شناسایی کانون‌های گردوغبار با استفاده از مدل WRF - Chem و طرح‌واره‌های فرسایش بادی GOCART و AFWA (طوفان شبیه سازی شده 2 خرداد 1397)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی طبیعت، دانشکده منابع طبیعی، دانشگاه جیرفت، جیرفت، ایران

2 گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی، دانشگاه تهران، تهران ، ایران

3 پژوهشکده هواشناسی و علوم جو، سازمان هواشناسی کشور، تهران ، ایران

4 پژوهشکده علوم جو و اقلیم پادوا، شورای ملی تحقیقات ایتالیا، ایتالیا

چکیده

سابقه و هدف: امروزه گردوغبار یک چالش اساسی جوامع انسانی محسوب می‌شود. گردوغبار‌ها تأثیر قابل‌توجهی روی بودجه تابشی زمینی، چرخه‌های بیوژئوشیمیایی جهانی، تشکیلات خاک، ترکیب­های شیمیایی اتمسفر می‌گذارند. این پدیده می‌تواند روی سنجه‌های سلامت عمومی تأثیر بگذارد. فلات مرکزی ایران به ­دلیل قرار گرفتن در اقلیم خشک و نیمه‌خشک سالانه با فراوانی بیشتری نسبت به دیگر منطقه­ ها با این پدیده روبرو است. مدیریت و کنترل گردوغبار منوط به شناسایی کانون‌های بحرانی آن و تثبیت در منطقه برداشت امکان‌پذیر است. هدف از این مطالعه، شناسایی کانون‌های گردوغبار داخلی با استفاده از پارامتر شار قائم گردوغبار است.
مواد و روش‌ها: این مطالعه در منطقه فلات مرکزی ایران که اقلیم بیشتر منطقه موردمطالعه گرم و خشک هست، انجام ‌شده است. بیابان ­های کویر و لوت منطقه وسیعی از این حوزه را می­پوشانند. در این مطالعه به‌منظور شناسایی کانون‌های گردوغبار از مدل WRF - Chem و طرح‌واره‌های فرسایش بادی GOCART و AFWA استفاده گردید. برای تشخیص کانون‌های گردوغبار از خروجی شار گسیل طرح‌واره‌های فرسایش بادی استفاده گردید. در همین راستا طوفان شدید 2 خرداد 1397 توسط مدل WRF - Chem برای شبیه‌سازی انتخاب گردید. به‌منظور صحت سنجی و انتخاب بهترین طرح‌واره فرسایش بادی فلات مرکزی ایران از داده‌های پایگاه باز تحلیل MERRA2 و مقادیر غلظت سطحی گردوغبار استفاده شد.
نتایج و بحث: نتایج نشان داد خروجی‌های طرح‌واره‌های GOCART و AFWA با یکدیگر متفاوت است. طرح‌واره GOCART سه کانون گردوغبار قوی در منطقه موردمطالعه شناسایی کرد که این چشمه‌ها در حوزه جازموریان، حوزه لوت و بیابان مرکزی (بیابان کویر) قرار دارند اما مدل AFWA فقط یک کانون ضعیف در حوزه لوت توانست شناسایی کند. نتایج نشان می‌دهد مرکز بیابان لوت، جنوب حوزه جازموریان و همچنین مرکز بیابان دشت کویر (بیابان مرکزی) به‌عنوان کانون‌های گردوغبار داخلی شناخته می‌شوند. به‌طوریکه از یک مترمربع این منطق­ها در ثانیه امکان برخاستن 5800 میکروگرم گردوغبار به اتمسفر وجود دارد. با توجه به اینکه مدت‌زمان طوفان 12 ساعت بوده است از هر هکتار کانون‌های گردوغبار داخلی حدود 2 تن و 505 کیلوگرم گردوخاک به اتمسفر انتقال داده می‌شود. به‌منظور صحت سنجی از داده‌های باز تحلیل MERRA2 و پارامتر غلظت سطحی استفاده گردید. نتایج طرح‌واره GOCART با داده‌های سری زمانی سه‌ساعته پایگاه باز تحلیل MERRA2 مطابقت بیشتری داشت و به‌عنوان بهترین طرح‌واره فرسایش بادی در فلات مرکزی ایران انتخاب شد.
نتیجه‌گیری: نتایج نشان داد که مدل WRF - Chem به‌خوبی توانایی شبیه‌سازی این پارامتر در منطقه موردمطالعه را دارد. نتایج حاصل از طرح‌واره‌های GOCART و AFWA بسیار متفاوت بود به‌طوریکه مدل AFWA کانون‌های گردوغبار داخلی را بسیار ضعیف برآورد کرد اما مدل GOCART به‌خوبی کانون‌های گردوغبار داخلی را شناسایی کرد.
 

