Analysis of the trend of long-term changes in the tropopause height on the Iranian atmosphere in the transition seasons

In this study, the trend of tropopause changes in the Iranian atmosphere in the spring and autumn months was analyzed using ECMWF database data from 1979 to 2018. The results of studying the trend of tropopause changes in spring and autumn showed that in large parts of the country the observed trend was without statistical significance and only in March in parts of the west and northwest of the country and in September in the Zagros Mountains was positive and statistically significant. The results of studying the temperature trend of two levels around the tropopause also showed that in all months of spring and the first two months of autumn, except for very limited areas of the country, the observed trend is without statistical significance. The two-level temperature trend around the tropopause in November was significantly different from other months under the study; this month, large parts of the country were statistically significant in the two levels around the tropopause. Examination of the temperature difference trend of the two levels around the tropopause also showed that in areas with a significant trend, the trend of the difference between the two levels of high and low tropopause was negative. Analysis of Variance, Skewness and Kurtosis Tropopause trends also showed that in the three months of spring in most areas the observed trend is not statistically significant, but in autumn (especially September) in some parts of the country, the observed trend is significant. According to the results, it can be said that during the last forty years, the effect of climate change on the tropopause layer on the Iranian atmosphere in spring and autumn has been very small and changes in spring have been much more limited than in autumn

The association of the paraoxonase 1 Q192R polymorphism with coronary artery disease (CAD) and cardiometabolic risk factors in Iranian patients suspected of CAD

IntroductionThe present study aimed to investigate the association of the paraoxonase 1 (PON1) Q192R polymorphism with coronary artery disease (CAD) and cardiometabolic risk factors in Iranian patients suspected of CAD.MethodsThis cross-sectional study was conducted on 428 patients undergoing angiography. The data related to demographic information and physical activity were collected by valid and reliable questionnaires. The PON-1 genotypes were detected by the polymerase chain reaction-restriction fragment length polymorphism (RFLP-PCR) technique. The Gensini and SYNTAX score, anthropometric measurements, and biochemical and clinical parameters were measured by standard protocols.Results and discussionFindings indicated that the odds of obesity was significantly higher in people with the RR genotype compared to the QQ genotype carriers (OR: 2.95 CI: 1.25–6.93, P = 0.014) and also odds of low high-density lipoprotein cholesterol (HDL-C) was marginally higher (OR: 2.31 CI: 0.97–5.49, P = 0.056). There was no significant association between other CAD risk factors with PON1 Q192R polymorphism (P > 0.05). Further analysis showed a significant interaction between sex and 192QR (P = 0.019) and 192 RR (P = 0.007) genotypes on body mass index (BMI). More specifically, the risk of obesity in men carrying the RR genotype was 3.38 times (OR: 3.38 CI: 1.08–10.58, P = 0.036). Also, a significant joint effect of the RR genotype and sex on HDL-C was seen (P = 0.003). The stratification based on sex showed that the risk of low HDL-C is significantly higher in women carrying the RR genotype (OR: 6.18 CI: 1.21–31.46, P = 0.028). A marginal sex-genotype interaction was also found in the risk of elevated alanine aminotransferase (ALT) (P = 0.057). In summary, the findings showed that the risk of obesity and low HDL-C was higher in people carrying the RR genotype. On the other hand, a Q192R polymorphism-sex interaction was observed on the risk of obesity, elevated ALT, and low HDL-C

Synoptic analysis of heavy precipitations of Kurdistan province

The aim of this study is synoptic analysis of heavy precipitations in Kurdistan Province during 1/1/1961 to 31/12/2010(18263days). By using two thresholds of extensively and intensity of precipitation, 107 days have been recognized. In temporal view, the selected days occurrences in wet seasons of year that start from October to June. By applying the principle component analysis on the sea level pressure during the 107 days, the results showed that 12 components explain about 93 percent of sea level pressure variation. The results of the applying cluster analysis on the component score showed that two circulation patterns result in occurrence of extreme and heavy precipitations in Kurdistan province. In order to recognize heavy precipitation in dry season (June to October), the area mean precipitation for the province have been calculated. According to the 99 percentile threshold and extensively of precipitation the heavy phenomena recognized. By two thresholds 32 days selected and same as to the wet season precipitation the sea level pressure data from NOAA extracted. The data analyzed by Principle Component Analysis and 11 components extracted that explain the 93 percent of variation sea level pressure in the frame study. By doing cluster analysis on the 11 components, one pattern recognized for the sea level pressure.  The results showed that in lower atmospheric levels (1000, 925 and 850 hpa) occurred highest convergence on the study region during wet season. The source of humidity in the lower levels is Arabian, Red, Oman, Persian Gulf and Mediterranean Seas. In the high level atmosphere, the value of convergence is low. The sources of humidity in high levels atmosphere are Red and Mediterranean Seas. In the mid level atmosphere (500 hpa) the presence of trough results in nutrition of the instability on the study region. Also during dry season, the highest moisture flux convergence occurred in the low levels but the resource of the moisture is Caspian Sea. In the upper levels (from 700 hpa to up) in addation to Caspian Sea, Mediterranean and Red sea are the resource of heavy precipitations

