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پاسخ فرایندهای خردفیزیکی ابر و بارش به حضور هواویزها طی یک رویداد بارش همرفتی در جنوب‌غرب ایران | ||
| فیزیک زمین و فضا | ||
| مقاله 6، دوره 50، شماره 2، تیر 1403، صفحه 357-371 اصل مقاله (1.24 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2024.346406.1007450 | ||
| نویسندگان | ||
| پریسا فتاحی مسرور؛ مریم رضازاده* | ||
| گروه علوم غیرزیستی جوی و اقیانوسی، دانشکده علوم و فنون دریایی، دانشگاه هرمزگان، بندرعباس، ایران. | ||
| چکیده | ||
| در این مطالعه یک رویداد بارش همرفتی، با استفاده از طرحواره خردفیزیکی حساس به هواویز در مدل WRF مورد بررسی قرار گرفت. دو شبیه‌سازی کنترلی و آلوده انجام شد. اختلاف بازتاب تابش خورشیدی به فضا توسط ابرها در آزمایش آلوده افزایش می‌یابد که نشان می‌دهد اولین اثر غیرمستقیم هواویزها نقش عمده‌ای در بودجه انرژی جو ایفا می‌کند. تأثیر غلظت هواویزها بر توسعه ابر در این شبیه‌سازی که دارای همگرایی بیشتر شار قائم رطوبت و سرعت‌های باد بیشتر در منطقه موردمطالعه است، قابل‌توجه است. باتوجه به همگرایی شار قائم رطوبت، بخارآب بیشتری برای میعان‌کردن روی ذرات هواویز وجود دارد و منجر به افزایش محتوای آب ابر می‌شود. چگالی عددی قطرک ابر در آزمایش آلوده در مقایسه با آزمایش کنترلی بیشتر است. افزایش مقدار یخ و برف که نشان‌دهنده بلند‌شدن بیشتر قطرات آب تا سطح انجماد است، می‌تواند به‌دلیل همگرایی شار قائم رطوبت منفی باشد وکاهش محتوای آب ابر به‌دلیل واگرایی رطوبت در این مناطق رخ داده است. اختلاف میزان بارش در دو آزمایش آلوده و کنترلی در بیشتر نقاط حوزه مقادیر مثبت را نشان می‌دهد که به این دلیل است که در جو مرطوب بخار آب به اندازه کافی برای میعان روی ذرات هواویز وجود دارد که موجب تشکیل قطرک های بزرگ‌تر ابر می‌شود. در نتیجه، قطرک‌های ابر برخوردهای مؤثرتری دارند و بارش افزایش می‌یابد. | ||
| کلیدواژه‌ها | ||
| برهم کنش هواویز-ابر؛ قطرات ابر؛ هواویزهای آب‌دوست؛ اثرات هواویز بر بارش؛ طرحواره خردفیزیکی | ||
| عنوان مقاله [English] | ||
| Cloud microphysical and precipitation response to the aerosols during a convective event over Southwestern Iran | ||
| نویسندگان [English] | ||
| Parisa Fattahi Masrour؛ Maryam Rezazadeh | ||
| Department of Marine and Atmospheric Science (Non-Biologic), Faculty of Marine Science and Technology, University of Hormozgan, Bandarabbas, Iran. | ||
| چکیده [English] | ||
| In this study a convective precipitation event in southwestern Iran was examined using the aerosol-aware bulk microphysical scheme implemented in the Weather Research and Forecasting (WRF) model. Two simulations were conducted for this event, which included the control and polluted simulations. In the control simulation, the concentration of aerosols in the current climate was not considrable. In contrast, the aerosol concentration was increased by a factor of 5 at all grid points in the polluted simulation. The main aim was to study the effects of aerosols on cloud microphysics and precipitation. The simulated vertical temperature and wind speed profiles were compared with the radiosonde data, and the model well simulated temperature and wind speed. During the convective event, southerly to southwesterly warm and dry winds dominated, causing a substantial transport of aerosols and humidity. The reflection of shortwave radiation by clouds in the innermost domain was increased in the polluted experiment, indicating that the first indirect effect of aerosols had a significant impact on the radiative balance of the atmosphere. In contrast to the effect of clouds on shortwave radiation, the effect of clouds on longwave radiation was positive at the top of the atmosphere (TOA) because clouds reflect longwave radiation emitted by the earth's surface. The impact of an increase in concentration of aerosols on cloud development was substantial in this simulation, which contained a high convergence of vertical moisture flux and strong winds over the region. The convergence of the vertical moisture flux indicates that more water vapor is available to be condensed on aerosols, which increases the cloud water content. Thus, the number density of cloud droplets is higher in the polluted compared