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References

  • Baigorria GA, Jones JW, Shin DW, Mishra A, O'Brien JJ. 2007. Assessing uncertainties in crop model simulations using daily bias-corrected Regional Circulation Model outputs. Climate Research 34: 211222.
  • Baigorria GA, Jones JW, O'Brien JJ. 2008. Potential predictability of crop yield using an ensemble climate forecast by a regional circulation model. Agricultural and Forest Meteorology 148: 13531361.
  • Baron C, Sultan B, Balme M, Sarr B, Traore S, Lebel T, Janicot S, Dingkuhn M. 2005. From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact. Philosophical Transactions of the Royal Society B 360: 20952108.
  • Challinor AJ, Slingo JM, Wheeler TR, Doblas-Reyes FJ. 2005. Probabilistic simulations of crop yield over western India using DEMETER seasonal hindcasts ensembles. Tellus A 57: 498512.
  • Dobler A, Ahrens B. 2008. Precipitation by a regional climate model and bias correction in Europe and South Asia. Meteorologische Zeitschrift 17: 499509.
  • Elshamy ME, Seierstad IA, Sorteberg A. 2009. Impacts of climate change on Blue Nile flows using bias-corrected GCM scenarios. Hydrology and Earth System Sciences 13: 551565.
  • Goddard L, Mason SJ. 2002. Sensitivity of seasonal climate forecasts to persisted SST anomalies. Climate Dynamics 19: 619632.
  • Goddard L, Mason SJ, Zebiak SE, Ropelewski CF, Basher R, Cane MA. 2001. Current approaches to seasonal to interannual climate predictions. International Journal of Climatology 21: 11111152.
  • Hansen JW, Challinor A, Ines AVM, Wheeler T, Moron V. 2006. Translating climate forecasts into agricultural terms: advances and challenges. Climate Research 33: 2741.
  • Hansen JW, Indeje M. 2004. Linking dynamic seasonal climate forecasts with crop simulation for maize yield prediction in semi-arid Kenya. Agricultural and Forest Meteorology 125: 143157.
  • Hansen JW, Ines AVM. 2005. Stochastic disaggregation of monthly rainfall data for crop simulation studies. Agricultural and Forest Meteorology 131: 233246.
  • Hansen JW, Jones JW. 2000. Scaling-up crop models for climate variability applications. Agricultural Systems 65: 4372.
  • Hansen JW, Mavromatis T. 2001. Correcting low-frequency variability bias in stochastic weather generators. Agricultural and Forest Meteorology 109: 297310.
  • Indeje M, Semazzi FHM, Ogallo LJ. 2000. ENSO signals in East African rainfall and their prediction potentials. International Journal of Climatology 20: 1946.
  • Ines AVM, Hansen JW. 2006. Bias correction of daily GCM rainfall for crop simulation studies. Agricultural and Forest Meteorology 138: 4453.
  • Ines AVM, Hansen JW. 2009. Extracting useful information from daily GCM rainfall for cropping system modeling. AgSAP Conference 2009. Egmond Aan Zee: The Netherlands.
  • Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT. 2003. The DSSAT cropping system model. European Journal of Agronomy 18: 235265.
  • Katz RW, Parlange MB. 1998. Overdispersion phenomenon in stochastic modeling of precipitation. Journal of Climate 11: 591601.
  • Keating BA, Wafula BM, Watiki JM. 1992. Exploring strategies for increased productivity—the case for maize in semi-arid Eastern Kenya. In A Search for Strategies for Sustainable Dryland Cropping in Semi-arid Eastern Kenya, ACIAR Proceedings, No. 41. Probert ME (ed). Australian Centre for International Agricultural Research: Canberra, 90101.
  • Mavromatis T, Jones PD. 1999. Evaluation of HADCM2 and direct use of daily GCM data in impact assessment studies. Climatic Change 41: 583614.
  • Mearns LO, Rosenzweig C, Goldberg R. 1996. The effects of changes in daily and interannual climatic variability on CERES-Wheat: a sensitivity study. Climatic Change 32: 257292.
  • Mishra A, Hansen JW, Dingkuhn M, Baron C, Traore SB, Ndiaye O, Ward MN. 2008. Sorghum yield prediction from seasonal rainfall forecasts in Burkina Faso. Agricultural and Forest Meteorology 148: 17981814.
  • Mishra AK, Singh VP. 2009. Analysis of drought severity-area-frequency curves using a general circulation model and scenario uncertainty. Journal of Geophysical Research D: Atmospheres 114(6): D06120.
  • Mishra AK, Özger M, Singh VP. 2009. Trend and persistence of precipitation under climate change scenarios for Kansabati basin, India. Hydrological Processes 23: 23452357.
  • Riha SJ, Wilks DS, Simeons P. 1996. Impacts of temperature and precipitation variability on crop model predictions. Climatic Change 32: 293311.
  • Ritchie JT, Singh U, Godwin DC, Bowen WT. 1998. Cereal growth, development and yield. In Understanding Options for Agricultural Production, Tsuji GY, Hoogenboom G, Thornton PK (eds). Kluwer Academic Publishers: Dordrecht, 7998.
  • Robertson AW, Ines AVM, Hansen JW. 2007. Downscaling of seasonal precipitation for crop simulation. Journal of Applied Meteorology and Climatology 46: 677693.
  • Roeckner E, Arpe K, Bengtsson L, Claussen CM, Dümenil L, Esch M, Giorgetta M, Schiese U, Schulzweida U. 1996. The atmospheric general circulation model ECHAM-4: model description and simulation of present-day climate. Report No. 218, Max Planck Institute for Meteorology. Hamburg.
  • Schmidli J, Frei C, Vidale PL. 2006. Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods. International Journal of Climatology 26: 679689.
  • Semenov MA, Doblas-Reyes FJ. 2007. Utility of dynamical seasonal forecasts in predicting crop yield. Climate Research 34: 7181.
  • Sharma D, Gupta AD, Babel MS. 2007. Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand. Hydrology and Earth System Sciences 11: 13731390.
  • Stern RD, Coe R. 1984. A model fitting analysis of daily rainfall data. Journal of Royal Statistical Society A 147: 134.
  • Tsuji GT, Uehara G, Salas S. (eds). 1994. DSSATv3.0, Vol. 3. University of Hawaii: Honolulu, Hawaii, p. 286.
  • Wilks DS. 1995. Statistical Methods in the Atmospheric Sciences, Academic Press: San Diego.
  • Wilks DS. 1999. Interannual variability and extreme-value characteristics of several stochastic daily precipitation models. Agricultural and Forest Meteorology 93: 153169.
  • Wilks DS, Wilby RL. 1999. The weather generation game: a review of stochastic weather models. Progress in Physical Geography 23: 329357.
  • Willmott CJ. 1982. Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society 63: 13091313.
  • Woolhiser DA, Roldán J. 1982. Stochastic daily precipitation models. 2. A comparison of distributions of amounts. Water Resources Research 18: 14611468.