AN ADVANCED WEATHER AWARENESS SYSTEM FOR SMALL AIRCRAFT

Abstract

Small aircraft are the ideal transport mode for operations from regional airports. The project COAST (Cost Optimized Avionics SysTem), funded from the Clean Sky 2 Joint Undertaking in the European Union's Horizon 2020 research and innovation programme under grant agreement No CS2-SYS-ITD-GAM-2004-2015-01, has the aim to develop key technology enablers for the affordable cockpit and avionics in the area of small aircraft. In the framework of this project, an Advanced Weather Awareness System (AWAS) is under development: its main function is to present weather conditions to improve the pilot awareness when airborne. More specifically, it provides observed and forecasted data concerning meteorological hazards having potentially not negligible impact on the aircraft. The ambition of the system is to provide weather conditions along the path, integrating multiple data sources also including an advanced and user-friendly visualization. AWAS consists of different functional blocks. The Meteo Service Centre (MSC) is the ground segment and the core of the entire system: it gathers and consolidates observational data and forecasts provided by different data sources, such as in-situ and remote sensing measurements, output of numerical weather prediction models and websites. Data are transferred on board thanks to low-cost satellite communication. An On-Board Subsystem is used to manage these data and to visualize in an appropriate way the available weather data. The Satellite Communication System provides a bidirectional link between the ground segment and the on-board segment also permitting to provide to MSC the position and velocity vector of the aircraft. Hence, MSC can provide more targeted information pertinent to the real trajectory, reducing data volume. Extended functionality to be considered is transmission of weather data measured on-board back to the ground segment to increase its accuracy.

Full text

AN ADVANCED WEATHER AWARENESS SYSTEM FOR SMALL AIRCRAFT
ALESSANDRA LUCIA ZOLLO, MYRIAM MONTESARCHIO, EDOARDO BUCCHIGNANI, PAOLA MERCOGLIANO
CIRA, Italian Aerospace Research Center
Via Maiorise snc, 81043 Capua (CE), Italy
a.zollo@cira.it, m.montesarchio@cira.it, e.bucchignani@cira.it, p.mercogliano@cira.it
http://www.cira.it
JAN BERAN
Honeywell International s.r.o.
V Parku 2325/16
Praha 148 00, Czech Republic
jan.beran@honeywell.com
http://www.honeywell.com
Abstract
Small aircraft are the ideal transport mode for operations from regional airports. The project COAST (Cost Optimized Avionics
SysTem), funded from the Clean Sky 2 Joint Undertaking in the European Union’s Horizon 2020 research and innovation programme
under grant agreement No CS2-SYS-ITD-GAM-2004-2015-01, has the aim to develop key technology enablers for the affordable
cockpit and avionics in the area of small aircraft. In the framework of this project, an Advanced Weather Awareness System (AWAS)
is under development: its main function is to present weather conditions to improve the pilot awareness when airborne. More
specifically, it provides observed and forecasted data concerning meteorological hazards having potentially not negligible impact on the
aircraft. The ambition of the system is to provide weather conditions along the path, integrating multiple data sources also including an
advanced and user-friendly visualization. AWAS consists of different functional blocks. The Meteo Service Centre (MSC) is the
ground segment and the core of the entire system: it gathers and consolidates observational data and forecasts provided by different
data sources, such as in-situ and remote sensing measurements, output of numerical weather prediction models and websites. Data are
transferred on board thanks to low-cost satellite communication. An On-Board Subsystem is used to manage these data and to visualize
in an appropriate way the available weather data. The Satellite Communication System provides a bidirectional link between the
ground segment and the on-board segment also permitting to provide to MSC the position and velocity vector of the aircraft. Hence,
MSC can provide more targeted information pertinent to the real trajectory, reducing data volume. Extended functionality to be
considered is transmission of weather data measured on-board back to the ground segment to increase its accuracy.
Keywords Small Air Transport, Advanced Weather Awareness System, Meteo Service Centre, Satellite Communication System.
1. Introduction
In the last decades the concept of Small Air Transport (SAT) gained an ever increasing importance across
Europe as well as in the United States. The concept refers to the use of fixed wing aircraft with 5 to 19 seats (or
similar cargo vehicles), belonging to the European Aviation Safety Agency (EASA) CS-23 category, in order to
enable the transportation of people (or goods) over a regional range based on the use of small airports. The SAT
topic has been included in the Clean Sky 2 Joint Undertaking in the European Union’s Horizon 2020 Research
and Innovation Programme and the project COAST (Cost Optimized Avionics SysTem) has been funded under
grant agreement No CS2-SYS-ITD-GAM-2004-2015-01. The project, started in the year 2016, aims to tackle the
SAT challenge and to deliver key technology enablers for the affordable cockpit and avionics, while also
enabling the single pilot operations for small aircraft.
This paper is devoted to the description of an Advanced Weather Awareness System (AWAS), which is one
of the COAST technologies, currently under development.
Monitoring and forecasting of adverse meteorological conditions are crucial for the safety and optimization
of all flight phases, especially for small aircraft that are not currently equipped with adequate instrumentation.
Weather phenomena that negatively affect air operations are defined aviation hazards; these indicate a weather
condition, event, or circumstance that could lead to or contribute to an unplanned or undesired situations, such as
an accident causing injury to people, damage to equipment or to facilities. Among the environmental hazard can
be recognized intense weather events, such as hurricanes, tornadoes or blizzards and adverse weather conditions,
e.g. icing, heavy rain, lightning, strong winds, poor visibility and convective weather. Some of these hazards are
potentially fatal; indeed, adverse weather conditions constitute a major factor causing aviation accidents (Kulesa,

