Sensible Temperature Calculation Using Ground Surface Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing sensible temperature calculation formulas for heatwave warnings, such as the KMA2016 model, have significant systemic errors and do not adequately consider participants in outdoor activities affected by ground heating, leading to frequent and ineffective heatwave warnings.
Innovation Solution
A method and apparatus that classify and cluster meteorological data, including globe temperature, atmospheric temperature, relative humidity, and ground surface temperature, to derive improved sensible temperature calculation formulas using regression analysis, incorporating the difference between ground surface and atmospheric temperatures to reduce systemic errors and provide more accurate heatwave warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the existing sensible temperature calculation formula (KMA2016 model) is used, then heatwave warnings can be issued based on atmospheric temperature and relative humidity, but significant systemic errors occur leading to frequent and ineffective warnings
Solution Approach 1:
The patent changes the parameters used in sensible temperature calculation from the conventional atmospheric temperature and relative humidity only, to include ground surface temperature as an additional parameter. This modifies the calculation formula to account for ground heating effects, thereby reducing systemic errors and improving warning reliability while maintaining appropriate warning frequency
Solution Approach 2:
The patent replaces the conventional sensible temperature calculation mechanism (based on atmospheric parameters only) with an improved mechanism that incorporates ground surface temperature measurements. This substitution allows the system to account for radiant heat from heated ground surfaces, significantly reducing calculation errors and improving the reliability of heatwave warnings
2Ease of operation
If the conventional sensible temperature formula is used, then calculation is simple using regular observation elements, but participants in outdoor activities affected by ground heating are not considered
Solution Approach 1:
The patent enhances the universality of the sensible temperature calculation system by making it applicable to both conventional weather reporting and outdoor activity-specific heat stress assessment. By incorporating ground surface temperature, the formula becomes versatile enough to account for ground heating effects that specifically impact outdoor participants, while still maintaining compatibility with existing observation systems
Solution Approach 2:
The patent segments the temperature measurement into two distinct components: atmospheric temperature (for general weather conditions) and ground surface temperature (for outdoor activity exposure). This segmentation allows the system to separately account for air temperature and radiant heat from ground surfaces, providing more accurate assessments for outdoor participants while maintaining calculation feasibility
3Adaptability or versatility
If ground surface temperature is incorporated into the calculation, then outdoor activity participants affected by ground heating are considered, but data classification and clustering complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-classifying meteorological data into precipitation and non-precipitation categories, and further clustering non-precipitation data into distinct groups based on environmental conditions. This pre-processing organizes the complex multi-parameter data (including ground surface temperature) into manageable clusters, enabling the application of appropriate regression models for each condition type and simplifying the overall calculation process
4Measurement precision
If K clusters and regression analysis are performed, then accurate sensible temperature calculation formulas are derived, but computational effort and data processing time increase
Solution Approach 1:
The patent applies partial action by performing clustering and regression analysis only on non-precipitation data, separating it from precipitation data handling. This selective approach focuses computational resources on the conditions where ground heating effects are most significant (sunny, clear conditions), achieving high measurement precision for outdoor activity scenarios while reducing overall computational effort compared to processing all data uniformly
Data Source
AI summary
Provided are an apparatus and method for calculating a sensible temperature in consideration of outdoor ground heating and a heatwave warning apparatus and method based on a sensible temperature in consideration of outdoor ground heating. The method of calculating a sensible temperature in consideration of outdoor ground heating includes classifying data which includes a globe temperature, an atmospheric temperature, a relative humidity, and a ground surface temperature and is observed by an automated synoptic observing system (ASOS) for a certain period of time, as precipitation data and non-precipitation data according to whether there is precipitation, clustering the non-precipitation data into K clusters, and deriving K+1 sensible temperature calculation formulae by performing regression analysis on the K clusters and the precipitation data.