Projects of the Global Climate Analysis Research Group

The Doctoral College Climate Change (DKCC) was an international programme at the University of Graz for outstanding doctoral students in the field of climate change.

• Final report
• Publications, presentations and further outcomes

Project leader: Andrea K. Steiner

Observations of the Earth’s surface temperature provide undeniable evidence of a changing climate. While surface temperature trends are in accordance amongst different groups, there are still unresolved issues regarding upper-air climate trends. Though overallagreement on a global warming of the troposphere and a cooling of the stratosphere is given, the uncertainty in trend rates and their vertical structure is large and limits the ability to draw robust and consistent inferences about climate trends. This is stated as a key issue in the recent IPCC report implying the need for data with better accuracy.

Addressing this need is challenging since uncertainties exist in observations, reanalyses, and climate model output. Observations from weather satellites and balloons have several shortcomings since they were not intended to serve climate monitoring needs, which demand accurate and long-term stable measurements. In atmospheric reanalyses observations are integrated into models, containing effects of both observation and model errors. In current climate models discrepancies to observations are evident in vertical thermal structure and trends, especially in the upper troposphere and stratosphere. Radio Occultation (RO) provides independent observations with beneficial characteristics in this context. The traceability to time measurements with precise atomic clocks assures a long-term stable and consistent data record with global coverage. Accuracy, low structural uncertainty, and use for climate studies have been demonstrated. High quality and vertical resolution offer the distinct advantage for assessing the vertical thermodynamic structure.

The central aim of the project VERTICLIM is the exploration and evaluation of the vertical structure of atmospheric climate variability and climate trends, their regional imprints, and relevant processes from the surface to the stratopause. Focus periods are 2002–2015 with dense data set coverage for rigorous short-term study, and 1979–2015 with good coverage for complementary longer-term study. New insights will be gained on recent climatic changes in the troposphere and stratosphere by systematically exploiting upper-air records from observations and reanalyses, and climate models. Evaluating the RO record as reference and the inter-consistency of other high-quality observations such as MIPAS, SABER, radiosondes, and of AMSU/SSU bulk temperatures, will provide essential new information on the climate quality of upper-air observations. Exploration of atmospheric key characteristics, including annual cycle, tropopause/stratopause dynamics, and climate variability modes will reveal key strengths, weaknesses, and improvement potential of reanalyses and models. Also new insights into the vertical structure of trends and their regional imprints in the atmosphere compared to the surface will be gained from RO and best-evaluated records.

Overall we aim with VERTICLIM to draw a picture of unprecedented quality and rigor of the vertical structure of atmospheric climate variability and trends and to reveal key skills o upper-air observations, reanalyses, and climate models with RO as reference climate data record.

Project leader: Barbara Scherllin-Pirscher (Herta Firnberg position)
Mentor: Andrea K. Steiner

El Niño Southern Oscillation (ENSO) is a coupled ocean-atmosphere phenomenon, which links sea surface temperature (SST) and ocean heat content to atmospheric dynamics. ENSO is the most significant mode of interannual climate variability of the tropical troposphere. Variations of convection, atmospheric temperature and circulation are strongly pronounced at tropospheric low latitudes but signatures associated with ENSO have also been observed at high latitudes as well as at stratospheric altitudes. Numerous studies over the last decades have analyzed the influence of ENSO on atmospheric temperature using observational data, e.g., from radiosondes or satellites, reanalyses, or model data. Since traditional observations have limited spatial coverage and most satellite data have a low vertical resolution in the upper troposphere and lower stratosphere (UTLS) region, substantial uncertainties remain in atmospheric dynamics in the UTLS during El Niño and La Niña conditions. 

In this context radio occultation (RO) offers new possibilities by providing high quality observations in the UTLS with global coverage. Atmospheric parameters like temperature, pressure, and geopotential height are retrieved with high vertical resolution and high accuracy and precision. A continuous RO record is available since 2001 but the number of RO measurements increased significantly in 2006, with the launch of the six Formosat-3/COSMIC (F3C) satellites. This constellation tracked more than 2000 RO events per day, enabling the derivation of fine-resolved atmospheric fields.

