Document Type : Research Article
Authors
Department of Geography, Faculty of Literature and Humanities, Razi University, Kermanshah, Iran
Abstract
Cold Temperature Extremes (CTEs), in addition to impacting the energy, agricultural, and environmental sectors, pose significant risks to biological systems and human health. Accordingly, understanding this hazard and the atmospheric mechanisms that contribute to its occurrence is considered essential for deepening conceptual insight and improving forecasting accuracy. Upper-tropospheric jet streams are among the principal drivers and modulators of CTEs. To investigate this relationship, temperature records from 30 stations and 300 hPa wind reanalysis data from the ECMWF database spanning a 32-year period were utilized. The gridded jet stream data were initially clustered using the Self-Organizing Map (SOM) neural network technique. Subsequently, CTE frequency within each cluster was quantified, and the corresponding synoptic patterns were analyzed. The study's findings revealed that the mean frequency of CTEs has declined in parallel with the rise in the country’s average air temperature between 1992 and 2023. The highest CTE frequencies occurred under conditions dominated by strong jet streams over the region, typically associated with the confluence of the polar front and subtropical jet streams during the colder months. In contrast, a smaller proportion of CTE events—more prevalent in autumn and spring—was linked to weaker upper-level flow, as indicated by the absence of pronounced jet stream activity at the 300 hPa level.
Introduction
Cold Temperature Extremes (CTEs) can adversely affect public health, agriculture, and the environment. Investigating the meteorological drivers of CTEs and analyzing the atmospheric patterns that trigger them enhances understanding, improves forecasting, and promotes awareness to help mitigate associated impacts. The 300 hPa level is a key layer for analyzing large-scale atmospheric flows and phenomena such as jet streams and planetary waves. Previous studies have examined patterns in the mid- and lower troposphere during CTE events. For example, the role of deep troughs and ridges at the 500 hPa level, along with temperature advection, has been explored in relation to the persistence of cold spells. The occurrence of cold anomalies and their relationship with atmospheric blocking patterns have also been studied. Eastward shifts in blocking systems can displace cold anomalies toward downstream regions, resulting in cold winter conditions. Analysis of jet streams and upper-level circulation is crucial for understanding meteorological phenomena near the Earth's surface. The two primary jet streams in the Northern Hemisphere—the polar front jet stream and the subtropical jet stream—play a significant role in this context. Increased curvature and intensification of these jet streams can lead to the advection of cold air toward lower latitudes, contributing to the occurrence of CTEs. The main objective of this study is to investigate the relationship between jet stream patterns and CTEs in the upper atmosphere over Iran.
Materials and Methods
In this study, daily temperature data from 30 stations operated by the Iranian Meteorological Organization were analyzed over a 32-year period (1992–2023) to identify CTEs. Days on which the average daily temperature at a station fell below the 10th percentile were classified as CTE days. Synoptic maps of the upper atmosphere were examined using daily wind direction and speed data at the 200, 300, and 500 hPa levels, with a horizontal resolution of 0.1 degrees, obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF). To identify dominant wind patterns, a Self-Organizing Map (SOM) neural network was applied using MATLAB’s built-in functions. SOM is an unsupervised learning algorithm designed to detect and visualize the distribution of multidimensional data. It is typically implemented by constructing a two-dimensional grid of nodes that represent clusters within the dataset.
Results and Discussion
The lowest annual average temperature in Iran during the study period was approximately 14.6°C, recorded in 1992—a year that also experienced the highest number of CTE events. The trend line of average temperatures over the 32-year period indicates a warming rate of 0.05°C per year.
Daily horizontal wind data at the 300 hPa level, spanning the same 32-year period, were clustered into six groups using the Self-Organizing Map (SOM) method. Based on the clustering results and the frequency of CTE events, Pattern 1 accounts for approximately 45% of the average CTE frequency across stations in Iran. This pattern is characterized by a strong jet stream at the 300 hPa level, with wind speeds reaching 40 m·s⁻¹ over the southern half of the country, positioning Iran within both the cold inlet and outlet zones of the jet stream. A comparison of wind flow at the 200, 300, and 500 hPa levels reveals the influence of both the polar front and subtropical jet streams on CTE events. Pattern 1 occurred most frequently in January, February, and March, with its highest annual frequency observed in 2019. Pattern 4 also played a significant role, accounting for about 36% of CTE occurrences. It was present in all months except June, July, August, and September. In this pattern, the 300 hPa jet stream extended across the entire country, with its core centered over the central and southern regions. In both Patterns 1 and 4, the presence of strong wind flow at all three levels suggests that the merging of the polar front and subtropical jet streams created favorable conditions for cold air advection into Iran. Patterns 2 and 5 ranked third and fourth, respectively, in terms of CTE frequency. In Pattern 2, no strong jet stream was observed at any of the three levels, and the prevailing wind direction was westerly. These conditions indicate a lack of significant kinetic energy in the upper troposphere. This pattern was most frequent in March, April, and May. Pattern 5 accounted for approximately 5% of CTE events and occurred predominantly in May, June, September, and October—transitional months between cold and warm seasons. In this pattern, a jet stream at the 200 hPa level, with maximum speeds of 35–40 m·s⁻¹, extended in a narrow band from Iraq to northeastern Iran. Patterns 3 and 6 did not play a significant role in CTE occurrence. Wind flow in the upper troposphere within these clusters clearly exhibited anticyclonic circulation associated with the dominance of the subtropical high-pressure system.
Conclusion
Based on the results of the statistical analysis, the mean frequency of CTEs has declined in parallel with the rise in the country’s average air temperature between 1992 and 2023. The analysis of clustering patterns and CTE event frequencies—consistent with previous studies—indicates that jet streams play a significant role in the occurrence of CTEs in Iran. Wind flow patterns at various atmospheric levels clearly demonstrate the influence of both the polar front and subtropical jet streams on these events. Among the six identified clusters, strong and persistent jet streams are defining features of Clusters 1 and 4, both of which have played a major role in CTE formation. Cluster 1 occurred most frequently during the cold months, while Cluster 4 was observed during both cold and temperate months. In these two patterns, the polar front jet stream is responsible for advecting cold air into Iran. In Cluster 2, strong jet streams were absent in the upper troposphere, and the prevailing currents were predominantly westerly. This pattern was more common in late winter and early spring. CTE events in Cluster 5 primarily occurred during the equinox months, when relatively weak jet streams were present over the northern half of the country. The frequency of CTE events in Clusters 3 and 6 was nearly zero across stations, due to the dominance of subtropical high-pressure and the absence of favorable conditions for CTE development.
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