بررسی کارایی مدل WRF-Chem در شبیه‌سازی میدان باد در توفان گردوغبار آوریل 2022 در استان خوزستان

اصغری، م.؛ مشکوتی، ا.ح.؛ رنجبر، ع. و مرادی، م. (1399). مطالعه و ارزیابی طرحواره‌های گسیل گرد و خاک در مدل WRF-Chem توفان شرق و جنوب‌شرق کشور (مطالعه موردی 11 تا 13 آگوست 2018، پژوهش‌های اقلیم شناسی، 43، 87-98.

بهمن‌زاده، ف.؛ قادر، س.؛ حق‌شناس، س. ع. و یازجی، د. (1398). بررسی موردی عملکرد مدل WRF جهت پیش‌یابی میدان باد تراز 10 متر و دمای تراز دومتر با استفاده از داده‌های ماهواره‌ای و ایستگاه‌های همدیدی در منطقه دریای عمان و دریای عرب. مجله فیزیک زمین و فضا، 45(2)، 441-458.

رضازاده، م.؛ ایران‌‌نژاد، پ. و شائو، ی. (1392). شبیه‌سازی گسیل غبار با مدل پیش‌بینی عددی وضع هوا WRF-Chem و با استفاده از داده‌های جدید سطح در منطقه خاورمیانه. مجله فیزیک زمین و فضا، 39(1)، 191-212.

زرین، آ.؛ صالح‌آبادی، ن.؛ مفیدی، ع. و داداشی رودباری، ع. (1401). بررسی فصلی گردوغبار‌ در شمال شرق ایران و شبیه‌‌سازی عددی رخدادهای گردوغبار‌ فرین با مدل WRF-Chem، مجله فیزیک زمین و فضا، 48(2)، 421-440.

Alizadeh Choobari, O., Zawar‐Reza, P., & Sturman, A. (2012). Atmospheric forcing of the three‐dimensional distribution of dust particles over australia: A case study. Journal of Geophysical Research: Atmospheres, 117(D11).

Alizadeh-Choobari, O., Zawar-Reza, P., & Sturman, A. (2014). The “wind of 120 days” and dust storm activity over the sistan basin. Atmospheric research, 143, 328-341.

Bahmanzade, F., Ghader, S., Haghshenas, S. A., & Yazgi, D. (2019). A case study of WRF model performance to hindcast of 10-m wind and 2-m temperature against the satellite and synoptic stations data over the gulf of oman and the arabian sea. Journal of the Earth and Space Physics, 45(2), 441-458. (In Perisan). https://doi.org/10.22059/jesphys.2019.267709.1007051

Bilal, M., Solbakken, K., & Birkelund, Y. (2016). Wind speed and direction predictions by WRF and windsim coupling over nygårdsfjell. Journal of Physics: Conference Series, 753(8), 082018. https://doi.org/10.1088/1742-6596/753/8/082018.

Chawla, I., Osuri, K. K., Mujumdar, P. P., & Niyogi, D. (2018). Assessment of the weather research and forecasting (WRF) model for simulation of extreme rainfall events in the upper ganga basin. Hydrology and Earth System Sciences, 22(2), 1095-1117.

Chen, F., Janjić, Z., & Mitchell, K. (1997). Impact of atmospheric surface-layer parameterizations in the new land-surface scheme of the NCEP mesoscale Eta model. Boundary-Layer Meteorology, 85(3), 391-421.

Dayal, K. K., Cater, J. E., Kingan, M. J., Bellon, G. D., & Sharma, R. N. (2020). Evaluation of the WRF model for simulating surface winds and the diurnal cycle of wind speed for the small island state of fiji. Journal of Physics: Conference Series, 1618(6), 062025. https://doi.org/10.1088/1742-6596/1618/6/062025.

Chen, F., & Dudhia, J. (2001). Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Review, 129(4), 569-585.

Chou, M.-D., & Suarez, M. J. (1994). An efficient thermal infrared radiation parameterization for use in general circulation models. Technical Memorandum, 102 P(104606).

Eltahan, M., & Magooda, M. (2018). Sensitivity of WRF microphysics schemes: Case study of simulating a severe rainfall over egypt. Journal of Physics: Conference Series.

Flaounas, E., Kotroni, V., Lagouvardos, K., Klose, M., Flamant, C., & Giannaros, T. M. (2017). Sensitivity of the WRF-Chem (v3. 6.1) model to different dust emission parametrisation: Assessment in the broader mediterranean region. Geoscientific Model Development, 10(8), 2925-2945.

Gbode, I. E., Dudhia, J., Ogunjobi, K. O., & Ajayi, V. O. (2019). Sensitivity of different physics schemes in the WRF model during a west african monsoon regime. Theoretical and Applied Climatology, 136, 733-751.

