MASTER THESIS

Deploying contrail forecasting service to reduce the impact of aviation on Environment

Supervisors:

Dr. Wolfram Hardt Dirk Schindler Chair of Computer Engineering Technical Manager - Faculty of Computer Science Operations Support Systems TU Chemnitz AIRBUS Defence & Space

A thesis submitted in fulfilment of the requirements for the degree of Master of Science in

AUTOMOTIVE SOFTWARE ENGINEERING TUCHEMNITZ

by Tejashree Chhajed MTR.-NO. : 335478

FEBRUARY 14, 2016 ABSTRACT

he principal objective of this thesis is to propose a Contrail forecasting Service for Aviation(ConSA) and a ConSA client to demonstrate the service. The subject Tis motivated by the fact that Contrails have a very harmful effect on the environ- ment and it has been researched thoroughly by scientists. But still we do not have an infrastructure to include these researches in the Aviation industry. This thesis has been conducted at Airbus Defence and Space, Friedrichshafen, Germany.

The first part of the thesis investigates the existence of contrails. The object of interest i.e. Contrails is caused by the passage of aeroplanes in ice-saturated areas. The algorithm which is used by the service is a part of the research conducted by Prof. Dr. Ulrich Schumann. The input dataset provided by Meteo France is a 4D weather cube. The algorithm computes a threshold temperature and ice supersaturation condition. When both of these conditions are satisfied Contrail formation is certain.

In the second part we explain the architecture and solution used i.e. OGC (Open Geospa- tial Consortium) and LuciadLightspeed to develop Web Services to deploy contrail forecasting methods. Such an architecture fast forwards and eases the task of developer by having inbuilt methods and interfaces. The OGC web services infrastructure has de- fined web feature service and client interface which ease development of geoinformatics solutions. We also use certain standards like WXXM for exchange of contrail information which will be stated in this chapter.

The third part is about the detailed implementation of the ConSA service and client. In this chapter we explain the service and client with uml diagrams to clarify the development concepts.

The final part of the thesis explains the results of ConSA service and client, operational benefits of ConSA and concludes the thesis.

i ACKNOWLEDGEMENTS

oremost, I would like to express my gratitude to my supervisor Dirk Schindler for his immense knowledge, guidance, patience and support. Without his rigorous Fefforts this thesis would not have been completed. He has been a mentor every student would like to learn from.

I would like to thank Robin Houtmeyers from Luciad for his guidance, support and for being there for all the queries. I would like to thank Prof. Ulrich Schumann for his guidance and support. I thank Airbus Defence and Space, Luciad, DLR and Meteo France for graciously providing their research, software and dataset. My experience at Airbus Defence and Space has been a journey of research, I always wanted to undertake.

I thank my boyfriend Surajit Dutta for his love, encouragement and care. He has been besides me for everything, everytime. A special thanks to Merecedes Cabezos Bueno who has been more than a landlady. I thank her for making settling in Deutschland so easy. I also thank her for teaching German, offering the delicious food, the car rides and the hardwork in shifting belongings to new flats. I thank all my friends in Lindau, Jekin Trivedi, Prajakta Bhagwat and Shashikant Chavan for the boat rides, amazing dinners and parties.

I finish with India, where my source of inspiration resides: my family. My mother Sunita Chhajed loved me unconditionally no matter I failed or succeeded. It was her who was always besides me. My father Rajkumar Chhajed taught me to always try and never give up. I owe them my entire self. My grand parents loved me and gave up many things for my dreams and my brother Kunal Chhajed was my companion in studies, fun and in the stupidest things in life. I thank them all and wish to have them forever in my life.

ii To my parents TABLEOF CONTENTS

Page

1 Introduction1 1.1 Background...... 2 1.1.1 Formation of Contrails...... 4 1.1.2 Impacts to Environment...... 5 1.1.3 Radiative forcing...... 7 1.2 Challenges...... 7 1.3 Contributions and Thesis Overview...... 8

2 State of the art 11 2.1 Related Work ...... 12 2.1.1 Statistical Contrail Forecasting...... 12 2.1.2 Prediction of Persistent Contrail Occurrence...... 12 2.1.3 Contrail Cirrus Prediction Tool ...... 13 2.2 Proposed approach ...... 14 2.2.1 Meteo Dataset...... 14 2.2.2 Flight Dataset...... 16 2.2.3 Algorithm...... 18

3 Architecture and Solution 22 3.1 Geographic Information Systems...... 22 3.2 LuciadLightspeed...... 24 3.2.1 Powerful Features...... 28 3.2.2 Benefits of Geospatial display ...... 29 3.3 Web Services ...... 29 3.3.1 Open Geospatial Consortium...... 29 3.3.2 OGC standards ...... 30 3.4 OGC Web Services...... 31 3.4.1 Web Map Service...... 32 3.4.2 Web Feature Service ...... 34 3.4.3 Web Coverage Service ...... 37

iv TABLE OF CONTENTS

3.5 Information exchange format...... 39 3.6 OGC Web Server Suite...... 43 3.6.1 LuciadLightspeed NetCDF Industry Specific Component . . . . 46 3.6.2 LuciadLightspeed WXXM Industry Specific Component . . . . 48

4 Implementation 49 4.1 Inputs from other projects...... 50 4.2 Service overview ...... 51 4.3 Service interface specifications...... 52 4.3.1 ConSA Service...... 52 4.3.2 ConSA Client...... 54 4.4 Service dynamic behaviour...... 55 4.4.1 The ConSA Service...... 55 4.4.2 The ConSA Client ...... 55 4.5 Technical Architecture ...... 56

