Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices. (arXiv:2001.09757v1 [physics.ao-ph])
<a href="http://arxiv.org/find/physics/1/au:+Dehghani_M/0/1/0/all/0/1">Majid Dehghani</a>, <a href="http://arxiv.org/find/physics/1/au:+Salehi_S/0/1/0/all/0/1">Somayeh Salehi</a>, <a href="http://arxiv.org/find/physics/1/au:+Mosavi_A/0/1/0/all/0/1">Amir Mosavi</a>, <a href="http://arxiv.org/find/physics/1/au:+Nabipour_N/0/1/0/all/0/1">Narjes Nabipour</a>, <a href="http://arxiv.org/find/physics/1/au:+Shamshirband_S/0/1/0/all/0/1">Shahaboddin Shamshirband</a>, <a href="http://arxiv.org/find/physics/1/au:+Ghamisi_P/0/1/0/all/0/1">Pedram Ghamisi</a>
Temporary changes in precipitation may lead to sustained and severe drought
or massive floods in different parts of the world. Knowing variation in
precipitation can effectively help the water resources decision-makers in water
resources management. Large-scale circulation drivers have a considerable
impact on precipitation in different parts of the world. In this research, the
impact of El Ni~no-Southern Oscillation (ENSO), Pacific Decadal Oscillation
(PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran
was investigated. For this purpose, 103 synoptic stations with at least 30
years of data were utilized. The Spearman correlation coefficient between the
indices in the previous 12 months with seasonal precipitation was calculated,
and the meaningful correlations were extracted. Then the month in which each of
these indices has the highest correlation with seasonal precipitation was
determined. Finally, the overall amount of increase or decrease in seasonal
precipitation due to each of these indices was calculated. Results indicate the
Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal
precipitation, respectively. Also, these indices have the highest impact on the
precipitation in winter, autumn, spring, and summer, respectively. SOI has a
diverse impact on winter precipitation compared to the PDO and NAO, while in
the other seasons, each index has its special impact on seasonal precipitation.
Generally, all indices in different phases may decrease the seasonal
precipitation up to 100%. However, the seasonal precipitation may increase more
than 100% in different seasons due to the impact of these indices. The results
of this study can be used effectively in water resources management and
especially in dam operation.
Temporary changes in precipitation may lead to sustained and severe drought
or massive floods in different parts of the world. Knowing variation in
precipitation can effectively help the water resources decision-makers in water
resources management. Large-scale circulation drivers have a considerable
impact on precipitation in different parts of the world. In this research, the
impact of El Ni~no-Southern Oscillation (ENSO), Pacific Decadal Oscillation
(PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran
was investigated. For this purpose, 103 synoptic stations with at least 30
years of data were utilized. The Spearman correlation coefficient between the
indices in the previous 12 months with seasonal precipitation was calculated,
and the meaningful correlations were extracted. Then the month in which each of
these indices has the highest correlation with seasonal precipitation was
determined. Finally, the overall amount of increase or decrease in seasonal
precipitation due to each of these indices was calculated. Results indicate the
Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal
precipitation, respectively. Also, these indices have the highest impact on the
precipitation in winter, autumn, spring, and summer, respectively. SOI has a
diverse impact on winter precipitation compared to the PDO and NAO, while in
the other seasons, each index has its special impact on seasonal precipitation.
Generally, all indices in different phases may decrease the seasonal
precipitation up to 100%. However, the seasonal precipitation may increase more
than 100% in different seasons due to the impact of these indices. The results
of this study can be used effectively in water resources management and
especially in dam operation.
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