Abstract. The ground-based measurements obtained from a lidar network and the 6-year OSIRIS (optical spectrograph and infrared imager system) limb-scanning radiance measurements made by the Odin satellite are used to study the climatology of the middle- and low-latitude sodium (Na) layer. Up to January 2021, four Na resonance fluorescence lidars at Beijing (40.5∘ N, 116.0∘ E), Hefei (31.8∘ N, 117.3∘ E), Wuhan (30.5∘ N, 114.4∘ E), and Haikou (19.5∘ N, 109.1∘ E) collected vertical profiles of Na density for a total of 2136 nights (19 587 h). These large datasets provide multi-year routine measurements of the Na layer with exceptionally high temporal and vertical resolution. The lidar measurements are particularly useful for filling in OSIRIS data gaps since the OSIRIS measurements were not made during the dark winter months because they utilize the solar-pumped resonance fluorescence from Na atoms. The observations of Na layers from the ground-based lidars and the satellite are comprehensively compared with a global model of meteoric Na in the atmosphere (WACCM–Na). The lidars present a unique test of OSIRIS and WACCM (Whole Atmosphere Community Climate Model), because they cover the latitude range along 120∘ E longitude in an unusual geographic location with significant gravity wave generation. In general, good agreement is found between lidar observations, satellite measurements, and WACCM simulations. On the other hand, the Na number density from OSIRIS is larger than that from the Na lidars at the four stations within one standard deviation of the OSIRIS monthly average, particularly in autumn and early winter arising from significant uncertainties in Na density retrieved from much less satellite radiance measurements. WACCM underestimates the seasonal variability of the Na layer observed at the lower latitude lidar stations (Wuhan and Haikou). This discrepancy suggests the seasonal variability of vertical constituent transport modelled in WACCM is underestimated because much of the gravity wave spectrum is not captured in the model.
Read full abstract