Ajaaj A, Mishra AK, Khan AA (2015) Comparison of bias correction techniques for GPCC rainfall. Stochastic Environmental Research and Risk Assessment 30(6):1659-1675
Aminyavari S, Saghafian B, Delavar M (2019) Post-processing the output of the numerical precipitation forecasting models of TIGGE database using bayesian model averaging (BMA). Iran-Water Resources Research 14(4):246-257 (In Persian)
Araghinejad Sh (2014) Data-driven modeling: Using MATLAB® in water resources and environmental engineering. Water Science and Technology Library 67
Campozano L, Tenelanda D, Sanchez E, Samaniego E, Feyen J (2016) Comparison of statistical downscaling methods for monthly total precipitation: case study for the Paute river basin in southern Ecuador. Advances in Meteorology 2016: 6526341
Gudmundsson L, Bremnes JB, Haugen JE, Engen-Skaugen, T (2012) Technical note: Downscaling RCM precipitation to the station scale using statistical transformations- A comparison of methods. Hydrology and Earth System Sciences 16:3383–3390
Gunn S (1998) Support vector machines for classification and regression. Technical Report, ISIS, Department of Electronics and Computer Science, University of Southampton
HEPEX, HEPEX-SIP Topic: Post-processing (1/3) (2018) [Online]. Available: http://hepex.irstea. fr/hepex-sip-topic-post-processing-13. Accessed December 2018
Ines AWM and Hansen JW (2006) Bias correction of daily GCM rainfall for crop simulation studies. Agricultural and Forest Meteorology 138(1-4):44–53
Javanmard Ghassab M, Delavar M, Morid S (2018) Medium-term forecast evaluation of TIGGE numerical weather prediction models for Karun Basin. Iran-Water Resources Research 14(3) (In Persian)
Khajehei S and Moradkhani H (2017) Towards an improved ensemble precipitation forecast: A probabilistic post-processing approach. Journal of Hydrology 546 (2017):476–48
Kim Y, Kim W, Ohn I, Kim YO (2017) Leave-one-out Bayesian model averaging for probabilistic ensemble forecasting. Communications for Statistical Applications and Methods 24(1):67–80
Kolachian R, Saghafian B (2019) Deterministic and probabilistic evaluation of raw and post processed sub-seasonal to seasonal precipitation forecasts in different precipitation regimes. Theoretical and Applied Climatology 137(1-2):1479–1493
Leander R, Buishand T (2007) Resampling of regional climate model output for the simulation of extreme river flows. Journal of Hydrology 332(3-4):487–496
Li H, Sheffield J, Wood EF (2010) Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching. Journal of Geophysical Research 115:D10101
Li Y, Jiang Y, Lei X, Tian F, Duan H, and Lu H (2017) Comparison of precipitation and streamflow correcting for ensemble streamflow forecasts. Water 10(2):177
Lucatero D, Madsen H, Refsgaard JC, Kidmose J, Jensen JH (2018) On the skill of raw and postprocessed ensemble seasonal meteorological forecasts in Denmark. Hydrol. Earth System Science 22:6591–6609
Ma F, Ye A, Deng X, Zhou Z, Liu X, Duan Q, Xu J, Miao C, Di Z, and Gong W (2016) Evaluating the skill of NMME seasonal precipitation ensemble predictions for 17 hydroclimatic regions in continental China. International Journal of Climatology 36:132–144
Monhart S, Spirig C, Bhend J, Bogner K, Schär C, and Liniger MA (2018) Skill of sub-seasonal forecasts in Europe: Effect of bias correction and downscaling using surface observations. American Geophysical Union 123(15):7999-8016
Ogutu GEO, Franssen WHP, Supit I, Omondi P, and Hutjes RWA (2017) Skill of ECMWF system-4 ensemble seasonal climate forecasts for East Africa. International Journal of Climatology 37(5):2734–2756
Raftery AD, Gneiting T, Balabdaoui F, and Polakowski M (2005) Using Bayesian model averaging to calibrate forecast ensembles. American Meteorological Society 133:1155-1174
Schepen A, Zhao T, Wang QJ, and Robertson DE (2017) A new method for post-processing daily sub-seasonal to seasonal rainfall forecasts from GCMs and evaluation for 12 Australian catchments. Hydrology and Earth System Sciences, Discuss.,
https://doi.org/10.5194/hess-2017-380.
Shah R, Sahai AK, and Mishra V (2017) Short to sub-seasonal hydrologic forecast to manage water and agricultural resources in India. Hydrology and Earth System Sciences 21(2):707–720
Sloughter M, Raftery AE, Gneiting T, and Fraley G (2007) Probabilistic quantitative precipitation forecasting using Bayesian model averaging. Monthly Weather Review, American Meteorological Society 135:3209-3220
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research106(D7):7183-7192
Terink W, Hurkmans RTWL, Torfs PJJF, and Uijlenhoet R (2009) Bias correction of temperature and precipitation data for regional climate model application to the Rhine basin. Hydrology and Earth System Sciences, Discuss., 6:5377–5413
Tian D, Wood EF, and Yuan X (2017) CFSv2-based sub-seasonal precipitation and temperature forecast skill over the contiguous United States. Hydrology and Earth System Sciences 21(3):1477–1490
Vapnik VN (1995) The nature of statistical learning theory. Springer, New York. ISBN 0-387-98780-0
Verkade JS, Brown JD, Reggiani P, and Weerts AH (2013) Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales. Journal of Hydrology 501(2013):73–91
Vitart F, Ardilouze C, Bonet A, Brookshaw A, Chen M, Codorean C, and et al. (2016) Sub-seasonal to Seasonal Prediction (S2S) project database. Bulletin of the American Meteorological Society 98(1), doi:BAMS-D-16- 0017.1.
Wang QJ, Schepen A, Robertson DE (2012) Merging seasonal rainfall forecasts from multiple statistical models through Bayesian model averaging. Journal of Climate 25:5524-5537
Yuan X, Wood EF, Ma Zh (2015) A review on climate-model-based seasonal hydrologic forecasting: physical understanding and system development. WIREs Water 2:523–536
Zhao T, Bennett J, Wang Q, Schepen A, Wood A, Robertson D, and Ramos M (2017) How suitable is quantile mapping for post-processing GCM precipitation forecasts? Journal of Climate 30(9):3185-3196