2003; Krozel et al., 2008). Also SESAR CONOPS (Concept Of Operations) identifies bad weather conditions as
a great factor for causing delays, restrictions to some operations and even closing of some airports. Furthermore,
they have an adverse impact on management operations and on system capacity, due to higher uncertainty
margins around trajectory predictions. For these reasons numerous projects, such as FLYSAFE (Tafferner et al.,
2008), SPADE (Van Eenige and Muehlhausen, 2006), EWENT (Juga and Vajda, 2012) and WxFusion (Gerz et
al., 2012) have been developed to increase pilots’ awareness of inflight meteorological conditions (so-called
weather awareness).
The goal to get complex real-time weather information on board is ambitious, since broadband connectivity
is expensive. At present, CS-23 pilots have to rely on recommendations on how to recognize weather conditions
and where to get the weather information. The quality and quantity of weather information can be increased
using airborne weather radar. However, it can only provide monitoring of weather situations around the aircraft.
Furthermore, in order to contain costs and dimensions, it typically works in single polarization and it cannot
distinguish the type of precipitation (rain, snow, hail, etc.), which decreases its benefit. Furthermore, in CS-23
only small airborne weather radar can be installed, but small antenna has a large beam width that involves a bad
azimuthal resolution. Then, CS-23 segment would benefit from weather information provided from the ground
and this consideration has motivated the push for the development of a technology to realize this objective.
Currently, some systems exist aimed to provide weather information to pilots. For example XMWX (Snyder and
Patsiokas, 2004) and AWARE (Ruokangas et al., 2006) systems are available in US. They provide, respectively,
information about observed weather conditions and enhanced weather briefing and report to pilots. However,
such kind of systems are not available in Europe. Other systems, such as AWDSS (Barrere Jr. et al., 2008) and
AerometWeb (developed by Meteo France International), integrate weather data from different sources for
aviation purposes, but they are only operational on ground.
The ambition of the Advanced Weather Awareness System, under development in the framework of COAST
project, is to provide consolidated weather information on board, integrating multiple data sources, for
monitoring and forecasting of weather conditions during all flight phases, and to provide an advanced and
intuitive visualization to pilots. AWAS is of great importance since it targets weather threat detection and
provides inputs for flight reconfiguration. So, it is very useful for air traffic control and it allows decision makers
at airports (e.g. pilots, ground personnel, air traffic controllers) to make plans with increased margins of safety
and improved efficiency, adapting routes and speed in response to the weather information.
In this paper, in section 2 an overview of the AWAS system, framed in COAST cockpit architecture, is
provided and in section 3 a description of the system architecture is reported. In section 4, finally, the outputs of
AWAS technology are described. Considering that this paper represents an introduction to the AWAS system,
whose development has been started since only one year, the evolution of the design activities and the achieved
technical results will be provided in future papers.
Some additional details about the COAST project can be found in the dedicated introductory paper by Di
Vito et al.(2017a), whereas a preliminary description of another of the COAST proposed technologies, namely
the Tactical Separation System (TSS), can be found in the dedicated paper by Di Vito et al.(2017b).
2. System overview
The COAST consortium worked on the identification of the most relevant enabling technologies for the
design of affordable avionic system for the SAT vehicles cockpit. A detailed overview of all technologies
addressed by COAST project are reported in Di Vito et al.(2017a). This paper focuses on one of the technologies
under development: the Advanced Weather Awareness System (AWAS).
Fig. 1 depicts the interface specifications between AWAS and adjacent systems in the COAST Cockpit
architecture.

