Fog Nowcasting

How We Do Fog Forecasting

Radiometrics utilizes a combination of advanced weather instruments and data processing algorithms to predict fog formation and dissipation with high accuracy. Our approach includes:

1. Data Collection

  • Microwave Profiling Radiometer (MPR): Measures thermodynamic properties such as temperature, humidity, and liquid water content in the atmosphere.
  • Radar Wind Profiler (RWP): Provides continuous wind speed and direction data at multiple altitudes.
  • Additional Meteorological Inputs: Factors such as dewpoint, atmospheric pressure, and visibility observations enhance accuracy.

2. Data Processing & Analysis

  • Fog Detection Algorithm: Our system integrates MPR and RWP data to identify the presence and concentration of radiative-based fog.
  • Liquid Water Content Calculation: Determines the amount of water in the air that contributes to fog formation.
  • Wind and Temperature Profiles: Assess vertical atmospheric stability, a key factor in fog persistence and dissipation.

3. Fog Nowcasting

  • One-Hour Fog Trend Forecast: Based on real-time data, the system predicts fog trends for the next hour, updating every 15 minutes.
  • Sunrise/Sunset Adjustments: Incorporates solar heating effects, which influence fog development and clearance.
  • Model Output Statistics (MOS): Combines local and regional meteorological data for enhanced accuracy.

4. Operational Benefits

  • Aviation & Space Launch: Enhances safety for airports and spaceports by providing real-time visibility forecasts.
  • Energy & Transportation: Supports wind energy optimization and reduces risks for road and maritime transport.
  • Emergency & Disaster Management: Improves decision-making for fire weather and hazardous weather response.

This integrated system ensures precise and timely fog predictions, minimizing operational risks and optimizing planning for weather-sensitive industries.

Click the link for more information:

Boundary Layer Thermodynamic and Wind Observations for Improved Fog and Marine Layer Modeling and Forecasting (Audio), AMS, 2016.