to the control simulation. The altitude of the maximum mass density of cloud droplets is between 3 and 6 km; due to higher specific humidity at these altitudes, higher water vapor can be condensed on condensation nuclei. Also, the mass density of rain drops is higher in the polluted compared to the control simulation up to the altitude of 3 km, which is due to a higher collision of cloud droplets in the polluted simulation. An increase in ice and snow, which indicates a higher lifting of droplets to the freezing level, is seen in this simulation with the negative convergence of vertical moisture flux. This indicates that these regions may help the large-scale collection of moisture and its lifting. On the other hand, with a divergence of moisture in the northern and the whole domain, the cloud water content decreases. In addition, with a high moisture difference, there is higher precipitation in the polluted compared to control simulations because in the humid atmosphere, there is enough water vapor to be condensed on aerosols, that leads to the formation of larger cloud droplets. Thus, the collision of cloud droplets is more efficient, and precipitation increases. In addition, due to a lower cloud base, there is less chance for the evaporation and melting of precipitation. | ||
| کلیدواژه‌ها [English] | ||
| Aerosol-cloud interactions, Cloud droplets, Hygroscopic aerosols, Aerosol effects on precipitation, microphysics schemes | ||
| مراجع | ||
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زارعی، ف.؛ قرایلو، م. و علیزاده چوبری، ا. (1396). تأثیر هواویزها بر بارش در شرایط رطوبت‌های نسبی متفاوت: مطالعه موردی. مجله ژئوفیزیک ایران. 11(2)، 135-155.
مصطفوی، آ.؛ علیزاده، ا. و ثابت قدم، س. (1401). مطالعه موردی تأثیر هواویزها بر ویژگی‌های ابر و بارش در شرایط رطوبت نسبی متفاوت. مجله ژئوفیزیک ایران. 16(1)، 33-46.
Albrecht, B.A. (1989). Aerosols, cloud microphysics, and fractional cloudiness. Science, 245(4923),1227-1230. Altaratz, O., Koren, I., Remer, L.A., & Hirsch, E. (2014). Cloud invigoration by aerosols—Coupling between microphysics and dynamics. Atmospheric Research, 140, 38-60. Andrea, M. O., & Rosenfeld, D. (2008). Aerosol–cloud–precipitation interactions. Part 1. The nature and sources of cloud-active aerosols. Earth-Science Reviews, 89(1-2), 13–41. Andreae, M.O., Rosenfeld, D., Artaxo, P., Costa, A.A., Frank, G.P., Longo, K.M., & Silva-Dias, M.D. (2004). Smoking rain clouds over the Amazon. Science, 303(5662), 1337-1342. Archer-Nicholls, S., Lowe, D., Schultz, D.M., & McFiggans, G. (2016). Aerosol–radiation–cloud interactions in a regional coupled model: the effects of convective parameterization and resolution. Atmospheric Chemistry and Physics, 16(9), 5573-5594. Alizadeh-Choobari, O., & Gharaylou, M. (2017). Aerosol impacts on radiative and microphysical properties of clouds and precipitation formation. Atmospheric Research, 185, 53-64. Colarco, P., Da Silva, A., Chin, M., & Diehl, T. (2010). Online simulations of global aerosol distributions in the NASA GEOS‐4 model and comparisons to satellite and ground‐based aerosol optical depth. Journal of Geophysical Research: Atmospheres, 115(D14). Da Silva, N., Mailler, S., & Drobinski, P. (2018). March. Aerosol indirect effects on summer precipitation in a regional climate model for the Euro-Mediterranean region. In Annales Geophysicae, 36(2), 321-335. Díaz-Fernández, J., Bolgiani, P., Santos-Muñoz, D., Sastre, M., Valero, F., Sebastián-Martín, L.I., Fernández-González, S., López, L., & Martín, M.L. (2021). On the characterization of mountain waves and the development of a warning method for aviation safety using WRF forecast. Atmospheric Research, 258, 105620. Fan, J., Rosenfeld, D., Ding, Y., Leung, L.R., & Li, Z. (2012). Potential aerosol indirect effects on atmospheric circulation and radiative forcing through deep convection. Geophysical Research Letters, 39(9). Fan, J., Yuan, T., Comstock, J.M., Ghan, S., Khain, A., Leung, L.R., Li, Z., Martins, V.J., & Ovchinnikov, M. (2009). Dominant