Title: Research on precipitation forecasting method in northwest China based on multi-model ensemble

Authors: Xinwei Liu; Dong Wei; Rong Li; Yicheng Wang; Na Liu; Deshuai Li

Addresses: Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, Gansu, China; Lanzhou Central Meteorological Observatory, Lanzhou 730020, Gansu, China ' Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, Gansu, China; Lanzhou Central Meteorological Observatory, Lanzhou 730020, Gansu, China ' Lanzhou Central Meteorological Observatory, Lanzhou 730020, Gansu, China ' Lanzhou Central Meteorological Observatory, Lanzhou 730020, Gansu, China ' Lanzhou Central Meteorological Observatory, Lanzhou 730020, Gansu, China ' Units 93995 of the Chinese People's Liberation Army, Xi'an 710000, China

Abstract: As a key meteorological element in weather forecasts, precipitation forecast has attracted much attention in many application fields. Due to the limited accuracy of forecast methods, the effect of quantitative precipitation forecast still needs to be optimised. Based on the optimal percentile method, this study established a forecasting method by multi-model for graded precipitation fitting Northwest China. Its forecast threat score (TS) of every 3 h/24 h precipitation were higher than each single model. Meanwhile, its forecast was closer to the actual situation in terms of rainfall area and grade, especially displaying an obvious improvement in light rain and rainstorm forecast. By analysing the selection of the optimal percentile, it was found that this method adopted a low percentile value in light rain forecasts, and this value grew larger with the increase of precipitation grade, which helped to improve the accuracy and stability of the precipitation forecast.

Keywords: precipitation forecast; graded precipitation; multi-model; optimal percentile; Northwest China; threat score.

DOI: 10.1504/IJGW.2022.122792

International Journal of Global Warming, 2022 Vol.27 No.1, pp.1 - 15

Received: 15 Jan 2021
Accepted: 24 Sep 2021
Published online: 11 May 2022 *

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