Artificial Intelligence for Air Quality

Near-surface temperature forecasting by deep learning

Autores: Gong, Bing; Langguth, Michael; Mozaffari, Amirpasha; Ji, Yianing ; Stadtler, Scarlet; Mache, Karim; Schultz, Martin
Publicado en: ML for Earth System Modelling and Analytics workshop 2021, online, Germany,, 2021
Editor: Forschungszentrum Jülich

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

Autores: Clara Betancourt; Sabine Schröder; Björn Hagemeier; Martin Schultz
Publicado en: EGU2020: Sharing Geoscience Online, EGU2020, online, online conference, 2020-05-04 - 2020-05-08, 2020
Editor: Copernicus
DOI: 10.5194/egusphere-egu2020-13637

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

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

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

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

Global fine resolution mapping of ozone metrics through explainable machine learning

Autores: Clara Betancourt; Scarlet Stadtler; Timo Stomberg; Ann-Kathrin Edrich; Ankit Patnala; Ribana Roscher; Julia Kowalski; Martin G. Schultz
Publicado en: EGU General Assembly 2021, vEGU21, Online, Online, 2021-04-19 - 2021-04-30, 2021
Editor: 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

Autores: Amirpasha Mozaffari; Schröder, Sabine; Apweiler, Sander; Rajveer Saini; Hagemeier, Björn; Schultz, Martin G.
Publicado en: RDA Deutschland Tagung 2020, Berlin, Germany, 2020-02-25 - 2020-02-27, Edición 1, 2020
Editor: Research Data Alliance
DOI: 10.13140/rg.2.2.24046.13123

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

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

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

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

FAIRness in Air Quality and Weather Forecast

Autores: Mozaffari, Amirpasha; Schröder, Sabine; Apweiler, Sander; Saini, Rajveer; Hagemeier, Björn; Schultz, Martin
Publicado en: Research Data Alliance 15th Plenary Meeting, RDA 15, Melbourne, Australia, 2020-03-18 - 2020-03-20, 2020
Editor: Research Data Alliance

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

Autores: Selke, N. Schröder, S. Romberg, M. Ahring, J. Leufen, L. H. Apweiler, S. Schultz, M.
Publicado en: 2021
Editor: FZJ

TOAR-II Data Workshop

Autores: 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.
Publicado en: 2021
Editor: Forschungszentrum Jülich

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

Autores: Gong, Bing; Stadtler, Scarlet; Langguth, Michael; Mozaffari, Amirpasha; Vogelsang, Jan; Schultz, Martin
Publicado en: European Geosciences Union 2020, EGU2020, Virtual, Austria, 2020-05-04 - 2020-05-08, 2020
Editor: Copernicus

Geodata enrichment for air quality

Autores: Selke, Niklas; Leufen, Lukas Hubert; Mozaffari, Amirpasha; Schröder, Sabine; Schultz, Martin
Publicado en: Living Planet Symposium 2022, LPS2022, Bonn, Germany, 2022
Editor: Forschungszentrum Jülich

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

Autores: Gong, Bing; Kleinert, Felix; Schultz, Martin
Publicado en: EGU General Assembly 2019, EGU2019, Vienna, Austria, 2019-04-07 - 2019-04-12, 2019
Editor: Copernicus

Near Surface Ozone Predictions Based on Multiple ANN Architectures

Autores: Kleinert, Felix; Gong, Bing; Götz, Markus; Schultz, Martin
Publicado en: EGU General Assembly 2019, EGU2019, Wien, Austria, 2019-04-07 - 2019-04-12, 2019
Editor: Copernicus

A Web Service Architecture for Objective Station Classification Purposes

Autores: Martin G. Schultz, Sander Apweiler, Jan Vogelsang, Bjorn Hagemeier, Felix Kleinert, Daniel Mallmann
Publicado en: 2018 IEEE 14th International Conference on e-Science (e-Science), 2018, Página(s) 283-284, ISBN 978-1-5386-9156-4
Editor: IEEE
DOI: 10.1109/escience.2018.00051

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

Autores: Gong, Bing; Vogelsang, Jan; Amirpasha Mozaffari; Schultz, Martin
Publicado en: NIC Symposium 2020, Jülich, Germany, 2020-02-27 - 2020-02-28, 2020
Editor: Forschungszentrum Jülich
DOI: 10.13140/rg.2.2.27401.57442

A Novel Concept for Automated Quality Control of Atmospheric Time Series

Autores: Kaffashzadeh, Najmeh; Schröder, Sabine; Schultz, Martin
Publicado en: European Geoscience Union (EGU), Vienna, Austria, 2019-04-07 - 2019-04-12, 2019
Editor: Copernicus

