نشریه پژوهشهای تغییرات آب و هوایی
پیاپی 13 (بهار 1402)

Climatic conditions shape the environmental situation of each region, something that the subsistence system of societies depends on and the belief system is based on. Therefore, any oscillation in the climate is not only able to change the way of life of humans but also affects their ideology and spirituality. Human cultural evolutions in the past twelve thousand years have been accompanied by abrupt climate events. These events have marked many ideological changes. In fact, from primitive rituals to advanced religions, all have been linked to the climate in some way and have had a strong connection with environmental conditions. During the pre-civilization period, a belief evolution occurred in the transition from the Younger Dryas to the early Holocene, which gradually developed into the middle Holocene. In the 4th millennium BC, with the emergence of urbanization, the formation of primitive priest-king governments, and the classification of society, the worship of natural phenomena turned into the worship of gods. Today's major religions, which have emerged since the second millennium BC, form two general groups that have completely separate natures according to the type of climate and environment of their origin. Indian polytheistic religions belonged to the villagers of wet and forested regions and Abrahamic monotheistic religions belonged to the pastoral-nomadic tribes of dry and desert regions. In this article, the relationship between climate and ideology in the course of human cultural evolution from the Neolithic to the Modern age is investigated. The main purpose is to raise awareness about the important mission of religious leaders in changing, modifying, and adjusting effectively some religious laws in line with the current climate change resilience, adaptation, and mitigation programs. This can also significantly reduce the possible domestic socio-political threats of the developing countries that are more involved with the climatic consequences of global warming.

Considering the importance of evaporation-transpiration in the hydrological cycle and its diverse applications in different sciences, calculating its value, especially the actual evaporation-transpiration, is of great importance. Considering that the abundance of vegetation is one of the most important factors influencing the temperature of the Earth's surface, this study aims to investigate the spatial autocorrelation of the Earth's surface temperature and evapotranspiration, the standardized precipitation index and the amount of albedo in relation to the vegetation in the city of Isfahan. Using data processing in the Google Earth Engine environment, a high-resolution MODIS data set was analyzed seasonally for each year during the period of 2000 to 2020. Then, evaporation and transpiration were compared and analyzed with the help of MODIS data and the Thornthwaite-Mather method, considering the calculated plant growth factor. In addition, drought prediction using the SPI index (one month, three months, six months, and twelve months) was done for the period from 2015 to 2044. After calculating the changes, a spatial analysis method (hot spots) was used in the ArcGIS software environment to identify and discover patterns and trends in the spatial data. The results of this research determined that, in the spring season, the highest percentage of NDVI does not correspond spatially with the lowest temperature, in other words, the percentage of vegetation index does not have an inverse relationship with the temperature of the Earth's surface. In the summer season, the highest percentage of the vegetation cover index is spatially compatible with the lowest temperature of the Earth's surface. In the winter season, the distribution of temperature patterns is completely different compared to other seasons due to the temperature-modulating role of vegetation using the mechanism of evaporation and transpiration.

Climate change has a wide range and affects various sectors such as agriculture, water, environment, etc. Climate change regulation is one of the international efforts to deal with this phenomenon. In this research, climate change adaptation laws in developing countries have been analyzed on two qualitative and quantitative levels. First, the laws are classified based on socio-ecological systems in the form of resource, actors, and governance systems. Then, based on these systems and their subsystems, the time and spatial trends of the laws are analyzed. Time analysis shows that climate change adaptation laws have been passed in developing countries from 1964 to 2021. The spatial analysis also indicates that Asia has the most laws in this field. In addition, the number of laws mentioned in the resource system is more than the other two systems, and this system has been considered in laws earlier than the others. In the next step, it is shown that water, transportation, and wide-economy subsystems have been mentioned more than other subsystems in each of the systems, and water and Land Use, Land-Use Change, and Forestry (LULUCF) subsystems, in the resource system, transportation and building in the actor system and social development in the governance system have been considered in the laws before the other subsystems. Finally, it was found that the passage of time and the increase in awareness about climate change have led to the expansion and comprehensiveness of the intended goals in the adaptation laws, and the climate change laws reduce the emission of greenhouse gases.

