Spatial Distribution of Changes in the Trend of Extreme Precipitation Indices in Northwest Iran and Its Relationship with The General Circulation of the Atmosphere in the Region

IntroductionExtreme precipitation has a significant impact on the frequency, severity, and duration of natural hazards, such as floods, droughts, and landslides. This has a significant impact on human life, the economy, natural ecosystems, and agriculture (Song et al, 2015: 34). Between 1880 and 2012, there was a 0.85 °C increase in the average global temperature, with a general increase in precipitation in the mid-latitudes of the Northern Hemisphere (IPCC, 2013: 2; Lio et al, 2017: 822). In addition, there is a possibility of a rise in extreme precipitation in the future (Klein Tank et al, 2006: 1), and so far, the reason for these changes and their relationship with the general circulation of the atmosphere have not been considered. The aim of this study is to analyze the trend of changes in extreme precipitation indices in northwestern Iran and its association with the general circulation of the atmosphere. Material and MethodsIn order to analyze the changes in extreme precipitation events in northwestern Iran, daily precipitation data was collected from 20 synoptic stations in the region between 1986 and 2010. The region that is being studied encompasses West Azerbaijan, East Azerbaijan, Ardabil, Zanjan, and Kurdistan. In assessing limit events, high quality and reliable long-term climate data with daily (or higher) resolution is required (Clintanak et al., 2009: 9). The first step was to examine the quality control and homogeneity of data. The RClimDex software package, introduced as a standard tool by ETCCDI, was used to perform quality control and evaluate data homogeneity in this research. The Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) introduced 11 indexes to examine changes in precipitation level indices in northwest Iran. RClimDex software calculates these indicators with a significance level of 0.05. This process seeks to establish a standard set of indicators to examine and compare the characteristics of different regions. The software was used to calculate precipitation indices and display the trend and rate of change on a map. Results and DiscussionThe extreme precipitation indices were calculated to determine the regional trend and percentage of stations with positive and negative trends for the studied stations in northwestern Iran. Afterward, a map was created showing the spatial distribution of the slope for each of the indices. All precipitation indexes, except for the maximum growth period index (CDD), are declining according to the results. The probability of precipitation has decreased due to the more stable winter atmosphere in the region from the point of view of general atmospheric circulation. The region's spring atmosphere, similar to that of winter, shows an increase in stability, which will result in less rainfall. In summer, except for the coastal provinces of the Caspian Sea and the coasts of the Oman Sea, the rest of the country has recorded a decrease in rainfall of 1 mm per day. Most parts of the country experienced an increase in atmosphere thickness to 6 meters in autumn in the study area. Autumn in the region is typically stable and barotropic, but the study area is experiencing less rainfall. This study examines the trend of changes in extreme precipitation indices in northwestern Iran and its relation to a large-scale general circulation of the atmosphere. According to the results, 75% of stations in the region are experiencing a decrease in the maximum daily rainfall (RX1day) and 80% are experiencing a decrease in the maximum five-day rainfall (RX5day). While both the very wet (R95P) and ultra-wet (R99P) day indices are experiencing a downward trend, the R95P index is experiencing a more pronounced downward trend. All three indices R10, R20, and R25 have been declining for the past 25 years, but the R10 index has fallen more rapidly than the other two indices. Sarab station has a positive CWD trend alone, while other stations have a negative and decreasing trend of this index. In most stations throughout the region, the CDD index is increasing. In 85% of stations in the region, the PRCPTOT index is decreasing and there is a noticeable increase in rainfall. The SDII index is experiencing a decrease in 60% of the stations in northwestern Iran, while an increase is being observed in 40%. All precipitation indices, except for the CDD index, have a decreasing trend in general. Drawing and analyzing combined difference maps for geopotential height parameters of 500 hPa, relative rotation of 500 hPa, vertical velocity (omega), rainwater and precipitation rate to study the general atmospheric circulation of the region indicates an increase in altitude has led to a 500 hPa increase in climate stability in the study area (northwest of Iran). The study of omega and relative rotation shows that the region is experiencing a decrease in upward currents and positive rotation. The lack of atmospheric moisture load and rainfall in all seasons can be seen in rainfall water difference maps and rates. Precipitation indices and the general circulation model of the region's atmosphere are compared, indicating that the moisture load of the region's atmosphere has decreased, resulting in drought

