Airborne Weather Profiler Network Using Segmented Mobile Sensing
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Solution Overview
Problem
Current meteorological models are limited by the scarcity and quality of weather data, particularly in remote areas like deserts, polar regions, and oceans, leading to inaccurate forecasts due to the lack of data over vast distances and rapid weather changes.
Innovation Solution
A network of remote profilers mounted on mobile platforms such as aircraft and UAVs, equipped with sensors like RADAR, LIDAR, and GPS, collect atmospheric data and transmit it to a modeling node for building three-dimensional weather models, enabling improved data collection and forecasting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If remote profilers are deployed on mobile platforms to gather weather data over larger regions, then the quantity and quality of weather data is improved, but the device complexity and network infrastructure requirements increase
Solution Approach 1:
The system divides the weather monitoring function into distributed mobile sensing nodes (profilers on aircraft and UAVs) that operate independently across different regions. Each node collects and transmits data separately, allowing the overall system to cover large areas without requiring a single complex centralized infrastructure.
Solution Approach 2:
The mobile platforms (aircraft and UAVs) serve multiple functions: they perform their primary transportation or operational roles while simultaneously carrying weather profilers to collect atmospheric data. This multi-functionality reduces the need for dedicated weather monitoring infrastructure.
2Area of stationary object
If profilers are mounted on mobile platforms to access remote areas, then the coverage area is improved, but the stability and consistency of data collection deteriorate due to platform movement
Solution Approach 1:
The system accepts and utilizes the dynamic nature of mobile platforms rather than trying to eliminate it. The profilers are designed to collect data during movement, and the network architecture accommodates varying data collection conditions as platforms move through different atmospheric zones, transforming the stability problem into a dynamic sampling advantage.
3Measurement precision
If more sensors are deployed in remote areas to improve weather data quality, then the measurement precision is improved, but the cost and difficulty of deployment and maintenance increase
Solution Approach 1:
The patent uses existing mobile platforms (commercial aircraft and UAVs) as intermediaries to deploy weather profilers in remote areas. Rather than building dedicated sensor stations in hard-to-reach locations, the system leverages platforms that already have the capability to access these regions, significantly reducing deployment complexity and cost.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly enhances the quality and quantity of weather data, leading to more accurate forecasts and improved operational safety and efficiency in aviation, while also reducing costs and environmental impacts.
Implementation Method 1
Each sensing node is equipped with a remote profiler using, for instance, RADAR (radio detection and ranging) or LIDAR (laser detection and ranging) to sense the profile of an atmospheric property
Implementation Method 2
Each sensing node is equipped with a remote profiler using, for instance, RADAR (radio detection and ranging) or LIDAR (laser detection and ranging) to sense the profile of an atmospheric property
Implementation Method 3
Another alternative is to use the scintillation of a GPS (Global Position System or other positioning system signal) to sense the profile along the signal path between the transmitting station and the receiver
Data Source
AI summary
Apparatus and methods for remotely sensing meteorological conditions and for building models from the sensed conditions. More particularly, networks and systems are provided for gathering remotely sensed profiles of the meteorological conditions and for building the meteorological model. The networks and systems can also predict the weather. Also, various remote profilers are provided including LIDAR, RADAR, nano-sondes, microwave, and even GPS (Global Positioning System) related instruments.