Fig. 1. AWAS boundary diagram
AWAS application on-board is a software running on a Compact Computing Platform (CCP), which is a
scalable, reusable and reliable platform for advanced cockpit functions, under development in COAST project.
As shown in Fig. 1, AWAS application interfaces with the following systems in frame of the COAST Innovative
Cockpit technology:
 DFMC_GNSS (Dual-Frequency and Multiple Constellation Global Navigation Satellite System). It is
another technology under development in COAST and it is a low-cost scalable dual-frequency multi-
constellation (DFMC) GNSS platform that allows all systems to rely on high-precision and high-availability
position and velocity information.
 SAT-COM. It is a low cost satellite communication system, which provides a bidirectional link between
AWAS application on-board and a ground segment devoted to data elaboration.
 Multifunctional Display (MFD) or Portable Electronic Device (PED). It is used to present information to the
pilot. The link between AWAS and MFD/PED is one-directional since AWAS is a fully automatic system
without requirements for the pilot inputs.
 MSC (Meteo Service Centre). It is the ground segment, representing the core of weather data elaboration.
MSC communicates through SAT-COM with AWAS application on-board.
The following section provides a more detailed description of AWAS technology and MSC.
3. AWAS architecture
The aim of AWAS is to present the weather conditions to the pilot in order to improve its awareness making it
able to manage the occurrence of adverse weather conditions along the flight route. It provides observed and
forecasted detailed information (through graphical maps) concerning the aviation hazard levels for different
meteorological situations. The system considers several meteorological variables to display multiple hazards
with a limited number of maps.
The AWAS high-level architecture consists of five functional blocks depicted in Fig. 2.