TOAR-II Overview and Database

Autores: Cooper, Owen; Schröder, Sabine; Romberg, Mathilde; Selke, Niklas; Leufen, Lukas Hubert; Ahring, Jessics; Mozaffari, Amirpasha; Schultz, Martin
Publicado en: 2022
Editor: Forschungszentrum Jülich

Tropospheric Ozone Assessment Report (TOAR) Data Infrastructure

Autores: Schröder, Sabine; Epp, Eleonora; Leufen, Lukas Hubert; Mozaffari, Amirpasha; Romberg, Mathilde; Schultz, Martin; Sun, Jianing
Publicado en: WMO Data Conference, Virtual, Virtual, 2020-11-16 - 2020-11-19, 2020
Editor: World Meteorological Organisation

Deep Learning for Weather Forecasting and Climate Prediction

Autores: Martin Schultz
Publicado en: 2022
Editor: aiforgood.itu.int

Advancing FAIRness for global air quality data analyses

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

JUWELS Booster – A Supercomputer for Large-Scale AI Research

Autores: 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
Publicado en: Lecture Notes in Computer Science ISBN: 9783030905385, Edición 1, 2022
Editor: 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

Autores: Lukas Hubert Leufen; Felix Kleinert; Martin G. Schultz
Publicado en: Artificial Intelligence for the Earth Systems, Edición Volume 2, Edición 3, 2023
Editor: American Meteorological Society
DOI: 10.1175/aies-d-22-0085.1

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

Autores: Christian Lessig, Ilaria Luise, Bing Gong, Michael Langguth, Scarlet Stadtler, Martin Schultz
Publicado en: Arxiv, 2023
Editor: 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

Autores: 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*
Publicado en: Environmental Science & Technology, Edición 2021,55,8, 2021, Página(s) 4389-4398
Editor: ACS Publications
DOI: 10.1021/acs.est.0c07742

Multi-decadal surface ozone trends at globally distributed remote locations

Autores: 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
Publicado en: Knowledge Domain: Atmospheric Science, Edición Elementa: Science of the Anthropocene (2020) 8: 23., 2020
Editor: ucpress.edu
DOI: 10.1525/elementa.420

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

Autores: Kai-Lan Chang, Martin G. Schultz, Xin Lan, Audra McClure-Begley, Irina Petropavlovskikh, Xiaobin Xu, Jerald R. Ziemke
Publicado en: Elementa Science of the Anthropocene, Edición (2021) 9 (1): 00035, 2021
Editor: ucpress.edu
DOI: 10.1525/elementa.2021.00035

Advancing caching and automation with FDO

Autores: Amirpasha Mozaffari, Niklas Selke, Martin Schultz
Publicado en: Research Ideas and Outcomes, Edición 8, e94856, 2022
Editor: Pensoft
DOI: 10.3897/rio.8.e94856

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

Autores: Clara Betancourt; Timo Stomberg; Scarlet Stadtler; Ribana Roscher; Martin G. Schultz
Publicado en: Earth System Science Data, 2021, ISSN 1866-3516
Editor: Copernicus
DOI: 10.5194/essd-2020-380

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

Autores: Lukas Hubert Leufen, Felix Kleinert, Martin G. Schultz
Publicado en: Geoscientific Model Development, Edición 14/3, 2021, Página(s) 1553-1574, ISSN 1991-9603
Editor: Copernicus
DOI: 10.5194/gmd-14-1553-2021

Can deep learning beat numerical weather prediction?

Autores: M. G. Schultz, C. Betancourt, B. Gong, F. Kleinert, M. Langguth, L. H. Leufen, A. Mozaffari, S. Stadtler
Publicado en: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Edición 379/2194, 2021, Página(s) 20200097, ISSN 1364-503X
Editor: 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

Autores: Scarlet Stadtler; Ribana Roscher; Clara Betancourt
Publicado en: Machine Learning and Knowledge Extraction; Volume 4; Edición 1; Pages: 150-171, Edición 1, 2022, ISSN 2504-4990
Editor: MDPI
DOI: 10.3390/make4010008

Artificial Intelligence for Air Quality

Autores: Martin Schultz
Publicado en: The Project Repository Journal (PRj), Edición Volume 6, June 2020, 2020, Página(s) 30-32, ISSN 2632-4067
Editor: http://www.europeandissemination.eu/

