ارزیابی شبیه‌سازی مدل‌های اقلیمی با استفاده از روش تصمیم‌گیری چندمعیاره و معیارهای عملکرد

Anil, S., & Raj P. A. (2022). Deciphering the projected changes in CMIP-6-based precipitation simulations over the Krishna River Basin. Journal of Water & Climate Change, 13(3), 1389–1407. https://doi.org/10.2166/wcc.2022.399.

Almazroui, M., Ashfaq, M., Islam, M. N., Rashid, I. U., Kamil, S., Adnan Abid, M., O'Brien, E., Ismail, M., Reboita, M. S., Sörensen, A. A., Arias, P. A., Alves, L. M., Tippett, M. K., Saeed, S., Haarsma, R., Doblas-Reyes, F. J., Saeed, F., Kucharski, F., Nadeem, I., Silva-Vidal, Y., Rivera, J. A., Ehsan, M. A., Martínez-Castro, D., Muñoz, Á. G., Coppola, E., & Bamba Sylla, M. (2021). Assessment of CMIP6 performance and projected temperature and precipitation changes over South America, Earth Systems and Environment, 5, 155–183. https://doi.org/10.1007/s41748-021-00233-6.

Ashofteh, P.-S., Bozorg-Haddad, O. & Mariño, M. (2013). Climate change impact on reservoir performance indexes in agricultural water supply. Journal of Irrigation and Drainage Engineering, 139(2), 85-97. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000496.

Ashofteh, P.-S. (2018). Evaluation of the flexibility of the reservoir system in terms of climate change in the optimal supply of water. Iranian Journal of Soil and Water Research, 49(2), 269–279. [In Persian]. https://doi.org/10.22059/ijswr.2017.226689.66762.

Abdolalizadeh, F., Khorshiddoust, A. M. & Jahanbakhsh, S. (2021). Assessment of the performance of the CMIP6 model for the analysis of temperature and precipitation in the Urmia Lake basin. Journal of Climate Change Research, 3(11), 17-30. [In Persian].

https://doi.org/10.30488/CCR.2022.361233.1093.

Bayissa, Y., Melesse, A., Bhat, M., Tadesse, T. & Shiferaw, A. (2021). Evaluation of regional climate models (RCMs) using precipitation and temperature-based climatic indices: (A case study of Florida, USA), Water, 13(17). https://doi.org/10.3390/w13172411.

Dehghani, A., Mortazavi, F., Dehghani, A., Rahmat, M. B., Galavi, H., Bolonio, D., Ng, J. L., Rezaverdinejad, V., & Mirzaei, M. (2025). Multi-model assessment of climate change impacts on drought characteristics. Natural Hazards, 121(5), 6069–6084. https://doi.org/10.1007/s11069-024-07015-z.

Farzaneh, M. R., Samadi, S. Z., Akbarpour, A. & Eslamian, S. S. (2010). Introducing selected predictors for statistical-regression downscaling in the Behesht Abad sub-basin of North Karun, 1st Iranian National Conference on Applied Research in Water Resources. 11 May 2010. Kermanshah, Kermanshah University of Technology. [In Persian]. https://civilica.com/doc/112792.

Gupta, H. V., Kling, H., Yilmaz, K. K. & Martinez, G.F. (2009). Decomposition of the mean squared error and NSE performance criteria: (Implications for improving hydrological modelling). Journal of Hydrology, 377(1–2), 80–91. https://doi.org/10.1016/j.jhydrol.2009.08.003.

Houngue, N.R., Almoradie, A.D.S. & Evers, M. (2022). A multi-criteria decision analysis approach for regional climate model selection and future climate assessment in the Mono River Basin, Benin and Togo. Journal of Atmosphere, 13(9), 1471. https://doi.org/10.3390/atmos13091471.

Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679–688. https://doi.org/10.1016/j.ijforecast.2006.03.001.

