<p>In a tropical region like Nigeria, accurate estimation and chaotic signatures of global solar radiation (<i>R_s</i>) are essential to the design of solar energy utilization systems in PV technology companies and one of the plant growth determinants in Agriculture. The <i>R_s</i> model is a function of solar declination angle, temperature difference, and relative humidity. In this paper, the daily re-analyzed atmospheric data obtained from the archive of ERA-Interim was used to estimate the nonlinear Global Solar radiation model and investigated chaotic signatures across the tropical climatic regions of Nigeria. The well-known statistical tools were used to analyze the chosen meteorological parameters and the correlation was found to be perfect, close with low values of RMSE across the selected regions over Nigeria. For proper modeling and prediction of the underlying dynamics, the extensive chaotic measures of phase space reconstruction using recurrence plots and recurrence quantification analyses are also presented, analyzed and discussed with the appropriate choice of embedded dimension, m, and time delay &tau;.</p> <p> The radiant energy from the sun is one of the most available and renewable resources across the season in a tropical region like Nigeria. The information, therefore, suggests how vital the solar irradiance can be useful in Agriculture and Photovoltaic technology companies. Based on the scarcely gauged of global solar radiation (GSR) at meteorological stations in developing countries. This demand necessitates a better understanding of the underlying dynamics for better prediction mostly by the nonlinear Global Solar radiation model estimate and chaotic signature measurement. The optimum usage of meteorological parameters such as solar radiation, relative humidity and temperature difference needs further studies, using RPs and RQA measures. However, several data such as rainfall data, geomagnetic data, ionospheric data, wind speed data etc obtained from different parts of the world have been estimated with several models and applied to RQA measures for better prediction and modeling. Using RPs and RQA, features due to external effects such as harmattan and intertropical discontinuity (ITD) on solar radiation data in this tropical region were uniquely identified. Meanwhile, the inverse characteristic behavior of solar radiation and relative humidity were vividly maintained. The results show a very low value of RMSE while the value of <i>R²</i> is very closed to 1, which depicts a good prediction for all locations. However, the highest values of both SSE and RMSE, as well as the lowest value of <i>R²</i> were observed in kano station, which indicates high solar irradiance location. The RPs reviewed the observed clusters points around the parallel diagonal lines with short segments, which implies the presence of chaos. Additional complex measure, the RQA also shows that the solar radiation during the dry season of the months has lower values of Lmax, determinism and entropy, and higher values during the wet season of the months.</p>