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Showing 3 results for Spatial Correlation
Dynamics of vegetation in Karun watershed within Khuzestan province in relation with Temperature factors and precipitation
Saman Alimoradi, Asadollah : Khoorani, Yahya Esmaeilpoor,
Volume 17, Issue 44 (3-2017)
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.


Detection of the effect of cloud microphysical structure on precipitation in Khuzestan province using MODIS cloud products
Mr Danesh Nasiri, Dr Reza Borna, Dr Manijeh Zohourian Pordel,
Volume 24, Issue 72 (3-2024)
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.
 
Detection of the effect of microphysical properties of flood-producing clouds in Lorestan province using MODIS cloud sensor products
Mr Ebrahim Bairanvand, Dr Amir Gandomkar, Dr Alireza Abbasi, Dr Morteza Khodaghoi,
Volume 25, Issue 79 (12-2025)
Abstract
The torrential rains that occurred in April 2017 in Lorestan Province exemplified severe precipitation that inflicted substantial damage on agricultural, urban, transportation, and communication infrastructures. This study aims to investigate and elucidate the relationship between the physical structure of clouds responsible for two waves of heavy rainfall in April 2017 within the Doroud catchment area of Boroujerd. In this context, the statistical characteristics of two precipitation events on March 25 and April 1, 2019, were analyzed. The microphysical properties of the clouds generating these two heavy rainfall events were examined utilizing the Madis superconductor product and MOD06. Four microphysical factors contributing to the formation of clouds during these two rainfall waves in the Doroud-Borujerd basin—including cloud top temperature (CTT), cloud top pressure (CTP), optical cloud thickness (OCT), and cloud cover ratio (CFR)—were analyzed. Statistical assessments indicated that the first wave of heavy rainfall, occurring on March 25, 2019 (5 April 1398), accounted for 15% of the total annual rainfall, while the second wave on April 1, 2019 (12 April 1398) contributed 20% of the region's average annual rainfall within these two days. The findings from the analysis of the microphysical structure of the clouds producing these two precipitation waves, based on data from the MODIS cloud sensor product, revealed a significant spatial correlation between the four microphysical factors and the recorded precipitation values of these two heavy rainfall events. Specifically, the cloud top temperature and pressure, indicative of vertical cloud expansion in the area, exhibited a significant inverse relationship with the precipitation amounts in the basin. Conversely, the cloud cover ratio and optical thickness demonstrated a direct and significant spatial correlation with the recorded rainfall values. The results of this study thus establish a significant and robust relationship between the microphysical structure of clouds and the precipitation amounts recorded in the region during these two heavy rainfall events. 

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