کلیدواژه‌ها


عنوان مقاله [English]

Identifying dust springs using WRF-Chem model and GOCART and AFWA wind erosion schemas (simulated dust storm on 05/22/2018)

نویسندگان [English]

  • Farshad Soleimani Sardoo 1
  • Tayebeh Mesbahzadeh 2
  • Ali Salajeghe 2
  • Gholamreza Zehtabian 2
  • Abbas Ranjbar 3
  • Mario Marcello miglietta 4
  • Sara Karami 3
1 Department of Ecological Engineering, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran
2 Department of Reclamation of Dry and Mountainous Regions, Faculty of Natural Resources, University of Tehran, Tehran, Iran
3 Institute of Meteorology and Atmospheric Sciences, Meteorological Organization, Tehran, Iran.
4 Padua Research Institute of Atmospheric and Climatic Sciences, Italian National Research Council, Italy
چکیده [English]

Introduction:
Today, dust is a major challenge for human societies. Dusts have a significant impact on the Earth's radiation budget, global biochemical cycles, soil formations, and chemical compounds in the atmosphere. This phenomenon can affect public health indicators. The Iranian Central Plateau is located in arid and semi-arid climates; it is more likely to face this phenomenon than other regions. Dust management and control depend on identifying critical hotspots and stabilizing the harvesting area. The aim of this study was to identify internal dust sources using the vertical dust flux parameter.
Material and methods:
Kavir and Loot deserts cover a large area of the Iranian Central Plateau. In this study, the WRF-Chem model and GOCART and AFWA wind erosion schemas were used to identify dust springs. Emission fluxes were used to detect dust springs. In this regard, a severe storm was selected on 05/22/2018 by WRF-Chem model for simulation. In order to verify and select the best wind erosion schematic of the Iranian Central Plateau, the data of MERRA2 re-analysis database and surface dust concentration values ​​were used.
Results and discussion:
The results showed that the outputs of GOCART and AFWA schemas were different. The GOCART schemas identified three strong dust sources in the study area that were located in the Jazmourian Basin, the Loot Basin, and the Central Desert (Kavir Desert), but the AFWA schemas were able to identify only one weak source in the Loot area. The results showed that Loot Desert Center, south of Jazmourian Basin, as well as Dasht-e Kavir Desert Center (Central Desert) are known as internal dust sources. So that from one square meter of these areas, it is possible for 5800 micrograms of dust to rise into the atmosphere per second. Due to the fact that the storm lasted for 12 hours, about 2 tons and 505 kg of dust were transferred to the atmosphere from each hectare of internal dust springs. The results of the GOCART schema were more consistent with the three-hour time-series data of the MERRA2 re-analysis database and were selected as the best wind erosion schematic in the Iranian Central Plateau.
Conclusion:
The results showed that the WRF-Chem model had a good ability to resemble the dust flux in the study area. The results of the GOCART and AFWA schemas were different. The AFWA model estimated the internal dust sources to be very weak. However, the GOCART model well detected internal dust sources.
 
 
 

کلیدواژه‌ها [English]