Global Navigation
Satellite System
(GNSS)
Meteo Service Center
(MSC)
•Acquisition and recording of weather data
•Data processing for weather monitoring
•Data processing for weather forecasting
•Synthesis and formatting of data for on
board transmission
On-Board Sub-System (OBSS)
•Access to GNSS
•Access to TLC-SAT
•Display of weather data (graphical end textual)
Satellite
Communication
System (TLC-SAT)
External Weather
Info Sources
Fig. 2. AWAS high-level architecture
The main functionalities are performed by the on-board segment (On-Board Sub-System, OBSS) and the
ground segment (Meteo Service Center, MSC), connected to each other via a satellite link (Satellite
Communication System, TLC-SAT). As a baseline, a cheap satellite technology is engaged due to affordable
price.
The On-Board Subsystem (OBSS) is designed as a software application running on Compact Computing
Platform (CCP). The system is tailored in order to facilitate optimum integration with the cockpit interfaces and
other on-board systems. It takes the position and the velocity of the aircraft in input from DFMC_GNSS (Dual-
Frequency and Multiple Constellation Satellite System) and send this information to ground segment via satellite
link. Then, OBSS accesses the satellite communication channel to retrieve the weather data, provided by the
ground segment, and deals with their visualization on the Multi-Functional Displays (MFD) or on the Portable
Electronic Device (PED) in the cockpit.
The Meteo Service Centre (MSC) is the ground segment and the core of the entire system. It gathers and
consolidates observational data and forecasts provided by different data sources, such as in-situ and remote
sensing measurements, forecast from numerical weather prediction (NWP) models and websites. At MSC, the
weather data are collected, elaborated and prepared to be sent to the aircraft. The amount of data to be
transmitted is chosen as a trade-off between the available bandwidth at low costs of TLC-SAT and weather
information as complete as possible. Then, the amount of data depends on the available transmission rate and on
the weather conditions. It is worth noting that the use of GNSS will allow a remarkable reduction of the
information to be uploaded, which will be cropped only over the specific zone of interest. Information about
meteorological hazards synthetized and optimized by MSC are, then, packaged and transmitted to the OBSS
using the TLC-SAT. MATISSE (Meteorological AviaTIon Supporting SystEm), a prototype software developed
by CIRA (Italian Aerospace Research Center), accomplishes most of the MSC functionalities (Rillo et al.,
2015a). This tool for monitoring and nowcasting meteorological hazards has been developed in the framework of
the CIRA project TECVOL II (Technologies for autonomous flight) founded by MIUR (Italian Ministry of
Education, University and Research). In the framework of COAST project, an optimization of this tool is in
progress in terms of weather products, synthetic visualization and format to send data on board. The following
section illustrate the main functionality of MSC.
3.1. Meteo Service Centre (MSC)
The core of the MSC is MATISSE, a software managing visualization and elaboration of data stored in a
geodatabase, allowing to easily obtain maps, graphs and statistics concerning different weather parameters. More
in details, the meteorological data available in MATISSE (both observations and forecasts) are the following:

 Satellite data provided by the Meteosat Second Generation (MSG) satellite, elaborated in order to detect
various meteorological hazards for aviation (such as turbulence, icing, snow, cumulonimbus clouds and
intense rainfall). In particular, three EUMETSAT products are used: Multisensor Precipitation Estimate
(MPE), Cloud Analysis (CLA) and Atmospheric Motion Vectors (AMV). MPE provides an estimate of
precipitation rates observed from satellite and occurring over Europe; CLA provides a classification of
types, phases and depths of clouds observed from satellite. Indeed, cloud phases are used in order to detect
areas affected by icing conditions (hazardous due to the formation of ice on aircraft walls and instruments);
AMV provides wind speeds and directions, at different pressures, observed from satellite.
 Data from meteorological archives, mainly provided by the European Center Medium Weather Forecast
(ECMWF) MARS Archive (Meteorological Archival and Retrieval System)
*
making weather data available
from stations located in Europe, comprising AIREP data, vertical soundings data (TEMP and PILOT), land
surface data (SYNOP and METAR) and sea surface data (SHIP). These data can be used to extract
numerous meteorological variables (e.g. visibility, wind speeds and directions, present and past weathers,
temperatures, cloud cover, three-hour pressure change).
 Free available data provided by website.
 Ground based data, if available.
 Outputs of numerical models.
As a preliminary step, all these data need to be preprocessed in order to import only the variables of interest in
the geodatabase accessed by MATISSE. Indeed, data are available in different formats, such as TXT, BUFR
(Binary Universal Form for the Representation of meteorological data), NetCDF (Network Common Data Form)
and GRIB (GRIdded Binary). After this phase data are elaborated and converted in the appropriate format for the
import procedure.
It is worth noting that these raw data are further elaborated through appropriate algorithms, developed in several
languages and using different software, in order to obtain specific products for monitoring and forecasting of
meteorological hazards. Also the output of these products is imported in the geodatabase.
After the storage, the variables can be visualized mainly in two modalities: maps (in GIS environment) or
graphs. Furthermore, it is also possible to compute statistics and obtain more complex information. The
workflow of MATISSE, shown in Fig. 3, summarizes all these steps. Further details concerning MATISSE are
reported in Rillo et al. (2015a).
Fig. 3. MATISSE workflow
Different monitoring products have been developed and are already available in MATISSE, such as a tool for
icing detection (Manzi et al., 2015) and a tool for characterization of cumulonimbus and their developing and
dissolving phases (Rillo et al., 2015b), both based on satellite data.
*
Available in research mode thanks to the CIRA agreement with Italian Meteorological Service (ITAF)