5 Results and Evaluation 59 5.1 Algorithm Evaluation...... 59 5.2 Validation and Verification ...... 64 5.3 ConSA evaluation...... 64

6 Conclusion 65 6.1 Thesis implications...... 66 6.2 Benefits ...... 68 6.3 Future Scope ...... 71

7 Appendix A 72 7.1 ConSA service physical interface description ...... 72 7.2 ConSA service: OGC WFS capabilities...... 72 7.3 Example of a Contrail object representation in WXXM 2.0 ...... 77

Bibliography 79

v LISTOF TABLES

TABLE Page

5.1 The above table is a given by DLR. It has input and output data to check the correctness of the Contral forecasting algorithm. The G and U values are given and we check if the algorithm outputs the TLC and TLM (temperature) values as given in the table. As it matched completely the algorithm was correct...... 63

vi LISTOF FIGURES

FIGURE Page

1.1 Sesar Objectives...... 3 1.2 Exhaust Contrails...... 4 1.3 Aero dynamic Contrails...... 4 1.4 Persistent Contrails...... 5 1.5 Countries ratifying the Doha amendment...... 6 1.6 Radiative Forcing induced by aviation...... 7

2.1 Contrails...... 11 2.2 MET-GATE...... 15 2.3 MET-ATM SWIM services...... 16 2.4 ADS-B ...... 17 2.5 Schmidt-Appleman Criterion...... 20

3.1 Model View Controller mind map ...... 25 3.2 Application development process...... 25 3.3 An aerodrome style descriptor and aerodrome layer...... 27 3.4 Airspace in 3D ...... 27 3.5 Airspace in 3D ...... 27 3.6 OGC standards ...... 31 3.7 OGC Web Service...... 32 3.8 Web Map Service...... 33 3.9 Web Feature Service ...... 35 3.10 Web Coverage Service ...... 37 3.11 WXXM...... 41 3.12 NetCDF...... 43 3.13 Architecture of the Luciad WMS server...... 44 3.14 Architecture using the Luciad WCS server...... 45 3.15 Architecture using the Luciad WFS server...... 46 3.16 Integrating NetCDF imagery into your application...... 47

4.1 Contrail Service - flow of data ...... 50

vii LISTOF FIGURES

4.2 ConSA Client- flow of data...... 51 4.3 ConSA overview [Operational node connectivity description ...... 52 4.4 ConSA Service interface specification ...... 53 4.5 ConSA Service interface specification ...... 54 4.6 The sequence diagram illustrates the dynamic behaviour of the ConSA Service 55 4.7 The sequence diagram illustrates the dynamic behaviour of the ConSA Client 56 4.8 The sequence diagram illustrates the dynamic behaviour of the ConSA Client 57 4.9 The sequence diagram illustrates the dynamic behaviour of the ConSA Client 58

6.1 4D corridor showing contrail probability along a trajectory from ConSA . . 67 6.2 Overview on ATM Stakeholders ...... 68

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C HAPTER 1 CHAPTER 1. INTRODUCTION

concept based on the ATM Master Plan. • Meteo: Understanding availability of met data, ways to analysis of weather data, establishment of forecast data and contrail forming effects.

This thesis aims to investigate the task of forecasting contrails using knowledge of both fields, Aviation and Meteorology. The aim of this thesis is achieved by deploying a contrail forecasting service and client. The service and client are abbreviated to CONSA service and client where CONSA stands for CONtrail Service for Aviation.

Throughout the thesis the focus is on implementing the algorithm, deploying the service and client, however there were many challenges working with diverse services, informa- tion exchange standards and frameworks. The task crucially involves deploying a service which is fast, reliable, real-time and integrable with any aviation platform, in spite of presence of such an imbalanced infrastructure. Specifically the focus is on the future of the service, which will be deployment of the service in the European Aviation infras- tructure. This thesis hence proposes solutions to develop a generalized infrastructure model of the entire Service and framework involved in the light of the future integration. Generalized in this sense means to provide high productivity on previously unknown circumstances.

The aviation industry is undergoing a revolutionary change which includes using such aforementioned infrastructure. This means the task is to choose the service interface, the information exchange standards and the framework very wisely, i.e. in our case depends on the use of forecasted information. The selection should be an information exchange standard which can hold and carry the contrail information unambiguously and uninterrupted. Next task is to select the service interface which would be in sync with the information exchange standard and is reliable. Last and the most important of all the need is to select a framework which would support the selected information exchange standard and the service interface.

To put it in a nutshell, in aviation best infrastructure selection plays an important role and is investigated in this thesis. The following sections describe Contrails essentials, the and related work. The chapter concludes with an overview of the thesis and a summary of our contributions.

1.1 Background

Knowledge of the three described domains has been gathered at Airbus Defence and Space (Germany). The department at Immenstaad participates actively in the SESAR

2 CHAPTER 1. INTRODUCTION work package “SESAR WP11.01”, from where access to latest aviation research under the current ATM Master Plan could be gained. Based on the knowledge of the software development team further research in latest IT had been carried out, in order to understand options and limits of current paradigms. The objectives of SESAR are shown in the pi chart in figure 1.1. The objective of the thesis is one of this objective, i.e. Reduction in environmental impact per flight - the green arc.