Evaluation Of Changes In Extreme Temperature Indices Over The Kurdistan Province During Last Half Century

To doing this research, daily minimum and maximum temperature data from 11 synoptic stations and 15 climatology stations on the in and out of Kurdistan province during 1/1/1962 to 31/12/2010 have been used. Data interpolated on 6  by Kriging interpolation method. The 811 pixels obtained that cover the whole of the province. Two data base in 17898 811 pixels have been created that located days on the rows and pixels on the columns. The 16 extreme temperature indices of Expert Team of Climate Change Detection and Indices (ETCCDI) have been used. For each pixel the 16 indices calculated and evaluated significant trend by non-parametric Mann-Kendal method in the 95% confidence level. The trend slope estimated by liner regression. To doing spatial analysis, the trend and slope rate changes for each indices have been shown in separate maps. The results of this study showed that extreme warm indices are increasing over the low lands and extreme cold indices are decreasing over the heights and mountains. The positive trend for extreme warm indices observed in the west, southwestern and semi-eastern parts of the province. The spatial extent of increasing warm nights is more than warm days. The cold extremes are increasing on the heights and decreasing over the low lands and floor plains. The durnal temperature range(DTR) has been decreased. The changes rate of extreme minimum temperature is more than  daily extreme temperature changes

Projected Changes in Iran Temperature Based on Different Scenarios RCP

The aim of the current study is spatiotemporal analysis of changes in minimum, maximum and mean air temperature over Iran based on Representative Concentration Pathway (RCP) of the fifth report of IPCC. To do this, three datasets have been used: 1) Daily maximum, minimum and mean air temperature data for 42 synoptic stations during 1/1/1979 to 31/12/2005, 2) National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) data for 26 variables, and 3) Representative Concentration Pathway (RCP) scenarios data during 1/1/2006 to 31/12/2100. The model was calibrated using predictors from the NCEP/NCAR reanalysis datasets over the base period 1979–2005. The selected downscaling model structure has been done by a recommended method by Mahmood and Babel (2013) which is a combination of the correlation matrix, partial correlation, and P-value was used. Due to the bias, downscaled temperature data forced by CanESM2 model was corrected using a bias correction technique for each station.  Finally, changes in the characteristics of temperature were estimated for the future period (2006–2100) based on the future scenarios RCP2.6, RCP4.5 and RCP8 compared to the base period (1979–2005). The projected changes were assessed with the nonparametric modified Mann-Kendal trend test and Sen Slope estimator at 95% confidence level. The results showed great reliability of SDSM downscaled model structure and screening of variables. The findings illustrated that minimum, maximum and mean air temperature were projected to increase. The projected increases was larger in semi western part of country. Minimum air temperature projected to increase 0.35, 0.6 and over 1 ℃ based on the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. Maximum air temperature increases rapidly after 2070 decade and projected to increase more than 1℃ rather than base period (1979-2005). The projected changes showed that warming of Iran’s air temperature more over 0.5 ℃ after 2040 and reached to 1.5 ℃ by the end of twenty first century

Spatiotemporal Changes in Precipitation Concentration Indicators Over Iran

Abstract This study was conducted to investigate the spatiotemporal variability in precipitation concentration over Iran. For that purpose, daily precipitation data with a spatial resolution of 0.25° × 0.25° from the Asfazari database for the period from 01/01/1962 to 31/12/2019 were used. Three indices including the precipitation concentration index (PCI), precipitation concentration period (PCP), and precipitation concentration degree (PCD) were utilized for examination of the variability in precipitation concentration over the country. The results demonstrated that the central, south-eastern, and eastern parts of the country exhibited maximum temporal precipitation concentration, while the least precipitation concentration could be observed over the Caspian coasts and the northern half of the country. The year 1998 was selected as the change point due to the considerable difference in the values of the examined indices, and the long-term statistical period was divided into two sub-periods before and after the change. During the sub-period after the change point (1999-2019), precipitation concentration has increased in the western, central, eastern, and south-eastern parts of Iran, according to PCI and PCD, and has decreased in the North and Northeast and along the northern coastline of Oman Sea. Furthermore, there have been great spatial differences in the period of occurrence of precipitation along the Northern coasts, according to PCP, varying from November, along the Caspian coasts, to August, along the northern foothills of Alborz Mountains. The PCP index has increased during the sub-period after the change point along the northern coastlines of Persian Gulf and Oman Sea and in parts of the North (along Alborz Mountains), indicating a shift in the period of precipitation from winter to the warm seasons of spring and summer. Moreover, the decrease in PCP in the Northwest and Northeast suggested that the period of occurrence of precipitation has shifted from the second half of winter toward early winter and late fall. After the year of change point, the frequency of rainy days and precipitation have decreased, and PCI and PCD have increased.</jats:p