Analysis of Ground Network Selection for Data Latency in Precipitation-observing Space Missions

Future precipitation-observing systems must deliver observed data within a short duration, called observation data latency, to detect potential hazards such as floods. This study performs a tradespace analysis to study the effect of ground station network selection on data latency for precipitation-observing missions using the GEOS-5 Nature Run data set as a convective storm environmental model. We develop a methodology that simulates storm observation and downlink opportunities between a constellation of satellites and a ground station network. An application case considers a Walker-delta satellite constellation with ground station locations based on a commercial network. The model computes the 95th percentile data latency of observed storms as a key performance metric. Results show that adding a ground station in New Zealand reduces the data latency distribution to a real-time level for all storms. Sensitivity analysis shows that orbital parameters such as inclination and altitude have a more substantial influence on the data latency than the sensor field of regard or the number of satellites.