The central aim of the proposed project DYNOCC is the assessment of ENSO related atmospheric dynamics and its effects on troposphere-stratosphere processes from this novel multi-year RO record. In a first step I will perform a thorough investigation of UTLS ENSO signals in temperature, pressure, geopotential height, and water vapor to analyze the detailed vertical and horizontal structure of ENSO. The consistency of results obtained from RO will be checked using data from other observations as well as from analyses and reanalyses. Furthermore, I will validate a state-of-the-art global climate model with regard to its representation of the vertical UTLS ENSO structure. In a second step I will use high resolution RO data to investigate details of atmospheric waves associated with local heating induced by El Niño. This will allow gaining deeper understanding of natural climate variability in the transition between the troposphere and stratosphere, an important coupling layer in the atmosphere which is a topic of active current research. Finally, I will use precise RO-based geopotential height profiles on constant pressure surfaces to investigate the vertical and horizontal displacement of the geostrophic zonal wind during El Niño and La Niña conditions. 

Addressing these key issues, DYNOCC aims at adding detailed understanding of atmospheric dynamics associated with natural climate variability. Extending the application of RO to further research fields, DYNOCC will strengthen its value also outside of the RO community

The SysSon project developed sonification for climate science. Sonification is the acoustic analogue to visualization. Climate scientists depend on visual displays to get an insight in their huge and multi-dimensional data sets. But visualization is limited for conceptual and perceptual reasons. Therefore, sonification may be used complementarily, using the human sense of hearing in order to explore climate processes.

The project’s focus was on the development of a systematic procedure to enable climate scientists to create their own sonifications. The technical barrier of compatibility between the data structures and sound synthesis programs was met by developing the open source software SysSon (freely downloadable from github.com/iem-projects/sysson). Furthermore, the interdisciplinary work process tackled communicational barriers, as, e.g., climate scientists are not used to working with sound and sonification experts are not used to climate science terminology. Therefore a series of evaluations was implemented, based on User Centered Design. This procedure of evaluations, design, and development lead to a process of systematic sonification that can be generalized to other scientific domains as well.

Sonification is on the edge between science and the arts. Therefore, two artistic projects have been co-developed within the project. Klima|Anlage is a joint project with a German radio station and other partners (http://www.klima-anlage.org). Climate data were pre-processed to control an interactive climate sound “machine”. The installation has been shown in Berlin; further exhibitions are planned. Furthermore, the art installation Turbulence – a climate sound portrait was presented in November 2014 in Forum Stadtpark, Graz, Austria, conveying the climate topic to the public.

EU-Marie Curie Fellow: Riccardo Biondi
Scientist in Charge: Gottfried Kirchengast
Advise: Andrea Steiner

Many aspects of deep convective systems and volcanic eruptive clouds are poorly represented in current global climate models. By statistically analysing satellite observations and providing long-term statistics from these data, the project CONSYDER (Convective systems detection and analysis using radio occultations) highlighted observational constraints for improving the theoretical representations. Researchers relied on radio occultation observations from global positioning system (GPS) satellites. Although GPS satellites are mostly used for navigation, signals sent from one GPS satellite to another are refracted by the atmosphere. From measurements of the associated propagation delay, the refractive index and bending angle, it is possible to estimate key atmospheric parameters.

The CONSYDER team used data acquired in the period 2001 – 2012 via this technique to create a reference atmosphere from the Earth’s surface to 80 km altitude. More specifically, they developed 3D maps of refractivity, pressure, temperature and water vapour together with the frequency and standard deviation of measurements at each location and altitude. These radio occultation observations were combined with high-resolution and high-precision measurements from other satellites and ground based sensors. This unique combination allowed researchers to detect the cloud top height and structure of the extreme events. The aim was to gain a better understanding of the clouds’ structure especially in the upper troposphere and the lower stratosphere. CONSYDER results indicated that tropical cyclones should be studied in connection to the ocean basin where they develop. Basins in the northern and southern hemisphere commonly show different thermal structures with storms reaching higher altitudes in the southern hemisphere. On the other hand, the temperature anomaly above the tropical cyclones’ cloud top becomes positive in northern hemisphere ocean basins. The reason for this puzzling warming of the storm cloud top was not clear and is a topic of further investigations beyond the end of CONSYDER. Before the end of the project, a dataset of radio occultation measurements co-located with tropical cyclones was compiled. Since GPS observations are evenly distributed over the globe, the dataset is suitable for studying extreme events even in remote areas.

