Satellite Remote Sensing

Computer modeling, known in the Atmospheric Sciences world as Numerical Weather Prediction (NWP), is the primary tool for modern weather forecasting. NWP has massively evolved due increased understanding of the atmosphere since the 1950’s, increased computational power, the integration of observations from various platforms (in-situ and remote sensing), international collaboration, and advancements in the representation of physics and dynamics in models. As a society, we rely on weather forecasts to protect life and property—goals that are taking precedence especially in the imminent increase of severe weather events. Fortunately, since the launch of the first weather satellite, TIROS-1 our capability to observe Earth from space over has catalyzed our understanding of the dynamic processes that govern air, ocean and land at various spatio-temporal scales. For example, in the event of extreme weather phenomena such as tropical cyclones, we heavily rely on satellites to track the location and intensity of the storm and inform weather prediction systems in real-time to provide more accurate short-term forecasts.

Spaceborne observations are used not only to understand the planet’s weather and climate, but also to make assessments and predictions of major environmental problems such as heavy precipitation, wildfires, ice melt, sea level rise, among others. Therefore, satellite observations combined with numerical weather prediction models and data assimilation techniques have become essential components and will continue to be in the future. Yet, many fundamental atmospheric research questions remain to be answered because our observation capability is still quite limited.  For example, while there are many missions that can retrieve good-quality profiles of atmospheric parameters (moisture, wind and temperature, etc.) retrieving highly resolved information of cloud and aerosol vertical distribution remains an extremely challenging endeavor, particularly in the lower atmosphere. This issue creates a shared predicament in the research community. For example, uncertainties in satellite retrievals significantly influence obtained radiative budgets and heating rates – and our understanding of the feedback these have in severe weather formation (i.e tropical cyclones) and long-term climate variability and trends (i.e ENSO).

Our group focuses on researching novel uses of infrared and radio occultation satellite data in weather prediction to examine links between aerosols, clouds, and precipitation. We accomplish this via collaboration with UW-Madison’s SSEC and CIMMS as well as NASA centers such as the Jet Propulsion Laboratory on this endeavor. We also look at potential applications of satellite data for Disaster Risk Reduction efforts via partnership with international organizations such as the UN-DRR and the International GNSS Service.