2025-09-03, 11:00–12:00 (Europe/Amsterdam), HugoTECH
This lecture discusses the use of models and data processing methods for efficient use of large volumes of satellite data, with application to atmospheric remote sensing. The lecture will come with exercises to gain hands-on experience using some of the techniques that are discussed.
With advancing satellite technology enabling improvements in spatial, temporal, and spectral resolution of every new missions that is launched, the data rate is rapidly increasing also. This calls for computationally efficient methods for processing the data that come down, preferably in near real time. The focus of this lecture is on the final steps in the data processing chain, where large volumes of data our combined using models to extract and interpret the most useful information in the data. We'll discuss data assimilation and inverse modeling methods that are used, for example, in weather forecasting and the estimation of air pollutant and greenhouse gas emissions.
Recently, the toolbox is being enriched with machine learning methods that are starting to outcompete some of the conventional methods, not only in processing speed but even in forecasting skill. The lecture will come with tutorials offering the opportunity to gain hands-on experience with some of these techniques.
Sander Houweling is professor in Atmosphere, Greenhouse Gases, and Climate of the Earth Sciences department of the Vrije Universiteit Amsterdam and affiliated also with NWO-i SRON Netherlands Institute for Space Research. His research focuses on the global cycles of long-lived greenhouse gases in the atmosphere and climate impacts of human activities. His research group at the Vrije Universiteit develops methods for estimating greenhouse gas emissions from atmospheric measurements using inverse modeling techniques at global, regional, and local scale. As member of the scientific steering committee of the Integrated Global Greenhouse Gas Information System (IG3IS) of the World Meteorological Organization (WMO) he is committed to independent evaluation of national greenhouse gas emission reports to the United Nations Convention on Climate Change (UNFCCC) using atmospheric measurements.