عنوان مقاله [English]
Teleconnection models are increasingly used to predict the average atmospheric conditions in different time periods. In other words, the connection between atmosphere and its slow changes in oceans provides the possibility of predicting climate conditions in different time scales, such as monthly, seasonal, annual and decennial time scales. Teleconnection has always been defined as the simultaneous connection between climate oscillations of a region with changes in pressure patterns and sea surface temperature in other geographical points. As El Nino South Oscillation (ENSO) is the most obvious teleconnection model in south hemisphere, North Atlantic Oscillation (NAO) is also the most obvious teleconnection model in the north hemisphere. This study aims to consider the relationship between drought and wet years in Iran with NAO in both station and regional scales based on one of the linear models.
Materials and Methods
Two datasets were used in this study to evaluate the relationship between NAO with droughts and wet years in Iran. The first dataset was monthly precipitation data of 63 synoptic weather stations received from Iran meteorological organization for a 30-year time interval (1986-2016), and in the second dataset, the values related to NAO for the same time interval (1986-2016) were taken from database of National Center for Environmental Prediction/National Center for Atmospheric Research (NECP/NCRA) of US National Oceanic and Atmospheric Administration (NOAA). After collecting the required data from different databases and forming their databank, Standardized Precipitation Index (SPI), which is one of the indices proposed by World Meteorological Organization, was used to quantify the droughts in Iran. In this step, SOI was calculated for all the studied stations in a monthly scale. In the next step, based on the spatial principle, Iran's droughts and wet years were divided in the same monthly scale into three classes of pervasive droughts (wet years), semi-pervasive droughts (wet years) and local droughts (wet years). After determining droughts in both station and regional scales, Pearson moment correlation coefficient was used to evaluate the relationship between Iran's droughts in station and regional scales with NAO in four concurrent, one-month, two-month and three-month delays.
Results and Discussion
The analysis of the results related to correlation coefficient between NAO with Iran's drought and wet years in a station scale showed that in autumn, more than 87% of droughts in stations in all delays, except November concurrent delay, have weak correlation with NAO. In November, drought in most stations in the north part of the country, especially Northwest stations, have an average positive significant correlation with NAO. This correlation can indicate the effect of different phases of this index on the rain systems entered from Mediterranean Sea to Northwest of Iran in autumn. More accurately, positive values of this correlation indicates that values higher than zero in NAO are associated with increasing the intensity and frequency of droughts in Iran, especially the given regions.
During winter months, spatial pattern of correlation is such that finding a certain spatial arrangement is difficult. It is shown that more than 85% of droughts in stations in different delays have weak correlation with NAO. But negative average correlations were observed for some months in different delays both for southeast and northeast. These negative correlations indicate that the negative phase of NAO is associated with reduction in the intensity and frequency of droughts in these two parts of Iran. The only month with positive correlation of these droughts with NOA is January for concurrent delay.
Spring droughts, compared to other seasons’ droughts, have the weakest correlation with NAO. This clearly points out that the oscillations of this index do not play a major role in drought variability of the study stations in this season. In addition, spatial arrangement of few stations that their droughts and wet years have average correlation with NAO, shows no clear pattern. Only in April two-month delay, we observe the density of stations with negative average correlation in the northwest and north of Iran. Perhaps the reason for the weak correlation of NAO with droughts and wet years of Iran' stations in this season is its transitory nature and changing the precipitations from frontal precipitation to other types of precipitation.
The results of correlation analysis related to the relationship between NAO with droughts and wet years also indicated that there is no strong relationship between these two variables in Iran and only an average significant relationship is observed in three-month delay of October and concurrent delay of May which was negative for October and positive for May.
Finally, it can be concluded that NAO cannot explain a large part of droughts and wet-years variability in station or regional scales. Therefore, since climatology of Iran's precipitation is very complex and the synoptic patterns which influence Iran in different months and seasons are different, it is necessary to pay attention to nonlinear models for investigation in this regard.