A Case study of comparing some interpolation methods for precipitation analysis over Iran

Precipitation is one of the most complicated climatic elements. Moreover, for many applications a climatological atlas of precipitation is needed. Preparing a climatological atlas of precipitation using observed rain gauge data is a challenging task.
In this research six interpolation methods including Inverse Distance Weighting (IDW), Gradient plus Inverse Distance Squared (GIDS), Multiple Linear Regression (MLR), Ordinary Kriging (O-K), Universal Kriging (U-K) and Simple Kriging (S-K) have been used to analyze the monthly, seasonal and annual means of precipitation at 354 synoptic stations over Iran during TIR 1393 to KHORDAD 1394 and the results have been compared.
Comparison of the results showed that the GIDS method gives relatively better performance for most of the times. It is also found that the U-K method has considerably lower errors particularly for the interpolation of precipitation over the regions/seasons with low amounts of precipitation. The final analyzed data agree well with the corresponding observations