Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran

Rousta, Imán; Doostkamian, Mehdi; Haghighi, Esmaeil; Malamiri, Hamid Reza Ghafarian; Yarahmadi, Parvane

doi:10.1007/s00376-017-6227-y

Cited by 27 publications

(11 citation statements)

References 22 publications

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“…e cold weather of Scandinavia and Advances in Meteorology Siberia transfers to lower latitudes by the low height centrality and its convergence with wet flows of Mediterranean and the Black Sea from the trough of the Mediterranean and its transfer to Iran by a relatively deep trough, based on the center of the country. In its movement from stack to the trough, the air has downward movement and with convergence, so the trough is the center of positive vorticity advection with amount of 2 × 10 −5 S −1 and the maximum of convergence located on the trough axis [5,47]. At the levels of 700 and 500 hPa, Figures 5(c) and 5(d), an elevation model of 850 hPa can also be clearly observed.…”

Section: E Ird Pattern: Lowmentioning

confidence: 92%

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Investigation of Vorticity during Prevalent Winter Precipitation in Iran

Rousta

Javadizadeh

Dargahian

et al. 2018

Advances in Meteorology

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In this study, precipitation data for 483 synoptic stations, and the U&V component of wind and HGT data for 4 atmospheric levels were respectively obtained from IRIMO and NCEP/NCAR databases (1961-2013). e precipitation threshold of 1 mm and a minimum prevalence of 50% were the criteria based on which the prevalent precipitation of Iran was identified. en, vorticity of days corresponding to prevalent winter precipitation was calculated and, by performing cluster analysis, the representative days of vorticity were specified. e results showed that prevalent winter precipitation vorticity in Iran is related to the vorticity patterns of low pressure of Mediterranean-low pressure of Persian Gulf dual-core, low pressure closed of central Iran-high pressure of East Europe, Ural low pressure-Middle East High pressure, Saudi Arabia low pressure-Europe high pressure, and high-pressure belt of Siberia-low pressure of central Iran. At the same time, the most intense vorticity occurred when the climate of Iran was influenced by a massive belt pattern of Siberian high pressure-low pressure of central Iran. However, at the time of prevalent winter precipitation in Iran, an intense vorticity is drawn with the direction of Northeast and Northwest from the center of Iraq to the south of Iran.

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Section: E Ird Pattern: Lowmentioning

confidence: 92%

“…Changes in extreme weather and climate events have significant impacts and are among the most serious challenges to society in coping with a changing climate [1][2][3][4][5][6][7][8][9]. e most important factor in the formation and guidance of atmospheric systems is vorticity process [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Vorticity during Prevalent Winter Precipitation in Iran

Rousta

Javadizadeh

Dargahian

et al. 2018

Advances in Meteorology

Self Cite

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“…The Moran's I will have a value between -1 (dispersed) to 1 (clustered) and also the larger the Z-score than 1.96 or less than -1.96 will show a significant value at the 95% confidence level [Górniak, 2016;Song et al, 2014]. The area with positive spatial autocorrelation will show a cluster of similar phenomena and negative spatial autocorrelation will depict a cluster of different phenomena [Rousta, Doostkamian, Haghighi, Ghafarian Malamiri, & Yarahmadi, 2017]. In addition, the hot spot location with significant statistic will have high values with its surroundings (High-high or Low-low values) [Zhou et al, 2017].…”

Section: The Methodsmentioning

confidence: 99%

An Exploratory Analysis in Mapping of Asthma Risk in Western Australia

Febriawan

Sodre

2018

IJG

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Exploratory Analysis as one of the spatial analysis tools that has been used widely in many study fields. This tool is usually intended to obtain the spatial pattern to observe and get relationship between study variables. The exploratory analysis is usually followed by the confirmatory analysis to exhibit the hypothesis that already obtain in the exploratory analysis. This study is aimed to investigate the prevalence of asthma in Western Australia since there are many factors that cause the asthma dispersion. Many provided variables have been tested to get the best correlation with the asthma percentage variable and four variables (humidity, annual rainfall, EVI and SEIFA) were chosen and tested with high asthma percentage variable. The result of confirmatory analysis indicates that the high level of humidity and low level of SEIFA confirm with the hypothesis and means that those factors can contribute significantly in Asthma prevalence in Western Australia.

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“…Getis-Ord-Gi (GOG) provides an index for spatial autocorrelation and presents an indication towards hot-spots (HS) or cold spot (CS; Oyana and Margai 2015). The combination of GOG and MKTT is used to identify emerging hotspots regions in climatic patterns, urban heat islands, forest fires, and diseases (Rumiantsev and Ivanova 1995;LukoviÊ et al 2014;Javari 2016Javari , 2017Abdrakhmanov et al 2017;Rousta et al 2017;Wangdi et al 2018;Rayadurgam & Rao, 2021). Bajat et al (2013) carried out spatial pattern analysis of monthly, seasonal, and annual rainfall across Serbia and the emerging HS analysis was used to identify HSs to understand the clustering of low and high values of precipitation.…”

Section: Introductionmentioning

confidence: 99%

Sub-division Level Temperature Patterns and Trends Across East-Coast Industrial Corridor, India

2021

Preprint

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Temperature patterns and trends influence many sectors. The newly planned industrial corridors will have to consider the variations in temperature and other climatic parameters. The present article aims to investigate the patterns and trends of maximum and minimum temperature at the Sub-division (sub-district) level. We analyse annual and seasonal temperature data from 1958 to 2018 for the India’s first east-coast corridor, the Visakhapatnam–Chennai industrial corridor (VCIC) using a combination of Getis–Ord–Gi and Mann–Kendall trend test for spatiotemporal patterns and trends. The results show domination of intensifying hot spots across the VCIC and an overall increase in both maximum and minimum temperature for annual (0.013 oC/y and 0.011 oC/y) and seasonal trends. However, the variations of pattern and trends are unambiguous within districts. There is a clear distinction in patterns and trends between southern and north-eastern districts, indicating the need for localised planning. As the industrial areas are planned at a microlevel, such studies will enable planners and decision-makers to plan and prioritise site-specific climate change adaptation and mitigation measures in industrial and urban areas.

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Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran

Cited by 27 publications

References 22 publications

Investigation of Vorticity during Prevalent Winter Precipitation in Iran

Investigation of Vorticity during Prevalent Winter Precipitation in Iran

An Exploratory Analysis in Mapping of Asthma Risk in Western Australia

Sub-division Level Temperature Patterns and Trends Across East-Coast Industrial Corridor, India

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