Increase in Reduction in Europe’s airspace capacity cost per flight

6% 27%

24.2% Other SESAR goals 40% 2.8% Reduction in Reduction in accident risk per flight environmental impact per flight

Figure 1.1: This diagram explains the objectives of SESAR. SESAR which is an initiative by Eurocontrol, Air Traffic Management(ATM) of Europe. This is the first step which has a deadline until 2020. SESAR has several WP which are distributed between public-private firms to achieve the goal of SES.

This was one among the major tasks the team works on, which is a very challenging field in the market of a growing global pollution. Contrail research work has started centuries ago but none of them posses an infrastructure which can be integrated in the existing Aviation environment without major changes. This also means that the forecast information needs to be knowledgeable and flexible enough to work with any aviation scenario. This is only possible with Open Standards. The Airbus Defence and Space exploits all its in-depth expertise in software development and also uses the expertise of major research institutes and companies to maintain a world-leading standard. The research institutes which contributed to the thesis are Deutschen Zentrums für Luft- und Raumfahrt (DLR) and Meteo France. The company which gracefully gave the software framework for the thesis is Luciad. The following subsections provide an overview of the formation of Contrails, the impact to the environment and the radiative forcing index.

3 CHAPTER 1. INTRODUCTION

1.1.1 Formation of Contrails The exhaust contrails. They are formed when water vapour condenses and freezes around small particles (aerosols) that exist in aircraft exhaust. The water vapour comes from the air around the plane and the exhaust of the aircraft. The factors leading to these contrails are relative humidity, temperature, pressure and aircraft exhaust [2][3] and aircraft engine. Various researchers have given their equations, criterion’s, threshold values to predict a contrail occurrence.

The aero dynamic contrails. The contrails occurs due to condensation by rapid de- pression of air which is accelerated. The common one are near the sharp tips [4]. For this the air needs to be very humid and almost saturated and the temperature must be warm (to hold the water vapour) [4]. The phenomenon can be explained with thermodynamics as follows: When the air flowing over the wing has a lower pressure than that flowing underneath it, and because the air flows from high pressure to low pressure, the air also flows from the wing’s bottom to its top. These movements create a vortex, at the tip of the wings. These vortices are lower pressure and temperature areas leading condensation of water vapour.

The figure 3.4 and 3.5 shows each of the contrails. The exhaust contrails are the ones which affect the environment and hence the objective of the thesis is limited to it.

Figure 1.2: Exhaust Contrails Figure 1.3: Aero dynamic Contrails

Cirrus Clouds For the contrails to persist the ice crystals need to be supersaturated [5]. These new ice crystals will grow in size as time passes. When contrails persist for longer duration they form anthropogenic cirrus clouds [6]. The cirrus clouds differ from natural clouds considering their micro-physical properties. Any naive observer must have observed transformation of contrails into cirrus clouds. The image 1.4 shows the sky filled with contrails and cirrus.

4 CHAPTER 1. INTRODUCTION

Figure 1.4: Persistent Contrails.

The contrail stretches for long distances behind an aircraft. Contrails which can persist, last for hours while growing to several kilometers in width and 200 to 400 meters in height. Contrails spread because of many reasons like the air turbulence generated by the passing aircraft or varied wind speed across the flight track. In the upper troposphere there are strong winds to spread the contrails across continents. In the experiment done by Minnis et al. [6] the observed contrails by geostationary satellites lasted from 7 to over 17 hours and expanded across 35000km2. Later the cirrus gets unrecognisable as contrails to the surface observer.

1.1.2 Impacts to Environment After September 9 attacks the national airspace was closed for 3 days from September 11-14 and as in these days no airplanes flew, there were no contrails in the sky. The meteorologists and researchers took advantage of this time. It was concluded that the difference between the day and night temperatures in these days was significant than the other temperature difference observed normally in the US [7]. Hence it was proofed that Contrail affects climate change.

Their radiative properties strongly depend on micro-physical characteristics such as number concentration, crystal shapes, size distribution, and the crystal diameter. Small ice crystals below 20-mm diameter would strongly affect radiative transfer through a cloud if they were present in larger numbers [8].

The contrails reduce the radiation reaching Earth’s surface and also blocks the radiation reflected back from the Earth to the skies(greenhouse effect) [3]. This means there is less radiation reaching the Earth and more radiation trapped in the Earth’s surface and atmosphere. Researchers have declared ’global warming’ in the areas they mostly

5 CHAPTER 1. INTRODUCTION occur [9]. It has its own positive effect and negative effect. But researchers claim the overall net effect is negative.

Another important impact is that the water vapour which would be normally used for the formation of normal cirrus, it gets absorbed for the formation of contrail cirrus [10]. Hence, contrail cirrus have the potential to inflect the optical properties of natural clouds, delaying their formation and substituting them.

Figure 1.5: The diagram above shows the countries participating in the Doha agreement which is extension of the Kyoto protocol. In Kyoto protocol 192 states have an agreement and as of 28 May 2015, 32 countries have ratified the Doha agreement. But for the acceptance of it a total of 144 states should accept it.

The United Nations Framework Convention on Climate Change was extended in 1992 to the Kyoto protocol. It is an international agreement which regulates the emissions harmful to the environment. The Kyoto Protocol was adopted in Kyoto, a city which is naturally decorated in Japan, on 11 December 1997 but came into effect on 16 February 2005. The parties involved have two commitment periods. The first commitment period, has the agenda to reduce the overall emissions by at least 5 percent below 1990 levels between 2008 and 2012. For the second commitment period, the same Parties have agreed, to reduce their emissions by at least 18 percent below 1990 levels between 2013 and 2020. But the Kyoto protocol till today does not concentrate on the contrails, even though it has a huge impact on the climate. The environmental affect of the contrails is estimated to be worst than the affect of CO2 emissions [10]. Aircraft engine emissions like smoke, nitrogen oxides and hydrocarbons are currently regulated (in airport zones) by the FAA and the ICAO [11]. Carbon dioxide regulation is in process. Next in the row will be the Contrail regulation, hence the thesis prepares the aviation community for such a change.