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

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

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

Autores: Felix Kleinert, Lukas H. Leufen, Martin G. Schultz
Publicado en: Geoscientific Model Development, Edición 14/1, 2021, Página(s) 1-25, ISSN 1991-9603
Editor: Copernicus GmbH
DOI: 10.5194/gmd-14-1-2021

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

Autores: Clara Betancourt, Björn Hagemeier, Sabine Schröder, Martin G. Schultz
Publicado en: Earth Science Informatics, Edición 14/3, 2021, Página(s) 1597-1607, ISSN 1865-0473
Editor: Springer Verlag
DOI: 10.1007/s12145-021-00631-4

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

Autores: Sabine Schröder, Eleonora Epp, Amirpasha Mozaffari, Mathilde Romberg, Niklas Selke, Martin G. Schultz
Publicado en: Data Intelligence, Edición Volume 4, Edición 2, 2022, Página(s) 259 - 270, ISSN 2641-435X
Editor: MIT Press Cambridge
DOI: 10.1162/dint_a_00130

Canonical Workflows to Make Data FAIR

Autores: Peter Wittenburg, Alex Hardisty, Yann Le Franc, Amirpasha Mozaffari, Limor Peer, Nikolay A. Skvortsov, Zhiming Zhao, Alessandro Spinuso
Publicado en: Data Intelligence, Edición Volume 4, Edición 2, 2022, Página(s) 286–305, ISSN 2641-435X
Editor: 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

Autores: Lukas Hubert Leufen, Felix Kleinert, Martin G. Schultz
Publicado en: Environmental Data Science, 2022, ISSN 2634-4602
Editor: 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

Autores: 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
Publicado en: Elementa: Science of the Anthropocene, Edición (2023) 11 (1): 00025, 2023, ISSN 2325-1026
Editor: University of California Press
DOI: 10.1525/elementa.2022.00025

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

Autores: Peter Wittenburg, Alex Hardisty, Amirpasha Mozzafari, Limor Peer, Nikolay Skvortsov, Alessandro Spinuso, Zhiming Zhao
Publicado en: Data Intelligence, Edición Volume 4, Edición 2, 2022, Página(s) 149–154, ISSN 2641-435X
Editor: MIT Press Cambridge
DOI: 10.1162/dint_e_00122

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

Autores: Clara Betancourt, Timo T. Stomberg, Ann-Kathrin Edrich, Ankit Patnala, Martin G. Schultz, Ribana Roscher, Julia Kowalski, and Scarlet Stadtler
Publicado en: Geoscientific Model Development, Edición Volume 15, Edición 11, 2022, Página(s) 4331-4354, ISSN 1991-9603
Editor: Copernicus Publications
DOI: 10.5194/gmd-15-4331-2022

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

Autores: 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
Publicado en: Elementa Science of the Anthropocene, Edición 5, 2017, Página(s) 58, ISSN 2325-1026
Editor: BioOne
DOI: 10.1525/elementa.244

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

Autores: Ankit Patnala; Scarlet Stadtler; Martin G. Schultz; Juergen Gall
Publicado en: IEEE Geoscience and Remote Sensing Letters, Edición Volume 20, 2023, ISSN 1558-0571
Editor: IEEE journal
DOI: 10.1109/lgrs.2023.3274493

Temperature forecasting by deep learning methods

Autores: Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz
Publicado en: Geoscientific Model Development, Edición Volume 15, Edición 23, 2022, Página(s) 8931–8956, ISSN 1991-9603
Editor: Copernicus
DOI: 10.5194/gmd-15-8931-2022

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

Autores: Amirpasha Mozaffari, Michael Langguth, Bing Gong, Jessica Ahring, Adrian Rojas Campos, Pascal Nieters, Otoniel José Campos Escobar, Martin Wittenbrink, Peter Baumann, Martin G. Schultz
Publicado en: Data Intelligence, Edición Volume 4, Edición 2, 2022, Página(s) 271-285, ISSN 2641-435X
Editor: 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

Autores: Felix Kleinert, Lukas H. Leufen, Aurelia Lupascu, Tim Butler, and Martin G. Schultz
Publicado en: Geoscientific Model Development, Edición Volume 15, Edición 23, 2022, Página(s) 8913–8930, ISSN 1991-9603
Editor: 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

Autores: Najmeh Kaffashzadeh, Felix Kleinert, Martin G. Schultz
Publicado en: Business Information Systems Workshops - BIS 2019 International Workshops, Seville, Spain, June 26–28, 2019, Revised Papers, Edición 373, 2019, Página(s) 513-518, ISBN 978-3-030-36690-2
Editor: Springer International Publishing
DOI: 10.1007/978-3-030-36691-9_43

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