Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data

Area of Science:

• Atmospheric Science
• Climate Dynamics
• Geophysics

Background:

• Subseasonal variability is crucial for weather and climate prediction.
• Understanding the dynamics of atmospheric variability across different scales is essential.
• Existing measures may not fully capture the contributions of various atmospheric modes.

Purpose of the Study:

• Introduce a novel scale-dependent measure for atmospheric variability.
• Quantify the contributions of different normal modes (Rossby and inertio-gravity) to subseasonal variability.
• Investigate recent trends in atmospheric variability using reanalysis data.

Main Methods:

• Developed a new measure for vertically and meridionally integrated atmospheric variability.
• Utilized normal modes of linearized primitive equations for scale-dependent analysis.
• Applied the measure to ERA-Interim reanalysis data to analyze subseasonal variability.

Main Results:

• Subseasonal variability decreases with increasing zonal wave numbers.
• Inertio-gravity (IG) modes' contribution to variability increases at smaller scales.
• ERA-Interim data show increased global variability after 2000, with a larger relative increase in IG modes.

Conclusions:

• The new measure effectively characterizes scale-dependent atmospheric variability.
• The increasing role of IG modes at smaller scales is significant.
• The observed increase in subseasonal variability, particularly in IG modes, may explain rising tropical precipitation variability.