Designing Satellite Observing Systems at the Intersection Between Science and Mathematics
Earth observing satellite missions are designed around a set of pre-defined measurement needs, and aimed at addressing a specific set of science questions. As such, mission design necessarily incorporates considerations of: measurement accuracy and uncertainty, spatial and temporal sampling, mission science impact, and impact of observations on numerical weather prediction. It is important to assess, and if possible quantify, the ability of a mission to meet its requirements at each stage of design and development. Miniaturization of instruments has made modern mission design far more flexible, but has also complicated the process by greatly expanding the number of possible satellite and instrument combinations.
Observing system simulation experiments (OSSEs) are used to evaluate new satellite missions pre-launch, and have traditionally assessed the impact of a new set of measurements on weather prediction. Weather forecast OSSEs are useful, in that they measure the effectiveness of a set of measurements in the context of the current global observing system. However, most satellite missions are not primarily intended to improve weather forecasts. Instead, the goal is to advance the state of scientific knowledge.
In this presentation, I will describe a spectrum of OSSEs that range from simple to complex, and are designed to assess the science impact of a new mission. These include:
1. Experiments that explore satellite spatial and temporal sampling
2. Quantification of uncertainty in mission science data products
3. Assessment of mission science goals
4. Observation impact on the state of scientific knowledge
I will highlight how each of these OSSE activities draws upon probability theory, and suggest new ways in which mathematics and physical sciences can partner in the mission design process.