Abstract

Aim. Taking care of the environment on Planet Earth is still important and has be- come popular exceeding boundaries of science. Therefore description of climate changes has evolved into the concept of Global Warming since the 20th century. On the other hand, principles of thermodynamics where temperature is defined locally (not globally) are still valid. In my research I have applied tools like ChatGPT to detect possible contra- dictions and propose bridging gaps between statistical physics and the concept of global warming. Methods. The concept of temperature based on calculations of local particles’ kinetic energy in a microcanonical ensemble has been confronted with the concept of so called ‘average’ temperature in ‘global’ warming. The principles of Kinetic Theory and Statisti- cal Ensembles provided by statistical physics have been applied to ChatGPT based on natural language Results. Contradictions between the concept of average temperature in global warming and the concept of temperature based on local particle kinetic energy arise due to the different scales, heterogeneity, presence of feedback mechanisms, and boundary conditions. According to the chatGPT’s verdict, the concept of temperature based on calculations of local particles kinetic energy in the microcanonical ensemble is statistically more accurate. Conclusion. The concept of so called ‘global’ warming (confronted with the physics- based concept of temperature, providing a more accurate and nuanced understanding of temperature changes in different scales and contexts) should be replaced by the idea of local warming which is consistent with the concept of temperature based on calcula- tions of local particles kinetic energy in the microcanonical ensemble and experimental measurements provided by NASA. Therefore, talking about local (not global) warming is more reasonable when our goal is to prevent our coexistence with environment on Planet Earth from disasters.

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