The Statistic Assessment of CMORPH Model Output For Precipitation Estimation Over The Northeast of Iran (Case Study: North Khurasan Province)

Precipitation is a key input to different crop and hydrological models. Usually، the rain gauge precipitation data is applied for the most management and researching projects. But because of non-appropriate spatial distribution of rain gauge network، this data does not have a desirable accurate. So estimation of daily areal rainfall can be obtained by spatial interpolation of rain gauges data. However، direct application of these techniques may produce inaccurate results. In the last years، applying the remote sensing for estimation of rainfall have got so popular all around the word and many techniques have been developed based on the satellite data with high temporal and spatial resolution. In this paper، CMORPH model was validated for precipitation estimation over the northeast of Iran. Results showed that this model could not estimate precipitation accurately in daily scale، but in monthly and seasonal scale the estimation was more accurate. Farooj and Namanloo station had the highest correlation equal to 0. 31 in daily scale. The highest correlation in monthly scale was equal to 0. 62 for Barzoo، Namanloo and Se yekAb station. In Seasonal scale Gholaman station had the highest correlation which was equal to 0. 63. Also، the probability of detection has been estimated accurately by CMORPH. But this technique did not have an accurate estimation for wet and dry days، mean annual precipitation and the number of non-rainy days.