An EOF Analysis of Water Vapor in the Middle Atmosphere and Lower Thermosphere Based on TIMED/SABER

As a critical trace gas and a sensitive indicator of climate change, water vapor (H2O) plays a pivotal role in regulating the Earth’s radiative budget and middle-atmospheric chemical cycles. In this study, H2O measurements from the Sounding of the Atmosphere using a Broadband Emission Radiometry (SABER) instrument on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite are analyzed to characterize the H2O spatiotemporal distribution throughout the stratosphere–mesosphere–lower thermosphere (SMLT) region. Using eigen analysis, the bimonthly mean H2O across different latitude bins between 2002 and 2025 is decomposed into four empirical orthogonal functions (EOFs). Results indicate that stratospheric water vapor remains relatively stable with weak latitudinal dependence, whereas H2O in the mesosphere–lower thermosphere (MLT) at middle-to-high latitudes exhibits pronounced seasonal variations and distinct hemispheric antisymmetry. The first mode captures a global H2O long-term increasing trend. Both EOF1 and EOF2 are associated with solar activity and the El Niño–Southern Oscillation (ENSO) to varying degrees, indicating that these dominant modes are driven by multiple concurrent forcing factors. EOF3 correlates with the Quasi-Biennial Oscillation (QBO), suggesting links to QBO-driven atmospheric dynamical processes, whereas EOF4 demonstrates no significant associations with natural activity indices, suggesting perturbations arising from alternative atmospheric mechanisms. By systematically applying EOF analysis to a 24-year dataset of H2O observations in the SMLT region, this study characterizes the principal distribution patterns and evolutionary characteristics of SMLT H2O. Through correlation analyses with natural forcing indices, the complex driving mechanisms governing its variability are elucidated. This work provides a comprehensive observational framework for SMLT water vapor variability, enhancing assessments of SMLT H2O responses to long-term climate change and refining the understanding of the Earth–atmosphere system. Furthermore, these findings provide critical data support for the subsequent development and optimization of SMLT water vapor models.