6 CHAPTER 1. INTRODUCTION

1.1.3 Radiative forcing In IPCC Radiative forcing is defined as "It is a measure of the influence a factor has in altering the balance of incoming and outgoing energy in the Earth-atmosphere system." The following are the findings in 1992 and 2000 [12]. It is an index of the importance of the factor as a potential climate change mechanism. In this report radiative forcing values are for changes relative to preindustrial conditions defined at 1750 and are expressed in Watts per square meter (W/m2).

50

40

30

]

2 RF [mW/m2] RF 20 1992 2000

RF [mW/m 10

0

-10

-20 CO2 03 CH4 H20 Direct Direct Contrails Total SulphateSoot Cirrus Aviation induced products

Figure 1.6: The bar graph above gives the radiative forcing from aviation based on Sausen et al. [12].The graph shows the affect of

1.2 Challenges

Irrespective of the clear idea of how there are formed and what effects they have, the algorithm selection problem persisted. In such a forecast problem using artificial intelligence and machine learning could be the best solution, but that required a specific dataset. The dataset should have the airplane properties i.e. airplane speed, engine type and of course the meteorological properties of similar latitude-longitude-altitude of flying. As such a dataset was not available for this thesis, the search was for alternatives.

It was clear that an ideal algorithm development needed meteorological expertise. And hence got allies from this field to help in this thesis.

7 CHAPTER 1. INTRODUCTION

The algorithm used in this thesis needed meteorological dataset of temperature, humidity and pressure of Europe. This dataset should include real-time and forecast numerical data, which should also be accurate. Hence in this thesis a client interface, which could connect to such service and decode the data to numerical format, has been implemented. However, having such connectors and decoders doing real-time operations usually exhibits huge computational complexity. In addition, having a clear display of the output contrail information is also not of less complexity. For this reason, this thesis focuses on a Geo- Informatics System which uses OpenGL and OpenCL for computation and graphics.

1.3 Contributions and Thesis Overview

The main contribution of this thesis is the proposal of the infrastructure, which can forecast contrails in real time and can be instantly used by pilots, ATC(Air Traffic Controllers) to avoid contrails while flying. An Service and Client implementation has been developed with a number of strategies, which will be introduced in next chapters. In addition, the proposed method is very flexible, fast and is able to obtain a 4D display of contrails which will enable end users visualize contrails in order to avoid it.

The presented approach is implemented in form of a Java OGC(Open Geospatial Consor- tium) Web Services. The meteorological services are accessed and decoded in real-time and accurately so that the Contrail output is also precise. Th OGC standards of data exchange, i.e. NetCDF and WXXM are used to seamlessly integrate with the existing infrastructure. A Contrail forecasting algorithm has been integrated in the service itself to deliver fast results. The meteorology data updates to the service are scheduled every 5 minutes with the OpenGL functions of software framework. With similar functions the computation of Contrail points with similar rate is possible.

The strategy is to inform ATM authorities about the contrail predictions so that they use another travel route. The modified route does not necessarily be too much deviated with the original route as the flying altitude is a one of the potential factors to decide if contrails will be formed or not. This means, even a small change in the flying altitude has potential to avoid contrail formation.

The access to the input services and the software framework was provided by the SWIM (System Wide Information Management) with its SWIM Master Class 2015 Competition. This competition is arranged by Eurocontrol, Europe’s ATM. With Eurocontrol’s earlier attempts with SESAR (Single European Sky ATM Research) [4], a public private part- nership project, a number of key changes for the future had already been proposed by the projects team members. SWIM [5, 6] is an important part of SESAR which enables assured standards, information flow, infrastructure and governance. SWIM Master Class

8 CHAPTER 1. INTRODUCTION is held every year and participants from all over the world become a part of it. The aim is to enable global interoperability in the ATM community. In the challenge it provides access to the latest SWIM developments and services through a SWIM registry. With this thesis we participated in the SWIM Master Class competition 2015 and hence had access to various software frameworks and data services.

The thesis proposes to bridge two sides: the latest meteorological research outcome and the aviation community. The purpose of this thesis could be perfectly achieved through SWIM. The determining factors to select the service and framework were, to make best use of the SWIM environment, to build the solution upon existing widespread and SWIM- adopted standards for any demanded transfer of data, to consider a high-performance and user-friendly Software Engine, to cope with mass data of highly complex structures, to build the solution upon existing and fielded systems to demonstrate advantages of enhanced technology and work flow, to foresee open interfaces to existing SWIM services and to consider variable perspectives from different ATM stakeholders (FOC/WOC, ASM, NM).

The web service will work as follows:

• (A built-in OGCWeb Coverage Service client is developed to access live weather data.)

• (This data is fed into the Contrail Calculation Algorithm, which outputs contrail objects based on the given meteorological data.)

• (The resulting contrail forecast information is published via an OGC Web Feature Service.)

To demonstrate the capabilities of the ConSA Service, building on a SWIM environment, and its use in a real mission planning environment, a ConSA Client has been developed. The client as the receiving part of the ConSA SWIM-based service has been implemented as standalone application capable of consuming and analysing contrail forecast data served by the ConSA service, together with live weather data and ADS-B flight tracks. The aim is to provide a means of support to ATM operators in identifying areas (in 4D) of intense contrail forming which in turn leads to forming of cirrus clouds. By use of the service probable environmental impact to the climate can be recognized.

