Analysis of Extreme Precipitation Events over Central Plateau of Iran

This paper describes the results of an analysis of extreme rainfall events in the central plateau of Iran. To study the extreme events, daily records of eighteen stations’ rainfalls in the region for different initial dates up to 2005 gathered from the bureau of meteorology. Then, the extreme rainfall threshold was calculated for each individual station using the statistical index of Gamble type I. Lastly, 22 mm was determined as the extreme rainfall value for the entire stations, and eventually 17 out of 169 extreme precipitation events were extracted in accordance with three factors including a) days with precipitation in not less than 50% of the stations, b) maximum rainfall is 22 mm or more in at least one of the stations, and c) mean precipitation of the basin is more than 3 mm. In the next step to analyze the synoptic features, the relevant meteorological data i.e. relative vorticity, geopotential height, sea level pressure, u and v wind components, relative humidity, vertical velocity, and precipitable water content at multiple levels of the atmosphere were examined from the NCEP/NCAR reanalysis dataset. The synoptic findings indicate that two patterns of deep trough and high ridge of the eastern Mediterranean were responsible for making the heavy precipitation events over the central plateau of Iran. The most and severest rainfall events occurred via deep tough pattern, which covered 76% of days with extreme precipitations during the examined period. Furthermore, the results suggest that the main moisture resources, which identified by HYSPLIT model’s outputs and moisture convergence/divergence zones for the rainy systems in the first pattern (deep trough) including Persian Gulf, Oman Sea, Indian Ocean, and Red Sea, while for the second pattern (high ridge) Persian Gulf and Red Sea play a significant role in feeding the storms in the central regions of Iran. Moreover, the southward movement of Polar Vortex is also considered as those important factors to produce extreme precipitation events over the central plateau of Iran. In general, the HYSPLIT trajectories model’s outputs confirmed the observed synoptic features in particular for the systems’ moisture feeding discussed in the patterns.

Analysis of Spatial Autocorrelation Patterns of Heavy and Super-Heavy Rainfall in Iran

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran＇s heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord Gi statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.

Monitoring of Carbon Monoxide (CO) changes in the atmosphere and urban environmental indices extracted from remote sensing images for 932 Iran cities from 2019 to 2021

Carbon Monoxide(CO)is an important urban pollutant with a relation to 5,transition economies based on emission intensities.In this study,Sentinel-MODerate resolution Imaging Spectroradiometer(MODIS),and Landsat-8 images were used to investigate the variations of CO and urban environmental indices and the correlations between them.From the assessed correlations for 932 Iranian cities,it occurred that the assessed indices were all correlated.The highest CO levels were 0.031 in the spring of 2019 and 2020,whereas in 2021 it was equal to 0.030 in both the spring and winter,respectively.In 2019 and 2020 the maximum values of the Enhanced Vegetation Index(EVI)in the spring were 0.181 and 0.183.Exceptionally high Absorbing Aerosol Index(AAI)values of–0.834 and–1.0,along with Urban Index(UI)of 0.102 and 0.092,were correlated with recorded spikes in CO level,despite that these seasons’EVI values were not so abnormal.It was forecasted that in 2030 rises in the CO level by 13.2%in the winter and by 17.5%in the fall are expected,with the simultaneous increase of AAI by 204.5%and 980.2%,and Aerosol Optical Depth(AOD)by 27%and 5%in the winter and spring,respectively.