Abstract
Abstract. In this study we investigate the spatial variabilities of the zonal mean temperature (20–100 km) from the TIMED (Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics)/SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) satellite using the empirical orthogonal functions (EOFs). After removing the climatological annual mean, the first three EOFs are able to explain 87.0% of temperature variabilities. The primary EOF represents 74.1% of total anomalies and is dominated by the north–south contrast. Patterns in the second and third EOFs are related to the semiannual oscillations (SAO) and mesospheric temperature inversions (MTI), respectively. The quasi-biennial oscillation (QBO) component is also decomposed into the seventh EOF with contributions of 1.2%. Last, we use the first three modes and annual mean temperature to reconstruct the data. The result shows small differences are in low latitude, which increase with latitude in the middle stratosphere and upper mesosphere.
Highlights
The thermal structure is significant for researching variations and coupling in the stratosphere and mesosphere
Most variances are from the first empirical orthogonal functions (EOFs)
Dominant modes in the first three EOFs are attributed to the annual oscillation (AO), semiannual oscillations (SAO) and mesospheric temperature inversions (MTI)
Summary
The thermal structure is significant for researching variations and coupling in the stratosphere and mesosphere. Instruments on satellites in the past, such as Nimbus 7 (Gille and Russell, 1984; Remsberg et al, 2004), SME (Clancy et al, 1994) and UARS (Wu et al, 2003; Leblanc and Hauchecorne, 1997; Shepherd et al, 2004; Ortland et al, 1998), were neither covering all local times nor high in resolution. Most shortcomings of previous measurements are overcome by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the TIMED (Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics) satellite. With the data of high vertical resolution and global coverage, Huang et al (2006) and Xu et al (2007a, b) analyzed 2 years and 5 years of SABER temperature, respectively. In this paper we attempt to derive dominant spatial distributions of the given data sets by decomposing SABER temperature using the empirical orthogonal functions (EOFs)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