The structure of the thesis document is as follows. The second chapter of the thesis investigates the existence of contrails and provides all relevant details with regards to the object of interest i.e. Contrails. In the third chapter the relevant aspects of the state of the

9 CHAPTER 1. INTRODUCTION art approaches along with our approach is explained. The fourth chapter introduces our software framework to deal with various formats, to develop the services and of course to manage the computational complexity of entire implementation. In the fifth chapter details of the implemented solution are specified and clearly described in detail. In the sixth results of the thesis and conclusion is explained. The last chapter is Appendix which stats the physical interface description of service and client and gives an introduction about the syntax of the service and output standard.

10

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C HAPTER CO 2 2 , NOx , CHAPTER 2. STATE OF THE ART diction theory was started by Schmidt (1945) and Appleman (1953). Since then the Schmidt-Appleman criteria [2] has been the basis of various researches in this area. This chapter aims to introduce to you important state-of-the-art contrail forecasting researches.

2.1 Related Work

In the next subsections the aim is to show a short overview of the approaches towards contrail detection and introduce different algorithms. Finally, this section concludes by discussing related work on the problem of integrating such researches in the aviation community.

2.1.1 Statistical Contrail Forecasting This technique was proposed by Jackson et al. [14]

Dataset The dataset used is from the Contrail Field Program which collected aircraft observations and co-incident radiosonde observations for a 10 day period. The aircraft ob- servations included aircraft data like latitude, longitude, altitude, type, speed and whether it produced a contrail or not(manually). The radiosonde data included temperature, pressure, relative humidity and winds within the projects domain.

Algorithm. The Statistical Contrail Forecast Model was built. It is multi-variate linear regression model as the relationship between the predictand (Contrail-yes/no observa- tions) and the predictors (radiosonde weather data) is linear. Input (Predictors) were chosen using a stepwise regression function and performing tests with a null model. This followed with the concept of using only those predictors which would produce the maximum variance in the predictand. Four regression models were developed each with respect to three data quadrants and the last quadrant was used for testing. The output prediction was a probability value.

Disadvantages The dataset was small(557 observations) and the radiosonde data is not accurate. Moreover the radiosonde data is nearly co-incident to aircraft observations but the the algorithm accuracy might depend vastly on this factor.

2.1.2 Prediction of Persistent Contrail Occurrence This technique was proposed by Duda and Minnis [15]

12 CHAPTER 2. STATE OF THE ART

Dataset. Dataset consists of meteorological data (of 15 months from the Advanced Regional Prediction System (ARPS) and the Rapid Update Cycle (RUC)) and the contrail occurrence data (from the surface and satellite observations). Satellite observations consisted visual inspection multi-spectral satellite data to detect persistent contrails. The surface observations were taken by school children in a program called GLOBE. The meterological data was matched with the contrail observation data with the method of linear interpolation.

Algorithm Logistic regression technique was used here too.

where P is the predictand (probability of persistent contrail formation) and predictors x1 (meteoro-logical quantities) to the model. The maximum likelihood method is used to estimate the unknown coefficients of βi and to fit the logistic regression model to the data. Same as proposed by Jackson etall 2.1.1 stepwise regression technique was used to find number optimal number of predictors. Two groups of logistic models were developed. One model used the surface and satellite data along with meteorological data and the other one used just the satellite data along with meteorological data.

Disadvantages As contrail altitude information is missing, it is difficult to use this information. The classification between real cloud and contrails is not possible in the satellite data, hence it results in false positives and false negatives. Moreover the meteo- rological data collection by RUC and ARPS have a drawback in measuring inaccurate relative humidity.

2.1.3 Contrail Cirrus Prediction Tool A new model to predict contrails was developed by Prof. Dr. Ulrich Schumann from DLR. The model is implemented in a tool called Contrail Cirrus Prediction Tool (CoCiP). The model is mathematical model and represented with a Lagrangian Gaussian plume model. This tool uses the Modified Schmidt-Appleman algorithm which was modified by Prof. Dr. Schumann himself in 1996 [16].

Dataset. Dataset consists of meteorological data and air traffic data. The meteoro- logical dataset is taken from European Centre for Medium-Range Weather Forecasts (ECMWF)which is 1-h forecast data at 0.5° resolution in numerical weather prediction.

13 CHAPTER 2. STATE OF THE ART

The air traffic data is taken from Aviation Climate Change Research Initiative (ACCRI) which is forecasted every 12 h.

Algorithm. The CoCiP tool computes contrail prediction in 3 model phases. In the phase 0 - initial conditions of contrail formation; phase 1 - the spreading of contrails shown with a Lagrangian plume model; Phase 2 - contrail evolution until dry-out. The contrail calculation requires about 10 s computing time on a single processor Laptop.

Disadvantages. The tool does not have state-of-the-art interfaces and implementation to be integrated in the aviation domain.

2.2 Proposed approach

In this thesis the focus is on integrating the state-of-the-art contrail forecasting approaches with the existing aviation infrastructure. By this the aviation community would benefit by the contrail forecasting researches. This thesis proposes to develop a contrail forecasting service which is based on a part of the CoCiP tool which was given to us gracefully by Prof. Dr. Ulrich Schumann.

2.2.1 Meteo Dataset The input to the algorithm is meteorological data provided by the MET Information Services Generation, ATM tailoring and Exchange (MET-GATE) schema. The following figure shows the MET-GATE Schema. The schema is accessed by the ATM clients.

