EGU2020-4332
https://doi.org/10.5194/egusphere-egu2020-4332
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Application of quasi 150 day rhythm method in the prediction of strong cold air extension period in spring in Gansu Province

Shu Lin, Danhua Li, Guoyang Lu, and Weiping Liu
Shu Lin et al.
  • Lanzhou Regional Climate Central, Gansu Meteorological Bureau, China (treewest@163.com)

Using daily minimum temperature of 77 stations in Gansu in spring 1981-2018,temporal and spatial distribution characteristics of strong cold air are analyzed in spring in Gansu Province in the past 38 years. The frequency of strong cold air in spring in Gansu was the lowest in 1980s,it increased since the new century. Strong cold air in the whole province and Hedong area mainly appeared in March and April, The strong cold air in Hexi area is more than April and May. The frequency of strong cold air in Hexi area is two times of that in Hedong area. Using NCEP daily 500hPa height field data for 1981-2018 and quasi 150 day rhythm method, the prediction of extended period of the strong cold air in spring in Gansu province was studied. The threshold value of circulation similarity is determined , evaluation criteria and multiple screening are established. Developing  evaluation criteria and multilayer screening, and selecting 4 typical weather forecasts of strong cold air in spring in Gansu province by calculating similarity coefficients and determining thresholds. In the case of 4 typical fields being applied at the same time, the prediction accuracy is obviously improved, the null rate is reduced to zero, and the omission rate is greatly reduced, which provides a new idea for the extended forecast of the strong cold air in Gansu.

How to cite: Lin, S., Li, D., Lu, G., and Liu, W.: Application of quasi 150 day rhythm method in the prediction of strong cold air extension period in spring in Gansu Province, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4332, https://doi.org/10.5194/egusphere-egu2020-4332, 2020