بررسی روند وارونگی‏ های دمایی کلان‏ شهرهای ایران (تهران، مشهد، و تبریز)

هدف از این پژوهش بررسی روند وارونگی دمای لایه مرزی کلان‏شهرهای تهران، مشهد، و تبریز است. در این راستا، از داده‏های پیمایش قائم جو سال‏های 2007- 2017 ساعت صفر (00) ایستگاه‏های هواشناسی تهران، مشهد، و تبریز از پایگاه داده‏های اقلیمی وایومینگ استفاده شد. برای تعیین انواع وارونگی دما، نمودارهای تفی‏گرام داده‎های جو بالا با استفاده از نرم‏افزار raob ترسیم شد. سه نوع وارونگی تابشی، فرونشستی و جبهه‏ای به‏عنوان سه تیپ اصلی و چهار نوع دیگر به‏عنوان تیپ‏های ترکیبی متشکل از این سه نوع وارونگی مشخص و توزیع زمانی فراوانی و درصد هر یک از 7 تیپ وارونگی در هر ماه محاسبه شد. روند یازده‏ساله هر یک از تیپ‏های وارونگی با استفاده از روش ناپارامتریک من کندال و تخمینگر شیب سن تعیین و مقایسه شد. نتایج نشان داد تیپ وارونگی تابشی در همه ایستگاه‏ها کاهش معنادار در سطح اطمینان 0.01 (z>2.58)) و برعکس وارونگی فرونشستی روند افزایشی معناداری در سطح اطمینان 0.05 (z>1.96) نشان داده است. از میان تیپ‏های ترکیبی، تیپ تابشی فرونشستی روند افزایشی معنادار داشت. در مجموع، نوع تیپ‏های وارونگی در دوره 2007-2017 از تیپ‏های وارونگی خالص به تیپ‏های ترکیبی و چندلایه و به‏طور شاخص تیپ تابشی فرونشستی تغییر یافته است.

A comparative Study of the Trend of Temperature Inversions of Iranian Metropolises in Tehran, Mashhad and Tabriz

Introduction The temperature in the troposphere usually decreases with increasing height, therefore, with increasing distance from the ground, the air temperature will be lower (roughly 0.6 degrees Celsius per 100 meters. However daily atmosphere evaluation shows unlike the above description, in many cases the opposite is seen to be called inversion. The purpose of this study was to investigate the adaptive trend of inversion of the temperature of the boundary layer of Tehran, Mashhad and Tabriz metropolis in 20072017 on the daily, monthly and annual time scale. Materials and methods The atmospheric sounding data from the Meteorological stations of Tehran, Mashhad and Tabriz for the years 20072017 were extracted from the Wyoming climate database at 0 o’clock. In order to determine the types of temperature inversion in each metropolis, the graphs of the atmospheric data of each station were mapped using RAOB software and the total number of days with temperature inversion was extracted at the stations. Three types of radiation, superstructure and frontal inversion were identified as three main types and four other types as combinational types of these three types of inversion. Then the frequency distribution and percent of each of the seven inversion types were calculated for each station in the 12 months of the year. The elevenyear process of each inversion type was determined using the nonparametric ManKendall method and the estimator of the Estimator slope and compared with each other. Results and discussion Results analysis indicated that from the seven inversion types, the inversion type of radiation in the three stations under study in all months of the year has been quite decreasing and significant trend at 95% and 99% levels. The subsurface inversion type at all three stations showed a positive and significant trend at 95% and 99% levels in the most months of the year. The trend of forward inversions in the stations under study has been decreasing for the most months (the Z score and Sen’s Estimator Slope is negative). Radiationsubmergedfrontal combined type inversion in the study period in all studied stations in most months has no significant trend. Among the seven types of inversion observed at the studied stations, the combination of radiationsubsidence type has the most significant and incremental trend in all three stations. In all three stations, for 6 months of the year, the increasing frequency of radiationsubsidence type at 95% and 99% confidence levels was significant and the most frequent increase in this type of inversion occurred in the winter and autumn seasons. The combined type of radialfrontal inversion and the Subsidence frontal type at all stations in Tehran, Mashhad and Tabriz have not been significantly trendy for most of the months. The investigation results of the number of inversion layers in the stations showed that in all three stations in all months of the year, the number of inversion layers increased significantly at 99% and 95% confidence levels. An annual review of the frequency of inversion days in all three stations showed a significant increase in the annual scale. In this study, using the inversion layer temperature difference, the thickness of the inversion layer and the station height were used to calculate the intensity of the inversions. Formula (1) I=((Δθ)2)/(3+Z(Δz)) The inversions were calculated only for inversions of the surface of the earth up to the surface of 500 hPa, then by applying the two conditions of the Haffter ((Δθ / (Δz)> 0/005 km ^ (1) and θ_"t" θ_"b" >2( Critical inversion was investigated by the total inversion occurred and the severity of the inversions trends. The results of applying the MannKendall test and the Sen’s Estimator Slope on the data of the severity of critical inversions in different months of the year showed that except for the months of October, November and December at the Mehrabad station, the rate of critical invertebrates was significant at 95 % level. For the rest of the months, the trend of severity of critical inversions has been increasing, but they are not significant at all levels of confidence. In February, the trend of inversion was decreasing in all three stations. Conclusion The results showed that the radiation type inversion occurred in the period 20072017 at all three stations decreased significantly, conversely, the subsidence inversion type showed a significant increase in all three stations. Radiation Subsidence combined type had a significant increase in all three stations. It can be concluded that the types of inversion in the period of 20072017 have changed from pure inversion types to combine and multilayer types and, specifically, to the Radiation Subsidence type. The significance of the increasing trend of inversion layers was also confirmed by statistical tests. Despite the increasing trend of the inversions occurring during the statistical period, this trend has not been significant at any level of confidence. However, the intensity of inversions other than the fall of Tehran station at other stations did not have a significant trend, although they have experienced a positive slope for many months. Several factors, including the release of high heat energy, the increase of greenhouse gases, as well as the increase in population and land use change, the change in surface evolution from heat transfer, pollutant emissions, evapotranspiration and land cover due to the impact of wind currents considered to be reasons of this increased air stability in the boundary layer and the local climate change of these metropolises.Despite the increasing trend of the inversions occurring during the statistical period, this trend has not been significant at any level of confidence. However, the intensity of inversions other than the fall of Tehran station at other stations did not have a significant trend, although they have experienced a positive slope for many months. Several factors, including the release of high heat energy, the increase of greenhouse gases, as well as the increase in population and land use change, the change in surface evolution from heat transfer, pollutant emissions, evapotranspiration and land cover due to the impact of wind currents considered to be reasons of this increased air stability in the boundary layer and the local climate change of these metropolises.