Four-Dimensional Weather Data Cube Storage
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Solution Overview
Problem
Current technologies fail to efficiently manage and process large volumes of volatile and disparate weather data in real-time, making it challenging to store, access, and analyze for accurate forecasting and decision-making.
Innovation Solution
A data cube framework that uses a geographic tile-based (Quad key) and time-indexed system for efficient storage and retrieval of weather data, allowing for quick access and visualization, enabling efficient management and processing of weather data through ingestion, pre-processing, and API-based access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional storage and processing methods are used for weather data, then data can be stored, but the processing efficiency and access speed deteriorate due to the large volume and volatility of data
Solution Approach 1:
The patent segments weather data into discrete four-dimensional data cubes with dimensions of latitude, longitude, time, and parameter type. Each data cube represents a specific spatial location and time point, allowing independent processing and retrieval. This segmentation enables efficient handling of large volumes of volatile weather data by breaking them into manageable, addressable units that can be processed in parallel.
Solution Approach 2:
The patent introduces a fourth dimension (time) to the traditional three-dimensional spatial data structure, creating a four-dimensional data cube framework. This dimensional expansion allows the system to efficiently organize and access weather data across multiple time points and spatial resolutions simultaneously, dramatically improving processing efficiency for temporal analysis and forecasting.
2Measurement precision
If detailed weather data is stored for accurate forecasting, then forecast accuracy improves, but data access time and processing latency increase
Solution Approach 1:
The patent pre-organizes weather data into a four-dimensional cube structure with predetermined spatial and temporal indexing during data ingestion. This preliminary organization allows for rapid retrieval of specific weather parameters at any location and time point without requiring full data processing, significantly reducing access time while maintaining complete data availability for accurate forecasting.
Solution Approach 2:
The patent enables selective access to specific regions, time periods, and parameter types within the four-dimensional data cube. Users can query only the necessary subset of data relevant to their forecasting needs rather than processing entire datasets, reducing access time while maintaining the precision needed for accurate local and regional forecasts.
3Adaptability or versatility
If a unified framework is created for disparate weather data types, then data integration improves, but system complexity increases
Solution Approach 1:
The patent creates a universal four-dimensional data cube framework that can accommodate multiple types of weather data (temperature, humidity, pressure, wind, precipitation, etc.) across different spatial resolutions and time intervals. This single unified structure replaces multiple separate data storage systems, improving data integration while the standardized cube format actually reduces overall system complexity by providing a consistent interface for all weather data types.
Data Source
AI summary
Storage of weather data in four dimensions in a mass storage data cube for ready access. Weather data to be stored is ingested and processed with respect to location and time to generate one or more tiles each characterized by a geographic location index and a time index. The tiles are stored in a mass storage data cube in accordance with the geographic location index and the time index of each tile. The tiles containing the stored weather data can be readily accessed and retrieved from the mass storage data cube.