  • Dust springs
  • WRF-Chem model
  • GOCART and AFWA schemas
  • Dust emission flux
  • MERRA2 re-analysis base
  • Central Plateau of Iran
Alfaro, S.C., Gaudichet, A., Gomes, L. and Maillé, M., 1997. Modeling the size distribution of a soil aerosol produced by sandblasting, Journal of Geophycal Research Atmospheric. 102, 11239–11249.
Alfaro, S.C., 2008. Influence of soil texture on the binding energies of fine mineral dust particles potentially released by wind erosion. Geomorphology. 93, 157e167.
Alizadeh Choobari, O., Zawar-Reza, P. and Sturman, A., 2013. Low level jet intensification by mineral dust aerosols. Annals of Geophysics. 31, 625–632.
Azizi, G., Shamsipour, A., Miri, M. and Safarrad, T., 2012. Synoptic and remote sensing analysis of dust events in southwestern Iran. Natural Hazards. 64, 1625–1638.
Baghbanan, P., Ghavidel, Y. and Farajzadeh, M., 2020. Spatial analysis of spring dust storms hazard in Iran. Theoretical and Applied Climatology. 139, 1447–1457.
Bian, H., Tie, X., Cao, J., Ying, Z., Han, S. and Xue, Y. 2011: Analysis of a severe dust storm event over China: Application of the WRF-Dust model. Aerosol and Air Quality Research. 11, 419–428.
Buschiazzo, D.E. and Zobeck, T.M., 2008. Validation of WEQ, RWEQ and WEPS wind erosion for different arable land management systems in the Argentinean Pampas. Earth Surface Processes and Landforms. 33, 1839e1850.
Cao, H., Liu, J. and Wang, G., 2015. Identification of sand and dust storm source areas in Iran. Journal of Arid Land. 7, 567–578.
Chen, S., Zhao, C., Qian, Y., Leung, L. R., Huang, J., Huang, Z., Bi, J., Zhang, W., Shi, J., Yang, L. and Li, D., 2014. Regional modeling of dust mass balance and radiative forcing over East Asia using WRF-Chem. Aeolian Research. 15, 15–30.
Chen, Y.S., Sheen, P.C., Chen, E.R., Liu, Y.K., Wu, T.N. and Yang, C.Y., 2004. Effects of Asian dust storm events on daily mortality in Taipei⁄ Taiwan. Environmental Research. 95, 151– 155.
Chin, M., Savoie, D.L., Huebert, B.J., Bandy, A.R., Thornton, D.C., Bates, T.S., Quinn, P.K., Saltzman, E.S. and De Bruyn, W.J., 2000. Atmospheric sulfur cycle simulated in the global model GOCART: Comparison with field observations and regional budgets. Journal of Geophycal Research Atmospheres. 105, 24689–24712.
Cremades, P.G., Fernández, R.P., Alllende, D.G., Mulena, G.C. and Puliafito, S.E., 2017. High resolution satellite derived erodibility factors for WRF/Chem windblown dust simulations in Argentina, Atmósfera. 30, 11–25.
Dipu, S., Prabha, T.V., Pandithurai, G., Dudhia, J., Pfister, G., Rajesh, K. and Goswami, B.N., 2013. Impact of elevated aerosol layer on the cloud macrophysical properties prior to monsoon onset, Atmospheric Environment. 70, 454–467.
Ebrahimi, S.J., Ebrahimzadeh, L., Eslami, A. and Bidarpoor, F., 2014. Effects of dust storm events on emergency admissions for cardiovascular and respiratory diseases in Sanandaj, Iran. Journal of Environmental Health Science and Engineering. 12, 110.
Fast, J.D., Gustafson J.R., W.I., Easter, R.C., Zaveri, R.A., Barnard, J.C., Chapman, E.G., Grell, G.A. and Peckham, S.E., 2006. Evolution of ozone, particulates, and aerosol direct forcing in an urban area using a new fully-coupled meteorology, chemistry, and aerosol model. Journal of Geophysical Research. 111, D21305.
Flaounas, E., Kotroni, V., Lagouvardos, K., Klose, M., Flamant, C. and Giannaros, T.M., 2016. Assessing atmospheric dust modeling performance of WRF-Chem over the semi-arid and arid regions around the Mediterranean Atmospheric Chemistry and Physics Discussions. https://doi.org /10.5194/acp-2016-307.
Fountoukis, C., Ackermann, L., Ayoub, M.A., Gladich, I., Hoehn, R.D. and Skillern, A., 2016. Impact of atmospheric dust emission schemes on dust production and concentration over the Arabian Peninsula, Model. Earth Systems and Environment. 2, 115.
Ginoux, P., Chin, M., Tegen, I., Prospero, J.M., Holben B., Dubovik, O. and Lin, S. J., 2001. Sources and distributions of dust aerosols simulated with the GOCART model. Journal of Geophysical Research Atmospheres. 106, 20255–20273.
Gong, S.L., 2003. A parameterization of sea-salt aerosol source function for sub-and super-micron particles, Global Biogeochem. Cy. 17, 1097–1104.
Gregory, J.M., Wilson, G.R., Singh, U.B. and Darwish, M.M., 2004. TEAM: integrated, process-based wind-erosion model. Environ. Modell. Softw. 19, 205e215.
