Babaeian, I., Kwon, W.T., Im, E.S., 2004. Application of weather generator technique for climate change assessment over Korea. Korea Meteorological Research Institute. Climate Research lab, 98.
Bannayan, M., Hoogenboom, G., 2008. Weather analogue: a tool for real-time prediction of daily weather data realizations based on a modified k-nearest neighbor approach. Environmental Modelling & Software, 23(6): 703-713.
Crawford, N.H., Linsley, R.K., 1966. Digital Simulation in Hydrology'Stanford Watershed Model 4 (39).
Badescu, V. 2008. Modeling soalr radiation at the earth surface. Verlag Berlin Heidelberg. Springer.
Forsythe, N., Fowler, H., Blenkinsop, S., Burton, A., Kilsby, C., Archer, D., Harpham, C., Hashmi. M. 2014. ApplicationApplication of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The upper Indus basin. The Upper Indus Basin. Journal of Hydrology, 517: 1019–1034.
Ghamghami, M., Bazrafshan, J. 2011. Evaluation of a nonparametric multivariate approach simulating monthly temperature and rainfall variables (Case study: Jazmourian catchment). First National Conference on Meteorology and Agricultural Water Management, University of Tehran, Karaj. (In Farsi)
Ghamghami, M., Bazrafshan, J., Ghahreman, N. 2010. Performance evaluation of a non-parametric approach in simulating monthly rainfall data of some old stations in Iran. 14th Iranian Geophysical Conference, Tehran. (In Farsi)
Khalili, N., Davari, K., Alizadeh, A., Ansari, H., Rezainejad, H., Kafi, M., Ghahreman, B. 2016. Evaluation of the performance of LARS-WG and ClimGen models in the production of rainfall and temperature time series in Sisab rainfed research station, North Khorasan. Journal of Water and Soil (Agricultural Sciences and Industries), 30: 322-333. (In Farsi)
Kiktev, D., Caesar, J., Alexander, L. V., Shiogama, H., Collier, M. 2007. Comparison of observed and multimodeled trends in annual extremes of temperature and precipitation. Geophysical Research Letters, 34.
Kleiber, W., Katz, R. W., Rajagopalan, B. 2013. Daily minimum and maximum temperature simulation over complex terrain. The Annals of Applied Statistics, 7: 588–612.
Kleiber, W., Katz, R. W., Rajagopalan, B. 2012. Daily spatiotemporal precipitation simulation using latent and transformed Gaussian processes. Water Resources Research, 48.
Matalas, N.C. 1967. Mathematical assessment of synthetic hydrology, Water Resources Research, 3: 937-945.
Mavromatis, ra T., Hansen, J. W. 2001. Interannual variability characteristics and simulated crop response of four stochastic weather generators. Agricultural and forest meteorology, 109: 283-296.
Nasiri, B., Yarmoradi, Z. 2017. Prediction of changes in climate parameters of Lorestan province in the next 50 years using HADCM3 model. Scientific - Research Quarterly of Geographical Data (SEPEHR), 26(101). (In Farsi)
Nosrati K., Zehtabian Gh. R., Moradi E., Shahbazi A. 2008. Evaluation of stochastic simulation method for generating meteorological data. Geographical Research Quarterly, 39 (62): 1-9. (in Farsi)
Parely, S. 2019. Generating a set of temperature time series representative of recent past and near future climate. Frontiers in Environmental Science, 7: 99.
Richardson, C. W. 1981. Stochastic simulation of daily precipitation, temperature, and solar radiation. Water resources research, 17: 182–190.
Richardson, C.W., Wright, D.A. 1984. WGEN: a model for generating daily weather variables. US Department of Agriculture, Agricultural Research Service, 8(83).
Khazaei, MR.,
Byzedi, M., Sharafati, A. 2017. Climate change impact on annual precipitation and temperature of Zanjan province with uncertainties investigation. Iranian Journal of Eco Hydrology,
4(3): 847 – 860. (In Farsi)
Semenov, M.A., Brooks, R.J., Barrow, E.M., Richardson, C.W. 1998. Comparison of WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Research 10: 95-107.
Skiles, J.W., Richardson, C.W. 1998. A stochastic weather generator model for Alaska. Ecological modeling, 110, 211-232.
Smith, K., Strong, C., Wang, S.-Y., Rassoul-Agha. F. 2017. A new method for generating stochastic simulations of daily air temperature for use in weather generators. Journal of Applied Meteorology and Climatology, 56: 953–963.
Smith, K., Strong, C., Wang, S.-Y. 2015. Connectivity between historical Great Basin precipitation and Pacific Ocean variability: A CMIP5 model evaluation. Journal of climate, 28: 6096–6112.
Smith, K., Strong, C., Rassoul-Agha, F. 2018. Multisite generalization of the SHArP weather generator. Journal of Applied Meteorology and Climatology, 57(9):2113-2127.
Stern, R. D., Coe, R. 1984. A model fitting analysis of daily rainfall data. Journal of the Royal Statistical Society, 147. 1–34.
Taylor, C. J., 1972. A stochastic model of temperature variations at weather stations in Britain Applied Statistics, 21(3): 248-260.
Thompson, G. A., Burke, D. B. 1974. Regional geophysics of the basin and range province. Annual Review of Earth and Planetary Sciences, 2: 213–238.
Wilks, D. S, Wilby, R. L. 1999. The weather generation game: A review of stochastic weather models. Progress in physical geography, 23: 329–357.
Wilks, D. S. 1992. Adapting stochastic weather generation algorithms for climate change studies. Climatic Change, 22: 67–84.
Wilks, D. S. 1999. Simultaneous stochastic simulation of daily precipitation, temperature and solar radiation at multiple sites in complex terrain. Agricultural and Forest Meteorology, 96: 85–101.