Climate dynamics

Abstract:

This work is focused on the application of neural network based models to the analysis of total ozone (TO) time series. Processes that affect total ozone are extremely non linear, especially at the considered European mid-latitudes. Artificial neural networks (ANNs) are intrinsically non-linear systems, hence they are expected to cope with TO series better than classical statistics do. Moreover, neural networks do not assume the stationarity of the data series so they are also able to follow time-changing situations among the implicated variables. These two features turn NNs into a promising tool to catch the interactions between atmospheric variables, and therefore to extract as much information as possible from the available data in order to make, for example, time series reconstructions or future predictions. Models based on NNs have also proved to be very suitable for the treatment of missing values within the data series. In this paper we present several models based on neural networks to fill the missing periods of data within a total ozone time series, and models able to reconstruct the data series. The results released by the ANNs have been compared with those obtained by using classical statistics methods, and better accuracy has been achieved with the non linear ANNs techniques. Different network structures and training strategies have been tested depending on the specific task to be accomplished. © European Geosciences Union 2004.

Abstract:

So far, general circulation model studies have not been able to capture the magnitude and characteristics of the observed 11-year solar signal in the stratosphere satisfactorily. Here results from model experiments with the Freie Universität Berlin Climate Middle Atmosphere Model are presented that are in considerable agreement with observations. The experiments used realistic spectral solar irradiance changes, ozone changes from a two-dimensional radiative-chemical-transport model, and a relaxation toward observed equatorial wind profiles throughout the stratosphere. During Northern Hemisphere winter a realistic poleward downward propagation of the polar night jet (PNJ) anomalies, significantly weaker planetary wave activity, and a weaker mean meridional circulation under solar maximum conditions are reproduced in the model. The observed interaction between the Sun and the Quasi-Biennial Oscillation (QBO) is captured and stratospheric warmings occur preferentially in the west phase of the QBO. Only the magnitude of the anomalies during the dynamically active season improves, whereas the summer signal and the signal at low latitudes are still too weak. The results emphasize the important role of equatorial winds in achieving a more realistic solar signal by producing a more realistic wind climatology. Furthermore, they confirm recent results that equatorial winds in the upper stratosphere, the region dominated by the Semiannual Oscillation, are an important factor in determining interannual variability of the PNJ. Copyright 2004 by the American Geophysical Union.

Abstract:

The effect on stratospheric temperature of changing ozone is investigated by comparing two 5-member ensembles of 20-year Unified Model transient runs, one with a linear trend in ozone and one without. A significant stratospheric mean temperature trend of -0.17 K/ decade is attributed to ozone depletion. It is found that, although increasing the ensemble size to 20 members would have considerable benefits, increasing the ensemble size further would not dramatically improve confidence in the results. The timeslice approach to climate change modeling is found to produce similar temperature trends to the transient approach for this experiment. Copyright 2004 by the American Geophysical Union.