Research area
We use a unique observational perspective complemented with climate model data to describe and understand atmospheric variability and climate trends, their drivers, feedbacks, and impacts. We focus on resolving changes in the atmospheric structure and global circulation, detecting and attributing natural and human-induced causes, and analyzing atmospheric extreme events. Through connecting global changes with changes in regional weather patterns we provide important foundations for research on the effects of climate change and its socio-economic impacts.
Research themes
Monitoring the atmosphere
- Monitoring and climate analysis of atmospheric key variables including temperature, water vapor, ozone, in global and regional contexts with a focus on atmospheric observations
- Robust characterization of the atmosphere and its changes over time using high resolution, high quality remote sensing observations, specifically from GNSS radio occultation
- Advancement and intercomparison of atmospheric data sets from different observations (in situ, satellites) including uncertainty estimates
- Evaluating the inter-consistency of atmospheric temperature observations
- Comparing observations with reanalyses and climate model simulations
Understanding global climate
- Advancing our understanding of atmospheric variability and climate change, their drivers, feedbacks and impacts
- Detection and attribution of short-term and long-term climate trends using observations and climate model simulations
- Analyzing atmospheric variability (such as ENSO, QBO, MJO), circulation (e.g., BDC), waves and fluxes
- Analyzing atmospheric extremes and their impacts including volcanic eruptions, wildfires, atmospheric blocking, and sudden stratospheric warmings
- Investigating changes in the atmospheric structure and specifically the tropopause region
- Detecting fingerprints of anthropogenic climate change and attribution of natural and human-induced drivers to temperature trends
- Assessing radiative and dynamical contributions to observed and modelled temperature changes
- Evaluating differences in the representation of variability and trends in observations and climate model simulations
Advancing analysis methods
- Development and application of machine-learning methods for climate analysis, diagnostics, and predictability
- Providing and improving uncertainty information of climate data records and derived trends
- Development of climate analysis specific ML methods
- Objective methods for detecting atmospheric features
- Physics-constrained evaluation of models, reanalyses, and observations
| +43 316 380 - 8432 https://homepage.uni-graz.at/andi.steiner/ |
| +43 316 380 - 8435 |
Sebastian Scher BSc MSc PhD | |
| +43 316 380 - 8436 |
| +43 316 380 - 8456 |
Viola Kaser | |
Armin Kienbacher | |
Anna Payer | |
Jiaqi Shi | |
Sabine Tschürtz | +43 316 380 - 8418 |