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Showing 3 results for Temporal Variations
Taghi Tavousi, Mohsen Hamidianpour, Rashed Dahani,
Volume 4, Issue 3 (9-2017)
Volume 4, Issue 3 (9-2017)
Abstract
Thunderstorms are one of the most important, abundant and severe atmospheric hazards. In addition to destroying a large amount of agricultural products and construction projects, cause many human casualties are annually in different parts of the world (Iran Pour and et al, 2015). This phenomenon is associated with severe storms, showery precipitation, hail (Puranik and Karekar, 2004), and thunder and lightning (Nath et al, 2009). These storms occur 50,000 times on a daily Basis. They account for 18,000,000 yearly (Ahrens, 2009). Extensive studies have been conducted in Iran and the world in this regard. For example, Wallace (1995) examined the abundance of lightning in the United States using 100 stations. He concluded that the greatest frequency of convectional showers occurs early in the night and at least at midnight. Sterling (2003) described the thunderstorms as a major dilemma for the United States in the twentieth century. The environmental and economic consequences of thunderstorms and their associated phenomena such as floods, hail and heavy precipitation are believed to be very ruinous on the US economy. Sistan and Baluchistan Province, Iran has annually been witnessing a variety of thunderstorms systems and associated precipitation. The province has suffered lots of damage resulted from the phenomena caused by thunderstorms. Therefore, this article aimed for a spatial analysis and the frequency of thunderstorm occurrences at different time scales. The article also examines the temporal variations and trends. The secondary questions outlined here are as follows: At what time of day do thunderstorms occur? How are thunderstorms recorded as various codes? Which one of these codes is the most commonly reported one? In terms of location, what are the stations with the greatest and least number of thunderstorms?
The area under study is Sistan and Baluchistan Province, Iran. With an area of almost 187,502 km2, the province is located in the southeastern part of Iran, on the Oman Sea coast and in the vicinity of Pakistan and Afghanistan. The province has 300 km water border with the Oman Sea in south, 1100 km land border with Pakistan and Afghanistan to the East, Khorasan Province to the North, and Kerman and Hormozgan to the West (Ebrahim Zadeh, 2009).
In this study, the frequency of thunderstorms was extracted based on 7 synoptic stations and the used of Presence Weather Codes. Temporal variations were then studied using the Man-Kendal and Sen's non-parametric tests. Finally, the relationship between the thunderstorms and ENSO was investigated. Meanwhile, spatial dispersion was also taken into account.
The results showed that thunderstorms have a peak region in southeast part with the center of the Saravan and Iranshahr stations and a minimum area in the Oman Sea coasts (Konarak and Chabahar). More precisely, Saravan Station scored the top with 567 thunders and lightning, while Konarak Station hit the lowest point with 96 in this 30-year period. In the maximum thunderstorm region, Saravan and Iranshahr are the main centers during different seasons so that the number of thunderstorms is higher in summer and fall in Iranshahr compared to Saravan. In winter and fall, such thunderstorms, caused by extra-tropical origin, are more in Saravan than Iranshahr Station.
The results of hourly investigations of thunderstorms showed that most of thunderstorms occur at noon and 3:00 p.m. Codes 13 and 17 were the most frequently reported codes with 605 and 571 occurrences, respectively, Codes 99 and 5 were the least. Monthly investigations showed that May and March had the highest number of thunderstorms (322 and 317, respectively), while September accounted for the least number (55). Quarterly investigations showed that spring had the highest number of thunderstorms (756) followed by winter (559). These thunderstorms are seen in spring more than other seasons because of the passage of extra-tropical air masses, which is abundant in the region under study. Summer, which is the Sub-tropical High pressure (STHP) season, had the least number of thunderstorms (340 occurrences of thunder and lightning). These thunderstorms mainly occur in Iranshahr and Saravan Stations, which was proven in the spatial analysis. The summer incidence increase of the thunderstorms is rooted in the Monsoon systems, preparing the ground for the phenomenon. The temporal variations at different monthly, quarterly, and yearly scales showed that no significant differences are found in thunderstorm trends. The phenomenon has experienced enormous fluctuations, likely to be associated with complex changes of macro-climate patterns. El Nino and the Lanino are likely to be the main factors affecting the ENSO's warm and cold phases. According to the results, almost 70% of thunderstorms are associated with the El Nino. In other words, more thunderstorms are expected during ENSO's warm phase.
