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Showing 3 results for Spatial Correlation

Mr Ebrahim Bairanvand, Dr Amir Gandomkar, Dr Alireza Abbasi, Dr Morteza Khodaghoi,
Volume 0, Issue 0 (3-1921)
Abstract

The occurrence of torrential rains in April 2017 in Lorestan province was a clear example of heavy rains that left very heavy damage to agricultural, urban, transportation and communications infrastructure. The purpose of this study is to investigate and reveal the relationship between the physical structure of clouds producing two waves of heavy rainfall in April 2017 in the Doroud catchment area of ​​Boroujerd. In this regard, the statistical characteristics of two precipitation waves on March 25 and April 1, 2019 were analyzed. The supernatural properties of the clouds producing these two heavy rainfall waves were investigated using the Madis superconductor product, MOD06. 4 Microphysical factors of generating clouds These two waves of heavy rainfall in the Doroud-Borujerd basin, including cloud peak temperature (CTT), cloud peak pressure (CTO), optical cloud thickness (COT) and cloud cover ratio (CF) were analyzed. Statistics of these two waves of heavy rainfall showed that in the first wave of heavy rainfall, ie the wave of March 25, 2019, (5 April 1398) 15% of the total annual rainfall and in the second wave, the wave of April 1, 2019 (April 12, 1398) 20% of the total The total average annual rainfall of the region was recorded in these two days. The results of analyzing the microphysical structure of the generating clouds of these two precipitation waves using the MODSI cloud sensor product data showed that the four microphysical factors of the cloud showed a significant spatial correlation with the recorded precipitation values ​​of these two heavy precipitation waves. The two factors of temperature and pressure of cloud peak, which show a vertical expansion of clouds in the area, showed a significant inverse relationship with the amount of precipitation in the basin, while the two factors of cloud ratio and cloud optical thickness have a direct and significant spatial correlation with values. Recorded rainfall showed. The results of this study showed that in these two events of heavy rainfall, a significant and strong relationship was established between the microphysical structure of the cloud and the amount of rainfall recorded in the region.
 
Saman Alimoradi, Asadollah : Khoorani, Yahya Esmaeilpoor,
Volume 17, Issue 44 (6-2017)
Abstract

The aim of this study is to retrieve land surface temperature (LST), air temperature (AT) and precipitation and to study their relationship with vegetation in rang lands of Karun watershed of Khuzestan province. For this purpose, land surface temperature (LST) and NDVI was drived from NOAA-AVHRR for maximum amount of greenness (April) for a period of 27 years. In order to extract LST, Price algorithm was used. Also air temperature and precipitation were interpolated for selected weather stations using IDW method. Spatial correlation outcomes (on 0.05) between NDVI with LST and air temperature show a reversed relation. This spatial relation is stronger for LST, so that this coefficient is often upper than 0.6, while seldom is 0.4 for air temperature and precipitation. Spatial regression models show that 62 percent of NDVI changes is determined by LST (R2=0.62) and air temperature and precipitation determine very limited amount of NDVI dynamics.


Mr Danesh Nasiri, Dr Reza Borna, Dr Manijeh Zohourian Pordel,
Volume 24, Issue 72 (6-2024)
Abstract

Knowledge of supernatural microphysical properties and revealing its relationship with the spatial temporal distribution of precipitation can significantly increase the accuracy of precipitation predictions. The main purpose of this study is to reveal the relationship between the Cloud microphysical structure and the distribution of precipitation in Khuzestan province. In this regard, first 3 inclusive rainfall events in Khuzestan province were selected and their 24-hour cumulative rainfall values were obtained. The rainfall event of 17December2006, was selected as a sample of heavy rainfall, 25 March 2019, as a medium rainfall case, and finally 27 October 2018, as a light rainfall case. Microphysical factors of clouds producing these precipitations were obtained from MODIS (MOD06) cloud product. These factors included temperature, pressure, and cloud top height, optical thickness, and cloud fraction. Finally, by generating a matrix with 64000 information codes, and performing spatial correlation analysis at a confidence level of 0.95, the relationship between the Cloud microphysical structure and the spatial values and distribution of selected precipitates was revealed. The results showed that in the case study of heavy and medium rainfall, the spatial average of 24-hour cumulative rainfall in the province was 36 and 12 mm, respectively. A fully developed cloud structure with a cloud ratio of more than 75% and a vertical expansion of 6 to 9 thousand meters, with an optical thickness of 40 to 50, has led to the occurrence of these widespread and significant rainfall in the province. While in the case of light rain, a significant discontinuation was seen in the horizontal expansion of the cloud cover in the province and the cloud cover percentage was less than 10%. In addition, the factors related to the vertical expansion of the cloud were much lower, so that the height of the cloud peak in this rainfall was between 3 to 5 thousand meters. The results of this study showed that in heavy and medium rainfall cases, a significant spatial correlation was observed at a confidence level of 0.95 between MOD06 Cloud microphysical factors and recorded precipitation values, while no significant spatial correlation was observed in light rainfall case.
 

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