Tropical Cyclone Forecast Error Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for tropical cyclone forecast verification lack comprehensive visualization of track and intensity errors, failing to effectively combine geographic information and traditional statistical methods, which limits the spatial expression and analysis of verification index data.
Innovation Solution
A visualization analysis method that acquires tropical cyclone data to calculate track and intensity forecast verification indices, combining them with geographic information to create visible error views, joint distribution maps, and composite box-shaped histograms, enhancing the spatial representation and comparability of forecast errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional statistical methods (average error histograms, line charts, ordinary box charts) are used to express verification indexes, then the overall performance can be shown, but the spatial expression and in-depth excavation of verification index data are lacking
Solution Approach 1:
The patent transforms traditional one-dimensional statistical charts into two-dimensional spatial visualizations by mapping verification index data onto geographic coordinates. The error histogram is repositioned from a simple statistical chart to a geographic map showing error distribution across different regions, adding spatial dimension to the data expression.
Solution Approach 2:
The patent combines multiple visualization elements (error histograms, box charts, geographic maps) into a unified visual system. The verification index data is merged with geographic information to create an integrated visualization that simultaneously displays statistical characteristics and spatial distribution.
2Measurement precision
If the track error is decomposed into ATE (Along-Track Error) and CTE (Cross-Track Error), then the error components can be analyzed separately, but the expression of the joint distribution of ATE and CTE has defects
Solution Approach 1:
The patent merges the separate ATE and CTE visualizations into a joint distribution map. The error histogram simultaneously displays both error components, allowing users to see not only individual error distributions but also their joint distribution patterns across different geographic regions.
Solution Approach 2:
The patent adds a spatial dimension to the error component analysis by mapping ATE and CTE values onto geographic coordinates. This transformation from abstract error values to spatially-referenced visualizations enables the joint distribution to be expressed in a comprehensible geographic context.
3Measurement precision
If the traditional box chart is used to express the distribution of error samples, then the distribution can be shown, but it cannot represent the mean absolute error (MAE)
Solution Approach 1:
The patent merges the box chart and histogram into a composite visualization. The box chart displays the distribution quartiles while the overlaid histogram shows the frequency distribution, and together they represent both the mean absolute error and the full error distribution characteristics.
Solution Approach 2:
The composite box-shaped histogram serves multiple functions simultaneously: it displays the error distribution range, identifies the mean absolute error position, shows frequency distribution patterns, and maintains geographic spatial reference. This multi-functional visualization replaces the need for separate charts.
Data Source
AI summary
This disclosure relates to the fields of applied meteorology, in particular to a visualization analysis method of the tropical cyclone forecast verification index data, which comprises the following steps: acquiring tropical cyclone data; obtaining a track forecast verification index and an intensity forecast verification index of the tropical cyclone with the tropical cyclone data; obtaining a visible view of the tropical cyclone track forecast error and a visible view of the tropical cyclone intensity forecast error according to the track forecast verification index and the intensity forecast verification index, and in combination with the geographic information of the tropical cyclone; obtaining a first error and a second error according to the track forecast verification index, and obtaining a joint distribution map of the first error and the second error by using the first error and the second error; obtaining a composite box-shaped histogram through the intensity forecast verification index.