Climate change has had a significant impact on the global production of agricultural products. Studying the impact of climate change on the production of agricultural products is very important to take preventive decisions to improve agricultural production. The aim of the present study is to investigate the direct and indirect effects of spatial spillovers of climate change on orange production in 10 provinces of Iran, during the period from 2015 to 2019. The data used were obtained from the Ministry of Agriculture and the Meteorological Organization. First, to prove the existence of spatial dependence, Moran's test was performed. Then the spatial Durbin model was determined as the optimal model using the Wald test. The model was estimated using Stata17 software. The results of the spatial Durbin model (SDM) showed that the variables of average annual rain, average annual temperature and cultivated area have a positive and significant effect on the average yield oranges of Iran, while the variables of minimum annual temperature and maximum annual temperature have a negative effect on an average yield of oranges in Iran. In addition, the effect of spatial overflows of cultivated area and minimum annual temperature on orange yield is positive. Spatial overflows of average annual temperature have a negative effect of 1.68 on orange yield. Increasing the area of orange cultivation in the country increases the yield of oranges per unit area, therefore, it is recommended that the Ministry of Agriculture use the policy of integrating orange orchards in the country.

In the present study, the spatio-temporal changes of the desertification status of Gavkhoni Basin during 6 decades from 1961 to 2020 were determined by using the IMDPA desertification intensity model.According to the results of this research, it was determined that the first decade with an average score of 3.17, the fourth decade with a score of 2.22 and the last decade with a score of 2.36 are the highest, lowest and average intensity of desertification, respectively.Although the findings of this study showed that the trend of desertification variability based on the decade average is decreasing, but in the last two decades, the maximum area of the basin has been in the severe desertification class, which is a warning about the vulnerability of the basin to the phenomenon of desertification.From the results of this research, it was found that among the 3 indicators of climate criteria, the highest score (average 3.6) is related to Transo index and other indicators are in the next ranks.Desertification intensity zonation map of Gaukhoni basin showed that the central and eastern regions have higher risk and the northwestern and southeastern regions have lower risk. In this research, NDVI index was used to validate the climate model.The variability of this index over time indicates the increase of barren lands and the decrease of the area of water areas and vegetation.Therefore, it can be seen that the outputs of the NDVI index and the climate criterion confirm each other's findings. Although the results of other previous studies show that the consequences of global warming lead to an increase in temperature -evaporation and a decrease in precipitation in dry areas, however, with the location of the Gavkhoni basin in a dry area, the possibility of the impact of climate change on the aggravation of natural hazards will be significant.

The effective and timely monitoring of drought can help to develop drought systems and optimal management of water resources. Therefore, in this research, the drought situation in the synoptic stations of Fars province (Abadeh, Shiraz, Fasa and Lar) was investigated in different time scales (3, 6, 9 and 12 months) using precipitation-evaporation and transpiration (SPEI) and Multivariate standardized precipitation (MSPI) indices. The Mann-Kendall test was used in order to check the trend of the investigated indicators. Based on the results, the frequency of dry and wet periods is high in short-term time scales. But with the increase of time scales, the frequency of dry and wet periods decreases and their duration increases. In terms of the SPEI index, in the 3-month time scale, the most severe drought is at Abadeh station (-5.20) and the most severe drought is at Shiraz station (5.21). In the time scale of 6 months, the most severe drought and drought were observed in Abadeh (-3.45) and Shiraz (3.10) stations, respectively. In the time scale of 9 months, the most severe drought and drought are in Lar station with values of -3.63 and 2.48, respectively. Also, on a 12-month scale, the most severe drought is in Shiraz station (-3.37) and the most severe drought is in Abadeh station (2.37). Principal component analysis of SPI time series showed that the first principal component (PC1) can account for a large percentage of changes in the original SPI time series in all regions studied in this research. Also, the results showed that MSPIs follow the fluctuations of the SPI time series, especially in long-term dry and wet periods. So, partial wet and dry periods in severe and prolonged dry or wet periods may be excluded by MSPI.