On the Construction Principle of Conceptual Models for Severe Convective Weather Forecasting Operations in China

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.

The Role of Weather Radar in Rainfall Estimation and Its Application in Meteorological and Hydrological Modelling—A Review

“…With the help of satellite and radar data, and a variety of forecast products from a NWP model, GANDOLF identifies convective cells and predicts their possible development. Other examples of the application of conceptual models can be found in Roberts et al [133] and Liu et al [134], and it has been used in AutoNowCaster [135,136] (https://www.weather.gov/mdl/AutoNowCaster).…”

A Bayes‐Based Approach Against Sample Imbalance to Improving the Potential Forecasts of Gale

“…For large‐scale gale, its predictability for a specific time and a specific site is very low, and with the decrease of scale, the predictability of gale is significantly reduced (Cai et al., 2021). In this regard, many efforts have been devoted to improving the forecasts of gale (e.g., Ehsan et al., 2019; Ling et al., 2021; Liu et al., 2020). As gale generally occurs with severe convective weather, gale forecast are often carried out along with the severe convective weather forecasts (e.g., Jiang et al., 2019; Liu, Duan, et al., 2021; Liu et al., 2020).…”

“…In this regard, many efforts have been devoted to improving the forecasts of gale (e.g., Ehsan et al., 2019; Ling et al., 2021; Liu et al., 2020). As gale generally occurs with severe convective weather, gale forecast are often carried out along with the severe convective weather forecasts (e.g., Jiang et al., 2019; Liu, Duan, et al., 2021; Liu et al., 2020). A large number of studies revealed that severe convective weather is closely related to environmental conditions, which are mainly divided into humidity, instability, and dynamic conditions (e.g., Ma et al., 2021; Taszarek & Kolendowicz, 2013; Tian et al., 2015).…”