Development of An Aviation Unusual Weather Now-casting System Based on Aircraft Automatic Dependent Surveillance-Broadcast (ADS-B) Data

At present the meteorology observation instruments provide two-dimensional wind speed and wind direction information in airports. However, the weather information which the aviation personnel most concern about is the weather situation between the layers of 2,000 feet and 4,000 feet when the aircraft approaches the airports. In order to obtain three-dimensional weather observation data, we developed a software-defined radio (SDR) receiver to receive and analyze the automatic dependent surveillance-broadcast (ADS-B) Mode-S Extended Squitter (ES) signals, and we developed a method of deriving meteorological information, wind vector and temperature, which were decoded from the ADS-B Mode-S ES signals. In our previous research, we used aircraft ADS-B Mode-S ES data to estimate wind speed and wind direction around the aircraft and developed a three-dimensional aviation unusual weather detection system. Therefore, in this paper we enhance this system and offer the hazardous weather information in more details, for instance, the intensity, location and continuity of the weather system. Furthermore, we develop a wind shear now-casting system for approaching aircrafts. As a result, the objectives of this work are 1) using aircraft ADS-B Mode-S ES signals to do data assimilation and obtain the best estimate of state variables which approximate the real weather conditions, 2) estimation of Gradient Richardson Number to indicate dynamic stability and the formation of turbulence, 3) analyze the parameters that have the close relation to wind shear conditions to do now-casting analysis. This paper first conduct Weather Research and Forecasting model (WRF) data assimilation system to obtain more reliable environmental field analysis and use the output parameters from the WRF data assimilation system (WRFDA) to do the identifications of turbulence and the principal components analysis. Because we could not calculate the Gradient Richardson Number directly from ADS-B Mode-S ES data to determine whether the detected wind shear is induced by turbulence, we therefore use WRF preprocessing system (WPS) to find the initial conditions and make ADS-B Mode-S ES data as the observation input data for WRFDA to obtain the necessary parameters to the equation of Gradient Richardson Number. These preprocessed data is then used to calculate the Gradient Richardson Number and applied to the now-casting analysis. As we confirm the hazardous wind shear through the Gradient Richardson Number, the next step is to do the principal components analysis during the wind shear period to identify parameters that their variations could indicate possible hazardous wind shear. Thus, when we recognize that the related parameters are changing significantly, we could predict that there might be wind shear near the airport. Finally, a three dimensional aviation unusual weather now-casting system prototype based on the ADS-B data that could provide aviation weather information such as the turbulence type, intensity of weather system and wind shear location is presented in this paper. From our results, these warning reports can assist air traffic controllers and pilots to take necessary actions to either change their original flight plans or to avoid the hazardous weather when approaching the airport.

Keywords:Automatic dependent surveillance-broadcast (ADS-B), wind shear, turbulence, principal analysis, Weather Research and Forecasting model Data Assimilation System (WRFDA), Gradient Richardson Number.

Significance of paper:

1. Wind-Profile estimation using airborne sensors.
2. Assimilation of high-resolution Mode-S wind observations in a regional NWP model for now-casting applications.
3. Identification of the hazardous wind shear condition through Gradient Richardson Number derived from ADS-B Mode-S ES data and WRFDA.