Concerning the forecast of meteorological parameters, at the moment in MATISSE forecast of the NWP
(Numerical Weather Prediction) COSMO-Model (Doms and Shӓttler, 2002) are available (only for research
purposes); nevertheless the same interface can be used to consider to include in the system also forecast provided
by other models. The COSMO-Model is a nonhydrostatic limited-area atmospheric prediction model. The basic
version of the COSMO-Model (formerly known as Lokal Modell (LM)) has been developed at the Deutscher
Wetterdienst (DWD). The COSMO-Model run operationally since end of 1999. The subsequent developments
related to the model have been organized within COSMO, the Consortium for Small-Scale Modelling. COSMO
aims at the improvement, maintenance and operational application of the non-hydrostatic limited-area modelling
system, which is now consequently called the COSMO-Model. It has been designed for both operational
numerical weather prediction (NWP) and various scientific applications on the meso-β and meso-γ scale. The
COSMO-Model is based on the primitive thermo-hydrodynamical equations describing compressible flow in a
moist atmosphere. A variety of physical processes are taken into account by parameterization schemes.
Additional info on COSMO-Model are reported on the web site http://www.cosmo-model.org/. Furthermore,
some products for the forecasting of specific variables have been developed, such as products for the nowcasting
of precipitation (Zollo et al., 2015) and fog (Zazzaro et al., 2015) based respectively on satellite and synoptic
observed data.
In the frame of the COAST project, other products will be developed in order to provide both monitoring and
forecasting of different meteorological hazards; and the whole technology to provide on board data in the CCP,
is implemented.
Fig. 4 and Fig. 5 show some examples of maps that is possible to obtain in MATISSE. In particular, Fig. 4
depicts maps of cloud cover and visibility over Europe obtained from synoptic observations, whereas Fig. 5
show winds and cumulonimbus over Italy obtained from satellite data. It is worth noting that in some cases the
value of the variable of interest is directly associated to a hazard level (low, medium, high or very high) colored
in green, orange or red.
In MATISSE the implementation of a specific function to support pilots during all the flight phases is in
continuous development. The goal is to provide synthetic, and as complete as possible, information concerning
meteorological hazards occurring over the area of interest. To this aim, there is the possibility to produce text
files containing only latitudes and longitudes of the vertexes of the polygons that identify the areas affected by
the hazard, with the values of the hazard level. In this way, it is reduced the amount of information to be sent on
board. Further details concerning this function are reported in the section 4.
Fig. 4. Maps over Europe obtained from synoptic observations reporting (a) cloud cover and (b) visibility conditions, with their
corresponding hazard level (high in red, medium in orange and low in green).

