مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

318
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

Evaluation of Post-Processing and Bias Correction of Monthly Precipitation and Temperature Forecasts in Karun Basin

Pages

  98-111

Abstract

 Efficient forecast of precipitation and temperature with a one-month horizon can provide managers with an exceptional opportunity to plan water resources and deal with floods and droughts. The application of proper Post-processing and bias correction methods can much improve the accuracy of these predictions. In this study, the S2S (Sub seasonal to Seasonal) precipitation and temperature forecasts of ECMWF were evaluated in one of the important basins of Iran. A variety of methods were used for Post-processing and bias correction of these predictions, and the results were compared with different evaluation criteria. Quantile Mapping (QM), Bayesian model averaging (BMA), Support vector regression (SVR), an Empirical equation for bias correction of temperature, and some hybrid methods were applied to forecasts. The BMA outperformed the other methods in improving both temperature and precipitation forecasts. Raw precipitation and temperature forecasts were only applicable in 2 or 3 months of the year, but Post-processing methods were able to accurately improve precipitation in half of the months, especially rainy months. The hybrid of empirical equation-BMA in 10 months of the year was led to better results than the estimate of the next month's temperature using climatological data.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    Kolachian, R., SAGHAFIAN, B., & MOAZAMI, S.. (2020). Evaluation of Post-Processing and Bias Correction of Monthly Precipitation and Temperature Forecasts in Karun Basin. IRAN-WATER RESOURCES RESEARCH, 16(4 ), 98-111. SID. https://sid.ir/paper/388042/en

    Vancouver: Copy

    Kolachian R., SAGHAFIAN B., MOAZAMI S.. Evaluation of Post-Processing and Bias Correction of Monthly Precipitation and Temperature Forecasts in Karun Basin. IRAN-WATER RESOURCES RESEARCH[Internet]. 2020;16(4 ):98-111. Available from: https://sid.ir/paper/388042/en

    IEEE: Copy

    R. Kolachian, B. SAGHAFIAN, and S. MOAZAMI, “Evaluation of Post-Processing and Bias Correction of Monthly Precipitation and Temperature Forecasts in Karun Basin,” IRAN-WATER RESOURCES RESEARCH, vol. 16, no. 4 , pp. 98–111, 2020, [Online]. Available: https://sid.ir/paper/388042/en

    Related Journal Papers

  • No record.
  • Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button