The relationship between surface pressure and temperature fields over Iran: An approach based on multiple time-scales analysis of NCEP/NCAR reanalysis data

Document Type : Research Article

Author

Department of Physics, Faculty of Science, Razi University, Kermanshah, Iran.

Abstract

Surface temperature and pressure are significant atmospheric parameters that, along with humidity and precipitation, can be regarded as the most effective quantities in determining the global and regional climate in small and large spatial scales. This importance stems from the fact that they can affect the dynamic elements of the weather. Surface air temperature (ST), as a crucial element of climate, is widely used in studies related to meteorology, climate change, energy and the environment and its changes (especially due to global warming) have a substantial impact on health, human well-being, and the environment. On the other hand, atmospheric pressure plays a vital role in determining the exact weather conditions and the climate of a specific location on Earth, and it is closely related to wind patterns and the formation of weather systems. Furthermore, the effects of heating and cooling in the atmosphere can depend on the level of atmospheric pressure.
To improve our ability to gain a clear understanding of the mutual coupling between temperature and pressure changes on intra-annual to inter-decadal scales, research is required to describe the possible relationship between these quantities from different points of view. This relationship can be complex on some time scales. Hence, in the current research, with using time series of monthly reanalysis data, the relationship between surface temperature and pressure at sea level has been investigated in different time scales over Iran. Based on the analysis of the linear trend of the raw data in the statistical period of 1948-2020, a tendency of increasing temperature and surface pressure was observed in all regions of Iran. The highest increase in temperature has occurred in the north-east (1.6 °C to 1.8 °C), and the lowest increase in temperature has been found in the extreme northwest of Iran (0.4 °C to 0.6 °C), which can be attributed to the effects of global warming. In addition, the highest increase in pressure (more than 4.5 hPa) was observed in the extreme northwest of the country, and the lowest increase in pressure (less than 1.5 hPa) was found in the southern coast of the country. Based on correlation and regression analyses, the inter-relationships between pressure and temperature were investigated for the raw data as well as the filtered data (in different time scales). The results demonstrate that the annual component has a large impact on the correlation pattern between the raw temperature and pressure data. A phase difference of 5-6 months was observed between the common annual periodic component of the temperature and pressure. For the intra-annual components, there is a negative correlation (-0.5 to -0.6) in the northeast at the lag = 0 and in the southeast at the lag = 3 months. In addition, the highest positive correlation (+0.5 to +0.6) was revealed in the lag = 6 months in the southeast of Iran. For the inter-annual plus inter-decadal components of the temperature and pressure at the lag of zero, the highest negative correlation coefficient (-0.3 to -0.4) was observed in the east and northeast of Iran. In larger time lags, the correlation coefficient gradually becomes positive, which reaches more than +0.4 in a large part of the country at the lag = 200 months. Therefore, with a phase (time) difference of several years (2 to 16 years), the correlation pattern tends to increase over a large area of Iran, which in turn indicates the presence of common inter-decadal quasi-periodic components (but with a specific phase difference) in the time series of surface pressure and temperature. Scatter plots and regression modeling for the selected stations and for different scales included in the time series display unique patterns for the relationship between the pressure and temperature so that these patterns can change over Iran depending on the latitude of the selected station.

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