Evaluation of Changes in Reference Evapotranspiration in Iran Over the Last Decades

IntroductionToday, one of the biggest challenges for mankind is the lack of water resources in the world. This is one of the limiting factors for agricultural development in Iran in recent years. Identifying and estimating reference evapotranspiration (ET0) can help make decisions to plan and mitigate the use of water resources and appropriate management methods in the country. Thus, one of the ways to reduce water losses in the fields is good irrigation planning, which is based on accurate estimation of the water requirements of plants and ET0. The aim of this research is to evaluate the ET0 changes using temperature and radiation methods, statistical tests such as Man-Kendall, Sen’s slope analysis in Iran over the last decades. Material and MethodsIn the current research, primary evaluation of data, such as sorting, etc., was conducted in the desired ET0 calculation format. For the classification of weather station climate, annual precipitation and temperature data from 1976 to 2020 were used. To estimate ET0, maximum temperature (°C), minimum temperature (°C), average relative humidity (%), wind speed (m/s), and sunshine hour (h) were used on a monthly time scale. The Koppen-Geiger climate classification method was used to classify the meteorological stations studied. For estimating monthly and annual ET0, the methods such as FAO Penman-Monteith (FAO PM), Hargreaves-Samani (H-S), and Priestley Taylor (PT) were used. Then, an attempt was made to introduce the appropriate model for each climate by using the results of ET0 estimation using RMSE and MAE. ET0 maps were produced with more accuracy based on the results of the RMSE. Among different geostatistical interpolation methods, the Kriging method worked better than the other methods, which was used as the superior interpolation method. The Mann-Kendall non-parametric test was used to detect the trend of time series. To examine the trend slope in the ET0 time series, the  non-parametric Sen's slope method was used. For qualitative analysis of the ET0 trend, the innovative ITA trend was used for all three methods on a yearly basis Results and DiscussionIn this research, the station climate classification results show that climate varieties in Iran are high and can be divided into seven different climates. According to the RMSE and MAE statistical evaluations, the H-S method in semi-desert climates, dry and cold steppe, dry desert, temperate with dry summers, very hot semi-desert and snowy climates; and PT method in dry desert climates, moderate with dry summers, semi-desert, and very hot semi-desert were recognized as superior methods. In the temperate and rainy climate zone of Bandar Anzali, the H-S, and in Rasht, the PT methods were evaluated as suitable methods. Based on the monthly ET0 estimation, the amount of ET0 is significantly reduced in the northwestern, western and northeastern regions during the winter season. In winter, ET0 decreases as a result of increased air moisture. In the spring season, the amount of ET0 declined in the northern latitudes. The onset of convective spring rains in the northern latitudes of the country is one of the reasons behind this reduction in ET0 in these areas. During the summer season, regions in the upper latitudes have a lower ET0 because of their lower temperature than southern latitudes. In the autumn, there is a lower ET0 in the northern latitudes than in the southern regions of the country. Trend analysis shows that with the exception of the Arak station with an ET0 downward trend in April, most ET0 time series have a positive trend in the rest of the stations. Sanandaj is the only station that has a downward trend in ET0 in November. An increasing trend is observed in most of the studied stations, but in some other stations such as Arak and Sanandaj, a downward trend in the Reference Evapotranspiration may be observed. Finally, the results of the Innovative Trend Analysis (ITA) showed an upward trend in the amount of ET0 in both high and low areas in all seasons. This shows the increase of the long-term ET0 trend, indicating the increase in water requirements for plants in Iran. In the present study, climatic data from 40 stations from 1976 to 2020 were used to estimate ET0 in Iran. The Koppen- Geiger method was also used to classify the weather stations into the seven climates classes. The FAO PM, H-S, and PT models were used to estimate monthly and annually ET0. To choose the appropriate method of estimating ET0 in each climate zones; the H-S and PT methods were compared with the FAO PM method, and validated using RMSE and MAE statistics. Due to the involvement of various processes in ET0 changes, the best estimation method differs between stations. In this research, the H-S method was more compatible than the PT method at most of the stations.  Results have been presented as monthly and annual zoning maps. The zoning results of the three ET0 calculation methods mentioned showed that changes in climatic elements in different regions and periods have different effects on the ET0 value. The trend in ET0 changes using the Mann-Kendall test showed that the ET0 data at most stations have an increasing slope. Only two stations (Arak representing the top stations and Sanandaj representing the bottom station) have a decreasing slope. Based on the results of the ET0 time series analysis using ITA, the ET0 trend increased at all stations representative of the high and low elevation zones. Overall results show that TE0 has increased in most parts of the country, resulting in increased water requirements for plants. In the absence of effective management, Iran will face a serious water crisis in the future

