Precipitation

Climate change is the main phenomenon that directly affects the world environment, and changes in the environment affect economic sectors differently. The most important impacts of climate change would be on enhancing the average global temperature and the decrease in precipitation. The agricultural sector is the first and most affected sector in the climate change. We examined the impact of temperature and precipitation variables on the agricultural yield for three common products namely fruits, rice and corn in 14 OIC countries including Iran. The share of employment in the agricultural sector as compared to the total employed is a control variable. By estimating the model using the panel data method over the years 1992 and 2015, the results indicate a negative effect of temperature on the agricultural sector. Precipitation has a positive effect and the share of employment in agriculture has a negative effect.

South Africa is a water-scarce country that is highly dependent on agriculture. This means that the local impacts of climate altering phenomenon, such as the El Niño-Southern Oscillation (ENSO), are critical to understand. At a broad scale, these systems are known to affect rainfall distribution, resulting in drought (flood) conditions during El Niño (La Niña) events in the majority of the country, and the converse in the southwestern Cape. However, fine resolution analyses of local impacts of these events have been restricted to the coastal zone, and little is known for the interior. We explore the uniformity in the transition of the climatic deviations [for minimum temperature (T_min) and maximum temperature (T_max), and rainfall] along a 12-site transect spanning the South African interior. The majority of the deviations determined were not statistically significant which suggests that the common understanding of the climatic impacts of ENSO events in South Africa is not well understood. However, it should be acknowledged that all the locations used in this research, aside from Hermanus, were located inland which may be the reason the deviations at these locations were not statistically significant.