شهرها و بازخورد های آب و هوایی آن(ابر-بارش) مطالعه موردی: کلان شهر تهران

نوع مقاله : مقاله کامل

نویسندگان

1 گروه جغرافیای طبیعی دانشگاه شهید بهشتی

2 دانشگاه شهید بهشتی

10.22059/jphgr.2026.396560.1007889

چکیده

در این مطالعه توسعه فیزیکی شهر تهران در سه دهه گذشته(2022-1992)، با کمک شاخص توسعه فیزیکی شهری بر روی تصاویر لندست اعمال گردید. متناسب با روند توسعه فیزیکی، ویژگیهای بارش ها، ارتفاع پایه ابر در تقابل با میدان آئروسل ها و کیفیت هوا با استفاده از کدهای سینوپ و داده های آلاینده شرکت کنترل کیفیت هوای تهران با بکارگیری بسته Corrplot در محیط برنامه نویسی R محاسبه گردید. در سه دهه گذشته تهران از روند رو به رشد سریعی(R=0.97) برخوردار بوده است و به همان نسبت مناطق طبیعی سطح کلانشهر (R=-0.98) در حال کاهش می باشند. متناسب با روند گسترش شهری، نسبت روزهای برفی با شدت بیش از اندازه ای(R=-0.94) کاهش یافته است. در اتمسفر شهر تهران بین مقادیر بارش همرفتی رخ داده و عمق اپتیکی آئروسل ها، همبستگی مثبت با مقدار آماری معنی داری مشاهده می شود. همچنین بین آلاینده های هوا و ارتفاع پایین ترین لایه ابر همبستگی منفی معنادار قابل توجهی وجود دارد، نتایج همبستگی نشان می دهد که ابرها با لایه مرزی شهری جفت شده و هوای آلوده شهری را در خود جذب و اندازه توزیع قطرات را تغییر می دهند که این امر منجر به کاهش ارتفاع پایه ابر نسبت به سطح زمین می شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Cities and their weather feedback (Cloud- Precipitation) Case Study: Tehran Metropolis

نویسندگان [English]

  • Ghasem Kikhosravei 1
  • Nazanin Hosseini Nia 2
1 Shahid Beheshti University
2 Shahid Beheshti University
چکیده [English]

Introduction:

Tehran is regarded as one of the most polluted cities in the world. This situation results from several factors, including the city's topography, its large population, incomplete combustion from vehicles, the irregular landscape of high-rise buildings without scientific standards, and the unconventional use of fossil fuels for heating and cooling homes. The factors mentioned above, along with the unprecedented expansion of urbanization over the past half century, have certainly affected the behavior of meteorological elements. Therefore, this study attempts to examine the effects of the city and its climatic feedbacks on clouds and precipitation characteristics, especially in the warm seasons when convective precipitation dominates, over a 30-year statistical period.

Methodology:

The time series data used in this study include hourly and daily data from meteorological stations and daily data from air quality monitoring stations, Landsat 7 and 8 ETM and OLI/TIR images, and the aerosol optical depth (AOD) product from the MODIS sensor for the period 1993 to 2022. Meteorological data of current weather codes (ww) related to convective precipitation (Sinop codes 80 to 90 for convective precipitation, codes 91 to 99 for storms, as well as codes where showers and thunderstorms occur outside the station include codes 17-19-25-27 and 29, which are in the convective precipitation group) and snowfall (Sinop codes 70 to 79), precipitation (R, mm), and the height of the lowest cloud layer (HL1) were received from the National Meteorological Organization (https://data.irimo.ir). Similarly, data on the daily average concentrations of standard atmospheric pollutants, namely carbon monoxide (CO, mg/m3), nitrogen dioxide (NO2, µg/m3), sulfur dioxide (SO2, µg/m3), ozone (O3, µg/m3), and particulate matter (PM10 and PM2.5, µg/m3), and air quality index (AQI) were obtained from Tehran air quality monitoring stations. The optical depth data of the MODIS sensor (MOD04_L2) with a spatial resolution of 1 km were extracted in the Google Earth Engine (GEE) system for the statistical period under study. Finally, to examine the physical development of Tehran in the past three decades, the Landsat 7 image from 2002 (representative of the first decade), the Landsat 8 image from 2013 (representative of the second decade), and the Landsat 8 image from 2022 (representative of the third decade) were received from the site (https://earthexplorer.usgs.gov). After performing radiometric and geometric corrections, the NDBI index was calculated, and the built-up areas were separated from the natural areas through Otsu thresholding. R software version 1.4.4 was used to perform statistical analysis of the data. The normality of the distribution of variables and the calculation of descriptive statistics of the data were performed using the functions provided in the MVN package. The relationship between meteorological parameters and air pollutant concentrations was analyzed by selecting the appropriate correlation analysis method based on the data distribution (normal and abnormal), and visualization of the results from the correlation matrix, including correlation coefficients and statistical significance of the coefficients at the 99.9% and 99% confidence levels, was provided by using the corrplot package.

Results and discussion:

Over these three decades, Tehran has experienced a rapid growth trend (R= 0.97), while natural areas in the Tehran metropolitan region have diminished in proportion (R=-0.98). In line with urban expansion, the proportion of snow days with excessive intensity has decreased (R=-0.94). This decline can be attributed to increased atmospheric pollutants, greenhouse gases, and the intensity of the urban heat island, which shifts the precipitation phase in favor of rain over snow. A positive correlation (R= 0.75) with a statistically significant value (P_value= 0.007) is observed between the amount of convective precipitation and the optical depth of aerosols, indicating that the amount and intensity of convective precipitation increase with greater optical depth of aerosols. There is a significant negative correlation between air pollutants (PM2.5, PM10 AQI) and the height of the lowest cloud layer. The correlation results demonstrate that clouds interact with the urban boundary layer, absorbing polluted urban air and altering droplet size distribution, which leads to a decrease in cloud base height relative to the ground surface. Based on the output of machine learning models, PM10 particulate matter and the AQI index are considered the most significant predictor variables affecting changes in cloud base height in Tehran.

Conclusion:

Investigating the impact of urbanization on precipitation phases and patterns is crucial for supporting long-term water resource planning, ensuring the sustainability of ecosystem services, and assessing and designing infrastructure risk amid climate change. Urbanization can change the local climate by modifying land-atmosphere feedback. Solid precipitation in cities is typically lower than in non-urban areas. This decrease stems from alterations in the surface energy balance of urban areas, which, due to increased greenhouse gases and the intensity of the urban heat island effect, shift the phases of solid precipitation in favor of rain. As urbanization and urban construction grow and temperatures rise, the number of snowy days decreases. In the atmosphere of Tehran, the amount of convective precipitation has increased with the increase in the optical depth of aerosols. The factors that affect the increase in convective precipitation can be attributed to the existence of an urban heat island, the roughness of large urban surfaces, and the higher concentration of atmospheric aerosols, which simultaneously increases the occurrence and intensity of convective precipitation with increasing urbanization. In examining the relationship between pollutants and the height of the lowest cloud layer, it was also determined that the atmospheric clouds of Tehran are coupled with the urban boundary layer, absorbing polluted urban air and changing the size distribution of droplets, which leads to a decrease in the height of the cloud base relative to the ground surface.

کلیدواژه‌ها [English]

  • Urban physical expansion
  • convective precipitation
  • air pollutants
  • cloud base height
  • snowfall

مقالات آماده انتشار، پذیرفته شده
انتشار آنلاین از تاریخ 25 اسفند 1404
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