Observing system simulation experiments (OSSEs) have been traditionally used to measure the anticipated impact of a new set of measurements on weather prediction. 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, forecast OSSEs also have a number of key limitations. First, they require simulation of all current measurements, along with calibration of their errors. Second, they rely on the availability of a forecast and data assimilation system that is capable of ingesting the new measurements. If measurement uncertainties are not properly calibrated, the measure of impact of a new observing system will be incorrect. If a data assimilation system is not capable of assimilating a new type of measurement, a forecast OSSE is not possible.
This presentation will discuss the specific application of OSSEs to the design of missions that target convective-scale processes. Most forecast systems do not represent convection realistically, making it necessary to consider new ways of quantifying the effectiveness of a proposed observing system. This presentation will describe a spectrum of OSSEs that range from simple to complex, and include:
1. Experiments that explore satellite spatial and temporal sampling
2. Quantification of retrieval (and forward model) uncertainty
3. Assessment of mission science goals
4. Observation impact on numerical weather prediction
The focus is on the types of experiments that may be required in the development of the 2017 Decadal Survey Aerosols, Clouds, Convection, and Precipitation mission.