Gilmore, M. S., Straka, J. M., & Rasmussen, E. N. (2004). Precipitation and evolution sensitivity in simulated deep convective storms: Comparisons between liquid-only and simple ice and liquid phase microphysics. Monthly Weather Review, 132(8), 1897-1916.

Grell, G. A., & Dévényi, D. (2002). A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophysical Research Letters, 29(14), 38-31-38-34.

Herman, J., Bhartia, P., Torres, O., Hsu, C., Seftor, C., & Celarier, E. (1997). Global distribution of uv‐absorbing aerosols from nimbus 7/toms data. Journal of Geophysical Research: Atmospheres, 102(D14), 16911-16922.

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.

Hong, S.-Y., & Lim, J.-O. J. (2006). The WRF single-moment 6-class microphysics scheme (WSM6). Asia-Pacific Journal of Atmospheric Sciences, 42(2), 129-151.

Janjić, Z. I. (1994). The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Monthly Weather Review, 122(5), 927-945.

Jankov, I., Grasso, L. D., Sengupta, M., Neiman, P. J., Zupanski, D., Zupanski, M., Lindsey, D., Hillger, D. W., Birkenheuer, D. L., & Brummer, R. (2011). An evaluation of five arw-WRF microphysics schemes using synthetic goes imagery for an atmospheric river event affecting the california coast. Journal of Hydrometeorology, 12(4), 618-633.

Karimkhani, M., Azadi, M., Meshkatee, A. H., & Saadatabadi, A. R. (2021). Evaluation of WRF microphysics schemes in the simulation of a squall line over iran using radar and reanalysis data. Nexo Revista Científica, 34(02), 682-697.

Kumar, R., Barth, M., Pfister, G., Naja, M., & Brasseur, G. (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, 14(5), 2431-2446.

LeGrand, S. L., Polashenski, C., Letcher, T. W., Creighton, G. A., Peckham, S. E., & Cetola, J. D. (2019). The afwa dust emission scheme for the gocart aerosol model in WRF-Chem v3. 8.1. Geoscientific Model Development, 12(1), 131-166.

Lin, Y.-L., Farley, R. D., & Orville, H. D. (1983). Bulk parameterization of the snow field in a cloud model. Journal of Applied Meteorology and climatology, 22(6), 1065-1092.

Lu, H., & Shao, Y. (2001). Toward quantitative prediction of dust storms: An integrated wind erosion modelling system and its applications. Environmental Modelling & Software, 16(3), 233-249.

Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., & Clough, S. A. (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated‐k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14), 16663-16682.

Mobarak Hassan, E., Ghafarian, P., Bahrami, F., Karimkhani, M., & Sabori, M. (2019). Sensitivity of mesoscale dust simulation to WRF-Chem boundary layer scheme (case study: March 14th 2012). Journal of Air Pollution and Health, 4(3). https://doi.org/10.18502/japh.v4i3.1547

Prakash, P. J., Stenchikov, G. L., Kalenderski, S., Osipov, S., & Bangalath, H. K. (2015). The impact of dust storms on the arabian peninsula and the red sea. Atmospheric Chemistry and Physics, 15(1), 199-222.

Prospero, J. M., Ginoux, P., Torres, O., Nicholson, S. E., & Gill, T. E. (2002). Environmental characterization of global sources of atmospheric soil dust identified with the nimbus 7 total ozone mapping spectrometer (toms) absorbing aerosol product. Reviews of Geophysics, 40(1), 2-1-2-31. https://doi.org/10.1029/2000rg000095

Rajeevan, M., Kesarkar, A., Thampi, S., Rao, T., Radhakrishna, B., & Rajasekhar, M. (2010). Sensitivity of WRF cloud microphysics to simulations of a severe thunderstorm event over southeast india. Annales Geophysicae.

Song, H.-J., & Sohn, B.-J. (2018). An evaluation of WRF microphysics schemes for simulating the warm-type heavy rain over the korean peninsula. Asia-Pacific Journal of Atmospheric Sciences, 54, 225-236.

Yin, D., Nickovic, S., Barbaris, B., Chandy, B., & Sprigg, W. A. (2005). Modeling wind-blown desert dust in the southwestern united states for public health warning: A case study. Atmospheric Environment, 39(33), 6243-6254. https://doi.org/https://doi.org/10.1016/j.atmosenv.2005.07.009

Yin, D., Nickovic, S., & Sprigg, W. A. (2007). The impact of using different land cover data on wind-blown desert dust modeling results in the southwestern united states. Atmospheric Environment, 41(10), 2214-2224. https://doi.org/https://doi.org/10.1016/j.atmosenv.2006.10.061