Abstract
The last decades have been successively warmer at the Earth’s surface. An increasing interest in climate variability is appearing, and many research works have investigated the main effects on different climate variables. Some of them apply complex networks approaches to explore the spatial relation between distinct grid points or stations. In this work, the authors investigate whether topological properties change over several years. To this aim, we explore the application of the horizontal visibility graph (HVG) approach which maps a time series into a complex network. Data used in this study include a 60-year period of daily mean temperature anomalies in several stations over the Iberian Peninsula (Spain). Average degree, degree distribution exponent, and global clustering coefficient were analyzed. Interestingly, results show that they agree on a lack of significant trends, unlike annual mean values of anomalies, which present a characteristic upward trend. The main conclusions obtained are that complex networks structures and nonlinear features, such as weak correlations, appear not to be affected by rising temperatures derived from global climate conditions. Furthermore, different locations present a similar behavior and the intrinsic nature of these signals seems to be well described by network parameters.
Highlights
The global increase of surface air temperatures on different time and spatial scales was confirmed in past decades by distinct studies [1,2,3]
Conclusions fit of these average values.Daily mean temperature anomalies show common horizontal visibility graph (HVG) structures over different locations which remain almost constant in a relative long period of time
Lower thanthese in the case ofare clearly affected by a positive trend which can be related to the global conditions of rising γ
Summary
The global increase of surface air temperatures on different time and spatial scales was confirmed in past decades by distinct studies [1,2,3]. Some consequences include change in migrations patterns and abundances of many terrestrial, freshwater, and marine species, an increase of vulnerability of some ecosystems and many human systems, shrinking of glaciers, or negative impacts in crops like wheat or maize yield in many regions, influencing current global politics and society [5]. A major interest in climate variability has appeared among researchers. Most studies have used climate models and statistical approaches to investigate extreme events linked to global warming. The study of temperature variables is a widespread research field [7,8,9,10,11]
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