No abstract

Climate change-induced extreme heat events are becoming a major issue in different parts of the world, especially in developing countries. The assessment of regional and temporal past and future change in heat waves is a crucial task for public health strategies and managements. The historical and future heat index (HI) time series are investigated for temporal change across Iran to study the impact of global warming on public health. The heat index is calculated, and the nonparametric trend assessment is carried out for historical time series (1981-2010). The future change in heat index is also projected for 2020-2049 and 2070-2099 periods. A rise in the historical heat index and extreme caution conditions for summer and spring seasons for major parts of Iran are notable for historical (1981-2010) series in this study. Using different climate change scenarios shows that heat index will exceed the critical threshold for human adaptability in the future in the country. The impact of climate change on heat index risk in Iran is significant in the future. To cope with this crucial situation, developing early warning systems and health care strategies to deal with population growth and remarkable socio-economic features in future is essential.

Future changes in extreme rainfall arising from climate change may have a significant influence on flood and water erosion control and management strategies to a great extent. The maximum daily rainfall time series were projected for 2020-2049 using six general climate models and two scenarios through artificial neural networks for 22 stations across the north of Iran. The results indicate a reduction of between −3.0 and −0.2% in maximum rainfall for the selected stations and five out of six of the general climate models. The changes in the frequency and magnitude of extreme rainfall were then investigated by fitting a generalized extreme value distribution to the historical (from 1981 to 2010) and projected maximum rainfall. The location parameter of the generalized extreme value distribution fitted to the projected maximum rainfall does not show a significant change while the scale and shape parameters exhibit significant changes compared to the historical period. Estimating the 2, 50 and 100 year return periods showed that the maximum rainfall will have a reduction in the probability of large amounts across the region compared with the base period while the number of extraordinary extreme events may show growth. As a region vulnerable to flash floods and water erosion due to rainfall characteristics and land use change from forest to agriculture, the results may send an alarm to define long term and effective strategies for future flood control management in the region.

No abstract

No abstract