Abstract

Abstract. In this investigation a statistical analysis of the characteristics of mesospheric inversion layers (MILs) over tropical regions is presented. This study involves the analysis of 16 years of lidar observations recorded at Réunion (20.8° S, 55.5° E) and 21 years of lidar observations recorded at Mauna Loa (19.5° N, 155.6° W) together with SABER observations at these two locations. MILs appear in 10 and 9.3 % of the observed temperature profiles recorded by Rayleigh lidar at Réunion and Mauna Loa, respectively. The parameters defining MILs show a semi-annual cycle over the two selected sites with maxima occurring near the equinoxes and minima occurring during the solstices. Over both sites, the maximum mean amplitude is observed in April and October, and this corresponds to a value greater than 35 K. According to lidar observations, the maximum and minimum mean of the base height ranged from 79 to 80.5 km and from 76 to 77.5 km, respectively. The MILs at Réunion appear on average ∼ 1 km thinner and ∼ 1 km lower, with an amplitude of ∼ 2 K higher than Mauna Loa. Generally, the statistical results for these two tropical locations as presented in this investigation are in fairly good agreement with previous studies. When compared to lidar measurements, on average SABER observations show MILs with greater amplitude, thickness and base altitudes of 4 K, 0.75 and 1.1 km, respectively. Taking into account the temperature error by SABER in the mesosphere, it can therefore be concluded that the measurements obtained from lidar and SABER observations are in significant agreement. The frequency spectrum analysis based on the lidar profiles and the 60-day averaged profile from SABER confirms the presence of the semi-annual oscillation where the magnitude maximum is found to coincide with the height range of the temperature inversion zone. This connection between increases in the semi-annual component close to the inversion zone is in agreement with most previously reported studies over tropics based on satellite observations. Results presented in this study confirm through the use of the ground-based Rayleigh lidar at Réunion and Mauna Loa that the semi-annual oscillation contributes to the formation of MILs over the tropical region.

Highlights

  • The thermal structure of the middle atmosphere cannot only be explained by radiative balance (Shepherd, 2000, 2007; Hauchecorne et al, 2010)

  • A statistical analysis of the characteristics of the mesospheric temperature inversion layers (MILs) for two tropical locations has been presented in this investigation

  • The analysis focused on Réunion (20.8◦ S, 55.5◦ E) and Mauna Loa (19.5◦ N, 155.6◦ W)

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Summary

Introduction

The thermal structure of the middle atmosphere cannot only be explained by radiative balance (Shepherd, 2000, 2007; Hauchecorne et al, 2010). Because of a lack of ground-based observations over Southern Hemisphere tropical/subtropical latitudes, questions arise regarding the characteristics of MILs and their formation mechanisms in these regions In this investigation, Rayleigh lidar data recorded at Réunion (20.8◦ S, 55.5◦ E) since 1994 and at Mauna Loa (19.5◦ N, 155.6◦ W) since 1993 have been employed. The Rayleigh lidar located at Mauna Loa constitutes a unique and valuable dataset to study the long-term middle atmospheric temperature and dynamical variability in the tropical/subtropical region in the Northern Hemisphere (Leblanc et al, 1998, 1999; Leblanc and McDermid, 2001; Li et al, 2008, 2010; Dou et al, 2009). Leblanc et al (1998) completed a climatological study of middle atmosphere temperature including lidar observations recorded at Mauna Loa during the period 1993–1997 They found that the amplitude of the seasonal temperature variation is weak and characterized by a clear semi-annual oscillation.

Ground-based Rayleigh lidar observations
Statistical analysis of temperature inversion layer
Intra- and inter-annual variability
Characteristics of the MILs
SABER and lidar observations: effects of spatial coincidences
Findings
Influence of the semi-annual oscillations
Summary and conclusion
Full Text
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