Grell, G.A., Peckham, S.E., Schmitz, R., McKeen, S.A., Frost, G.,Skamarock, W.C., and Eder, B., 2005. Fully coupled “online” chemistry within the WRF model. Atmospheric Environment. 39, 6957–6975.
Jish Prakash, P., Stenchikov, G., Kalenderski, S., Osipov, S. and Bangalath, H., 2014. The impact of dust storms on the Arabian Peninsula and the Red Sea. Atmospheric Chemistry and Physics Discussions. 14, 19181–19245.
Kalenderski, S. and Stenchikov, G., 2016: High-resolution regional modeling of summertime transport and impact of African dust over the Red Sea and Arabian Peninsula. Journal of Geophysical Research Atmospheres. 121, 6435–6458.
Kalenderski, S., Stenchikov, G.L. and Zhao, C., 2013. Modeling a typical winter-time dust event over the Arabian Peninsula and the Red Sea, Atmospheric Chemistry and Physics Discussions. 13, 1999 - 2013.
Klose, M. and Shao, Y., 2012. Stochastic parameterization of dust emission and application to convective atmospheric conditions. Atmospheric Chemistry and Physics Discussions. 12, 7309–7320.
Klose, M. and Shao, Y., 2013. Large-eddy simulation of turbulent dust emission. Aeolian Research. 8, 49–58.
Kumar, R., Barth, M.C., Pfister, G.G., Naja, M. and Brasseur, G.P., 2014. WRF-Chem simulations of a typical pre-monsoon dust storm in northern India: influences on aerosol optical properties and radiation budget. Atmospheric Chemistry and Physics Discussions. 14, 2431–2446.
Liu, M., Westphal, D.L., Walker, A.L., Holt, T.R., Richardson, K.A. and Miller, S.D., 2007. COAMPS real-time dust storm forecasting during Operation Iraqi Freedom. Weather Forecast. 22, 192–206.
Liu, M., Westphal, D.L., Wang, S., Shimizu, A., Sugimoto, N., Zhou, J. and Chen, Y., 2003. A high-resolution numerical study of the Asian dust storms of April 2001. Journal of Geophysical Research Atmospheres. 108, 8653.
Liu, Z., Liu, Q., Lin, H.-C., Schwartz, C.S., Lee, Y.-H. and Wang, T., 2011: Three dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia. Journal of Geophysical Research Atmospheres. 116, D23206.
Mang, S.H., Gong, S.L., Zhao, T.L., Vet, R.J., Bouchet, V.S., Gong, W., Makar, P.A., Moran, M.D., Stroud, C. and Zhang, J., 2007: Simulation of entrainment and transport of dust particles within North America in April 2001 (“Red Dust Episode”). Journal of Geophysical Research Atmospheres. 112, D20209.
Marticorena, B. and Bergametti, G., 1995. Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme. Journal of Geophysical Research Atmospheres. 100, 16415–16430.
Nabavi, S.O., Haimberger, L. and Samimi, C., 2017. Sensitivity of WRF-chem predictions to dust source function specification in West Asia. Aeolian Research. 24, 115–131.
Naderi, M. and Raeisi, E., 2015. Climate change in a region with altitude differences and with precipitation from various sources, South-Central Iran. Theoretical and Applied Climatology. 3, 529-540.
Nickovic, S., Kallos, G., Papadopoulos, A. and Kakaliagou, O., 2001. A model for prediction of desert dust cycle in the atmosphere, Journal of Geophysical Research Atmosphere. 106, 18113–18129.
Peckham, S.E., Fast, J., Schmitz, R., Grell, G.A., Gustafson,W.I., McKeen, S.A., Ghan, S.J., Zaveri, R., Easter, R.C., Barnard, J. and Chapman, E., 2011. WRF/Chem Version 3.3 User’s Guide, NOAA Technical Memo.
Rezazadeh, M., Irannejad, P. and Shao, .Y., 2013. Dust emission simulation with the WRF-Chem model using new surface data in the Middle East region. Journal of Earth and Space Physics. 39(1), 191-212.
Rizza, U., Miglietta, M., Mangiaa, C., Lelpo, P., Morichetti, M., Iachini, C., Vigili, S. and Passerini, G., 2018. Sensitivity of WRF-Chem model to land surface schemes: Assessment in a severe dust outbreak episode in the Central Mediterranean (Apulia Region). Atmospheric Research. 201, 168-180.
Rizza, U., Anabor, V., Mangia, C., Miglietta, M.M., Degrazia, G.A. and Passerini, G., 2016. WRF-Chem simulation of a saharan dust outbreak over the mediterranean regions. Ciência e Natura. 38, 330–336.
Shao, Y., 2001: A model for mineral dust emission. Journal of Geophysical Research Atmosphere. 106, 20239–20254.
Shao, Y. and Dong, C.H., 2006. A review on East Asian dust storm climate, modelling and monitoring. Global and Planetary Change. 52, 1–22.
