Point Environmental Prediction Using Grid Interpolation
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Solution Overview
Problem
Current global weather forecasting methods require significant computational power and rely on synoptic scale forecasts with low spatial resolution, failing to accurately predict weather conditions at specific points within a region, especially in areas without dense observation networks.
Innovation Solution
A system for generating point environmental element predictions using a receiver to collect broadcast data, a processor to generate predictions, and a method to interpolate data from a three-dimensional grid to a two-dimensional grid, incorporating observation points and error correction to provide accurate local forecasts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If global weather models are used to generate forecasts, then the computational power required is tremendous, but the spatial resolution remains low (synoptic scale)
Solution Approach 1:
The patent divides the atmospheric domain into multiple levels: global models provide broad-scale forecasts, regional models refine these for specific areas, and local models generate high-resolution predictions for specific points of interest. This segmentation allows each model to operate at appropriate resolution without requiring excessive computational power for the entire domain.
Solution Approach 2:
The patent transitions from two-dimensional regional forecasts to three-dimensional point-specific predictions by incorporating vertical atmospheric layers and local topographic features. This dimensional enhancement enables accurate point forecasts without requiring complete re-computation of global models.
2Power
If synoptic scale forecasts with low spatial resolution are used, then computational resources are saved, but accurate point-specific predictions cannot be provided
Solution Approach 1:
The system performs preliminary global and regional forecasting to establish baseline conditions, then applies local correction factors and observational data to generate accurate point-specific predictions. This preliminary action reduces the computational burden for point forecasts by building upon pre-computed regional fields.
Solution Approach 2:
The patent introduces regional models as intermediary between global and local scales, and uses observational stations as intermediaries to provide local correction data. These intermediaries bridge the gap between low-resolution global models and high-precision point forecasts without requiring direct computation of both extremes.
3Area of stationary object
If regional forecasts covering large areas are generated, then the forecast coverage is improved, but the weather conditions cannot be differentiated between specific locations within the region
Solution Approach 1:
The patent applies different quality levels to different regions: global models provide uniform coverage, regional models provide differentiated coverage for major areas, and local models provide highly differentiated predictions for specific points of interest. This local quality approach maintains comprehensive coverage while enabling precise location-specific differentiation where needed.
Data Source
AI summary
An apparatus for generating environmental element predictions at a point location includes a receiver for collecting broadcast environmental element prediction data. A processor generates at least one environmental element prediction for the point location.