When the Earth goes white: the Snowball Earth attractor

Using an intermediate complexity climate model we investigate the so-called snowball Earth transition. For certain values (including its current value) of the solar constant, the climate system allows two different stable states: one of them is the snowball Earth, covered by ice and snow, and the other one is today's climate

The theory of parallel climate realizations as a new framework for teleconnection analysis

Teleconnections are striking features of the Earth climate system which appear as statistically correlated climate-related patterns between remote geographical regions of the globe. In a changing climate, however, the strength of teleconnections might change, and an appropriate characterization of these correlations and their change (more appropriate than detrending the time series) is lacking in the literature. Here we present a novel approach, based on the theory of snapshot attractors, corresponding in our context to studying parallel climate realizations. Imagining an ensemble of parallel Earth systems, instead of the single one observed (i.e., the real Earth), the ensemble, after some time, characterizes the appropriate probabilities of all options permitted by the climate dynamics, reflecting the internal variability of the climate. We claim that the relevant quantities for characterizing teleconnections in a changing climate are correlation coefficients taken over the temporally evolving ensemble in any time instant. As a particular example, we consider the teleconnections of the North Atlantic Oscillation (NAO). In a numerical climate model, we demonstrate that this approach provides the only statistically correct characterization, in contrast to commonly used temporal correlations evaluated along single detrended time series. The teleconnections of the NAO are found to survive the climate change, but their strength might be time-dependent

Ensemble-based analysis of the pollutant spreading intensity induced by climate change

Abstract The intensity of the atmospheric large-scale spreading can be characterized by a measure of chaotic systems, called topological entropy. A pollutant cloud stretches in an exponential manner in time, and in the atmospheric context the topological entropy corresponds to the stretching rate of its length. To explore the plethora of possible climate evolutions, we investigate here pollutant spreading in climate realizations of two climate models to learn what the typical spreading behavior is over a climate change. An overall decrease in the areal mean of the stretching rate is found to be typical in the ensembles of both climate models. This results in larger pollutant concentrations for several geographical regions implying higher environmental risk. A strong correlation is found between the time series of the ensemble mean values of the stretching rate and of the absolute value of the relative vorticity. Here we show that, based on the obtained relationship, the typical intensity of the spreading in an arbitrary climate realization can be estimated by using only the ensemble means of the relative vorticity data of a climate model

Where are the coexisting parallel climates? Large ensemble climate predictions from the point of view of chaos theory

We review recent results of large ensemble climate projections considering them to be simulations of chaotic systems

On the Time Evolution of the Arctic Oscillation and Related Wintertime Phenomena under Different Forcing Scenarios in an Ensemble Approach

The Arctic Oscillation (AO) and its related wintertime phenomena are investigated under climate change by 2099 in an ensemble approach using the CESM1 Large Ensemble and the MPI-ESM Grand Ensemble with different RCP scenarios. The loading pattern of the AO is defined as the leading mode of the empirical orthogonal function (EOF) analysis of sea level pressure from 20° to 90°N. It is shown that the traditional AO index (AOI) calculation method, using a base period in a single climate realization, brings subjectivity to the investigation of the AO-related phenomena. Therefore, if an ensemble is available, the changes in the AO and its related phenomena should rather be studied by a reconsidered EOF analysis (snapshot EOF) introduced herein. This novel method is based only on the instantaneous fields of the ensemble, and hence it is capable of monitoring the time evolution of the AO’s pattern and amplitude. Furthermore, the instantaneous correlation coefficient r can objectively be calculated between the AOI and, for example, the surface temperature, and thus the time dependence of the strength of these connections can also be revealed. Results emphasize that both the AO and the related surface temperature pattern are nonstationary and their time evolution depends on the forcing. The AO’s amplitude increases and the Pacific center strengthens considerably in each scenario. Additionally, there exist such regions (e.g., northern Europe or western North America) where r shows remarkable change (0.2–0.4) by 2099. This study emphasizes the importance of the snapshot framework when studying changes in the climate system