Annual to Decadal Prediction of Precipitation over Iran during 2019-2023 using statistical downscaling of DCPP models

Decadal Climate Prediction Project (DCPP), is one of the ambitious programs to bridge the gap between climate prediction and climate. In order to provide climate services to stakeholders, the IRIMO provides daily and seasonal forecasts and climate projections. In the meantime, providing annual prediction has been one of the main requests of users from IRIMO, the gap of annual prediction was evident in previous years. In this study, Iran’s precipiation prediction for the period 2019-2023 were predictedusing the post-processing of the Decadal Climate Prediction Project (DCPP). For this purpose, two types of data have been used, including: output of DCPP project models in historical (1989-2018) and prediction (2019-2023) periods and observed precipitation data from GPCC, a grided databases as an alternative to observational (quasi-observational) data. The results showed that, Iran’s average precipitation in the period 2019-2023 will be normal to less than normal based on 4 methods of bias correction, multi-model weighting, probability prediction and climatic teleconections. As an average, findings of this project showed that the mean precipitation of Iran in the period 2019-2023 will be in the range of normal to less than normal, based on the DCPP model outputs and two decadal scale teleconnections of AMO and PDO. Based on bias correction and weighting system, precipitation in the western and southern half of the Iran will be more than normal and in the east it is normal to less than normal, in the probabilistic method precipitation in 2019 and 2020 preicted to be more than normal and in 2021- 2023, it will be less than normal to normal. Also, the average precipitation in the period of 2019-2023 will be in the range of less than normal, based on the teleconnection method.