Temperature intelligent grid optimal integrated forecasting method

Abstract

The invention relates to a temperature intelligent grid optimal integrated forecasting method. The method comprises following steps of: processing a numerical forecasting product, obtaining temperature real condition and a forecasting value of an observation station, selecting an optimal numerical forecasting product, correcting temperature forecasting, analyzing forecasting effects of different objective correction methods, researching a proper, optimal integrated forecasting method, generating a temperature intelligent grid optimal integrated forecasting product, so as to realize business operation. The method aims to find the optimal forecasting way. The first step is to find an optimal numerical mode, temperature forecasting is corrected based on the optimal numerical mode, object correction methods that forecast better and complement each other are to be find, and temperature forecasting accuracy is further improved by forecasting optimal sets of different correction methods.

Description

Technical field [0001] The invention belongs to the technical field of weather forecasting, and relates to an optimal integrated forecast method of a temperature intelligent grid. Background technique [0002] With the improvement of the level of numerical weather forecasting and the development of refined weather forecasting services, the weather forecast has transformed from traditional irregular site forecasts to smart grid forecasts with uniform grids (equal latitude and longitude or equidistant), with accuracy and fineness of the forecast. The level of chemistry continues to improve. Combined with advanced numerical forecast products and MOS and other numerical forecast product interpretation technologies, the accuracy of temperature forecasts has been significantly improved, and the current objective temperature forecast accuracy has reached or exceeded the level of forecasters' subjective forecasts. However, due to the differences in different numerical models and differe...

AI Technical Summary

Problems solved by technology

However, from the perspective of actual business applications, even if the corrections and interpretations are based on the same numerical forecast, due to the differences in the predictors and correction methods considered by different methods, no one forecast product is absolutely optimal

However, based on different numerical forecast products, the correction and interpretation or integration of temperature forecasts will have a great impact on the interpretation results due to the differences in the forecasts of different numerical models, and it is difficult to obtain better forecast results.

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