Stratospheric Temperature Measurements from NanoSatellite Observations of Stellar Occultation Bending.

Stellar occultation observations from space can probe the stratosphere and mesosphere at a fine vertical scale around the globe unlike other measurement techniques like radiosondes, aircraft, and radio occultation. We imaged the refractive bending angle of a star centroid for a series of occultations by the atmosphere. Atmospheric refractivity, density, and then temperature are retrieved from the bending observations with the Abel transformation and Edlén's law, the hydrostatic equation, and the ideal gas law. 5 The retrieval technique is applied to data collected by two nanosatellites operated by Terran Orbital. Measurements were primarily taken by the GEOStare SV2 mission, with a dedicated imaging telescope, supplemented with images captured by spacecraft bus sensors, namely the star trackers on other Terran Orbital missions. The bending angle noise floor is arcseconds and 30 arcseconds for the star tracker and GEOStare SV2 data, respectively. The most significant sources of uncertainty are due to centroiding errors due to the fairly low-resolution stellar images and telescope pointing knowledge de10 rived from noisy satellite attitude sensors. The former mainly affects the star tracker data, while the latter limits the GEOStare SV2 accuracy with both providing low vertical resolution. This translates to a temperature profile retrieval up to roughly km for both star tracker and GEOStare SV2 datasets. In preparation of an upcoming 2023 mission designed to correct these deficiencies, SOHIP, we simulated bending angle measurements with varying magnitudes of error. The expected maximum altitude of retrieved temperature is 41 km on average for these simulated measurements with a noise floor of 0.39 arcseconds. Our work highlights the capabilities of stellar occultation observations from nanosatellites for atmospheric sounding. Future work will investigate high frequency observations of atmospheric gravity waves and turbulence, mitigating the major uncertainties observed in these datasets. [ABSTRACT FROM AUTHOR]