Abstract: When dealing with the general problem of turbulence there are several theoretical and practical related problems: the generation (origin) of fluid fluctuations (real eddies and mathematical vorticity), the turbulent transfer of kinetic energy, heat and mass, drag resistance, clean-air fluctuations, hurricanes and tornadoes, atmospheric circulation and plumes, and other natural or human-induced phenomena. We are tempted by the intent to formulate a unified approach, where turbulence is the general feature of these problems. We attempt here to draw some connections between the theoretical turbulence modeling and the experimental results interpreted using such models and the reality of large-scale natural events strongly related to anthropogenic climate changes, such as heatwaves and the cooling effect of aerosols. In fact we believe that more sophisticated practical results could be drawn from connecting theoretical turbulence studies to natural real phenomena, especially those under the influence of climate change. The mathematical modeling aimed at increasing predictability did not produce yet a fundamental breakthrough in the understanding of turbulence. In dealing with real turbulent flows we constantly rely on phenomenological approaches. To date, the large-scale spatio-temporal characteristics of turbulence has yet to be fully understood, due to the lack of sufficient in situ detection instruments in the atmosphere. As such, there is much room for improvement in turbulence-related parameterizations in global weather and climate prediction models. Short presentations of the heatwaves and cooling effect of aerosols are considered from the point of view that the study of weather data and the use of statistical modeling should be coupled with the fundamental studies on the fluid dynamics features of turbulence which play the primary role in the atmospheric circulation and thus in weather and climate changes.
Abstract: When dealing with the general problem of turbulence there are several theoretical and practical related problems: the generation (origin) of fluid fluctuations (real eddies and mathematical vorticity), the turbulent transfer of kinetic energy, heat and mass, drag resistance, clean-air fluctuations, hurricanes and tornadoes, atmospheric circulation ...Show More
Abstract: Understanding climate variability and monitoring time-series trends of temperature and rainfall is crucial for the sustainable development of our planet. This study utilized historical data from the Global Historical Climatology Network-Monthly (GHCN-M) provided by the National Centers for Environmental Information (NCEI) to analyze the temperature and rainfall data from 2015 to 2022. The analysis was conducted using Python 3.1.1 on Anaconda Jupyter Notebook and the package matplotlib 3.2.1 was used for data visualization. The results revealed a pattern of maximum rainfall between March to May for the years 2020, 2021, and 2022, while for the years 2017, 2018, and 2019, the maximum rainfall was recorded in October, December, and November. Additionally, the annual maximum rainfalls were recorded in the years 2020 and 2022, and the annual maximum temperatures for all study years were recorded in January, February, and March months. On the other hand, the annual minimum temperatures for all study years occurred in June, July, August, and September months. Similarly, annual average temperatures were recorded in January, February, and March months. This study emphasizes the importance of monitoring climate change and its impacts on our planet. By understanding climate variability and time-series trends, we can better prepare for the future and work towards a sustainable world.
Abstract: Understanding climate variability and monitoring time-series trends of temperature and rainfall is crucial for the sustainable development of our planet. This study utilized historical data from the Global Historical Climatology Network-Monthly (GHCN-M) provided by the National Centers for Environmental Information (NCEI) to analyze the temperature...Show More