Climate Change Dynamics and Modeling: Future Perspectives

Dear Colleagues,

Terms such as Stick Hockey effect, slogans such as “There is no planet B” and proposals such as “Go green to save the blue” are consistently used in daily news and refer to the theme of climate change, a theme to which an ever greater need is attributed today, and not only by the scientific community. It is well known that the history of the climate has ancient origins. In fact, the Greek term “klima” designated the inclination of the Sun’s rays with respect to the Earth’s surface, thus testifying to the understanding of the correlation between the flow of solar energy and daily and seasonal temperature variations. The Earth’s climate change is shaped in fascinating ways by the atmospheric processes that fuel climate change, by increasing water vapor, withdrawing snow and ice, or changing cloud cover. It is important to know how dynamic and wet processes, clouds, and convection control the Earth’s climate sensitivity, change in the hydrological cycle, and natural variability. In fact, the climate has a substantial influence on both humanity and the Earth. Strong precipitations and high temperature can cause increased carbon accumulation in plants and soil due to vegetation growth, or increased carbon release into the atmosphere. These difficulties have been present since the beginning of humanity, and for these reasons, people have had to take into account the climate of their respective regions and adapt to it accordingly. Thus, people throughout history have struggled to understand climatic variations. In the past, primarily mythological and religious explanations were used to provide predictions, but in the meantime, climate evolved as a science, allowing us to elaborate on ever more sophisticated representations of the observed phenomena. Such a description of the climate now involves a very broad range of skills, corresponding to several domains of science including physics, chemistry, biology, and geology. Due to the complexity of the climate, most of the analyses dedicated to the quantitative estimation of climate change or climate variability are based on the employment of numerical models. In order to better analyze climate variability and its reaction to a perturbation, a lot of information is provided on the interactions between the different elements of the climate system and on the dominant feedbacks. Using this information, it is possible to understand the main causes of past climate changes and evaluate climate change projects over the next centuries or millennia. Furthermore, another goal is to provide students with the foundation for understanding what climate models look like and how they can be used to make quantitative estimates of climate variability and climate change, as well as to illustrate how models could be used to better understand the important links of climate science.  Furthermore, in addition to the usual modeling techniques, given the amount of data to be pre-processed and/or modeled, when necessary, machine learning techniques (including deep learning) are used, for example, for the analysis of historical series (big historical/heterogeneous data) or even for model training. This Special Issue titled “Climate Change Dynamics and Modeling: Future Perspectives” is focused on the varied range of interdisciplinary issues related to climatic changes. To this end, a series of past climate study approaches will be used, and innovative interpretative models will be presented together with a comparison to the most important approaches currently adopted. Furthermore, it is well known that floods, droughts, sea level rise, and landscape changes greatly influence several fields and aspects, such as, for example, national and international economics and politics stakeholders and ethical issues. In this framework, the authors contributing to the Special Issue will have the opportunity to communicate the contents of their studies to scholars operating in other climate-related disciplines and to interested non-disciplinarians.

Dr. Maria Teresa Caccamo
Prof. Dr. Salvatore Magazù
Guest Editors

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• climate change
• climate dynamics
• climate modeling
• physical and mathematical approaches
• interdisciplinary approach
• transdisciplinary approach
• machine learning