Forecasting of aerosols in southwest Asia based on SSP scenarios of CMIP 6 models

Document Type : Original Article

Authors

Department of Physical Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran

Abstract

Introduction: Climate change has had irreversible effects on the planet Earth. The impacts of these changes are observable in all natural and human phenomena. One of the affected phenomena by climate change is dust storms. Besides their short-term and long-term effects, these storms significantly influence air quality on both local and global scales. In recent decades, the frequency of dust storms has increased due to climate variations and human activities, and it is predicted that this increasing trend will continue in the future. Investigating the effects of climate change on dust storms in Southwest Asia, as one of the most significant dust storm hotspots globally, holds great importance. The objective of this research is to examine the impacts of climate change and forecast dust storms in Southwest Asia using the GRDL-ESM4 model from the CMIP6 model ensemble under the optimistic scenario (SSP1.2.6) during the near-future period (2021-2060).
Materials and methods: Southwest Asia is located in the global desert belt. The intensification of climate change in this region has distinct impacts on the trends of dust storms, especially mineral dust storms. Therefore, this study focuses on forecasting dust storms in Southwest Asia using the CMIP6 model ensemble, specifically the GFDL-ESM4 model, under the optimistic scenario (SSP1-2.6). The research methodology involves initially using a 40-year historical period (1975-2014) to analyze dust storm anomalies. Then, the CMIP6 model ensemble, specifically the GRDL-ESM4 model, is utilized to examine the dust storm trends until the end of the present century. Furthermore, the optimistic scenario (SSP1-2.6) is employed for the near-future forecasting period (2021-2060).
Results and discussion: The results show that the maximum amount of dust storms occurs during the summer and spring seasons. In the summer season, the significant increase in temperature and decrease in precipitation contribute to the highest level of dust storms. The spring season exhibits a high level of dust storms compared to other seasons, with northern latitudes having more dust storms than southern latitudes. The minimum dust storm occurrence is observed during the autumn and winter seasons. Autumn is characterized by decreasing temperatures and increasing precipitation processes, leading to a reduction in dust storm frequency. In the winter season, the semi-Arabian Peninsula, especially the eastern regions, experiences the highest dust storm occurrence. In the spring season, the eastern part of the Arabian Peninsula, during the summer season, the southeastern regions of the Arabian Peninsula and southeastern Iran, and during the autumn season, the northern half of Arabia and eastern Iran have the highest frequency of dust storms. According to the optimistic scenario, the summer and spring seasons have the highest dust storm occurrence. Furthermore, it is evident that the intensity of dust storm trends will be higher in the southeastern regions of the Arabian Peninsula, the Makran coasts, the northern half of Iran, northern Arabia, and between the rivers compared to other areas.
Conclusion: In general, southern latitudes experience higher levels of dust storms compared to northern latitudes. The primary center of dust storms is located over the Arabian Peninsula in early winter, gradually shifting towards the eastern regions. During this season, the center of dust storms moves from eastern Arabia to southeastern parts of the Arabian Peninsula and southeastern Iran.
 

