Navigation and service


04 May 2020 AutoQA4Env has been presented by Najmeh Kaffashzadeh in the virtual EGU conference session on atmospheric composition variability and trends. Many scientific and statistical efforts are devoted to developing advanced analytic tools or methods, but a better quantification of trend and uncertainty cannot be achieved without proper data quality control (QC). Automated QC tools are needed to allow better use of existing data, for example in the machine learning applications of the IntelliAQ project. The presentation discusses the challenges involved and presents a methodology for automated QC and its integration into the workflow used for the TOAR-database.

26 February 2020 Bing Gong attended the Eumetnet workshop on “AI for weather and climate studies” held at Royal Meteorological Institute of Belgium. In the two-day workshop, 20 presentations were given on the existing or exploring potential weather and climate application of AI. Bing Gong gave a presentation on “Parallel deep learning workflow for short-term temperature forecasts with video frame prediction methods”.

05 September 2019 Martin Schultz and Lukas Leufen attended a workshop on "Machine Learning in weather and climate modelling" at Corpus Christi college in Oxford. This workshop assembled more than 100 top-notch climate scientists and experts in HPC computer science and machine learning to present ongoing work and discuss the way forward. It became clear from the start that machine learning can likely play an important role in almost all stages of a weather and climate modelling workflow. Much discussed topics were the perceived need to impose physical constraints on the machine learning algorithms and quantify uncertainties. Martin Schultz's presentation on the IntelliAQ and DeepRain projects was well received and the positive response confirmed the research strategy followed by these projects.

10 May 2019 A first alpha version of the auto-qc tool has been released to the Helmholtz Digital Earth community for testing and further developments.

17 April 2019 Severin Hußmann ran the first movie frame prediction tests using the Lotter et al. (2016) neural network architecture on the JSC supercomputer JURECA.

11 April 2019 The auto-qc tool was presented at the European Geoscience Union conference in Vienna. Najmeh Kaffashzadeh presented a poster in session AS3.20 - Atmospheric gases and particles: metrology, quality control and measurement comparability.

9 April 2019 Bing Gong gave her presentation on “Prediction of daily maximum ozone threshold exceedances by artificial intelligence techniques in Germany” and Felix Kleinert presented “Near Surface Ozone Predictions Based on Multiple Artificial Neural Network Architectures” in the session on Big data and machine learning in geosciences at the European Geosciences Union General Assembly in Vienna, Austria.

02 April 2019 Martin Schultz and Severin Hußmann implemented a parallel workflow for extracting arbitrary fields from large numerical weather model data files for use in machine learning applications. This workflow uses the JUBE tool developed at JSC for benchmarking purposes.

19 March 2019 At the Computational and Data Science (CaDS) Seminar, JSC, on Tuesday, 19th Mar 2019, Bing Gong gave a presentation about the preliminary results of her latest research on using the synthetic minority oversampling technique (SMOTE) to improve ozone threshold exceedances prediction with various machine learning techniques.

01 March 2019 Felix Kleinert and Bing Gong obtained the first test results with deep neural networks on the experimental zam347 system.

27 February 2019 The auto-qc tool was presented at the "Workshop on observation data QA/QC" organized in the context of the Helmholtz Digital Earth initiative by FZ Jülich from February 25-27 2019 at the Jülich Supercomputing Center. The project developer Najmeh Kaffashzadeh gave an oral presentation about the tool and led a hands-on training session at this workshop.

20 February 2019 Abstract “Near Surface Ozone Predictions Based on Multiple Artificial Neural Network Architectures” by Felix Kleinert is accepted at EGU as oral presentation on Monday, 8th of April 2019.

12 February 2019 Lukas Leufen and Jessica Ahring successfully imported sample high-resolution topographic data from the 90 m TanDEM-X data product into the Rasdaman data base at JSC, which will be used to store and retrieve geophysical data for the IntelliAQ project.

10 December 2018 A novel concept for automated quality control of the global air quality data from the Tropospheric Ozone Assessment Report (TOAR) database has been proposed. The approach seeks to quantify the quality of individual measurements after applying a set of statistical tests that are in use in several environmental agencies such as EPA. To prove the concept, we have started to develop a software package (auto-qc) for double-checking the quality of the multi-annual hourly ozone time series from the TOAR database.

01 October 2018 IntelliAQ started