APPLICATION OF NORTH AMERICAN MULTI-MODEL ENSEMBLE FOR IRAN'S SEASONAL PRECIPITATION FORECASTS

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NAJAFI H.; MASSAH BAVANI A.R.; IRANNEJAD P.; ROBERTSON A.V.

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Journal: IRAN-WATER RESOURCES RESEARCH Year:2018 | Volume:13 | Issue:4 Page(s): 28-38

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Title

APPLICATION OF NORTH AMERICAN MULTI-MODEL ENSEMBLE FOR IRAN'S SEASONAL PRECIPITATION FORECASTS

Author(s)

NAJAFI H. | MASSAH BAVANI A.R. | IRANNEJAD P. | ROBERTSON A.V. | Issue Writer Certificate

Keywords

SEASONAL FORECAST SYSTEMSQ1

NORTH AMERICAN MULTI- MODEL ENSEMBLE (NMME)Q1

EVALUATING ATMOSPHERE- OCEAN GENERAL CIRCULATION MODELSQ1

PRECIPITATION FORECASTQ1

IRANQ1

Abstract

The analysis and assessment of climate model outputs for Atmosphere- Ocean General Circulation have become of great global interest. If the appropriate skill of the dynamic seasonal climate forecasts is approved over the long-term (hindcast period) in IRAN, decision makers can be supported by real-time SEASONAL FORECAST SYSTEMS for monthly and seasonal planning. In this research, the output of 8 models enrolling in the North American Multi-Model Ensemble (NMME) including NASA, National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), Environment Canada models, and Geophysical Fluid Dynamics Laboratory (GFDL) models are used for evaluating seasonal PRECIPITATION FORECASTs over IRAN. Analyses are provided for the first 6 months of the water-year when the proportion of precipitation is the highest of total annual rainfall over many parts of the country. The bias and anomaly correlation of NMME precipitation outputs are calculated for three seasons (OND, DJF, JFM) in different lead times with respect to a reference data over the period of 1983-2013. The results showed that the skill of NMME seasonal PRECIPITATION FORECASTs is not similar over IRAN's 30 main river basins. Moreover, the anomaly correlation of NMME individual models is significant for all seasons in lead 0 over many river basins and also for 1-month and 2-month lead time for OND. For the Southwest IRAN the raw NMME outputs without any post-processing exhibited anomaly correlation coefficient of more than 0.6. The bias between -1 to+1 mm/day was identified over almost all grid points within the study area. The results of the research addressed the need to apply post- processing methods and develop multi- model ensembles to benefit from high skills in each individual model for forecasting seasonal amount of precipitation in IRAN.

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APA: Copy

NAJAFI, H., MASSAH BAVANI, A.R., IRANNEJAD, P., & ROBERTSON, A.V.. (2018). APPLICATION OF NORTH AMERICAN MULTI-MODEL ENSEMBLE FOR IRAN'S SEASONAL PRECIPITATION FORECASTS. IRAN-WATER RESOURCES RESEARCH, 13(4 ), 28-38. SID. https://sid.ir/paper/100316/en

Vancouver: Copy

NAJAFI H., MASSAH BAVANI A.R., IRANNEJAD P., ROBERTSON A.V.. APPLICATION OF NORTH AMERICAN MULTI-MODEL ENSEMBLE FOR IRAN'S SEASONAL PRECIPITATION FORECASTS. IRAN-WATER RESOURCES RESEARCH[Internet]. 2018;13(4 ):28-38. Available from: https://sid.ir/paper/100316/en

IEEE: Copy

H. NAJAFI, A.R. MASSAH BAVANI, P. IRANNEJAD, and A.V. ROBERTSON, “APPLICATION OF NORTH AMERICAN MULTI-MODEL ENSEMBLE FOR IRAN'S SEASONAL PRECIPITATION FORECASTS,” IRAN-WATER RESOURCES RESEARCH, vol. 13, no. 4 , pp. 28–38, 2018, [Online]. Available: https://sid.ir/paper/100316/en

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