| تعداد نشریات | 127 |
| تعداد شمارهها | 7,140 |
| تعداد مقالات | 76,861 |
| تعداد مشاهده مقاله | 154,555,021 |
| تعداد دریافت فایل اصل مقاله | 116,593,562 |
بررسی اثر دورپیوندها بر متغیرهای برف تازه، میانگین و ماکزیمم عمق برف در ایران | ||
| تحقیقات آب و خاک ایران | ||
| دوره 57، شماره 2، اردیبهشت 1405، صفحه 283-308 اصل مقاله (1.81 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2026.407829.670069 | ||
| نویسنده | ||
| علیرضا سعادت مقدسی* | ||
| گروه آبیاری و آبادانی- دانشکده کشاورزی و منابع طبیعی البرز-دانشگاه تهران- کرج -ایران | ||
| چکیده | ||
| این پژوهش نقش دورپیوندهای جوی و اقیانوسی را بر روی سه متغیر کلیدی برف تازه، میانگین بیشینه عمق برف و بیشینه عمق برف در ۳۷ ایستگاه سینوپتیک واقع در شمالغرب، نیمهشمالی و دامنههای زاگرس در دوره زمستانی ژانویه تا مارس ۲۰25–۲000 بررسی میکند. برای استخراج الگوهای همنوسان غالب، از چارچوب نوین R‑PCA مبتنی بر تعبیه مختلط هیلبرت، کرنلهای خطی/غیرخطی و چرخش Varimax/Promax استفاده شد و با بهرهگیری از همبستگی رتبهای اسپیرمن، پاسخ زمانی و مکانی برف نسبت به مجموعهای از شاخصهای دورپیوندی شامل AMO، NAO، EAWR، SCAND، EP‑NP کمیسازی گردید. نتایج نشان داد شاخص چنددههای اطلس با میانگین همبستگی نزدیک به ۶/۰– در ۱۰ ایستگاه، مؤثرترین عامل کلانمقیاس بر تضعیف برف زمستانه است و فاز مثبت فرین آن با زمستانهای گرم و کمبرف، از جمله رخدادهای کمسابقه سالهای ۲۰۲۳–۲۰۲۴ همزمانی دارد؛ در حالی که فاز منفی با تقویت نفوذ ناوههای سرد و افزایش رخداد برف سنگین در شمالغرب و زاگرس همراه است. الگوی اسکاندیناوی (SCAND) نیز با میانگین همبستگی حدود ۶/۰– در 5 ایستگاه کوهستانی، نقش مهمی در تنظیم ابرناکی و فراوانی برف ایفا میکند. همچنین ، شاخصهای EAWR و EP‑NP بهصورت منطقهای درمرز شمالشرق و زاگرس مرکزی معنادار شدند و فاز مثبت NAO، تقویت برف سنگین اردبیل را در ماه مارس توضیح میدهد. تلفیق تحلیل عددی چندمتغیره با تفسیر کیفی نقشههای ترکیبی ترازهای ۵۰۰ و ۲۵۰ هکتوپاسکال، دمای دو متری و ابرناکی نشان داد که برهمکنش فازهای مختلف دورپیوندها با ENSO، ساختار جتقطبی و جت جنبحاره، سازوکار اصلی ناهمگنی برف ایران است و میتواند مبنایی برای بهبود پیشبینی فصلی و مدیریت ریسک سیلاب برفی باشد. | ||
| کلیدواژهها | ||
| ' برف انباشته '؛ ' پیوند از دور'؛ ' ایران' | ||
| مراجع | ||
|
Akhtar‑Danesh, N. (2023). Impact of factor rotation on Q‑methodology analysis. PLOS ONE, 18(8), e0286587. https://doi.org/10.1371/journal.pone.0290728 Baldwin, M. P., Gray, L. J., Dunkerton, T. J., Hamilton, K., Haynes, P. H (2021). The Quasi‐Biennial Oscillation. Reviews of Geophysics, 59(2), e2020RG000702. https://doi.org/10.1029/2020RG000702. Barnston, A. G., & Livezey, R. E. (1987). Classification, Seasonality and Persistence of Low-Frequency Atmospheric Circulation Patterns. Monthly Weather Review, 115(6), 1083–1126. https://doi.org/10.1175/1520-0493(1987)115<1083 Bharati, P., Deb, P., Dimri, A. P., & Turner, A. G. (2025). Pacific Decadal Oscillation‑driven interdecadal variability of snowfall over the Karakoram and the Western Himalayas. *Weather and Climate Dynamics*, 6, 197–219. https://doi.org/10.5194/wcd-6-197-2025 Bonsoms, J., López-Moreno, J. I., & Alonso-González, E. (2023). Snow sensitivity to temperature and precipitation change during compound cold–hot and wet–dry seasons in the Pyrenees. The Cryosphere, 17(3), 1307-1326. https://doi.org/10.5194/tc-17-1307-2023 Bozzoli, M., Crespi, A., Matiu, M., Majone, B., Giovannini, L., Zardi, D., ... & Bertoldi, G. (2024). Long‐term snowfall trends and variability in the Alps. International Journal of Climatology, 44(13), 4571-4591. https://doi.org/10.1002/joc.8597 Bueso, D., Piles, M., & Camps‑Valls, G. (2022). Let’s consider more