Fig. 5. Maps over Italy obtained from satellite data reporting (a) wind barbs and (b) cumulonimbus simplified as rectangles with their
corresponding hazard level (very high in red, high in orange and medium in green).
4. Monitored and forecasted AWAS output
As already highlighted in the previous sections, the aim of AWAS is to provide information, concerning
observed and forecasted meteorological hazards, to the pilot on board. To reduce communication costs and the
required throughput, it is under development a functionality that allows to generate several text files with only
synthetic information concerning meteorological hazards occurring during all the flight phases.
These files will be automatically sent on board, at a constant frequency, and the information will be displayed on
the MFD installed in the cockpit.
More in details, two kinds of data are provided by AWAS:
(1) Text files concerning monitored meteo hazards;
(2) Text files concerning forecasted meteo hazards.
Specifically, every 15 minutes, a text file is produced for each hazard monitored and for each hazard forecasted.
The files are organized in columns containing longitude and latitude of polygon’s vertices enclosing the area
affected by hazard, values of meteorological variable of interest and corresponding hazard level. Each row of
these files is representative of a polygon and each file can contain hundreds of rows, in the case of bad weather
conditions. Clearly, in a day with better weather conditions the amount of information to be sent is lower.
As consequence, the size of each file is very variable because it depends on the intensity and extent of the
hazards on the considered geographical area. It is worth noting that the format of the file could be slightly
different depending on the specific features of the hazard analyzed; for example, for lightning data only the
position will be provided without information on the hazard level.
An example of the text files produced by AWAS on ground segment (MSC), concerning heavy precipitation, is
shown in Fig. 6 (a), whereas Fig. 6 (b) depicts an example of map with colors associated to hazard level (red for
high level and orange for medium level). Through SAT-COM, these files are sent to AWAS on board application
that deals with their visualization on the Multi-Functional Displays (MFD) or Portable Electronic Device (PED)
in the cockpit.

Fig. 6. Example of AWAS output: (a) text file containing coordinates of polygons vertices enclosing areas affected by heavy precipitation;
(b) map with polygons’ colors associated to hazard level (red for high level and orange for medium level).
On the base of available satellite throughput, the amount of data to be transmitted can be optimized arranging
weather data in order to meet channel requirements. For example, it is possible to consider a smaller
geographical area cropped on a reduced domain around the aircraft or to identify fewer vertices to characterize
polygons enclosing areas affected by meteorological hazards. Furthermore, since it is planned to send a single
text file for each hazard monitored and for each hazard forecasted, AWAS application allows to avoid the file
sending if the hazard doesn’t occur, reducing then the data amount to transfer.
5. Conclusions
In the present paper, the main features of the AWAS (Advanced Weather Awareness System) technology are
described. AWAS is one of the different enabling technologies for SAT vehicles, under development in the
overall framework of COAST project. This specific technology is aimed to provide the pilot with increased
weather awareness, including monitoring and forecast conditions, for a proper decision-making support, also in
compliance with the expected pilot responsibilities in the future SESAR environment.
The main functionalities of the AWAS subsystem have been described, specifying the basic concepts underlying
its design, that is ongoing in the COAST project, and by emphasizing the innovation potential expected by its
introduction among the technologies in the SAT domain. Some basic features of the monitored and forecasted
products, that will be available in the AWAS subsystem, are also introduced to give an overview of the expected
output. Furthermore, it is important to emphasize that this output takes also into account the current satellite
throughput, representing a limitation for the amount of data to be transmitted and, then, requiring in this initial
phase a multi-disciplinary activity for its optimization. In fact, it is necessary, firstly, to match the requirement to
have a fast upgrade of the weather information, to take into account sudden change of the weather condition, but
also to provide detailed geographical information on the area interested by hazardous weather condition.

Acknowledgments
The project COAST (Cost Optimized Avionics SysTem) has been funded from the Clean Sky 2 Joint
Undertaking in the European Union’s Horizon 2020 research and innovation programme, under grant agreement
No CS2-SYS-ITD-GAM-2004-2015-01. The authors acknowledge the CIRA project TECVOL II (Technologies
for autonomous flight) founded by MIUR (Italian Ministry of Education, University and Research).
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