Climate dynamics

Abstract:

Stratospheric sudden warmings (SSWs) are a major source of variability during Northern Hemisphere winter. The frequency of occurrence of SSWs is influenced by El Nio-Southern Oscillation (ENSO), the quasi-biennial oscillation (QBO), the 11 year solar cycle, and volcanic eruptions. This study investigates the role of ENSO and the QBO on the frequency of SSWs using the National Center for Atmospheric Research's Whole Atmosphere Community Climate Model, version 3.5 (WACCM3.5). In addition to a control simulation, WACCM3.5 simulations with different combinations of natural variability factors such as the QBO and variable sea surface temperatures (SSTs) are performed to investigate the role of QBO and ENSO. Removing only one forcing, variable SSTs or QBO, yields a SSW frequency similar to that in the control experiment; however, removing both forcings results in a significantly decreased SSW frequency. These results imply nonlinear interactions between ENSO and QBO signals in the polar stratosphere during Northern Hemisphere winter. This study also suggests that ENSO and QBO force SSWs differently. The QBO forces SSW events that are very intense and whose impact on the stratospheric temperature can be seen between December and June, whereas ENSO forces less intense SSWs whose response is primarily confined to the months of January, February, and March. The effects of SSWs on the stratospheric background climate is also addressed here. Copyright 2011 by the American Geophysical Union.

Abstract:

The stratospheric climate and variability from simulations of sixteen chemistry-climate models is evaluated. On average the polar night jet is well reproduced though its variability is less well reproduced with a large spread between models. Polar temperature biases are less than 5 K except in the Southern Hemisphere (SH) lower stratosphere in spring. The accumulated area of low temperatures responsible for polar stratospheric cloud formation is accurately reproduced for the Antarctic but underestimated for the Arctic. The shape and position of the polar vortex is well simulated, as is the tropical upwelling in the lower stratosphere. There is a wide model spread in the frequency of major sudden stratospheric warnings (SSWs), late biases in the breakup of the SH vortex, and a weak annual cycle in the zonal wind in the tropical upper stratosphere. Quantitatively, "metrics" indicate a wide spread in model performance for most diagnostics with systematic biases in many, and poorer performance in the SH than in the Northern Hemisphere (NH). Correlations were found in the SH between errors in the final warming, polar temperatures, the leading mode of variability, and jet strength, and in the NH between errors in polar temperatures, frequency of major SSWs, and jet strength. Models with a stronger QBO have stronger tropical upwelling and a colder NH vortex. Both the qualitative and quantitative analysis indicate a number of common and long-standing model problems, particularly related to the simulation of the SH and stratospheric variability. Copyright 2011 by the American Geophysical Union.

Abstract:

The persistence and climate noise properties of North Atlantic climate variability are of importance for trend identification and assessing predictability on all time scales from several days to many decades. Here, the authors analyze these properties by applying empirical mode decomposition to a time series of the latitude of the North Atlantic eddy-driven jet stream. In previous studies, it has been argued that a slow decay of the autocorrelation function at large lags suggests potential extended-range predictability during the winter season. The authors show that the increased autocorrelation time scale does not necessarily lead to enhanced intraseasonal predictive skill. They estimate the fraction of interannual variability that likely arises due to climate noise as 43%-48% in winter and 70%-71% in summer. The analysis also indentifies a significant poleward trend of the jet stream that cannot be explained as arising from climate noise. These findings have important implications for the predictability of North Atlantic climate variability. © 2011 American Meteorological Society.