Association of heat shock protein70-2 (HSP70-2) gene polymorphism with obesity

Peer reviewedPublisher PD

Projected changes in extreme precipitation indices over the Lake Urmia basin in Iran

This study investigates the future changes in precipitation extreme indices in the Lake Urmia Basin during the period 2021–2100 compared to the base period (1987–2016), using the Coupled Model Intercomparison Project Phase 5 models. Trend analysis was performed using Mann–Kendall test and Sen's estimator. The output of these models was downscaled by the Long Ashton Research Station Weather Generator method for the representative concentration pathway (RCPs) 4.5 and 8.5. A model averaging technique was employed to create an ensemble model. The results showed that the average precipitation of the basin will decrease by the end of the 21st century. The projection also showed that the consecutive dry day's index increases based on both scenarios. However, other indices (maximum 1-day precipitation, maximum 5-day precipitation, very wet days, consecutive wet days, simple daily intensity index, and wet-day precipitation) are reduced compared to the base period. Moreover, the slope of significant trends in the RCP8.5 is greater and more severe than that in RCP4.5. HIGHLIGHTS This study focuses on the future change of extreme rainfall in the Lake Urmia basin in Iran.; The projected results are decreasing trends in extreme precipitation and in wet days and increasing trends in dry days by the end of the 21st century.; This study predicts that the basin may face more drought in the future.; The results of this study have important implications for the management of water resources.

Estimating the occurrence probability of Spring Thunderstorms using Markov chain, Case Study: Tabriz

Thunderstorms are one of the climatic phenomena that cause numerous damages in different parts of the world, due to the accompaniment with thunder, high winds, hail and heavy precipitation. In this study, the probability of thunderstorm days in Tabriz in the spring is analyzed using probabilistic rules and Markov chain model. For this purpose, the daily data related to thunderstorms (codes 95 to 99) was used for 65 years (1951-2015). At first, the daily data is classified into the normal days (code 0) and thunderstorm days (code 1). Then the frequency matrix is formed and the probability matrix is created accordingly based on maximum likelihood method. The Markov chain properties such as empirical probability and equilibrium probability, Frequency of occurrence, mean time periods and weather cycle were investigated. Finally, Occurrence Probability and return period of these spells were determined. The results show that the shortest weather cycle is in May, which has the highest frequency of thunderstorms. Conversely, the longest weather cycle is in April, which has the lowest frequency of thunderstorms. Also, in 65 years period, the one-day and two-day stormy sequences have the highest frequency. And For longer sequences, the frequency of thunderstorm days is reduced. The return period of one-day and two-day stormy spells is 1.5 and 5 days. Regression relation between the observed and estimated values of n-step periods of thunderstorm days shows that the considered accuracy and reliability for all months is more than 99%

Prevalence Study of GJB2 Gene Mutations in Iranian Ethnics

Objective: Hereditary hearing loss (HHL) is a very common disorder. When inherited in an autosomal recessive manner, it typically presents as an isolated finding. Interestingly and unexpectedly, in spite of extreme heterogeneity, mutations in one gene, GJB2, are the most common cause of congenital severe-to-profound deafness in many different populations. In this study, we assessed the contributions made by GJB2 mutations and deletion in a portion of GJB6 to the autosomal recessive non-syndromic deafness genetic load in Iran. Materials & Methods: In this descriptive and cross – sectional study1605 probands from 1605 different nuclear families with autosomal recessive non-syndromic hearing loss were investigated. Hearing loss tests and clinical examination were done and 10 ml blood was drawn as DNA source. After study of 35delG mutation by ARMs PCR, negative or heterozygote individuals were sent to IOWA University for detection of other GJB2 mutations.  Results: GJB2-related deafness was found in 243 families (15.1%). Conclusion: Varient geographic pattern for GJB2-related deafness has considerable results in Iran in comparable with other study in Europe and our neighboring countries and deletion in GJB6. [∆ (GJB6-D13S1830)] hasn't been detected in our studied population