The shaded 4D cube is indeed a 4D cube for weather information (4DWxCube). This innovative solution was developed to work with ATM infrastructure. It is formed by the sharing of meteorological information by European MET providers.

MET-GATE services The services are defined such that the information exchange is open and supports international standard. The following are the services offered by the MET-GATE till today.

The service which are used to retrieve weather data is the Wind/Temperature AROME grids. AROME is the high-resolution Meteo France’s model. The aim of the Arome project is to improve local forecasts, especially for dangerous convective phenomena (thunderstorms, flood risk, heavy precipitation) and low-level conditions (wind, tem- perature, ground state, fog, heat islands, etc. ). One of the most interesting features is that Arome will assimilate radar data (Doppler winds and 3D reflectivities) and satellite radiances. The higher resolution of the model improves the meteorological impact of

14 CHAPTER 2. STATE OF THE ART

Figure 2.2: MET-GATE geography in a spectacular way. For instance, the meteorological effects of cities, coasts and large valleys are well represented: urban heat islands, diurnal cycle of sea breezes and valley breezes, frost zones, local winds forced by orography etc. Arome is intended to improve and diversify towards new applications. The geographical area covered by the model is the area defined by (38N, 9W ; 55N, 14E) with a resolution of 0.025° ( 2.5km). AROME provides forecast up to 36h with a 1h time step. It is updated every 6 hours There is one coverage per physical parameter: Relative humidity, Geopotential, Reflectivity, Temperature, Wind speed, Wind direction.

The list of available vertical levels (FL) is [50, 65, 80, 100, 120, 140, 160, 180, 210, 240, 270, 300, 320, 340, 360, 390, 410, 450, 530] for all coverages except for the Reflectivity for which it is [50, 65, 80, 100, 120, 140, 160, 180, 210, 240, 270, 300, 340, 390].

WCS Service The data from the Arome model can be accessed by a WCS service. The details of the WCS service can be found in chapter3 section 3.4.3. The details of the WCS service is mentioned as below: The Server Endpoint: http://claudius.meteo.fr and the Resource: /geoserver/metgate/wcs/

Supported methods: GET queries for retrieving metadata about the service in order to

15 CHAPTER 2. STATE OF THE ART

Figure 2.3: MET-ATM SWIM services know how to use it and coverages of MET Information.

Query Parameters: service [WCS], The service version 2.0, request [GetCapabilities | GetCapabilitiesEnsemble | DescribeCoverage | DescribeEnsemble GetCoverage] The operation name to be requested to the service: coverageId [optional, string], The unique id of a coverage ensembleId[optional, string], The unique id of an ensemble subset [optional, time | height | latitude | longitude], The sub selection coordinates to trim or slice a coverage. The syntax accepted by the subset values is: Slice by time (minValue, maxValue), Trim by time (value). The same applies to height, latitude and longitude. The data output format NetCDF.

2.2.2 Flight Dataset The flight dataset is required by the client to calculate contrails on the path specified. It is provided by Flightradar 24. Flightradar 24 provides real time flight track data from various aircraft around the world. Flightradar24 merges the track data from many different data sources including MLAT (Multilateration), ADS-B (Automatic dependent surveillance- broadcast) and FAA (Federal Aviation Administration.). The data is amassed together with the agenda and flight status data from airports and airlines to create a exclusive flight tracking experience. The tracking information the users receive consists of arrivals,

16 CHAPTER 2. STATE OF THE ART destinations, flight tracks, flight numbers, aircraft types, positions, altitudes, headings and speeds.

Automatic dependent surveillance-broadcast One of the technology which is used by Flightradar24 is called automatic dependent surveillance-broadcast (ADS-B) [17]. The technology can be explained clearly with the image figure 2.4. The location of the aircraft is sent to the aircraft via GPS in satellites. The aircraft have a ADS-B transponder on plane which would transmit a signal containing the location and aircraft data. The signal sent by the ADS-B transponder can be received by certain receivers which are connected to Flightradar24. Receivers recieve the signal and feed it to Flightradar24.

Figure 2.4: ADS-B

Aircraft currently use primary Radar mechanism. The technology ADS-B itself is very advanced in time and is rarely used the aviation authorities. The statistics on the website of Flightradar 24 estimates that in commercial aircraft category : 80% in Europe and 55% in the US are equipped with ADS-B transponder. However ADS-B used in general

17 CHAPTER 2. STATE OF THE ART aviation is below 20%. The technology is greatly appreciated around the world and hence the demand for this technology is increasing evenly. It is predicted that by 2020 ADS-B will be mandatory for all aircraft.

Flightradar24 receives data from more than 8000 ADS-B receivers around the globe and this information is further sent to the company servers. The frequency used for the ADS-B signals is 1090 MHz and the coverage range from the receiver is 250-450 km in all directions but depending on location. Hence there is one shortcoming when flying above the oceans. Generally the aircraft has to fly higher to be covered by the receiver.

There is good coverage in Canada, Mexico, Caribbean, Venezuela, Colombia, Ecuador, Peru, Brazil, South Africa, Russia, Middle East, Pakistan, India, China, Taiwan, Japan, Thailand, Malaysia, Indonesia, Australia and New Zealand.

Estimations Flightradar24 uses estimations to predict the position of aircraft for upto 1 hour, provided the destination of the aircraft is known. The aircraft whose destination is unknown, FR 24 estimated the position for 10 minutes. the position estimated is calculated on the basis of a lot of aircraft data and is generally accurate and in case of long flights it may be about 100km deviation from the estimated path.

