Generating Synthetic Monthly Net Radiation Data Conditioned on Wind Speed

Abstract

Aims: This study aimed at generating synthetic monthly net radiation data conditioned on wind speed over Port Harcourt, Benue, Kano and Enugu in Nigeria.
 Duration of Study: The daily maximum and minimum Relative-Humidity, maximum and minimum air temperature, solar radiation and wind speed data was obtained from the International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria for the period of thirty-four (34) years (1977-2010).
 Method: The Penman-Monteith (FAO-56) step by step method was used to compute the daily net radiation. The autocorrelation function was used to establish the fact that net radiation and wind speed exhibit the Markov property. Lastly, a two – state Markov Chain model and an indicator function of energy balance and imbalance was developed and used in the course of this work.
 Results: The finding reveals that net radiation is surplus over the study areas. The Lag one autocorrelation coefficient confirms the fact that an actual day net radiation and wind speed state depends on the previous day’s state. The monthly steady state probabilities of surplus net radiation conditioned on low wind speed is higher compared to monthly steady state probabilities of surplus net radiation conditioned on high wind speed. The indicator function of energy balance or imbalance reveals that there is energy imbalance over study areas.
 Conclusion: The generated synthetic net radiation data conditioned on wind speed preserved the characteristics of actual net radiation data when compared as observed in the study. This data is essential in the study of climate change, weather monitoring, agricultural meteorology and estimation of evapotranspiration.