On the construction principle of conceptual models for severe convective weather forecasting operations in China

Xinhua Liu, Kanghui Zhou, Y. U. Lan, X. U. Mao, Robert J. Trapp

Research output: Contribution to journalArticlepeer-review

Abstract

It is argued here that even with the development of objective algorithms, convection-allowing numerical models, and artificial intelligence/machine learning, conceptual models will still be useful for forecasters until all these methods can fully satisfy the forecast requirements in the future. Conceptual models can help forecasters form forecast ideas quickly. They also can make up for the deficiencies of the numerical model and other objective methods. Furthermore, they can help forecasters understand the weather, and then help the forecasters lock in on the key features affecting the forecast as soon as possible. Ultimately, conceptual models can help the forecaster serve the end users faster, and better understand the forecast results during the service process. Based on the above considerations, construction of new conceptual models should have the following characteristics: 1) be guided by purpose, 2) focus on improving the ability of forecasters, 3) have multiangle consideration, 4) have multiscale fusion, and 5) need to be tested and corrected continuously. The traditional conceptual models used for forecasts of severe convective weather should be replaced gradually by new models that incorporate these principles.

Original languageEnglish (US)
Pages (from-to)299-308
Number of pages10
JournalWeather and Forecasting
Volume35
Issue number1
DOIs
StatePublished - Feb 2020

Keywords

  • Atmosphere
  • Forecasting
  • Forecasting techniques
  • Mesoscale forecasting
  • Operational forecasting

ASJC Scopus subject areas

  • Atmospheric Science

Fingerprint Dive into the research topics of 'On the construction principle of conceptual models for severe convective weather forecasting operations in China'. Together they form a unique fingerprint.

Cite this