Temperature changes (T) and humidity (U) of the upper troposphere/lower stratosphere (UTLS) are primarily due to increasing concentrations of well-mixed greenhouse gases and the depletion of stratospheric ozone. A rigorous assessment of the evolution of T and U in the UTLS, based on “reference” measurements, is key for addressing global climate change.The GCOS Reference Upper-Air Network, GRUAN (https://www.gruan.org/), provides traceable upper-air measurements with quantified uncertainties to create climate data records of Essential Climate Variables including T, U, and wind from ground level to the lower stratosphere.Within this project, the PhD student shall gain a good knowledge of atmospheric physics and statistics for studying Earth’s climate, including training on balloon-borne measurement uncertainty.The PhD student will also develop a data fusion spatiotemporal statistical model merging the GRUAN radiosonde with other data sources measuring T and U in the UTLS to understand the spatiotemporal trend mentioned above. Specifically, data will include satellite observation, Earth system reanalysis, radio occultation GNSS, and climate models (CMIP5/6). Moreover, the PhD student will develop statistical models for multivariate dynamic random fields defined on a spheric sector (UTLS) cross time, in medium to high resolution able to consider measurement uncertainty based on non-Gaussian distributed errors.

In the first 18 months, the training (in Bergamo, Potenza, Pavia and abroad) will focus on the following:- Atmospheric and climate physics- Balloon-borne and remote sensing observations- Frequentist and Bayesian statistical theory- Time series analysis- Advanced geostatistical models for large spatiotemporal data- Machine learning for spatiotemporal data- Advanced computational statistics and high-performance computing.Training will be based on classes and learning by doing.

The research project will be developed in close connection between the Climate and Upper-air measurement Team of the CNR-IMAA (PI: Fabio Madonna), which is a leading institute for balloon-borne and ground-based reference observations for weather and climate, and the research group on environmental statistics at the Department of economics of the University of Bergamo (UNIBG, Tutor: Alessandro Fasso'). The PhD student will be provided with a desktop position, computing facilities, library access, etc. both at CNR-IMA and UNIBG, where they will also develop a practice on performing balloon-borne measurements.