Localized Heat Stress Analysis Using Terrain-Corrected Weather Data
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Solution Overview
Problem
Traditional methods for measuring and predicting heat stress, such as the Wet Bulb Globe Temperature (WBGT), often rely on costly equipment and specialized expertise, and fail to capture localized variations in environmental conditions, leading to inaccurate assessments at microscale locations like sports fields or construction sites.
Innovation Solution
Integrate localized terrain data with broader weather forecast data to refine WBGT estimates by incorporating specific local details such as vegetation cover, surface typologies, and built environment factors, using bias-corrected data to improve accuracy at a microscale level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional WBGT measurement methods using specialized meteorological equipment are employed, then measurement reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses satellite imagery to create a remote copy of the terrain and environmental conditions, replacing the need for physical specialized meteorological equipment. The satellite data serves as a surrogate that captures the essential information needed for WBGT calculation without requiring expensive on-site instruments.
Solution Approach 2:
The patent replaces the mechanical system of physical weather stations and specialized equipment with a remote sensing system using satellite imagery. This substitution eliminates the need for complex mechanical measurement devices while maintaining the ability to assess environmental conditions.
2Device complexity
If WBGT is estimated from non-proximate sources such as airport weather stations, then device complexity is reduced, but measurement precision deteriorates due to inability to capture localized variations
Solution Approach 1:
The patent applies local quality by using satellite imagery to capture specific localized terrain features, vegetation cover, and surface characteristics of the exact area of interest. This allows the WBGT calculation to reflect the unique microclimate conditions of the specific location rather than relying on regional averages from distant weather stations.
Solution Approach 2:
The patent segments the broad regional weather data into localized microclimate assessments by analyzing specific terrain features, land cover types, and surface properties of the target area. This segmentation allows for precise local heat stress evaluation independent of broader regional conditions.
3Reliability
If specialized expertise is required to interpret WBGT data accurately, then measurement reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements self-service by providing automated WBGT calculations that process satellite imagery and terrain data to generate heat stress assessments without requiring specialized human expertise. The system performs the complex analysis automatically, making the output accessible to users without meteorological training.
Solution Approach 2:
The patent introduces an intermediary computational system that translates complex satellite imagery and terrain data into simplified WBGT values and heat stress recommendations. This intermediary layer bridges the gap between complex raw data and user-friendly interpretations, eliminating the need for specialized expertise.
Data Source
AI summary
Some embodiments of the present disclosure provide inventive concepts for estimating a value for an environmental heat stress index at a target microscale location. Meteorological data indicative of parameters such as relative humidity, air temperature, wind characteristics, or atmospheric cloud cover for a geographic area representative of a larger geographic area that includes the target microscale location can be obtained. Localized terrain data specific to the target microscale location can be obtained. A bias correction can be performed on the meteorological data based on the localized terrain data, generating microscale meteorological data that reflects conditions at the target microscale location. The heat stress index value, representing heat-related risk specific to the target microscale location, can be determined using the microscale meteorological data and can be a real-time or forecast value used for providing actionable insights or alerts for health and safety purposes.