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

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Abstract

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 (TL), 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.

  • The correlation matrixes and linear regression pair plots show a strong relationship between the variations of refractivity, equivalent potential temperature, temperature at the lifting condensation level, mixing ratio, vapor pressure, specific humidity, and the dew point temperature.

  • The Standard Normal Homogeneity test (SNHT) and the Pettitt test were applied to test for homogeneity and both tests agree that the atmospheric pressure and maximum temperature data are inhomogeneous and have significant change points.

  • The potential temperature, saturated vapor pressure, saturated mixing ratio, and the average temperature relationships showed a robust positive correlation/regression.

  • Linear regression pair plots as well as the results from the correlation matrixes show a strong relationship between the parameters relating to equivalent potential temperature and refractivity.

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Data availability

Data were obtained from the Nigeran Meteorological Agency (NiMet) and will be made available on request.

Code availability

The link to the codes for the study can be accessed from https://github.com/Emmaestro001/Meteorological-Analysis-of-the-Relationship-Between-Climatic-Parameters.

Abbreviations

EPT:

Equivalent potential temperature

ET:

Equivalent temperature

PT:

Potential temperature

MT :

Maximum temperature

T L :

Absolute temperature at the lifting condensation level

MR:

Mixing ratio

SMR:

Saturated mixing ratio

VP:

Vapor pressure

SVP:

Saturated vapor pressure

DPT:

Dew point temperature

SH:

Specific humidity

RH:

Relative humidity

AT:

Average temperature

AP :

Atmospheric pressure

M–K :

Mann–Kendall

SSE:

Sen’s slope estimator

p value:

Probability value

EM:

Electromagnetic

VHFs:

Very high frequency(ies)

ITU:

International Telecommunication Union

SNHT:

Standard normal homogeneity test

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Acknowledgements

The authors thank the reviewer for his comments on the manuscript, which have greatly improved the study and made it more holistic.

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Authors and Affiliations

  1. Department of Physics, Cross River University of Technology, Calabar, Nigeria

    Emmanuel P. Agbo & Collins O. Edet

  2. Institute of Engineering Mathematics, Universiti Malaysia, Perlis, 02600, Arau, Perlis, Malaysia

    Collins O. Edet

  3. Faculty of Electronic Engineering Technology, Universiti Malaysia, Perlis, 02600, Arau, Perlis, Malaysia

    Collins O. Edet

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Emmanuel P. Agbo designed the study, handled the review, acquired and analyzed, and interpreted the data; Collins O Edet interpreted the data and revised the article critically for important intellectual content. Both authors gave their approval to the final manuscript after reading it.

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Correspondence to Emmanuel P. Agbo.

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Agbo, E.P., Edet, C.O. Meteorological analysis of the relationship between climatic parameters: understanding the dynamics of the troposphere. Theor Appl Climatol 150, 1677–1698 (2022). https://doi.org/10.1007/s00704-022-04226-x

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