Shao, Y., Wyrwoll, K.H., Chappell, A., Huang, J., Lin, Z., McTainsh, G.H., Mikami, M., Tanaka, T.Y., Wang, X. and Yoon, S., 2011: Dust cycle: An emerging core theme in Earth system science. Aeolian Research. 2, 181–204.
Song, H., Wang, K., Zhang, Y., Hong, C. and Zhou, S., 2017. Simulation and evaluation of dust emissions with WRF-Chem (v3.7.1) and its relationship to the changing climate over East Asia from 1980 to 2015. Atmospheric Environment. 167, 511-522.
Steven A. Ackerman., 1997. Remote sensing aerosols using satellite infrared observations. Journal of Geophysical Research. 102(17), 069-079.
Su, L. and Fung, J.C.H., 2015. Sensitivities of WRF-Chem to dust emission schemes and land surface properties in simulating dust cycles during springtime over East Asia. Journal of Geophysical Research Atmospheres. 120, 11215–11230.
Tanaka, T.Y. and Chiba, M., 2005. Global simulation of dust aerosol with a chemical transport model, MASINGAR. Journal of Meteorological Society of Japan. 83, 255–278.
Tang,Y. Han, Y. and Liu, Z., 2018. Temporal and spatial characteristics of dust devils and their contribution to the aerosol budget in East Asia—An analysis using a new parameterization scheme for dust devils. Atmospheric Environment. 182, 225-233.
Tegen, I. and Fung, I., 1994. Modeling of mineral dust in the atmosphere: Sources, transport, and optical thickness. Journal of Geophysical Research Atmospheres. 99, 22897–22914.
Teixeira, J.C., Carvalho, A.C., Tuccella, P., Curci, G. and Rocha, A., 2016. WRF-chem sensitivity to vertical resolution during a Saharan dust event, Physics and Chemistry of the Earth, Parts A/B/C. 94, 188–195.
Teixeira, J.C. Carvalho, A.C. Tuccella, P. Curci, G. and Rocha, A., 2016. WRF-chem sensitivity to vertical resolution during a Saharan dust event. Physics and Chemistry of the Earth. 94,188-195.
Thomson, M.C., Molesworth, A.M., Djingarey, M.H., Yameogo, K.R., Belanger, F. and Cuevas, L.E., 2006. Potential of environmental models to predict meningitis epidemics in Africa. Tropical Medicine and International Health. 11(6), 781–788.
Uzan, L., Egert, S. and Alpert, P., 2016. Ceilometer evaluation of the eastern Mediterranean summer boundary layer height – first study of two Israeli sites, Atmospheric Measurement Techniques. 9, 4387–4398.
Wang, K., Zhang, Y., Yahya, K.,Wu, S. Y. and Grell, G., 2015. Implementation and initial application of new chemistry-aerosol options in WRF/Chem for simulating secondary organic aerosols and aerosol indirect effects for regional air quality. Atmosphric Environment. 115, 716–732.
Wang, Z., Ueda, H. and Huang, M.Y., 2000. A deflation module for use in modeling long-range transport of yellow sand over East Asia. Journal of Geophysical Research Atmospheres. 105, 26947–26959.
Webb, N.P., McGowan, H.A., Phinn, S.R., Leys, J.F. and McTainsh, G.H., 2009: A model to predict land susceptibility to wind erosion in western Queensland. Australia. Environmental Modelling and Software. 24, 214e227 .
Woodward, S., 2001. Modeling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model. Journal of Geophysical Research Atmospheres. 106, 18155–18166.
Xiaolan, L. and Hongsheng, Z., 2014. Soil Moisture Effects on Sand Saltation and Dust Emission Observed over the Horqin Sandy Land Area in China. Jou Meteorological Researche. 28, 444-452
Zender, C.S., 2003. Mineral Dust Entrainment and Deposition (DEAD) Model: Description and 1990s dust climatology. Journal of Geophyscal Research. 108, 4416-4437.
Zhang, Y., Liu, Y., Kucera, P.A., Alharbi, B.H., Pan, L. and Ghulam, A., 2015. Dust modeling over Saudi Arabia using WRF-Chem: March 2009 severe dust case. Atmospheric Environmental. 119, 118–130.
Zhao, C., Chen, S., Leung, L.R., Qian, Y., Kok, J.F., Zaveri, R.A. and Huang, J., 2013. Uncertainty in modeling dust mass balance and radiative forcing from size parameterization. Atmospheric Chemistry and Physics. 13, 10733–10753.
Zhao, C., Liu, X., Leung, L.R., Johnson, B., McFarlane, S.A., Gustafson Jr., W.I., Fast, J.D., and Easter, R., 2010. The spatial distribution of mineral dust and its shortwave radiative forcingover North Africa: modeling sensitivities to dust emissions and aerosol size treatments. Atmospheric Chemistry and Physics. 10, 8821–8838.
Zhao, C., Liu, X., Ruby Leung, L. and Hagos, S., 2011. Radiative impact of mineral dust on monsoon precipitation variability over West Africa. Atmospheric Chemistry and Physics. 11, 1879-1893.