The area under study is Sistan and Baluchistan Province, Iran. With an area of almost 187,502 km2, the province is located in the southeastern part of Iran, on the Oman Sea coast and in the vicinity of Pakistan and Afghanistan. The province has 300 km water border with the Oman Sea in south, 1100 km land border with Pakistan and Afghanistan to the East, Khorasan Province to the North, and Kerman and Hormozgan to the West (Ebrahim Zadeh, 2009).
In this study, the frequency of thunderstorms was extracted based on 7 synoptic stations and the used of Presence Weather Codes. Temporal variations were then studied using the Man-Kendal and Sen's non-parametric tests. Finally, the relationship between the thunderstorms and ENSO was investigated. Meanwhile, spatial dispersion was also taken into account.
The results showed that thunderstorms have a peak region in southeast part with the center of the Saravan and Iranshahr stations and a minimum area in the Oman Sea coasts (Konarak and Chabahar). More precisely, Saravan Station scored the top with 567 thunders and lightning, while Konarak Station hit the lowest point with 96 in this 30-year period. In the maximum thunderstorm region, Saravan and Iranshahr are the main centers during different seasons so that the number of thunderstorms is higher in summer and fall in Iranshahr compared to Saravan. In winter and fall, such thunderstorms, caused by extra-tropical origin, are more in Saravan than Iranshahr Station.
The results of hourly investigations of thunderstorms showed that most of thunderstorms occur at noon and 3:00 p.m. Codes 13 and 17 were the most frequently reported codes with 605 and 571 occurrences, respectively, Codes 99 and 5 were the least. Monthly investigations showed that May and March had the highest number of thunderstorms (322 and 317, respectively), while September accounted for the least number (55). Quarterly investigations showed that spring had the highest number of thunderstorms (756) followed by winter (559). These thunderstorms are seen in spring more than other seasons because of the passage of extra-tropical air masses, which is abundant in the region under study. Summer, which is the Sub-tropical High pressure (STHP) season, had the least number of thunderstorms (340 occurrences of thunder and lightning). These thunderstorms mainly occur in Iranshahr and Saravan Stations, which was proven in the spatial analysis. The summer incidence increase of the thunderstorms is rooted in the Monsoon systems, preparing the ground for the phenomenon. The temporal variations at different monthly, quarterly, and yearly scales showed that no significant differences are found in thunderstorm trends. The phenomenon has experienced enormous fluctuations, likely to be associated with complex changes of macro-climate patterns. El Nino and the Lanino are likely to be the main factors affecting the ENSO's warm and cold phases. According to the results, almost 70% of thunderstorms are associated with the El Nino. In other words, more thunderstorms are expected during ENSO's warm phase.
Behrooz Mohseni, Kaka Shahedi, Seyyed Mohsen Manavi, Narjes Mahmoodi-Vanolya,
Volume 9, Issue 2 (9-2022)
Volume 9, Issue 2 (9-2022)
Abstract
The sedimentation, sediment transport, erosion and sedimentation problems are important discussions in the planning of wisdom and macro watershed strategies and management of watershed basins. The sediment collection in lower areas causes regional damage, the destruction of the pathway of the waterways, the flow of water pollution, the accumulation of streams of sediment and reducing the capacity of reservoirs of dams and environmental bottlenecks. The sediment resulting from the watersheds erosion, in addition to soil loss and its degradation results in a decrease in water quality and endangers the useful life of dams due to the accumulation of deposits in their reservoirs. In this research, Spatiotemporal variations of suspended sediment load were investigated at three hydrometric stations of Sefidchah, Gelevard and Ablou located on the main channel of the Nakaroud Basin using sediment rating curves and linear regression model through applying MINITAB and EXCEL softwares. In order to determine the best model, determination coefficient (R2) was used. The results of this study showed that in seasonal variations of spring season in all three stations with a determination coefficient of at least 82% and a maximum of 89% as the most suitable model for estimating suspended sediment load among the models studied. In spatial studies, the Ablou station located at the outlet of the watershed has the highest determination coefficient (0.934) between sediment discharge and streamflow discharge.
