  The need to understand the role of statistical methods for the forecasting of
climatological parameters cannot be trivialized. This study gives an in depth
review on the different variations of the Mann-Kendall (M-K) trend test and how
they can be applied, regression techniques (Simple and Multiple), the
Angstrom-Prescott model for solar radiation, etc. The study then goes ahead to
apply some of them with data obtained from the Nigerian Meteorological Agency
(NiMet), and applying tools like the python programming language and Wolfram
Mathematica. Results show that the maximum ambient temperature for Calabar is
increasing (Z=2.52) significantly after the calculated p-value < 0.05
(significant level). The seasonal M-K test was also applied for the dry and wet
seasons and both were found to be increasing (Z=3.23 and Z=4.04 respectively)
after their calculated p-values < 0.05. The relationship between refractivity
and other meteorological parameters relating to it was discerned using partial
differential equations giving the gradient of each with refractivity; this was
compared with results from the correlation matrix to show that the water vapour
contents of the atmosphere contributes significantly to the variation of
refractivity. Multiple linear regression has also been adopted to give an
accurate model for the prediction of refractivity in the region after the
residual error between the calculated refractivity and predicted refractivity
was minimal.