role by vertical wind shear in regulating aerosol effects on deep convective clouds. Journal of Geophysical Research: Atmospheres, 114(D22). Geerts, B., Parsons, D., Ziegler, C.L., Weckwerth, T.M., Biggerstaff, M.I., Clark, R.D., Coniglio, M.C., Demoz, B.B., Ferrare, R.A., Gallus Jr, W.A., & Haghi, K. (2017). The 2015 plains elevated convection at night field project. Bulletin of the American Meteorological Society, 98(4), 767-786. Ginoux, P., Garbuzov, D., & Hsu, N.C. (2010). Identification of anthropogenic and natural dust sources using Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue level 2 data. Journal of Geophysical Research: Atmospheres, 115(D5). Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., & Schepers, D. (2018). ERA5 hourly data on pressure levels from 1979 to present. Copernicus climate change service (c3s) climate data store (cds), 10. Holloway, C.E., & Neelin, J.D. (2009). Moisture vertical structure, column water vapor, and tropical deep convection. Journal of the atmospheric sciences, 66(6), 1665-1683. Hong, S.Y., Noh, Y., & Dudhia, J. (2006). A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly weather review, 134(9), 2318-2341. Iacono, M.J., Delamere, J.S., Mlawer, E.J., Shephard, M.W., Clough, S.A., & Collins, W.D. (2008). Radiative forcing by long‐lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research: Atmospheres, 113(D13). Jiménez, P.A., Dudhia, J., González-Rouco, J.F., Navarro, J., Montávez, J.P., & García-Bustamante, E. (2012). A revised scheme for the WRF surface layer formulation. Monthly weather review, 140(3).898-918. Kain, J.S. (2004). The Kain–Fritsch convective parameterization: an update. Journal of applied meteorology, 43(1), 170-181. Kant, S., Panda, J., Pani, S.K., & Wang, P.K. (2019). Long-term study of aerosol–cloud–precipitation interaction over the eastern part of India using satellite observations during pre-monsoon season. Theor. Appl. Clim., 136, 605–626. Khain, A.P. (2009). Notes on state-of-the-art investigations of aerosol effects on precipitation: a critical review. Environmental Research Letters, 4(1), 015004. Khain, A.P., Beheng, K.D., Heymsfield, A., Korolev, A., Krichak, S.O., Levin, Z., Pinsky, M., Phillips, V., Prabhakaran, T., Teller, A., & Van Den Heever, S.C. (2015). Representation of microphysical processes in cloud‐resolving models: Spectral (bin) microphysics versus bulk parameterization. Reviews of Geophysics, 53(2), 247-322. Khain, A.P., BenMoshe, N., & Pokrovsky, A. (2008). Factors determining the impact of aerosols on surface precipitation from clouds: An attempt at classification. Journal of the Atmospheric Sciences, 65(6), 1721-1748. Koren, I., Remer, L.A., Altaratz, O., Martins, J.V., & Davidi, A. (2010). Aerosol-induced changes of convective cloud anvils produce strong climate warming. Atmospheric Chemistry and Physics, 10(10).5001-5010. Kumar, V.V., Protat, A., May, P.T., Jakob, C., Penide, G., Kumar, S., & Davies, L. (2013). On the effects of large-scale environment and surface types on convective cloud characteristics over Darwin, Australia. Monthly Weather Review, 141(4), 1358-1374. Lee, D., Sud, Y.C., Oreopoulos, L., Kim, K.M., Lau, W.K., & Kang, I.S. (2014). Modeling the influences of aerosols on pre-monsoon circulation and rainfall over Southeast Asia. Atmospheric Chemistry and Physics, 14(13), 6853-6866. Li, G., Wang, Y., & Zhang, R. (2008). Implementation of a two‐moment bulk microphysics scheme to the WRF model to investigate aerosol‐cloud interaction. Journal of Geophysical Research: Atmospheres, 113(D15). Li, Z., Lau, W.K.M., Ramanathan, V., Wu, G., Ding, Y., Manoj, M.G., Liu, J., Qian, Y., Li, J., Zhou, T., Fan, J., Rosenfeld, D., Ming, Y., Wang, Y., Huang, J., Wang, B., Xu, X., Lee, S.S., Cribb, M., Zhang, F., Yang, X., Zhao, C., Takemura, T., Wang, K., Xia, X., Yin, Y., Zhang, H., Guo, J., Zhai, P.M., Sugimoto, N., Babu, S.S., & Brasseur, G.P. (2016). Aerosol and monsoon climate interactions over Asia. Rev. Geophys. 