general nonlinear approaches to study teleconnections of climate variables. arXiv preprint, arXiv:2212.07635. https://doi.org/10.48550/arXiv.2212.07635 Cape, J. (2024). On varimax asymptotic in network models and spectral methods. arXiv preprint, arXiv:2403.05461. https://doi.org/10.48550/arXiv.2403.05461 Craig, P. M., & Allan, R. P. (2022). The role of teleconnection patterns in the variability and trends of growing season indices across Europe. International Journal of Climatology, 42(2), 1072-1091. https://doi.org/10.1002/joc.7290 Dargahian, F., Razavizadeh, S., & Lotfinasabasl, S. (2022). Iranian temperature anomaly is more than twice the global temperature anomaly according to ECMWF ERA5 data. Iran Nature, 7(4), https://doi.org/37-44. 10.22092/irn.2022.357773.1446 Fang, K., Tao, Q., Lv, K., He, M., Huang, X., & Yang, J. (2024). Kernel PCA for out‑of‑distribution detection. NeurIPS 2024 Proceedings, Proc. 38th NeurIPS. Chiang, J. C. H., & Vimont, D. J. (2004). Analogous Pacific and Atlantic Meridional Modes of Tropical Atmosphere–Ocean Variability. Journal of Climate, 17(12), 2417–2427. https://doi.org/10.1175/1520-0442 Enfield, D. B., Mestas-Nuñez, A. M., & Trimble, P. J. (2001). The Atlantic Multidecadal Oscillation and its relation to rainfall and river flows in the continental U.S. Geophysical Research Letters, 28(10), 2077–2080. https://doi.org/10.1029/2000GL012745. Gottlieb, A. R., & Mankin, J. S. (2024). Evidence of human influence on Northern Hemisphere snow loss. Nature, 625(7994), 293-300. Hoell, A., Barlow, M., Landman, W. A., & others. (2025). An unexpected outcome followed an apparent seasonal forecast: Southwest Asia precipitation in OND 2023. *International Journal of Climatology*, 45, e8851. https://doi.org/10.1002/joc.8851 Holton, Dynamic., Introductory on Dynamical Meteorology, Translation by Rostami hosseinkhani,M.M, Torabi azad, M.(2018). Kordestan University central Press. (In Persian). Horan, M. F., Li, S., White, R. H., Vecchi, G. A., & Levin, E. J. T. (2024). Winter precipitation predictability in Central Southwest Asia. *npj Climate and Atmospheric Science*, 7, 122. https://doi.org/10.1038/s41612-024-00594-5 Hurrell, J. W. (1995). Decadal Trends in the North Atlantic Oscillation: Regional Temperatures and Precipitation. Science, 269(5224), 676–679. https://doi.org/10.1126/science.269.5224.676. Irannejad, P., Ahmadi-Givi, F., & Nikouei, N. (2017). A study of winter temperature anomalies in Iran by using the NCEP/NCAR reanalysis dataset. Iranian Journal of Geophysics, 10(4), 12-27. https://doi.org/20.1001.1.20080336.1395.10.4.2.3 Jafary Nadoshan, M., Kamal, O. (2017). Effect of Arctic Oscillation on Temperature and precipitation fluctuation in cold season in central of Iran, Geographical Science 13,26-19-30. (In Persian). Javorskyj, I., Yuzefovych, R., Lychak, O., & Matsko, I. (2024). Hilbert transform for covariance analysis of periodically nonstationary random signals with high‑frequency modulation. ISA Transactions, 144, 452–481. https://doi.org/10.1016/j.isatra.2023.10.025 Johnthon.E.Martin, Atmosphere Dynamic in midlatitude, Translation by Masodyan.S.Abolfazl (2010), Esfahan University Press. (Jonthon,2010). In Persian. Khomsi, K., Tramblay, Y., Alami, R., Saidi, M. E. M., & El Adlouni, S. (2023). A review of large‑scale climate indicators (LSCI) and their impacts. *Discover Water*, 3, 24. https://doi.org/10.1007/s43832-023-00115-6 Khoshravi,M., Mesgary, E (2016). The analysis of Teleconnections relationship