Helmi, M., Neyshabouri, S. Z., Amirabadizadeh, M. & Yaghoobzadeh, M. (2024). Evaluation of SDSM, LARS-WG, and ANN methods in downscaling of temperature and precipitation for two different climates. Journal of Drought and Climate Change Research (JDCR), 1(4), 105–118. [In Persian]. https://doi.org/10.22077/JDCR.2023.6996.1049.

Kim, Y.-H., Min, S.-K., Zhang, X., Sillmann, J. & Sandstad, M. (2020). Evaluation of the CMIP6 multi-model ensemble for climate extreme indices. Weather and Climate Extremes, 29, 100269. https://doi.org/10.1016/j.wace.2020.100269.

Kjellström, E., Boberg, F., Castro, M. & Christensen, J. H. (2010). Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models. Climate Research, 44(2-3), 135-150. https://doi.org/10.3354/cr00932.

Khayat, A., Amirabadizadeh, M., Pourreza-Bilondi, M. & Khozeymehnehad, H. (2020). Study temperature and precipitation parameters under the effect of climate change (Case study: Birjand Plain). Journal of Irrigation and Water Engineering, 11(1), 200–210. [In Persian]. https://doi.org/10.22059/iwe.2020.114963.

Mirzaei, M., Shirmohammadi, A., Ruiz-Barradas, A., Olson, L. J., & Negahban-Azar, M. (2025). Climate change effects on the spatial and temporal distribution of extreme precipitation in the Mid-Atlantic region. Urban Climate, 61, 102382. https://doi.org/10.1016/j.uclim.2025.102382.

Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D. & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885–900. https://doi.org/10.13031/2013.23153.

Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models, Part I—A discussion of principles. Journal of Hydrology, 10(3), 282–290. https://doi.org/10.1016/0022-1694(70)90255-6.

Parviz, L., Kazemi, B., & Hatef, M. A. (2024). Utilization of the climate indices and the multi-criteria decision-making approach in crop yield forecasting in line with policy-making in agriculture. Journal of Drought and Climate Change Research (JDCR), 2(3), 49–66. https://doi.org/10.22077/jdcr.2024.7942.1072.

Pradhan, P., Shhrestha, S., Sundram, S.M.M. & Virdis, S. (2021). Evaluation of the CMPI5 general circulation models for simulating the precipitation and temperature of the Koshi River basin in Nepal. Journal of Water and Climate Change, 12(1). https://doi.org/10.2166/wcc.2021.124.

Legg, S. (2021). IPCC, 2021: Climate change 2021-the physical science basis. Interaction, 49(4), 44-45.

Pearson, K. (1895). VII. Note on regression and inheritance in the case of two parents. proceedings of the royal society of London, 58(347-352), 240-242. https://doi.org/10.1098/rspl.1895.0041.

Ramezani Etedali, H., & Koohi, S. (2024). Investigating the impact of climate change on the aridity in Iran with a population exposure approach. Journal of Drought and Climate Change Research (JDCR), In Press. [In Persian]. https://doi.org/10.22077/jdcr.2024.8258.1079.

Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. https://doi.org/10.1016/0377-2217(90)90057-I.

Samadi, S. Z., Massah Bavani, A. R. & Mahdavi, M. (2009). Selecting a predictor variable for statistical downscaling of temperature and precipitation data in the Karkheh watershed, Fifth National Conference on Watershed Management Science and Engineering of Iran. 11-12 May 2010. Golestan, Gorgan University of Agricultural Sciences and Natural Resources. [In Persian]. https://civilica.com/doc/87064

Weyant, J. (2017). Some contributions of integrated assessment models of global climate change. Review of Environmental Economics and Policy, 11(1), 115-137. https://doi.org/10.1093/reep/rew018.

Willmott, C. J., & Matsuura, K. (2005). Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate Research, 30(1), 79–82. https://doi.org/10.3354/cr030079.

Yaghoobzadeh, M. (2022). Selecting the best general circulation model and historical period to determine the effects of climate change on precipitation, IDŐJÁRÁS/Quarterly journal of the Hungarian meteorological service, 126(2): 247-265. https://doi.org/10.28974/idojaras.2022.2.5.