CONSYDER also demonstrated that the technique developed for detecting cloud tops of convective systems and tropical cyclones can also be used for detecting and monitoring volcanic cloud tops and inner structure. Volcanic ash clouds and SO2 clouds have a different impact on the atmospheric thermal structure. The results revealed a clear warming signature from SO2 clouds after the eruption of Nabro and a cooling signature from the ash cloud after the Puyehue eruption. The evolution of tropical cyclones and eruptive clouds, the lifetime of deep convective systems and associated environmental parameters analysed in CONSYDER provide a framework for comparison with model simulations. Besides diagnosing the underlying mechanisms, project outcomes provide guidance for parameterising convective processes in global climate models.

Project leader: Andrea K. Steiner

Observations for atmospheric climate monitoring and change detection have to meet stringent quality requirements as defined by the Global Climate Observing System (GCOS) program. Conventional measurements from weather satellites and balloons have several shortcomings since they were not intended to serve climate monitoring needs. Radio Occultation (RO) based on Global Positioning System (GPS) signals provides a new upper-air record with beneficial characteristics including long-term stability, all-weather capability, global coverage, high accuracy and vertical resolution in the upper troposphere and lower stratosphere.

Knowledge of errors is an important prerequisite for the use of data in climate trendstudies. The central aim of the project TRENDEVAL was the assessment of uncertainties in the RO climate record and its application for climate change detection and for climate model evaluation. We investigated available RO data for 1995/1997 and for 2001 onwards from several satellite missions for the atmospheric variables bending angle, refractivity, pressure, geopotential height, temperature, and specific humidity.

We provided error estimates for individual RO profiles and gridded climatological fields. Climatologies from different RO missions were found highly consistent. This allows for combining them to a single record, which is a key feature of climate benchmark data. We quantified the structural uncertainty of the RO record from six processing centers. Structural uncertainty in trends was found lowest within 50°S and 50°N from 8 km to 25 km meeting the GCOS stability requirements.

The assessment of lower stratospheric temperatures from different observation systems (microwave sounders (AMSU), radiosondes, and RO) revealed a significant difference between AMSU and RO. Analysis of error sources and the good agreement with radiosondes indicated that the difference is not caused by RO.

The validation of the representation of tropical convective regions in the HadGEM2 climate model (Met Office Hadley Centre) with RO revealed a cold bias of the model near the tropical tropopause. Our results showed the high utility of RO data for the evaluation of observations and climate models.

RO parameters were shown to provide useful indicators of climate change. We demonstrated the utility of RO for climate change detection. An emerging climate change signal for geopotential height and temperature was detected in the RO record, reflecting warming of the troposphere and cooling of the lower stratosphere. Overall, the quality, consistency, and reproducibility of RO data was found favorable for becoming a climate benchmark record for use in climate monitoring and change detection.

Project leader: Andrea K. Steiner
Final report

Considerable efforts are undertaken by the international scientific community in global climate change research, but still large discrepancies and uncertainties exist regarding the detection, attribution and projections of climate trends. One main cause is the lack of suitably accurate and stable long-term climate observations, an urgent need which was addressed by the Intergovernmental Panel on Climate Change (IPCC) in its “high priority areas of actions” for future research in the IPCC Third Assessment Report 2001. Climate benchmark observations provided by the Radio Occultation (RO) technique using Global Navigation Satellite System (GNSS) signals are well suited to overcome this problem for atmospheric observation, due to their unique combination of properties of accuracy, long-term stability, global coverage, and all-weather capability. Highest accuracy of key climate variables (such as temperature and geopotential height of pressure levels) is obtained in the upper troposphere and lower stratosphere (UTLS), the changing thermal structure in this height domain being a sensitive indicator of climate change. 

In this context the main aim of the proposed project was the exploration and provision of benchmark indicators of atmospheric climate change for the UTLS region by using available RO based climatologies and, for exploring the long-term value, “proxy” RO climatologies from re-analyses and climate model runs. Given the limited length of the available RO data (continuous since 2002 only), re-analyses were used to extend the observational datasets back to 1979. Furthermore, Global Climate Model (GCM) scenario simulations for the IPCC 4th Assessment Report (AR4) were used as multi-decadal “proxy” datasets out to year 2050. The datasets were systematically explored for finding the most robust and sensitive RO based change indicators both by testing pre-defined potentially useful indicators within a multi-model/multi-ensemble approach and by using a new visualization-driven 4D field exploration technique. Based on the identified most promising indicators, the trend detection capabilities of RO observations were investigated using methods of optimal trend detection (“fingerprinting”). 

In summary INDICATE aimed at revealing optimal UTLS climate trend indicators available from RO combined with validating the skill of climate models with RO data, thereby making a substantial contribution to climate change monitoring and research