with monthly temperature in Northwest of Iran, Geographical of city & zone.21(6), 203-214. (In Persian). Li, X., Zhang, Y., Chen, H., & Wang, J. (2025). Interdecadal response of Eurasian snow water equivalent to sea surface temperatures in the Northern Hemisphere. *Journal of Hydrology*, 655, 132888. https://doi.org/10.1016/j.jhydrol.2025.132888 Liu, Z., Zhang, R., He, J., & Wang, W. (2022). Impacts of the North Atlantic Oscillation on Eurasian winter precipitation variability. *Journal of Geophysical Research: Atmospheres*, 127, e2022JD037172. https://doi.org/10.1029/2022JD037172 López-Moreno, J. I., Vicente-Serrano, S. M., Morán-Tejeda, E., Lorenzo-Lacruz, J., Kenawy, A., & Beniston, M. (2011). Effects of the North Atlantic Oscillation (NAO) on combined temperature and precipitation winter modes in the Mediterranean mountains: Observed relationships and projections for the 21st century. Global and Planetary Change, 77(1-2), 62-76. https://doi.org/10.1016/j.gloplacha.2011.03.003 Mantua, N. J., Hare, S. R., Zhang, Y., Wallace, J. M., & Francis, R. C. (1997). A Pacific Interdecadal Climate Oscillation with Impacts on Salmon Production. Bulletin of the American Meteorological Society, 78(6), 1069–1079. https://doi.org/10.1175/1520-0477(1997)078<1069: APICOW>2.0.CO;2. Marukatat, S. (2023). Tutorial on PCA and approximate kernel PCA. Artificial Intelligence Review, 56, 5445–5477. https://doi.org/10.1007/s10462-022-10297-z Matsuki, A., Kori, H., & Kobayashi, R. (2023). An extended Hilbert transform method for reconstructing the phase from an oscillatory signal. Scientific Reports, 13, 3535. https://doi.org/10.1038/s41598-023-30405-5 Mehmood, S., Palazzi, E., Ridley, J., & others. (2022). Dominant controls of cold‑season precipitation variability in High Mountains of Asia. *npj Climate and Atmospheric Science*, 5, 58. https://doi.org/10.1038/s41612-022-00282-2 Mortimer, C., Brown, R., Decharme, B., & others. (2025). Northern Hemisphere in situ snow water equivalent dataset (NorSWE). *Earth System Science Data*, 17, 3619–3642. https://doi.org/10.5194/essd-17-3619-2025 Nazemosadat, M. J., & Cordery, I. (2000). On the relationships between ENSO and autumn rainfall in Iran. International Journal of Climatology: A Journal of the Royal Meteorological Society, 20(1), 47-61. https://doi.org/10.1002/(SICI)1097-0088(200001)20:1<47: AID-JOC461>3.0.CO;2-P NOAA Climate Prediction Center. (2018). ENSO: Recent Evolution, Current Status and Predictions. https://doi.org/10.25923/ytkx-gn91. Polo, I., Lazar, A., Rodríguez-Fonseca, B., & Mignot, J. (2018). Oceanic control of the interannual variability of the Tropical South Atlantic (TSA). Climate Dynamics, 51, 3539–3555. https://doi.org/10.1007/s00382-018-4084-3. Rohe, K., & Zeng, M. (2023). Vintage factor analysis with Varimax performs statistical inference. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 85(4), 1037–1066. https://doi.org/10.1093/jrsssb/qkad029 Ru, Y., Li, J., & Sun, C. (2024). Subseasonal variability of sea level pressure and its modulation by SCAN and EAWR. *Climate Dynamics*. https://doi.org/10.1007/s00382-024-07345-5 Sabziparvar, M., Firozmand., A., Varsavin., Z., Vahid,A. (2020). The analysis of impact of teleconnections in occurrence of first and last of frost in autumn and spring in Iran. Natural Geography Research.52 (2).295-311. (In Persian). Sadeghi, M., Asakereh, H., & Darand, M. (2025). Climatological analysis of variability in snow cover features across Iran during 