عنوان مقاله [English]
Introduction: Identifying the teleconnection patterns and analyzing their effects on the horizontal structure of circulation patterns can be useful for better recognition and understanding of anomalous climatic events. Temperature, precipitation, and wind, which are the main factors in weather and climatology classifications, are among the parameters whose abnormal increase or decrease can cause irreparable harm and damage to humans, and predicting the abnormalities of these factors can be useful. The teleconnection is as the name suggests; In fact, it deals with the relationship of different climatic parameters in different parts of the world. A significant part of the damages caused by climatic hazards is related to hot and cold waves, destructive floods and violent storms. The term teleconnection is often used in atmospheric science to describe climate links between geographically separated regions. Climatic signals that express changes in temperature and air pressure in the oceans are considered one of the most influential parameters on a global scale on weather patterns, especially precipitation, considering the effect of large-scale climatic factors on extreme events, by examining the effect of these signals on the accuracy of monitoring and forecasting. Floods increase. Atmospheric circulations are very variable. In general, the occurrence of extreme atmospheric-climatic phenomena such as heavy rains and sudden changes have the largest scope of damage to water resources, agriculture and even people's daily life. Having the necessary knowledge of the extent of these phenomena, changes and their prediction will be of great help for more accurate planning in different watersheds, which will reduce the negative effects caused by the occurrence of these phenomena and benefit from their positive effects. These changes lead to the emergence of weather patterns and forms of atmospheric currents that occur on different time scales. teleconnection patterns represent large-scale changes that occur in the pattern of atmospheric waves and rivers and affect the pattern of temperature, precipitation, the path of showers and especially the performance of remote climates in vast territories. During the El Nino-Frein event, the positive sea surface temperature anomalies are more intense in the tropical eastern Pacific Ocean, which causes a significant reduction in the sea surface temperature gradient and, as a result, the weakening of the easterly winds between the tropical eastern and western Pacific Ocean. The purpose of this research is to investigate the relationship between temperature, precipitation and wind anomalies in Mazandaran with Teleconnection indicators. For this purpose, the data of 4 stations of Ramsar, Nowshahr, Babolsar and Qarakhil Qaimshahr were used in the period of 1984-2020. Teleconnection indicators data were obtained from the National Oceanic and Atmospheric Administration (NOAA).
Materials and methods: Using the multivariate regression method, the relationships between Teleconnection indices and weather parameter anomalies were investigated. The method used is the backward type, in which all predictor variables that were selected according to the highest correlation coefficient are first entered into the equation and those with lower confidence coefficients are removed one by one from the model. In this research, four-time steps were used: monthly, simultaneous, one month ahead, two months ahead and three months ahead. In most of the indices, which are less related to the surface temperature of the oceans and are subject to pressure changes, the correlation coefficient was often accompanied by a decrease with the increase of the time period. For each month, temperature, precipitation and wind anomalies were extracted in two stages, first by using the (Z) value greater than 0.5 and less than -0.5, and then by applying the 90th and 10th percentile methods. The efficiency of the relationships obtained was calculated through RMSE.
Results and discussion: The lowest RMSE with a value of 0.81 and a standard error of 0.85 is specific to the wind parameter in the time step of the same month and from the first method (0.5<Z<-0.5) whose changes have a negative relationship with the CAR index (Caribbean SST Index) and a positive relationship with the indices It has SOI (Southern Oscillation Index), AMO (Atlantic multidecadal Oscillation) and PWP (Warm Pool Pacific). The average correlation coefficients of different time steps for the output data of the first method (moderate to very severe anomaly) are 0.72 for wind, temperature 0.57 and precipitation 0.49 and in the second method (very severe anomaly) for precipitation 0.97, wind 0.86 and temperature 0.68.
Conclusion: AMO, GLBT.s (Global Mean Lan/Ocean Temperature) and SOI indices are the most important oceanic indices of this research in the cold season of Mazandaran. According to the observed changes, there is a significant relationship between the periodic phase change of the AMO index and the Mazandaran wind parameter; So, the correlation coefficient between these two is 0.7.
Keywords: Multivariate regression, Teleconnection, anomaly, temperature, precipitation, wind, Mazandaran