autorzy: Scarlet Stadtler; Ribana Roscher; Clara Betancourt
Opublikowane w: Machine Learning and Knowledge Extraction; Volume 4; Numer 1; Pages: 150-171, Numer 1, 2022, ISSN 2504-4990
Wydawca: MDPI
DOI: 10.3390/make4010008

Artificial Intelligence for Air Quality

Autorzy: Martin Schultz
Opublikowane w: The Project Repository Journal (PRj), Numer Volume 6, June 2020, 2020, Strona(/y) 30-32, ISSN 2632-4067
Wydawca: http://www.europeandissemination.eu/

IntelliO3-ts v1.0: A neural network approach to predict near-surface ozone concentrations in Germany

Autorzy: Lukas Hubert Leufen; Martin Schultz; Felix Kleinert
Opublikowane w: Geoscientific model development 14(1), 1 - 25 (2021). doi:10.5194/gmd-14-1-2021, 2021, ISSN 1991-9603
Wydawca: Copernicus
DOI: 10.5194/gmd-2020-169

IntelliO3-ts v1.0: a neural network approach to predict near-surface ozone concentrations in Germany

Autorzy: Felix Kleinert, Lukas H. Leufen, Martin G. Schultz
Opublikowane w: Geoscientific Model Development, Numer 14/1, 2021, Strona(/y) 1-25, ISSN 1991-9603
Wydawca: Copernicus GmbH
DOI: 10.5194/gmd-14-1-2021

Context aware benchmarking and tuning of a TByte-scale air quality database and web service

Autorzy: Clara Betancourt, Björn Hagemeier, Sabine Schröder, Martin G. Schultz
Opublikowane w: Earth Science Informatics, Numer 14/3, 2021, Strona(/y) 1597-1607, ISSN 1865-0473
Wydawca: Springer Verlag
DOI: 10.1007/s12145-021-00631-4

Enabling Canonical Analysis Workflows Documented Data Harmonization on Global Air Quality Data

Autorzy: Sabine Schröder, Eleonora Epp, Amirpasha Mozaffari, Mathilde Romberg, Niklas Selke, Martin G. Schultz
Opublikowane w: Data Intelligence, Numer Volume 4, Numer 2, 2022, Strona(/y) 259 - 270, ISSN 2641-435X
Wydawca: MIT Press Cambridge
DOI: 10.1162/dint_a_00130

Canonical Workflows to Make Data FAIR

Autorzy: Peter Wittenburg, Alex Hardisty, Yann Le Franc, Amirpasha Mozaffari, Limor Peer, Nikolay A. Skvortsov, Zhiming Zhao, Alessandro Spinuso
Opublikowane w: Data Intelligence, Numer Volume 4, Numer 2, 2022, Strona(/y) 286–305, ISSN 2641-435X
Wydawca: MIT Press Cambridge
DOI: 10.1162/dint_a_00132

Exploring decomposition of temporal patterns to facilitate learning of neural networks for ground-level daily maximum 8-hour average ozone prediction

Autorzy: Lukas Hubert Leufen, Felix Kleinert, Martin G. Schultz
Opublikowane w: Environmental Data Science, 2022, ISSN 2634-4602
Wydawca: Cambridge University Press
DOI: 10.1017/eds.2022.9

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy data fusion to map global surface ozone concentration

Autorzy: Jacob S. Becker, Marissa N. DeLang, Kai-Lan Chang, Marc L. Serre, Owen R. Cooper, Hantao Wang, Martin G. Schultz, Sabine Schröder, Xiao Lu, Lin Zhang, Makoto Deushi, Beatrice Josse, Christoph A. Keller, Jean-François Lamarque, Meiyun Lin, Junhua Liu, Virginie Marécal, Sarah A. Strode, Kengo Sudo, Simone Tilmes, Li Zhang, Michael Brauer, J. Jason West
Opublikowane w: Elementa: Science of the Anthropocene, Numer (2023) 11 (1): 00025, 2023, ISSN 2325-1026
Wydawca: University of California Press
DOI: 10.1525/elementa.2022.00025

Editors’ Note: Special Issue on Canonical Workflow Frameworks for Research

Autorzy: Peter Wittenburg, Alex Hardisty, Amirpasha Mozzafari, Limor Peer, Nikolay Skvortsov, Alessandro Spinuso, Zhiming Zhao
Opublikowane w: Data Intelligence, Numer Volume 4, Numer 2, 2022, Strona(/y) 149–154, ISSN 2641-435X
Wydawca: MIT Press Cambridge
DOI: 10.1162/dint_e_00122

Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties

Autorzy: Clara Betancourt, Timo T. Stomberg, Ann-Kathrin Edrich, Ankit Patnala, Martin G. Schultz, Ribana Roscher, Julia Kowalski, and Scarlet Stadtler
Opublikowane w: Geoscientific Model Development, Numer Volume 15, Numer 11, 2022, Strona(/y) 4331-4354, ISSN 1991-9603
Wydawca: Copernicus Publications
DOI: 10.5194/gmd-15-4331-2022

Tropospheric Ozone Assessment Report: Database and metrics data of global surface ozone observations

Autorzy: Martin G. Schultz, Sabine Schröder, Olga Lyapina, Owen R. Cooper, Ian Galbally, Irina Petropavlovskikh, Erika von Schneidemesser, Hiroshi Tanimoto, Yasin Elshorbany, Manish Naja, Rodrigo J. Seguel, Ute Dauert, Paul Eckhardt, Stefan Feigenspan, Markus Fiebig, Anne-Gunn Hjellbrekke, You-Deog Hong, Peter Christian Kjeld, Hiroshi Koide, Gary Lear, David Tarasick, Mikio Ueno, Markus Wallasch, Darrel B
Opublikowane w: Elementa Science of the Anthropocene, Numer 5, 2017, Strona(/y) 58, ISSN 2325-1026
Wydawca: BioOne
DOI: 10.1525/elementa.244

Generating Views Using Atmospheric Correction for Contrastive Self-Supervised Learning of Multispectral Images

Autorzy: Ankit Patnala; Scarlet Stadtler; Martin G. Schultz; Juergen Gall
Opublikowane w: IEEE Geoscience and Remote Sensing Letters, Numer Volume 20, 2023, ISSN 1558-0571
Wydawca: IEEE journal
DOI: 10.1109/lgrs.2023.3274493

Temperature forecasting by deep learning methods

Autorzy: Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz
Opublikowane w: Geoscientific Model Development, Numer Volume 15, Numer 23, 2022, Strona(/y) 8931–8956, ISSN 1991-9603
Wydawca: Copernicus
DOI: 10.5194/gmd-15-8931-2022

HPC-oriented Canonical Workflows for Machine Learning Applications in Climate and Weather Prediction

Autorzy: Amirpasha Mozaffari, Michael Langguth, Bing Gong, Jessica Ahring, Adrian Rojas Campos, Pascal Nieters, Otoniel José Campos Escobar, Martin Wittenbrink, Peter Baumann, Martin G. Schultz
Opublikowane w: Data Intelligence, Numer Volume 4, Numer 2, 2022, Strona(/y) 271-285, ISSN 2641-435X
Wydawca: MIT Press Cambridge
DOI: 10.1162/dint_a_00131

Representing chemical history in ozone time-series predictions – a model experiment study building on the MLAir (v1.5) deep learning framework

Autorzy: Felix Kleinert, Lukas H. Leufen, Aurelia Lupascu, Tim Butler, and Martin G. Schultz
Opublikowane w: Geoscientific Model Development, Numer Volume 15, Numer 23, 2022, Strona(/y) 8913–8930, ISSN 1991-9603
Wydawca: Copernicus Publications
DOI: 10.5194/gmd-15-8913-2022

A New Tool for Automated Quality Control of Environmental Time Series (AutoQC4Env) in Open Web Services

Autorzy: Najmeh Kaffashzadeh, Felix Kleinert, Martin G. Schultz
Opublikowane w: Business Information Systems Workshops - BIS 2019 International Workshops, Seville, Spain, June 26–28, 2019, Revised Papers, Numer 373, 2019, Strona(/y) 513-518, ISBN 978-3-030-36690-2
Wydawca: Springer International Publishing
DOI: 10.1007/978-3-030-36691-9_43

Prawa własności intelektualnej

MLAir (v1.0.0) - a tool to enable fast and flexible machine learning on air data time series - Source Code

Numer wniosku/publikacji: https://doi.org/10.34730/5a6c3533512541a79c5c41061 B2SHARE
Data: 2021-02-11

AQ-Bench

Numer wniosku/publikacji: http://doi.org/10.23728/b2share.30d42b5a87344e8285 B2SHARE
Data: 2020-11-05

IntelliO3-ts (v1.0): Source code and data

Numer wniosku/publikacji: http://doi.org/10.23728/b2share.5042cda41a4c49769c B2SHARE
Data: 2020-11-13

Wyszukiwanie danych OpenAIRE...

Podczas wyszukiwania danych OpenAIRE wystąpił błąd

Brak wyników