[P-EM12] Coupling Processes in the Atmosphere-Ionosphere System

[PEM12-34] Retrieval of the day-to-day variability of MLT tides at low latitudes from a radar network: Feasibility study using WACCM-X and JAWARA

*Jose Suclupe¹、Jorge L. Chau¹、Miguel Urco¹、Federico Conte¹、Huixin Liu²、Nicholas M Pedatella³、Kaoru Sato⁴、Dai Koshin³ (1.Leibniz-Institute of Atmospheric Physics at the University of Rostock, Kühlungsborn, Germany、2.Department of Earth and Planetary Science, Kyushu University, Fukuoka, Japan、3.High Altitude Observatory, NSF National Center for Atmospheric Research, Boulder, CO, USA、4.Department of Earth and Planetary Science, The University of Tokyo, Tokyo, Japan)

The large-scale dynamics of the mesosphere and lower thermosphere (MLT) are driven by various atmospheric waves, including solar tides primarily generated in the lower atmosphere. Understanding and predicting space weather requires studying the day-to-day variability of these tides. Studying the MLT region at low latitudes is essential for understanding how forces from the lower atmosphere influence the upper atmosphere, where their effects are expected to be most significant. Satellites provide a reasonable representation of spatial features but lack temporal resolution, while single radars provide high temporal coverage but no spatial information, making it difficult to distinguish between different wavenumbers (e.g., migrating and non-migrating tides). Ideally, multiple satellites and/or a network of coordinated radars are needed to achieve good spatial and temporal characterization of these global waves. The LoLa (Low-Latitude mesosphere and lower thermosphere radar network) Project aims to address this challenge by establishing a coordinated ground-based radar network at low latitudes. However, representing the latitudinal variability of tides remains difficult due to the sparse distribution of radars, constrained by logistical and geographical factors. In this study, we propose a method to assess the feasibility of retrieving the day-to-day variability of migrating and non-migrating four-day mean tides using sparse data, emulating radar networks like LoLa. Our approach is validated using synthetic horizontal wind data from the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X) and reanalysis data from the JAGUAR-DAS Whole Neutral Atmosphere Reanalysis (JAWARA) model.