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Alam, K., Trautmann, T., Blaschke, T. and Subhan, F., 2014. Changes in aerosol optical properties due to dust storms in the Middle East and Southwest Asia, Remote sensing of environment, v. 143, p. 216-227.
Adebiyi, A.A. and Kok, J.F., 2020. Climate models miss most of the coarse dust in the atmosphere, Science advances, v. 6(15), p. 25-39.
Asghari Sareskanrood, S. and Zeinali, B., 2014. Analyzing and Mapping of Dust Storms Seasonal Frequency over Iran for Hazards Reduction. Environmental Management Hazards, v. 1(2), p. 217-239. doi: 10.22059/jhsci.2014.53122 (in Persian).
Chen, J., Brissette, F.P., Zhang, X.J., Chen, H., Guo, S. and Zhao, Y., 2019. Bias correcting climate model multi-member ensembles to assess climate change impacts on hydrology, Climatic Change, v. 153(3), p. 361-377.
Darvishi Boloorani, A., Najafi, M.S., and Mirzaie, S., 2021. Role of land surface parameter change in dust emission and impacts of dust on climate in Southwest Asia, Natural Hazards, v. 109(1), p. 111-132.
Goodarzi, M., Hoseini, A., Ahmadi, H., 2018. Assessing Temporal and Spatial Distribution of Dust Storm in the south and south west of Iran. jwmseir 2018, v. 11(39), p. 1-10,
 Doi: 20.1001.1.20089554.1396.11.39.9.7 (in Persian).
Ghorbani, S., Moddress, R., 2019. Modelling the Relationship between the Frequency of Dust Storms and Climatic Variables in the Summer Time in Desert Areas of Iran. jwss 2019, v. 23 (3), p. 125-140 (in Persian).
Ginoux, P., Prospero, J.M., Gill, T.E., Hsu, N.C. and Zhao, M., 2012. Global‐scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products, Reviews of Geophysics, v. 50(3), p. 1-21.
Huang, J., Wang, T., Wang, W., Li, Z. and Yan, H., 2014. Climate effects of dust aerosols over East Asian arid and semiarid regions, Journal of Geophysical Research: Atmospheres, v. 119(19), p. 11-398.
Heidary, P., 2015. Development of a model for extracting the optical depth of particles with high spatial resolution. Msc. Thesis, Sharif university of Technology, Tehran, Iran.
Hara, Y., Uno, I. and Wang, Z., 2006. Long-term variation of Asian dust and related climate factors, Atmospheric Environment, v. 40(35), p. 6730-6740.
IPCC. 2021. Climate change 2021 the physical science basis, AR6, Summary for policymakers.
Ji, Z., Wang, G., Yu, M. and Pal, J.S., 2018. Potential climate effect of mineral aerosols over West Africa: Part II—contribution of dust and land cover to future climate change, Climate dynamics, v. 50(7-8), p. 2335-2353.
Lababpour, A., 2020. The response of dust emission sources to climate change: Current and future simulation for southwest of Iran, Science of The Total Environment, v. 714, p. 136821.
Malboosi, S., Babaeian, E., Babaeian, E., Abbasi, F., Asmari, M. and Mokhtari, L. 2012. Climate Change Assessment over Iran during Future Decades, Using Statistical Downscaling of ECHO-G Model. Geographical Research, v. 27(104), p. 205-230 (in Persian).
Modeling the relationship between the frequency of dust storms and climatic variables of the summer season in the desert areas of Iran (in Persian).
Pu, B. and Ginoux, P., 2017. Projection of American dustiness in the late 21 st century due to climate change, Scientific reports, v. 7(1), p. 1-10.
Rezaei, M., Farajzadeh, M. and Kant, S., 2023. The observational evidence of association between types of aerosol mode-cloud-precipitation interaction over Iran. Atmospheric Pollution Research, v. 14(6), p. 101760 (in Persian).
Rahnama, M., Sehat, S., Karami, S., Ranjbar, A. and Khoddam, N., 2023. Vegetation Cover Variation and Dust Frequency analysis over West of Asia. Nivar, v. 47(122-123), p. 17-36. doi: 10.30467/nivar.2023.395654.1245 (in Persian).
Rasouli, A.A., Sari sarraf, B. and Mohammadi, G.H., 2011. long term trend analysis of observed dusty days in the west of iran, applying non-parametric statistics. journal of physical geography, v. 4(11), p. 1-16 (in Persian).
Riahi, K., Van Vuuren, D.P., Kriegler, E., Edmonds, J., O’neill, B.C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O. and Lutz, W., 2017. The shared socioeconomic pathways and their energy, land use and greenhouse gas emissions implications: an overview, Global Environmental Change, v. 42, p. 153-168.
Rolnick, D., Donti, P.L., Kaack, L.H., Kochanski, K., Lacoste, A., Sankaran, K. and Bengio, Y., 2022. Tackling climate change with machine learning. ACM Computing Surveys (CSUR), v. 55(2), p. 1-96.
Shao, Y., Wyrwoll, K.H., Chappell, A., Huang, J., Lin, Z., McTainsh, G.H. and Yoon, S., 2011. Dust cycle: An emerging core theme in Earth system science, Aeolian Research, v. 2(4), p. 181-204.
Wu, C., Lin, Z., Liu, X., Li, Y., Lu, Z. and Wu, M., 2018. Can climate models reproduce the decadal change of dust aerosol in East Asia?. Geophysical Research Letters, v. 45(18), p. 9953-9962.
Yoshino, M., 2002. Climatology of yellow sand (Asian sand, Asian dust or Kosa) in East Asia, Journal of Science China Dearth, v. 45(S), p. 59-70.
Zhang, D.F., Gao, X.J., Zakey, A. and Giorgi, F., 2016. Effects of climate changes on dust aerosol over East Asia from RegCM3, Advances in Climate Change Research, v. 7(3), p. 145-153.
Zhao, A., Ryder, C.L. and Wilcox, L.J., 2022. How well do the CMIP6 models simulate dust aerosols?. Atmospheric Chemistry and Physics, v. 22(3), p. 2095-2119.
Zhao, L., Xu, J. and Powell, A., 2013. Discrepancies of surface temperature trends in the CMIP5 simulations and observations on the global and regional scales: Clim Past Discuss, v. 9, p. 6161-6178.
Keramat, A., Marivani, B. and Samsami, M., 2011. Climatic change, drought and dust crisis in Iran, International Journal of Geological and Environmental Engineering, v. 5(9), p. 472-475.
Schweitzer, M.D., Calzadilla, A.S., Salamo, O., Sharifi, A., Kumar, N., Holt, G. and Mirsaeidi, M., 2018. Lung health in era of climate change and dust storms, Environmental research, v. 163, p. 36-42.
Wang, W. and Fang, Z., 2006.Numerical simulation and synoptic analysis of dust emission and transport in East Asia. Global and Planetary Change, v. 52(1), p. 57-70.
Kang, L., Huang, J., Chen, S. and Wang, X., 2015. Long-Term Trends of Dust Events Over Tibetan Plateau during1961–2010, Atmospheric Environment, v. 125, p. 188-198.
Rabbani, F. and Sharifikia, M., 2023. Prediction of sand and dust storms in West Asia under climate change scenario (RCPs), Theoretical and Applied Climatology, v. 151(1-2), p. 553-566