1981–2022. *International Journal of Climatology*, 45, e8780. https://doi.org/10.1002/joc.8780 Sadeqi, A., Irannezhad, M., Bahmani, S., Jelodarlu, K. A., Varandili, S. A., & Pham, Q. B. (2024). Long‑term variability and trends in snow depth and cover days throughout Iranian mountain ranges. *Water Resources Research*, 60, e2023WR035411. https://doi.org/10.1029/2023WR035411 Shen, X., Sun, C., Ding, R., & Li, J. (2025). Intraseasonal linkages of winter surface air temperature between Eurasia and North America. *Geophysical Research Letters*, 52, e2024GL113301. https://doi.org/10.1029/2024GL113301 Shirvani, A., Landman, W. A., Barlow, M., & Hoell, A. (2022). Evaluation of the forecast skill of the North American Multi‑Model Ensemble for monthly and seasonal precipitation forecasts over Iran. *International Journal of Climatology*, 43(2), 1141–1166. https://doi.org/10.1002/joc.7900 Trenberth, K. E. (1984). Signal versus Noise in the Southern Oscillation. Monthly Weather Review, 112(2), 326–332. https://doi.org/10.1175/1520-0493(1984)112<0326 Thompson, D. W. J., & Wallace, J. M. (1998). The Arctic Oscillation signature in the wintertime geopotential height and temperature fields. Geophysical Research Letters, 25(9), 1297–1300. https://doi.org/10.1029/98GL00950. Thornton, H. E., Dunstone, N., Smith, D., & Scaife, A. (2023). Seasonal predictability of the East Atlantic pattern. *Geophysical Research Letters*, 50, e2022GL100712. https://doi.org/10.1029/2022GL100712 Umirbekov, A., Kalashnik, A., Dubakina, L., & Semenova, O. (2024). Hydroclimatic teleconnections and their value for modelling snow‑dominated river basins. *EGUsphere* (preprint). https://doi.org/10.5194/hess-2024-174 Wallace, J. M., & Gutzler, D. S. (1981). Teleconnections in the Geopotential Height Field during the Northern Hemisphere Winter. Monthly Weather Review, 109(4), 784–812. https://doi.org/10.1175/1520-0493(1981)109<0784: TITGHF>2.0.CO;2 Wang, H., Li, D., Liu, W., & Sun, C. (2024). Thermodynamic effect dictates AMO influence on Eurasian winter surface air temperature. *npj Climate and Atmospheric Science*, 7, 198. https://doi.org/10.1038/s41612-024-00686-2 Webster, M. A., Merkouriadi, I., Petty, A. A., Liston, G. E., & Perovich, D. K. (2024). Summer snow on Arctic Sea ice modulated by the Arctic Oscillation. *Nature Geoscience*, 17(10), 995–1002. https://doi.org/10.1038/s41561-024-01525-y Wolter, K., & Timlin, M. S. (2011). El Niño/Southern Oscillation behavior since 1871 as diagnosed in an extended Multivariate ENSO Index (MEI. Ext). International Journal of Climatology, 31(7), 1074–1087. https://doi.org/10.1002/joc.2336. Xu, W. L., Li, Y., Chen, Q. L., Zhou, X., Jiang, X. W., Huyan, L. D., ... Zhu, Y. (2025). Remote influence of the Atlantic Multidecadal Oscillation on the autumn surface air temperature in Southwest China. *Earth and Planetary Physics*, 9(5), 1061–1072. https://doi.org/10.26464/epp2025081 Zhang, T., Feng, Y., & Chen, H. (2023). Revealing the formation of the dipole mode of Eurasian snow cover variability during late autumn. Journal of Geophysical Research: Atmospheres, 128(6), e2022JD038233. https://doi.org/10.1029/2022JD038233 Zheng, F., Liu, X. N., Chen, J. H., Huang, W., Sun, C., & Wang, H. (2023). Physical mechanism of winter temperature multidecadal variations in arid Central Asia: The role of the AMO. *Journal of Climate*, 36(21), 7363–7 377. https://doi.org/10.1175/JCLI-D-22-0946.1 | ||
|
آمار تعداد مشاهده مقاله: 48 تعداد دریافت فایل اصل مقاله: 58 |
||