121(9), 4386–4403. Myhre, G., Aas, W., Cherian, R., Collins, W., Faluvegi, G., Flanner, M., Forster, P., Hodnebrog, Ø., Klimont, Z., Lund, M.T., & Mülmenstädt, J. (2017). Multi-model simulations of aerosol and ozone radiative forcing due to anthropogenic emission changes during the period 1990–2015. Atmospheric Chemistry and Physics, 17(4), 2709-2720. Niu, F., & Li, Z. (2012). Systematic variations of cloud top temperature and precipitation rate with aerosols over the global tropics. Atmospheric Chemistry and Physics, 12(18), 8491-8498. Platnick, S., & Twomey, S. (1994). Remote sensing the susceptibility of cloud albedo to changes in drop concentration. Atmospheric research, 34(1-4), 85-98. Rosenfeld, D. (1999). TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall. Geophysical research letters, 26(20), 3105-3108. Rosenfeld, D., Sherwood, S., Wood, R., & Donner, L. (2014). Climate effects of aerosol-cloud interactions. Science, 343(6169), 379-380. Schiro, K.A., Neelin, J.D., Adams, D.K., & Lintner, B.R. (2016). Deep convection and column water vapor over tropical land versus tropical ocean: A comparison between the Amazon and the tropical western Pacific. Journal of the Atmospheric Sciences, 73(10), 4043-4063. Shapiro, A., Fedorovich, E., & Gebauer, J. G. (2018). Mesoscale ascent in nocturnal low-level jets. J. Atmos. Sci., 75, 1403–1427. Sherwood, S.C., Minnis, P., & McGill, M. (2004). Deep convective cloud‐top heights and their thermodynamic control during CRYSTAL‐FACE. Journal of Geophysical Research: Atmospheres, 109(D20). Storer, R.L., & Van den Heever, S.C. (2013). Microphysical processes evident in aerosol forcing of tropical deep convective clouds. Journal of the Atmospheric Sciences, 70(2), 430-446. Storer, R.L., Van Den Heever, S.C., & Stephens, G.L. (2010). Modeling aerosol impacts on convective storms in different environments. Journal of the Atmospheric Sciences, 67(12), 3904-3915. Tao, W.K., Chen, J.P., Li, Z., Wang, C., & Zhang, C. (2012). Impact of aerosols on convective clouds and precipitation. Reviews of Geophysics, 50(2). Thompson, G., & Eidhammer, T. (2014). A study of aerosol impacts on clouds and precipitation development in a large winter cyclone. Journal of the atmospheric sciences, 71(10), 3636-3658. Trier, S. B., Wilson, J. W., Ahijevych, D. A., & Sobash, R. A. (2017). Mesoscale vertical motions near nocturnal convection initiation in PECAN. Mon. Wea. Rev., 145, 2919–2941. Twomey, S. (1977). The influence of pollution on the shortwave albedo of clouds. Journal of the Atmospheric Sciences, 34, 1149-1152. Twomey, S.A., Piepgrass, M., & Wolfe, T.L. (1984). An assessment of the impact of pollution on global cloud albedo. Tellus B, 36(5), 356-366. Waite, M.L., & Khouider, B. (2010). The deepening of tropical convection by congestus preconditioning. Journal of the Atmospheric Sciences, 67(8), 2601-2615. Wang, J., Feng, J., Wu, Q., & Yan, Z. (2016a). Impact of anthropogenic aerosols on summer precipitation in the Beijing–Tianjin–Hebei urban agglomeration in China: Regional climate modeling using WRF-Chem. Adv. Atmos. Sci., 33(6), 753–766. Wang, X.C., Liu, Y.M., & Bao, Q. (2016b). Impacts of cloud overlap assumptions on radiative budgets and heating fields in convective regions. Atmos. Res., 84, 122–132. Wang, Y., Lee, K.-H., Lin, Y., Levy, M., & Zhang, R. (2014). Distinct effects of anthropogenic aerosols on tropical cyclones. Nat. Clim. Chang. 4, 368–373. Zhang, M., Meng, Z., Huang, Y., & Wang, D. (2019). The mechanism and predictability of an elevated convection initiation event in a weak-lifting environment in central-eastern China. Monthly Weather Review, 147, 1823– 1841, Zhang, Y., & Klein, S.A. (2010). Mechanisms affecting the transition from shallow to deep convection over land: Inferences from observations of the diurnal cycle collected at the ARM Southern Great Plains site. Journal of the Atmospheric Sciences, 67(9), 2943-2959. | ||
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