SWIM service Flightradar24 is participating in SWIM Master Class 2015 and giving the ADS-B tracking information for free of charge to the participants of SWIM Mas- ter Class 2015. The ConSA service is consumed in ConSA client and show contrail occurrence because of aircraft and how it could be avoided.

2.2.3 Algorithm The contrail formation depends on the atmospheric parameters - temperature, pressure and relative humidity. Before going in to the details of the algorithm, the following paragraphs will explain the properties.

Relative Humidity. Water vapour exist in the atmosphere and is responsible for var- ious green house effect, for cloud formation , precipitation, condensation and freez- ing, etc. The measure of water vapour can be done in simplest way by measuring the number of water molecules per mass of air. It is called absolute humidity. So Relative humidity can be defined as the ratio of partial pressure of water molecules to the partial pressure of water molecules at saturation. It lies in the known percentage range ı.e. 0% to 100%. Relative humidity is used more popular among the scientists being a driven factor for many research topics, including cloud formation. It is entirely property of water vapour and not of any other particles in the air.

18 CHAPTER 2. STATE OF THE ART

Atmospheric Pressure. Pressure is defined as force per unit area. The standard unit for pressure is Pascal. Atmospheric pressure is the force exerted by the weight of air on the Earth’s surface. By this meaning if the number of air molecules increases above a surface, the force exerted by those molecules on the surface increases and thereby the pressure increases and the vice-versa is also true. The pressure measuring instrument is called as barometer and hence atmospheric pressure is also called as barometric pressure. With the increase in altitude above the Earth’s surface, the atmospheric pressure decreases. The atmospheric pressure also plays a key part in Contrail formation.

Ice Supersaturation. Supersaturation means a state of solution that contains dissolved substance than normally it would contain it or in terms of physics, vapour of a compound having higher pressure than normal vapour pressure of that compound. At higher altitudes areas in the troposphere the water saturation often leads to ice supersaturation. However water saturation will not directly lead to ice formation, it requires the relative humidity of ice over atmosphere to be above 100% for ice supersaturation. In upper troposphere the temperatures are generally very low i.e. t > -40°C where pure water will freeze immediately. Ice supersaturation is responsible for formation of clouds and evolution and hence is vital to maintain habitable weather and climate.

Ice formation in the atmosphere is a totally different thing from ice saturation. For ice formation a very high supersaturation would be needed. Ice supersaturation is a metastable state and not an unstable state because ice supersaturation would persist in the atmosphere for long time (more than 24 hours). Ice Supersaturation is very important for Cirrus cloud persistence.

The first observations of Ice supersaturation were made by A.Wegener in 1906 but he and W.Findeisen thought that ice formation came from deposition on solid particles, it was by L.Krastanow and E.Wall who came up with thermodynamic equations of the idea that ice phase originated from liquid phase. But it was in 1945, E.Glückauf and H.K.Weickmann who measured ice saturation in research flights. Later in 1984 Detweiler and Pratt came up with the word ’ice-supersaturated region’ (ISSR). The major important step came with the implementation of ISSR’s into the forecast model of the European Centre for Medium -Range Weather Forecasts(ECWMF) in September 2006.

Graphical Method The pioneers of contrail formation process are Schmidt(1943) and Appleman(1953). Contrail formation is like breathing on cold air; the condensation that becomes visible is due to isobaric mixing of two air masses of different temperature and different moisture content. Mixing of air masses can lead to condensation because the saturation pressure of water vapour decreases almost exponentially with decreasing temperature. Isobaric mixing thus can end up in a supersaturated state even if none of

19 CHAPTER 2. STATE OF THE ART the two mixed air masses was saturated before. The figure 2.5 represents the graphical method to compute contrails. The figure indicates the ’Always’, ’Possible’ and ’Never’ conditions for contrail formation. These conditions are function of atmospheric pressure, temperature and relative humidity.

Relative Humidity (%) 0 60 90 100 100

200

300

400 Pressure (mb) Pressure 500

600

700

800 900 1000 -80 -70 -60 -50 -40 -30 -20 Temperature (°C)

Figure 2.5: A graph of the required relative humidity for contrail formation as a function for pressure and temperature of the environment. The dashed lines are empirically derived curves of contrail probability in percentage.

Mathematical formulation The Schimdt- Appleman criterion (SAC) [2] calculates a threshold temperature such that if ambient temperature lies above the threshold tempera- ture contrail formation is certain. At this threshold temperature the mixture of ambient air and engine exhaust reaches saturation. Contrails can persist for not more than a few minutes if the air is subsaturated with respect to ice; but contrails can persist for up to

20 CHAPTER 2. STATE OF THE ART several hours if the supersaturation with respect to ice occurs, i.e. (RHice > 100%). The input to this algorithm is ambient temperature, pressure and relative humidity.

2 TLM = −46.46 + 9.43 ln(G − 0.053) + 0.72[ln(G − 0.053)]

-1 where G is the gradient of mixing line, unit of G is Pa K and TLM in °C.

c pEI 2 G = p H O (MH2O/Mair)Qfuel(1 − η) where cp = 1004 J (kg K)p is pressure EI

21

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C HAPTER 3 CHAPTER 3. ARCHITECTURE AND SOLUTION

Applications The GIS applications evaluated in this thesis are Carmenta Engine, Esri ArcGIS Runtime, WorldWindJava, Envitia Maplink Pro and LuciadLightspeed. All latest versions of these products are compared in this thesis.

