A temperature ensemble forecasting method and system

Abstract

The invention provides a temperature ensemble forecasting method and system. The method starts from a plurality of numerical mode forecasting fields through temperature ensemble forecasting. dynamic error correction and forecast effect inspection are carried out on each forecast field according to past 15-day forecast fields and observation fields; the temperature abrupt change condition is adjusted; the weight of each mode is calculated by adopting a gradient descent method; the optimal ground temperature forecasting field is obtained through weighted average; According to the temperature ensemble forecasting method and system provided by the invention, the system error caused by the error of the numerical mode forecasting, especially the mode error under the condition of sudden temperature rise or temperature drop, is improved, a gradient descent method is used for solving the weight of each mode, so that a better forecasting effect can be obtained, and a reliable reference is provided for weather forecasting.

Description

technical field [0001] The invention relates to the technical field of weather forecasting, in particular to a temperature ensemble forecasting system and method. Background technique [0002] Internationally, Krishnamurti et al. (1999) first proposed the idea of ​​multi-model ensemble forecasting, and statistically optimized the forecast results of multiple different models to finally obtain the result of ensemble forecasting. A large number of experiments have shown that ensemble forecasting can effectively reduce the errors of seasonal climate forecasting and weather forecasting, and the forecasting effect is far better than that of a single model and multi-model ensemble average. In terms of precipitation forecasting, Krishnamurti et al. based on TIGGE data from the United Kingdom Meteorological Office (UKMO), the National Centers for Environmental Prediction (NCEP), the European Center for Medium-Range Weather Forecasts (ECMWF ), the Bureau of Meteorology (Australia, B...

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Problems solved by technology

[0004] The existing ensemble forecasting technology has been significantly developed, but the ensemble forecasting model building method is still relatively simple, and the ensemble average or linear weighted average method is mostly used. The system error correction caused by the error of the numerical model forecast itself also needs to be improved, especially the temperature The error of the model is relatively large in the event of a sudden change in temperature (sudden temperature rise or drop). In Shenzhen and even Guangdong, Hong Kong and Macao, extreme weather such as high temperature often occurs, and the numerical model forecast products often have large deviations in this case. It is urgent to build such a stable environment. The temperature ensemble forecast system provides a reliable reference for weather forecast

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