SA036-0016
Thermospheric data-model comparison using GOLD’s solar eclipse observations

Wednesday, 16 December 2020
Poster
Saurav Aryal1, J. Scott Evans2, John Correira3, Jerry D Lumpe4, Tong Dang5, Stanley C Solomon6, Wenbin Wang6, Alan Geoffrey Burns6, Richard Eastes1, Jiuhou Lei7, Huixin Liu8 and Geonhwa Jee9, (1)University of Colorado, Laboratory for Atmospheric and Space Physics, Boulder, CO, United States, (2)Computational Physics, Inc., Springfield, VA, United States, (3)Computational Physics Inc. Springfield, Springfield, VA, United States, (4)Computational Physics, Inc., Boulder, CO, United States, (5)University of Science and Techonology, Hefei, China, (6)NCAR, HAO, Boulder, CO, United States, (7)Univ. of Sci. & Tech. of Chin, Hefei, Anhui, China, (8)Kyushu University, Fukuoka, Japan, (9)Korea Polar Research Institute, Division of Polar Climate Sciences, Incheon, South Korea
Abstract:
Solar eclipses impulsively drive the thermosphere by briefly attenuating the high energy X-ray and UV solar radiation that heat and ionize it. Thermospheric observations of such impulsive events, thus, provide us better understanding of the thermosphere and the thermosphere-ionosphere (T-I) system. However, until recently synoptic observations of an eclipse in the thermosphere had not been made. NASA’s Global-scale Observation of Limb and Disk’s (GOLD) made such observations during the July 2, 2019 total solar eclipse. These first-of-a-kind observations show that the eclipse induced significant compositional (factor of 1.8) and neutral temperature changes (~ 150 K) near the totality when compared to the baseline observations made a couple of days prior. GOLD observations were simulated using the Thermospheric Ionospheric Electrodynamics General Circulation Model (TIE-GCM) and GLobal airglOW (GLOW) model. The simulations significantly underestimated compositional (by a factor of 1.6) and temperature (by > 100K) changes near the totality when compared to observations. These discrepancies show inadequacies in current knowledge of the Earth’s thermosphere and its modelling. Resolving these data-model disagreements has the potential to revolutionize the understanding of the thermosphere.
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