Carmenta Engine is the product of Swedish software company named Carmenta. The programming languages supported by Carmenta Engine are C++, C#, .NET, Java and Python. A major effort is needed by the developer to visualize data. The approach of Carmenta Engine is to give flexibility to developers to visualize the dataset as required and hence only fundamental visualization tools are provided. OGC web services support is limited in this engine. Carmenta Engine is ISO 9001 certified for its quality.

Esri ArcGIS Runtime is provided by Esri, an international American company. The various SDK’s supported by it are Java, WPF, C++ and .Net. Regarding reading file formats, ArcGIS Runtime can only read package files created in ArcGIS Desktop. These package files can include various data formats. There is limited support for OGC web services.

WorldWindJava is developed by NASA and is an open source map engine. As stated implicitly by its name- it is written in Java. It used Java OpenGL technology to display information in three-dimension. OGC web services and data formats are not completely supported by it.

Envitia is a British company and thier software product MapLink Pro has been examined in this thesis. The API which are supported by it are C++, .NET and COM. But the full-featured one is the C++ API. It uses Microsoft Foundation classes (MFC) to provide a graphical user interface. It support a variety of data formats but to read these data formats at runtime is upto the developers efforts.

LuciadLightpseed is a product of the Belgian GIS software company Luciad. It is platform independent and runs on mobile, tablet, embedded or server-with or without GPU. The classes and functions provided are in Java and it also provided functions and interfaces for easy integration of C#, C and C++ applications. It has pre-implemented OGC interfaces for web services and exchange formats. I found the documentation provided with LuciadLightpseed sufficient for any person who is new to GIS technology. It supports both 2D ad 3D visualization. It has predefined interfaces, classes and functions to read data formats, process information and display them and the developer efforts are completely minimized.

Comparison This section compares the previously introduced GIS applications. As Carmenta Engine is ISO certified it is very reliable product. However it has fundamental

23 CHAPTER 3. ARCHITECTURE AND SOLUTION tools library only. The fact that it has limited OGC support is not a good fact for this thesis as OGC standards implementation are widely required in the aviation community. Esri ArcGIS Runtime seems very much like Carmenta Engine. Although Esri ArcGIS Runtime accepts variety of input formats, it depends on its ArcGIS Desktop application heavily to preprocess data. WorldWindJava has a big advantage of displaying data in 3D but the primary source of data in it is the code itself. Due to this it seems very difficult to understand it, especially for a new comer. MapLink Pro reads very few formats at runtime, this is also a limitation and cannot be accepted because this matters to this thesis a lot. LuciadLightspeed has exceptional features of displaying information in 2D and 3D, large number of libraries support and huge support for OGC standards. Out of all previously mentioned comparisons LuciadLightspeed seems to be performing very well and best amongst all. Hence we choose LuciadLightspeed as the GIS application. The next section explains some features, functions and interfaces of LuciadLightspeed which are used in this thesis.

3.2 LuciadLightspeed

The LuciadLightspeed API is based on the Model-View-Controller (MVC) architecture. This separation results in a simpler design of the application and a higher flexibility and re-usability of code.

Model, View and Controller and their relation among each other is explained as follows:

• Model stores and describes geographical data regardless of how to visualize and interact with the data. • View contains all information for the representation of data contained in models. A view does not contain data itself. • Controller interprets user interaction and performs the required action on models and views regardless of the type of model and view.

By separating the different parts of the application flexibility can be gained in the develop- ment. Reuse of objects for different purposes and redefine objects without changing other objects. For example, change a view without making changes to the models represented in the view. Or redefine user interaction on a view without changing the view. Object reuse shortens the time for writing an application. In addition, it enhances a consistent functionality and design of all your applications.

24 CHAPTER 3. ARCHITECTURE AND SOLUTION

View

Model Controller

Figure 3.1: The underlying concept of the MVC architecture is to separate the data (model), representation of the data (view), and the user interaction (controller) from each other.

Building applications with LuciadLightspeed The process to create an application covers the following functions:

• Define the model. • Create layers for the model. • Define View and add layers to the view. • Define controller for the view.

Model Layer View Controller

Figure 3.2: The separate components of LuciadLightspeed application.

There is flexibility of adding layers to an existing view, adding multiple layers onto the same view, update and display views when model data changes. One can select or deselect the layers which shall be visible on the map. This is helpful at times when the user needs to focus on one model.

Data formats support It supports use of various standards of data formats through:

• Model decoders, encoders provided with the API • Self-created Custom model decoders and encoders are easily developed for un- definded data formats.

25 CHAPTER 3. ARCHITECTURE AND SOLUTION

Styling data with OGC SLD A Styled Layer Descriptor (SLD) [18] is an XML schema specified by the Open Geospatial Consortium (OGC) for describing the appear- ance of geospatial layers. It allows to define uniform styling information for geospatial data through symbology encoding. Symbology encoding is based on the paradigm that style and content should be separated. As Luciad- Lightspeed adheres to the same paradigm, it is particularly well-suited to implement SLD. Although the styling model may be constructed programmatically, it is usually decoded from XML files. This facility helps us to speed up the development process. SLD addresses to the requirements of the individuals and software itself to have the ability to control the visual sketch of the geospatial data. In case of a client server architecture the styling rules are required to be understood by both sides.

It was initially designed for Web Map Service (WMS) but later it was found useful in applications and other services too. WeThe next chapter will introduce the details about OGC web services. Below is a part of Aerodrome SLD.

Listing 3.1: MyAerodromeType.sld