Dr Masoud Moradi, Dr Mohammad Hosein Gholizadeh, Mr Meysam Rahmani,
Volume 10, Issue 2 (9-2023)
Volume 10, Issue 2 (9-2023)
Abstract
Investigation of the Temporal and Spatial Variation of Maximum Soil Temperature in Iran
Extended Abstract
Introduction
The study of soil temperature in different depths of soil is important in climatology, hydrology, agrometeorology and water resource management. Different depths has a different temporal and spatial soil temperature variation. It represents the regional ground temperature regime. Furthermore, due to its rapid response to environmental changes, soil temperature is one of the most important indicators of climate change. The increase in soil temperature because of global warming can promotes disasters such as drought by increasing the water demand of agricultural products during the plant growth period. The increase in soil temperature also have a various consequences, include increasing evaporation from the soil surface, soil salinity in susceptible areas, which can lead to a decrease in soil yield and failure in plant growth. Therefore, knowledge of soil temperature changes in different environments is very important in climate studies. The aim of the current research is to analyze the spatial and temporal variations of soil temperature at different depths from five to 30cm of the ground and to investigate the existence of any kind of increasing or decreasing trend at different climates of Iran.
Methodology
Hourly soil temperature data (depths of 5, 10, 20 and 30 cm) were used in this research for the period of 1998-2017. The soil depth temperature is measured three times a day at 6:30 am, 12:30 pm, and 6:30 pm local time (3, 9, and 3 p.m. UTC). These data have been received for 150 synoptic stations of Iran on a daily basis from the Iran Meteorological Organization (IRIMO). IRIMO monitored the quality of soil temperature for data entry, data recording, and data reformatting errors. Data availability, discrepancies, errors, and outliers were identified during the second stage.
At the first step, temporal coefficient of variation were calculated for available soil temperature time series from five to 30 cm depths of each station. For this purpose, the average of three daily measurements of soil temperature was calculated and then the temporal coefficient of variation was obtained. In the next step, trend analysis of soil temperature has been investigated using the non-parametric Mann-Kendal test. The trend slope was calculated using Sen’s slope for each station in seasonal time scale. Trend analysis has been done for all three observations of the day.
Results and Discussion
The studied stations show significant spatial patterns in the temporal variability of soil temperature. In all four investigated depths, from five to 30 cm, the northwest parts of Iran, and some parts of Zagros and Alborz mountain ranges have high temporal coefficient of variation. In contrast, the stations located on the southern coasts and southern islands had the lowest temporal variability. In warm and cold seasons (summer and late autumn to mid-winter), the spatial changes of soil temperature at different depths are lower than spring and early autumn. However, in the warm period of the year, the soil temperature experiences lower spatial variations at different depths. Spring and autumn seasons, as the transition period from cold to warm and warm to cold seasons, show the most spatial temperature variations in Iran. Detected trends do not have significant differences among the three observations of the day. Soil temperature Trend analysis at different depths showed positive values for two seasons of summer and winter over most of the stations throughout Iran. Extreme trends are more frequent in the summertime of Zagros and Alborz mountainous regions, while in the winter season the stations located at the southern latitudes of Iran have experienced the most positive trends. In the summer season, higher trends with 99% confidence are more frequent in the mountainous areas. These positive trends in soil temperature have occurred in all studied depths. The negative trend at different depths is a distinct feature of the autumn season, which is significantly more prevalent than other seasons throughout Iran. The analysis of soil temperature trends in different depths shows that values above 1 degree Celsius often occur in 5 to 20 cm deeps. The increasing trend of soil temperature in winter shows a greater spatial expansion, which is indicate increasing annual minimum soil temperatures and the increasing trend of Iran's soil temperature.
Keywords: Soil Temperature, Spatiotemporal Variations, Man-Kendal Test, Sen's Slope, Iran
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