The KCDS workshop on Data Processing and Data Assimilation took place on September 11-12, 2024, at KIT Campus South.

The workshop was open to KCDS members, as well as doctoral researchers from KIT and other universities or research centers. We were happy to welcome 21 participants, including KCDS members, and members from various KIT institutes and graduate schools, such as GRACE.

The workshop featured a combination of theoretical and hands-on sessions, along with a poster session and a networking dinner. The theoretical sessions, focusing on data processing and data assimilation, were delivered by Dr. Annika Oertel from the Institute of Meteorology and Climate Research (IMKTRO) and Dr. Vandana Jha from Scientific Computing Center (SCC). During the hands-on coding exercises, participants utilized the JupyterHub for Teaching (Beta) service to perform practical exercises.

In the poster session, several participants presented their own research projects, facilitating engaging discussions and feedback.

We'd like to thank everyone who contributed to and participated in the workshop. Special thanks to the participant who brought a homemade cake on the second workshop day. The sweet surprise made everyone's day!

We look forward to future opportunities for similar events.

Report and photos: Na Luo

Content of the workshop

During data assimilation, observations are optimally combined with a (numerical) model to obtain the best estimate of the system's state taking all observations into account. As observations are often noisy, incomplete and inconsistent, substantial observation pre-processing is required. In this session, we provide insight into various data pre-processing and visualization methods and introduce the concept of data assimilation using the example of numerical weather prediction. The practical exercises based on Jupyter notebooks will illustrate different methods for data processing and data assimilation.

For the hands-on parts, the workshop participants will be able to use the JupyterHub for Teaching (Beta) service.

Practical information

The workshop will run from September 11 - 12 on-site at KIT Campus South in Karlsruhe and include:

• theoretical and hands-on sessions on data processing and data assimilation
• networking opportunities during coffee breaks and a networking dinner
• a poster session, where participants can present their own research projects

Agenda
See the detailed workshop agenda here.

KCDS members as well as doctoral researchers from KIT and other universities/ research centers are welcome to join! There is no participation fee. Please note that KCDS doesn't cover travel and accomodation expenses.

For KCDS members, workshop participation is credited with 1 CP (cutting-edge knowledge category), with an additional 1 CP if you bring a poster. Non-members will receive a confirmation of participation.

The registration for the workshop is closed.

Dr. Annika Oertel, Institute of Meteorology and Climate Research (IMKTRO) at KIT

• BSc in Environmental sciences with minor in Climatology and Meteorology, 10/2010-08/2013, University of Freiburg, Germany
• MSc in Environmental science with major in Atmosphere and Climate, 09/2014-10/2016, ETH Zurich, Switzerland
• PhD in Atmospheric Dynamics, 12/2016-12/2019, ETH Zurich, Switzerland; Subject: ‘Embedded convection in warm conveyor belts’
• 01/2020-04/2020, Postdoctoral researcher, Atmospheric Dynamics group, ETH Zürich
• 05/2020-06/2023, Postdoctoral researcher, Cloud Physics and Large-Scale Dynamics and Predictability groups;  DFG project ‘Waves to Weather’ (phase 2)
• Since 07/2023, Young Investigator Group leader "Mesoscale processes and predictability" (https://www.imk-tro.kit.edu/english/12440.php), KIT Karlsruhe, Germany BMDV project: ‘Increasing the value of campaign observations through data assimilation to advance convective predictability’

Annika's research interests include: Atmospheric dynamics, (convective-scale) numerical weather prediction, mesoscale processes, cloud microphysical sensitivities, physics-dynamics interactions, and scale interactions

Dr. Vandana Jha, Data Exploitation Methods, Scientific Computing Center (SCC) at KIT

• Bachelors of Engineering in Computer Science, 09/1999-08/2003, MDU, India.
• Master of technology in Computer Science, 09/2007-11/2009, Kuvempu University, India.
• PhD in Computer Science and Engineering, 08/2013-06/2018, Bangalore University, India; Subject: ‘Sentiment Analysis in Hindi using Data Mining Techniques’
• Worked as Professor in India.
• Since 02/2022, Postdoctoral researcher in KIT Karlsruhe, Germany, working on DFG project ‘Metaphors of Religion’.

Vandana's research interests include: Data Mining, Sentiment Analysis and Opinion Mining, Machine Learning and Natural Language Processing