Avi Gozolchiani

Pattern of climate network blinking links follows El Niño events

Using measurements of atmospheric temperatures, we create a weighted network in different regions on the globe. The weight of each link is composed of two numbers —the correlations strength between the two places and the time delay between them. A characterization of the different typical links that exist is presented. A surprising outcome of the analysis is a new dynamical quantity of link blinking that seems to be sensitive especially to El Nino even in geographical regimes outside the Pacific Ocean. Copyright c EPLA, 2008

Improved El Niño forecasting by cooperativity detection

Although anomalous episodic warming of the eastern equatorial Pacific, dubbed El Niño by Peruvian fishermen, has major (and occasionally devastating) impacts around the globe, robust forecasting is still limited to about 6 mo ahead. A significant extension of the prewarning time would be instrumental for avoiding some of the worst damages such as harvest failures in developing countries. Here we introduce a unique avenue toward El Niño prediction based on network methods, inspecting emerging teleconnections. Our approach starts from the evidence that a large-scale cooperative mode—linking the El Niño basin (equatorial Pacific corridor) and the rest of the ocean—builds up in the calendar year before the warming event. On this basis, we can develop an efficient 12-mo forecasting scheme, i.e., achieve some doubling of the early-warning period. Our method is based on high-quality observational data available since 1950 and yields hit rates above 0.5, whereas false-alarm rates are below 0.1.

Very early warning of next El Niño

The most important driver of climate variability is the El Niño Southern Oscillation, which can trigger disasters in various parts of the globe. Despite its importance, conventional forecasting is still limited to 6 mo ahead. Recently, we developed an approach based on network analysis, which allows projection of an El Niño event about 1 y ahead. Here we show that our method correctly predicted the absence of El Niño events in 2012 and 2013 and now announce that our approach indicated (in September 2013 already) the return of El Niño in late 2014 with a 3-in-4 likelihood. We also discuss the relevance of the next El Niño to the question of global warming and the present hiatus in the global mean surface temperature.

Emergence of El Nino as an Autonomous Component in the Climate Network

We construct and analyze a climate network which represents the interdependent structure of the climate in different geographical zones and find that the network responds in a unique way to El Niño events. Analyzing the dynamics of the climate network shows that when El Niño events begin, the El Niño basin partially loses its influence on its surroundings. After typically three months, this influence is restored while the basin loses almost all dependence on its surroundings and becomes autonomous. The formation of an autonomous basin is the missing link to understand the seemingly contradicting phenomena of the afore-noticed weakening of the interdependencies in the climate network during El Niño and the known impact of the anomalies inside the El Niño basin on the global climate system.

Stability of Climate Networks with Time

The pattern of local daily fluctuations of climate fields such as temperatures and geopotential heights is not stable and hard to predict. Surprisingly, we find that the observed relations between such fluctuations in different geographical regions yields a very robust network pattern that remains highly stable during time. Using a new systematic methodology we track the origins of the network stability. It is found that about half of this network stability is due to the spatial 2D embedding of the network, and half is due to physical coupling between climate in different locations. We also find that around the equator, the contribution of the physical coupling is significantly less pronounced compared to off–equatorial regimes. Finally, we show that there is a gradual monotonic modification of the network pattern as a function of altitude difference.

Climate network structure evolves with North Atlantic Oscillation phases

We construct a network from climate records of temperature and geopotential-height in two pressure levels at different geographical sites in the North Atlantic. A link between two sites represents the cross-correlations between the records of each site. We find that within the different phases of the North Atlantic Oscillation (NAO) the correlation values of the links in the climate network are significantly different. By setting an optimized threshold on the correlation values, we find that the number of strong links in the network increases during times of positive NAO indices, and decreases during times of negative NAO indices. We find a pronounced sensitivity of the network structure to the NAO oscillations which is significantly higher compared to the observed response of spatial average of the climate records. Our results suggest a new measure that tracks the NAO pattern. Copyright c EPLA, 2012 Introduction. - A network approach has recently been applied in order to follow climate dynamics (1,2). The nodes of the climate network are geographical sites. The dynamics recorded in each site is composed of its intrinsic dynamics and the coupling with the dynamics of other sites. The cross-correlations due to the coupling between the dynamics in two different sites are represented in our network by a link between the sites (see (3) for a lab experiment that demonstrates the relation between the coupling and the correlation). The maximum value of the correlation might appear with a time delay between the two data records. The climate network approach has recently led to the discovery of several novel insights related to El-Nino dynamics (4-12).

Climate Networks Based on Phase Synchronization Analysis Track El-Niño

Eight networks, based on temperature records from four different geographical regions in two pressure levels, are created in resolute snapshots of time for the last 28 years. The links represent the level of robust phase synchronization between places in the interior of each regime. The number of links appears to be a sensitive measure of the El-Nino influence even on regimes far away from the El-Nino basin. A comparison between the statistical information of the phase synchronization network and the similar information obtained previously using cross correlation technique is provided.

Teleconnection Paths via Climate Network Direct Link Detection.

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

Global climate network evolves with North Atlantic Oscillation phases: Coupling to Southern Pacific Ocean

We construct a network from climate records of the atmospheric temperature at the surface level, at different geographical sites in the globe, using reanalysis data from years 1948–2010. We find that the network correlates with the North Atlantic Oscillation (NAO), both locally in the North Atlantic, and through coupling to the Southern Pacific Ocean. The existence of tele-connection links between those areas and their stability over time allows us to suggest a possible physical explanation for this phenomenon.

Influence of autocorrelation on the topology of the climate network.

Different definitions of links in climate networks may lead to considerably different network topologies. We construct a network from climate records of surface level atmospheric temperature in different geographical sites around the globe using two commonly used definitions of links. Utilizing detrended fluctuation analysis, shuffled surrogates, and separation analysis of maritime and continental records, we find that one of the major influences on the structure of climate networks is due to the autocorrelation in the records, which may introduce spurious links. This may explain why different methods could lead to different climate network topologies.