Results of verification of WRF numerical forecasting model in Lorestan Meteorology and Meteorological and Atmospheric Sciences Research Institute during March and April 2019

Document Type : Original Article

Authors

1 Deputy of Lorestan Meteorological Development and Forecasting

2 Associate Prof. ASMERC

3 Lorestan Meteorological Department

Abstract

n this study, the results of 24 and 48 hour predictions of mid-scale WRF model with nested slopes with 18 and 6 km separations (implemented in Lorestan meteorology) and with 27 and 9 km separations (implementation) At 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. For this purpose, 2 * 2 agreement table was used for verification. The results obtained from PC skill score showed that in a period of 24 hours, the ranges of 27, 18 and 9 km in more than 80% of cases were able to occur or not rain. At the provincial level, correctly predict that this score was a minimum of 6% for a range of 6 km. Also, studies performed for a period of 48 hours showed that all slopes in more than 77% of cases showed the accuracy of the occurrence or absence of precipitation. The results of validation in this study have been for days with precipitation and no specific threshold has been considered for precipitation values. It is suggested that in order to improve the relative weakness of the model, validation quantities for specific thresholds (light precipitation, Moderate rainfall and heavy rainfall).

The results obtained from the PC skill score showed that in a period of 24 hours, the slopes of 27, 18 and 9 km in more than 80% of cases were able to accurately predict the occurrence or non-occurrence of rainfall in the province. The range of 6 km was minimal and amounted to 67%. Also, studies performed for a period of 48 hours showed that all slopes in more than 77% of cases showed the accuracy of the occurrence or absence of precipitation.

* The average quantity of B slope for 4 slopes showed that the number of precipitation forecasts for a period of 24 hours in the surveyed slopes is between 1.39 to 1.49 percent higher than the cases in which precipitation occurred, which indicates that the previous precipitation was higher. The occurrence of precipitation is relative to the occurrence of precipitation. For prediction over a 48-hour period, this quantity is slightly improved and has less error.

* The average quantity of TS in the forecast for a period of 24 hours is more than 66% for the ranges of 27, 18 and 9 km, which with the increase of the forecast period to 48 hours, this quantity has improved and in all 4 ranges to more than 72%. it is arrived.



* The quantity of FAR in a 24-hour period for all 4 ranges varies from 29 to 38% on average, indicating that only 29 to 38% of the precipitation predictions have not been met. In a period of 48 hours, this quantity has also improved a bit and has reached 21 to 26.

The results of quantifying the H collision rate over a 24-hour period indicate that the three slopes of 27, 18 and 9 km had a high ability to predict the occurrence of positive precipitation. Also, in a period of 48 hours, almost all 4 domains had high power.

* Examination of the average quantity of F shows that in a 24-hour period for slopes 9, 18 and 27 between 29 to 33% of the cases where no precipitation has occurred, the model has erroneously predicted that this error is 47% for a range of 6 km. Is. In a period of 48 hours, the rate of this error for 4 domains has reached 35 to 50%, which indicates an increase in this type of error with increasing time interval.

* Quantity of Pierce PSS skill score in 24-hour period shows 39 to 69% improvement for the studied slopes, among which the 9 and 27 km slopes have better performance. In a period of 48 hours, the value of this quantity has reached 48 to 61%, which, unlike the period of 24 hours, is the best value in the range of 6 km.

In order to evaluate the model more accurately, further case studies are suggested in different seasons of the year.

* Increase model execution time.

* The model should be executed with different schemas.

* The results of validation in this study have been for days with precipitation and no specific threshold has been considered for precipitation values. It is suggested that in order to improve the relative weakness of the model, validation quantities for specific thresholds (light precipitation) , Moderate rainfall and heavy rainfall).

* The results of this research should be compared with GFS and ECMWF models.

Keywords

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Journal of Climate Research
Volume 1401, Issue 50 - Serial Number 50
Vol. 13, No. 50, Summer 2022
September 2022
Pages 167-182

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