
Studies on stratospheric ozone have attracted much attention due to its serious impacts on climate changes and its important role as a tracer of Earth’s global circulation. Tropospheric ozone as a main atmospheric pollutant damages human health as well as the growth of vegetation. Yet, there is still a lack of a theoretical framework to fully describe the variation of ozone. To understand ozone’s spatiotemporal variance, we introduce the eigen microstate method to analyze the global ozone mass mixing ratio between January 1, 1979 and June 30, 2020 at 37 pressure layers. We find that eigen microstates at different geopotential heights can capture different climate phenomena and modes. Without deseasonalization, the first eigen microstates capture the seasonal effect and reveal that the phase of the intra-annual cycle moves with the geopotential heights. After deseasonalization, by contrast, the collective patterns from the overall trend, El Niño-Southern Oscillation (ENSO), quasi-biennial oscillation, and tropopause pressure are identified by the first few significant eigen microstates. The theoretical framework proposed here can also be applied to other complex Earth systems.
Physics - Atmospheric and Oceanic Physics, Atmospheric and Oceanic Physics (physics.ao-ph), FOS: Physical sciences, Adaptation and Self-Organizing Systems (nlin.AO), Nonlinear Sciences - Adaptation and Self-Organizing Systems
Physics - Atmospheric and Oceanic Physics, Atmospheric and Oceanic Physics (physics.ao-ph), FOS: Physical sciences, Adaptation and Self-Organizing Systems (nlin.AO), Nonlinear Sciences - Adaptation and Self-Organizing Systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
