Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data. Issue 23 (2nd December 2018) - Žagar, N.; Jelić, D.; Alexander, M. J.; Manzini, E.
Abstract: A new measure of subseasonal variability is introduced that provides a scale‐dependent estimation of vertically and meridionally integrated atmospheric variability in terms of the normal modes of linearized primitive equations. Applied to the ERA‐Interim data, the new measure shows that subseasonal variability decreases for larger zonal wave numbers. Most of variability is due to balanced (Rossby mode) dynamics but the portion associated with the inertio‐gravity (IG) modes increases as the scale reduces. Time series of globally integrated variability anomalies in ERA‐Interim show an increase in variability after year 2000. In recent years the anomalies have been about 2% above the 1981–2010 average. The relative increase in variability projecting on the IG modes is larger and more persistent than for the Rossby modes. Although the IG part is a small component of the subseasonal variability, it is an important effect likely reflecting the observed increase in the tropical precipitation variability. Plain Language Summary: The multiaspect nature of atmospheric variability has traditionally been approached by analyzing selected spatiotemporal components of circulation variability. For example, estimating trends in extreme events often rely on surface temperature and precipitation data that can be validated with long observation records. Trends in circulation need to be analyzed using global gridded three‐dimensional data which are provided by reanalyses. This article provides the first quantification of global subseasonal variability using reanalysis data. A new measure, named subseasonal variability integral, spatially integrates variability in surface pressure and variability in winds and geopotential height (i.e., temperature) on levels in the troposphere and stratosphere. The subseasonal variability integral is applied to the ERA‐Interim reanalyses. Results show that estimated subseasonal variability has on average increased for about 2% in recent years relative to 1981–2010. A larger and more persistent increase is found in the inertio‐gravity modes which are to a large extent associated with tropical unbalanced circulation. This likely reflects previously reported increase in latent heat in ERA‐Interim and the observed increase in precipitation variability. Key Points: A new measure of global subseasonal variability provides scale and dynamics dependent variability estimates An increase in variability in recent years for about 2% relative to 1981 to 2010 is found in ERA‐Interim data The increase is larger in variability associated with inertio‐gravity modes than with Rossby modes