Meteorological analysis of the relationship between climatic parameters: understanding the dynamics of the troposphere

• Published in: Theoretical and applied climatology 2022-11, Vol.150 (3-4), p.1677-1698
• Main Authors: Agbo, Emmanuel P., Edet, Collins O.
• Format: Article
• Language: English
• Subjects: Adiabatic; Adiabatic processes; Ambient temperature; Analysis; Aquatic Pollution; Atmospheric pressure; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Climate; Climate science; Climatology; Condensation; Correlation; Correlation analysis; Derivatives; Dew; Dew point; Differential equations; Earth and Environmental Science; Earth Sciences; Equivalence; Equivalent potential temperature; Homogeneity; Humidity; Lifting; Lifting condensation level; Mathematical analysis; Maximum temperatures; Meteorological parameters; Methods; Mixing ratio; Original Paper; Parameters; Partial differential equations; Potential temperature; Process parameters; Programming languages; Rainy season; Refractive index; Refractivity; Regression; Regression analysis; Robustness (mathematics); Specific humidity; Temperature data; Trend analysis; Trends; Troposphere; Vapor pressure; Vapors; Vapour pressure; Variation; Waste Water Technology; Water Management; Water Pollution Control; Weather; Wet season
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-022-04226-x

Understanding the relationship between the variations of meteorological parameters is vital in tackling the climatic problem. This paper presents methods for analyzing parameters that directly or indirectly relate to each other, and accurate methods for interpreting their results. Using obtained and calculated data for 14 years, we adopt the Mann–Kendall (M–K) test for the trend analysis; the Pettit and the standard normal homogeneity test (SNHT) was also used to test for homogeneity or change points for the annual series. Using the Python programming software, the correlation matrixes and linear regression pair plots have been adopted to discern the relationship between all parameters. To crystalize results, partial derivatives relating to the equivalent potential temperature (EPT) for a pseudo-adiabatic process with parameters affecting its variation from equations are obtained. The magnitude of these derivatives’ gradients was used to bolster regression results, showing the mixing ratio (MR) of air as the parameter with the most effect on EPT variation. The MK test results show that the atmospheric pressure (AP) and average ambient temperature (AT) were all increasing significantly for all variations (annual, dry and wet seasons). In contrast, others varied between dry and wet seasons after adopting a benchmark significance level of 5% (0.05). The correlation matrixes and linear regression pair plots show a strong relationship between the variations of refractivity, EPT, the temperature at the lifting condensation level (T L ), MR, vapor pressure (VP), specific humidity (SH), and the dew point temperature (DPT). The potential temperature (PT), saturated vapor pressure (SVP), saturated mixing ratio (SMR), and the AT relationships showed a robust positive correlation/regression. This correlation offers a connection between the AT and the PT. The processes, including the partial derivatives, pair plots, correlation matrixes, and tests for trends, provide a solution to the meteorological analysis problem. Results and methods can be applied in other regions. Graphical abstract Highlights The gradient of the partial differential equations relating the equivalent potential temperature with all parameters affecting her variability shows the direct effect of these parameters on the variation of the equivalent potential temperature. The correlation matrixes and linear regression pair plots shows the similarity between the trends of all meteorological parameters.