Post-processing results of WRF numerical forecasting model in Lorestan Meteorology and Meteorological and Atmospheric Sciences Research Institute during March and April 2019

In this study, the results of 24 and 48 hour rainfall forecasts in the mid-scale WRF model with nested slopes with 18 and 6 km (performed in Lorestan meteorology) and with 27 and 9 km (performed) In the Institute of Meteorology and Atmospheric Sciences), without schematic, for a period of 2 months from March 1, 2019 to the end of April 2019 and compared with precipitation observation data for 10 synoptic meteorological stations in Lorestan. Output post-slip results showed that the 27, 9 and 18 km outputs with values ​​of 7.3, 4.8 and 1%, respectively, had the highest increase in the accuracy of 24-hour forecasts after post-processing. And only 6 km output has decreased performance by 7.7% after post-processing. Also, the output of 27, 18 and 9 km ranges with values ​​of 9.4, 7.8 and 4.8%, respectively, had the highest increase in the accuracy of 48-hour forecasts after post-processing, and only the output of 6 km with -0.9% has decreased performance after post-processing. Post-processing zoning for the province showed that post-processing by weighted average slider method for both 24 and 48-hour intervals in correcting the model outputs, the altitude factor reduced the accuracy of predictions so that in areas with altitude The less they have been, the more effective they have been.